<?xml version="1.0" encoding="UTF-8"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2013-05-24T22:16:59Z</responseDate><request verb="ListRecords" from="2007-11-17" metadataPrefix="pmc" set="pmc-open" until="2007-11-18">http://www.ncbi.nlm.nih.gov/oai/oai.cgi</request><ListRecords><record><header><identifier>oai:pubmedcentral.nih.gov:2080627</identifier><datestamp>2007-11-17</datestamp><setSpec>bmcpsyc</setSpec><setSpec>pmc-open</setSpec></header><metadata><article xmlns="http://dtd.nlm.nih.gov/2.0/xsd/archivearticle" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://dtd.nlm.nih.gov/archiving/2.3/xsd/archivearticle.xsd" article-type="research-article">
  <front>
    <journal-meta>
      <journal-id journal-id-type="nlm-ta">BMC Psychiatry</journal-id>
      <journal-title>BMC Psychiatry</journal-title>
      <issn pub-type="epub">1471-244X</issn>
      <publisher>
        <publisher-name>BioMed Central</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="pmc">2080627</article-id>
      <article-id pub-id-type="publisher-id">1471-244X-7-48</article-id>
      <article-id pub-id-type="pmid">17850674</article-id>
      <article-id pub-id-type="doi">10.1186/1471-244X-7-48</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>The assessment of depression awareness and help-seeking behaviour: experiences with the International Depression Literacy Survey</article-title>
      </title-group>
      <contrib-group>
        <contrib id="A1" corresp="yes" contrib-type="author">
          <name>
            <surname>Hickie AM</surname>
            <given-names>Ian B</given-names>
          </name>
          <xref ref-type="aff" rid="I1">1</xref>
          <email>ianh@med.usyd.edu.au</email>
        </contrib>
        <contrib id="A2" contrib-type="author">
          <name>
            <surname>Davenport</surname>
            <given-names>Tracey A</given-names>
          </name>
          <xref ref-type="aff" rid="I1">1</xref>
          <email>tdavenport@med.usyd.edu.au</email>
        </contrib>
        <contrib id="A3" contrib-type="author">
          <name>
            <surname>Luscombe</surname>
            <given-names>Georgina M</given-names>
          </name>
          <xref ref-type="aff" rid="I1">1</xref>
          <email>gluscomb@med.usyd.edu.au</email>
        </contrib>
        <contrib id="A4" contrib-type="author">
          <name>
            <surname>Rong</surname>
            <given-names>Ye</given-names>
          </name>
          <xref ref-type="aff" rid="I2">2</xref>
          <email>yrong@med.usyd.edu.au</email>
        </contrib>
        <contrib id="A5" contrib-type="author">
          <name>
            <surname>Hickie</surname>
            <given-names>Megan L</given-names>
          </name>
          <xref ref-type="aff" rid="I1">1</xref>
          <email>megan_22886@hotmail.com</email>
        </contrib>
        <contrib id="A6" contrib-type="author">
          <name>
            <surname>Bell</surname>
            <given-names>Morag I</given-names>
          </name>
          <xref ref-type="aff" rid="I1">1</xref>
          <email>mbell@med.usyd.edu.au</email>
        </contrib>
      </contrib-group>
      <aff id="I1"><label>1</label>Brain &amp; Mind Research Institute, The University of Sydney, Sydney, Australia</aff>
      <aff id="I2"><label>2</label>Discipline of Psychological Medicine, The University of Sydney, Sydney, Australia</aff>
      <pub-date pub-type="collection">
        <year>2007</year>
      </pub-date>
      <pub-date pub-type="epub">
        <day>13</day>
        <month>9</month>
        <year>2007</year>
      </pub-date>
      <volume>7</volume>
      <fpage>48</fpage>
      <lpage>48</lpage>
      <ext-link ext-link-type="uri" xlink:href="http://www.biomedcentral.com/1471-244X/7/48"/>
      <history>
        <date date-type="received">
          <day>20</day>
          <month>12</month>
          <year>2006</year>
        </date>
        <date date-type="accepted">
          <day>13</day>
          <month>9</month>
          <year>2007</year>
        </date>
      </history>
      <permissions>
        <copyright-statement>Copyright © 2007 Hickie AM et al; licensee BioMed Central Ltd.</copyright-statement>
        <copyright-year>2007</copyright-year>
        <copyright-holder>Hickie AM et al; licensee BioMed Central Ltd.</copyright-holder>
        <license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/2.0">
          <p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/2.0"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>
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               Hickie AM
               B
               Ian
               
               ianh@med.usyd.edu.au
            </dc:author><dc:title>
            The assessment of depression awareness and help-seeking behaviour: experiences with the International Depression Literacy Survey
         </dc:title><dc:date>2007</dc:date><dcterms:bibliographicCitation>BMC Psychiatry 7(1): 48-. (2007)</dcterms:bibliographicCitation><dc:identifier type="sici">1471-244X(2007)7:1&#x0003c;48&#x0003e;</dc:identifier><dcterms:isPartOf>urn:ISSN:1471-244X</dcterms:isPartOf><License rdf:about="http://creativecommons.org/licenses/by/2.0"><permits rdf:resource="http://web.resource.org/cc/Reproduction" xmlns=""/><permits rdf:resource="http://web.resource.org/cc/Distribution" xmlns=""/><requires rdf:resource="http://web.resource.org/cc/Notice" xmlns=""/><requires rdf:resource="http://web.resource.org/cc/Attribution" xmlns=""/><permits rdf:resource="http://web.resource.org/cc/DerivativeWorks" xmlns=""/></License></Work></rdf>-->
        </license>
      </permissions>
      <abstract>
        <sec>
          <title>Background</title>
          <p>Depression causes substantial disease burden in both developed and developing countries. To reduce this burden, we need to promote understanding of depression as a major health condition. The International Depression Literacy Survey (IDLS) has been developed to assess understanding of depression in different cultural and health care settings.</p>
        </sec>
        <sec sec-type="methods">
          <title>Methods</title>
          <p>Four groups of Australian university students completed the survey: medical students in second (n = 103) and fourth (n = 82) years of a graduate course, ethnic Chinese students (n = 184) and general undergraduate students (n = 38).</p>
        </sec>
        <sec>
          <title>Results</title>
          <p>Differences between the student groups were evident, with fourth year medical students demonstrating greater general health and depression literacy than second year medical students. Australian undergraduate students demonstrated better depression literacy than those from ethnic Chinese backgrounds. Ethnicity also influenced help seeking and treatment preferences (with more Chinese students being inclined to seek help from pharmacists), beliefs about discrimination and perceptions regarding stigma.</p>
        </sec>
        <sec>
          <title>Conclusion</title>
          <p>The IDLS does detect significant differences in understanding of depression among groups from different ethnic backgrounds and between those who differ in terms of prior health training. These preliminary results suggest that it may be well suited for use in a wider international context. Further investigation of the utility of the IDLS is required before these results could be extrapolated to other populations.</p>
        </sec>
      </abstract>
    </article-meta>
  </front>
  <body>
    <sec>
      <title>Background</title>
      <p>Depressive disorders are a major source of non-fatal disease burden in developed countries, as well as being a key determinant of health-related disability in the developing world [<xref ref-type="bibr" rid="B1">1</xref>,<xref ref-type="bibr" rid="B2">2</xref>]. To achieve meaningful reductions in depression-related health burden a range of preventative and treatment strategies are urgently required [<xref ref-type="bibr" rid="B3">3</xref>,<xref ref-type="bibr" rid="B4">4</xref>]. The development of such initiatives, however, usually depends on broad recognition that depression is not only common and disabling but that it also responds to evidence-based treatments.</p>
      <p>The concept of 'mental health literacy' has emerged to describe "<italic>knowledge and beliefs about mental disorders which aid their recognition, management or prevention</italic>" [<xref ref-type="bibr" rid="B5">5</xref>]. To date, assessment has rested largely on typical case-based vignettes of persons with schizophrenia or depression. This approach requires the respondent to identify the person as a 'case' of mental disorder and then disclose their knowledge or attitudes about available health services or treatments. This has proved to be a useful way of tracking community attitudes to a range of mental health problems and their treatments, particularly in English-speaking countries [<xref ref-type="bibr" rid="B6">6</xref>].</p>
      <p>We propose an alternative approach which specifically describes depression as a health condition, and then seeks to determine understanding of its characteristics and impacts relative to other medical and psychological conditions. Through our social marketing strategies for <italic>beyondblue: the national depression initiative </italic>in Australia, we focused more on these general health and depression-specific literacy issues than on an individual's capacity to recognise a typical 'case' of mental disorder. Our earlier work indicated that while the general public was aware of the potential impacts of depression, common mental disorders generally were not seen to be as important as other major physical disorders such as cancer and heart disease [<xref ref-type="bibr" rid="B7">7</xref>]. Further, a range of other factors such as personal or family experiences of depression, previous experiences of seeking care or encountering other stigmatising attitudes towards persons with depression appeared to be impacting on willingness to seek mental health care.</p>
      <p>As part of an international movement to promote greater recognition of the social and economic costs of depression [<xref ref-type="bibr" rid="B3">3</xref>,<xref ref-type="bibr" rid="B4">4</xref>], we were keen to develop this alternative approach to rating depression literacy. A priority was that the method should be able to be utilised easily in countries where English is not the first language or where there was little priority given to the provision of relevant health services. Consequently, we developed a modular depression literacy self-report instrument for use primarily in countries that are participating in the 'Reducing the <underline>S</underline>ocial and <underline>E</underline>conomic <underline>B</underline>urdens <underline>o</underline>f <underline>D</underline>epression' (SEBoD) movement in Asia.</p>
      <p>As the SEBoD movement aims to improve depression literacy within general health workforces, we were interested to determine whether the instrument was sensitive to differences in mental health training. As many countries are not culturally homogeneous, we also sought to determine whether significant ethnic differences had impacts on depression literacy among persons residing in the same country. Therefore, in this Australian study we endeavoured to examine the utility of our instrument when it was completed by university students from different ethnic and health training backgrounds.</p>
    </sec>
    <sec sec-type="methods">
      <title>Methods</title>
      <p>The study was a cross-sectional survey of four groups of Australian university students. There were two groups of general students (ethnic Chinese and non-ethnically selected students) and two groups of medical students (second and fourth year students of The University of Sydney Graduate Medical Program).</p>
      <sec>
        <title>Study procedure</title>
        <p>Students 18 years or older, who were enrolled in a university, were included in the study. The second and fourth year medical students were recruited during seminar series devoted to the teaching of mental health topics. The fourth year students were engaged in the clinical aspects of psychiatry and addiction medicine. Ethnic Chinese students were contacted and invited to the study through Chinese student organisations. The survey was also distributed to students attending a college of The Australian National University (ANU, Canberra) using a convenience sampling approach. The study was approved by The University of Sydney Human Research Ethics Committee.</p>
      </sec>
      <sec>
        <title>Instrument</title>
        <p>Version 1.1 of the survey was divided into seven sections [see Additional file <xref ref-type="supplementary-material" rid="S1">1</xref>]. At the end of each section, subjects are given the option of continuing the survey or terminating. The survey covers a range of topics, including:</p>
        <sec>
          <title>Section A</title>
          <sec>
            <title>Demographics</title>
            <p>This section includes questions on ethnicity, education and identity in the health care system.</p>
          </sec>
        </sec>
        <sec>
          <title>Section B</title>
          <sec>
            <title>Major health problems</title>
            <p>In order to determine the salience of mental health disorders, and depression in particular, as health issues, respondents are requested to nominate the main causes of death or disability in their country from a list of general health problem categories, a list of specific illness and injuries and a list of mental health problems. These lists were based on the top 13 'health problems' and the top 23 'diseases' causing the most death or disability in Disability Adjusted Life Years (DALYs) in the world as determined by World Health Organization [<xref ref-type="bibr" rid="B8">8</xref>], and the mental and behavioural disorder sub-categories listed in the International Classification of Diseases [ICD-10; 9].</p>
          </sec>
          <sec>
            <title>Knowledge of depression</title>
            <p>Respondents nominate from lists what they believe are the most typical symptoms and common experiences with depression [<xref ref-type="bibr" rid="B10">10</xref>], and the prevalence of depression.</p>
          </sec>
        </sec>
        <sec>
          <title>Section C</title>
          <sec>
            <title>Help and treatment</title>
            <p>These questions are based on research about treatments for depression previously conducted in Australia [<xref ref-type="bibr" rid="B11">11</xref>,<xref ref-type="bibr" rid="B12">12</xref>]. Respondents are asked their opinion about the most likely outcome of depression with or without professional help. The likelihood of seeking help from professionals or non-professionals and level of helpfulness of various treatments are also rated using a five-point Likert-type scale. Personal experience with depression is included in this section.</p>
          </sec>
        </sec>
        <sec>
          <title>Section D</title>
          <sec>
            <title>Information</title>
            <p>This question identifies experiences in seeking information for depression.</p>
          </sec>
        </sec>
        <sec>
          <title>Section E</title>
          <sec>
            <title>Perceived needs</title>
            <p>The General-practice Users' Perceived-need Inventory (GUPI) is used to identify perceived need for mental health care provided by general practitioners (GPs) [<xref ref-type="bibr" rid="B13">13</xref>]. The questions ask about personal willingness to discuss emotional problems with GPs and any reasons stopping the individual doing so. This section only applies to subjects who sought help from a GP for an emotional problem during the 12 months prior to their participation in the study.</p>
          </sec>
        </sec>
        <sec>
          <title>Section F</title>
          <sec>
            <title>Attitudes to depression and its treatment</title>
            <p>The first question about discrimination was taken from previous Australian research on attitudes to depression [<xref ref-type="bibr" rid="B7">7</xref>]. The second item asks about attitudes towards people with "<italic>severe depression</italic>" and was derived from research conducted in the United Kingdom investigating the stigma associated with mental health problems [<xref ref-type="bibr" rid="B14">14</xref>].</p>
          </sec>
        </sec>
        <sec>
          <title>Section G</title>
          <sec>
            <title>General information</title>
            <p>The Kessler Psychological Distress Scale (K10) [<xref ref-type="bibr" rid="B15">15</xref>] is included in this section to measure current levels of psychological distress. The 12-item Somatic and Psychological HEalth REport (SPHERE) [<xref ref-type="bibr" rid="B16">16</xref>] is used to assess the severity of psychological and/or somatic symptoms. Two disability questions follow [<xref ref-type="bibr" rid="B17">17</xref>]. Two further demographic questions obtain information on living and employment conditions.</p>
          </sec>
        </sec>
      </sec>
      <sec>
        <title>Development of the survey</title>
        <p>The survey utilised the concepts of knowledge, awareness and attitudes that have been more generally used in mental health literacy research and the evaluation of other mental health promotion campaigns [<xref ref-type="bibr" rid="B6">6</xref>]. However, it made additional use of those items that were developed to assist with the assessment of the impact of <italic>beyondblue </italic>in Australia [<xref ref-type="bibr" rid="B12">12</xref>]. Additional elements drew on previous research assessing the impacts of stigma in relation to persons with mental disorders [<xref ref-type="bibr" rid="B14">14</xref>] as well as the specific development of a brief questionnaire to assess experiences of mental health service use [<xref ref-type="bibr" rid="B13">13</xref>].</p>
        <p>As the aim was to develop a basic self-report format for use in the countries and cultures of the Asia Pacific Region, a draft survey was sent to SEBoD committee members and country chapter heads. They were asked to comment particularly on the suitability and comprehensibility of the survey in their local circumstances. The draft was modified according to their comments and suggestions. The items were simplified and pre-tested among a group of native English speakers to ensure the survey was understandable for people with various levels of English literacy. It was also tested and commented upon by culturally diverse community members, including Chinese, Japanese and Korean, for cultural appropriateness.</p>
      </sec>
      <sec>
        <title>Statistical analysis</title>
        <p>For the items regarding major health problems, specific illness or injuries and mental health problems, only those categories nominated by over 10% of students are reported. Additionally, only those categories nominated by over 20% of students within the items concerning typical signs, behaviours and experiences of persons with depression are reported in this article. For the questions on help seeking, only the combined percentages of the answers "probably likely" and "definitely likely" are presented. Likewise, only the percentages for combined positive answers are described, such as "probably likely" and "definitely likely" for the discrimination item, and "agree" and "strongly agree" for the stigma item. These combined categories were also used for the purposes of statistical analysis.</p>
        <p>For the K10, the response options "none of the time", "a little of the time", "some of the time", "most of the time" and "all of the time" were coded as 1, 2, 3, 4 and 5 respectively. The sum of the scores for each item were calculated and recoded into three levels of psychological distress: 10–15 representing low or no, 16–29 representing medium, and 30–50 representing high distress. The last two categories were combined both for the purposes of presentation and for statistical analysis.</p>
        <p>The response options in the SPHERE questionnaire, "never or some of the time", "a good part of the time" and "most of the time" were coded as 0, 1, and 2 respectively. The total scores of the six psychological questions and the six somatic questions were calculated separately. The students with a total score of two or more for the six psychological items were categorised as having strong psychological symptoms (PSYCH-6); the students with a total score of three or more for the six somatic items were categorised as having strong somatic symptoms [<xref ref-type="bibr" rid="B16">16</xref>]. The percentages of students who showed significant psychological and/or somatic symptoms were reported and compared among the groups.</p>
        <p>Two sets of analyses were conducted, the first comparing second year medical students with fourth year medical students (to examine the effect of mental health training), the second comparing Chinese students with ANU students (to examine the effect of culture). Associations between group membership (type of student) and item responses were made using the Chi-square test, the continuity correction value being considered for two by two tables. Age was significantly skewed, and this could not be rectified, so the non-parametric Mann-Whitney U test was used for the two group comparison. All calculations and analyses were carried out using the Statistical Package for the Social Sciences (SPSS) version 12. Where appropriate, Bonferroni corrections were applied to alpha to account for multiple comparisons.</p>
      </sec>
    </sec>
    <sec>
      <title>Results</title>
      <p>The English version of the International Depression Literacy Survey (IDLS) was administered to four student groups: medical students from The University of Sydney in second year (n = 103) and fourth year (n = 82); tertiary students from The ANU (n = 38); and Chinese students from The University of Sydney, The University of Technology (Sydney) and The University of New South Wales (n = 184). In total the survey was completed by N = 407 students. Eighty-two percent of the sample completed the entire survey (n = 333/407), 33 terminated after section B (i.e. only completed the first two sections), 17 after section C, 12 after section D, six after section E and six after section F.</p>
      <sec>
        <title>Demographics</title>
        <p>The mean age of students was 24.4 years (SD = 4.0 years; range = 15 – 43 years), with Chinese students being significantly older than ANU students, and fourth year medical students significantly older than second year students (see Table <xref ref-type="table" rid="T1">1</xref>). A small proportion of the ANU students had a medical/health care background (8%), as did the ethnic Chinese students (9%). Conversely, a small proportion of medical students reported Chinese nationality (second year: 4%, fourth year: 1%), as did the ANU students (3%).</p>
        <table-wrap position="float" id="T1">
          <label>Table 1</label>
          <caption>
            <p>Demographic characteristics of sample (N = 407)</p>
          </caption>
          <table frame="hsides" rules="groups">
            <thead>
              <tr>
                <td/>
                <td align="center">
                  <bold>2<sup>nd </sup>Year Medical</bold>
                </td>
                <td align="center">
                  <bold>4<sup>th </sup>Year Medical</bold>
                </td>
                <td align="center">
                  <bold>ANU</bold>
                </td>
                <td align="center">
                  <bold>Chinese</bold>
                </td>
                <td align="center">
                  <bold>2<sup>nd </sup>vs 4<sup>th </sup>Year Medical</bold>
                </td>
                <td align="center">
                  <bold>ANU vs Chinese</bold>
                </td>
              </tr>
              <tr>
                <td/>
                <td colspan="4">
                  <hr/>
                </td>
                <td/>
                <td/>
              </tr>
              <tr>
                <td/>
                <td align="center">
                  <italic>n = 103*</italic>
                </td>
                <td align="center">
                  <italic>n = 82*</italic>
                </td>
                <td align="center">
                  <italic>n = 38*</italic>
                </td>
                <td align="center">
                  <italic>n = 184*</italic>
                </td>
                <td align="center">
                  <bold>p value</bold>
                </td>
                <td align="center">
                  <bold>p value</bold>
                </td>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td align="left">Age (years): mean (SD)</td>
                <td align="center">25.5 (4.0)</td>
                <td align="center">27.5 (3.2)</td>
                <td align="center">20.3 (2.1)</td>
                <td align="center">23.3 (3.5)</td>
                <td align="center">&lt; 0.001<sup>1</sup></td>
                <td align="center">&lt; 0.001<sup>1</sup></td>
              </tr>
              <tr>
                <td align="left">Age (years): range</td>
                <td align="center">21 – 42</td>
                <td align="center">23 – 43</td>
                <td align="center">18 – 26</td>
                <td align="center">15 – 39</td>
                <td/>
                <td/>
              </tr>
              <tr>
                <td align="left">% female</td>
                <td align="center">55</td>
                <td align="center">59</td>
                <td align="center">47</td>
                <td align="center">46</td>
                <td align="center">0.693</td>
                <td align="center">1.000</td>
              </tr>
              <tr>
                <td align="left">Area inhabited: urban, %</td>
                <td align="center">97</td>
                <td align="center">99</td>
                <td align="center">82</td>
                <td align="center">75</td>
                <td align="center">0.819</td>
                <td align="center">0.502</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <p><sup>1 </sup>Mann-Whitney U test.</p>
            <p>*There are missing data for different items (age, gender: 2<sup>nd </sup>year medical n = 1, 4<sup>th </sup>year medical n = 4, ANU none missing, Chinese n = 8 for age and n = 1 for gender; area inhabited: 2<sup>nd </sup>year medical none missing, 4<sup>th </sup>year medical n = 4, ANU none missing, Chinese n = 5).</p>
          </table-wrap-foot>
        </table-wrap>
      </sec>
      <sec>
        <title>Major health problems</title>
        <p>There were significant differences between the various student groups with regard to the recognition of major health problems in Australia (see Table <xref ref-type="table" rid="T2">2</xref>). For example, approximately half of the Chinese students nominated "<italic>heart disease and stroke</italic>" as a main cause of death or disability, compared to the majority of ANU students. By contrast for "<italic>brain, behavioural and mental health disorders</italic>", just over half of the ANU students rated this key area as a major health problem compared with only a quarter of ethnic Chinese students.</p>
        <table-wrap position="float" id="T2">
          <label>Table 2</label>
          <caption>
            <p>Major health problems students nominated as the main causes of death or disability in Australia (N = 382*)</p>
          </caption>
          <table frame="hsides" rules="groups">
            <thead>
              <tr>
                <td/>
                <td align="center">
                  <bold>2<sup>nd </sup>Year Medical</bold>
                </td>
                <td align="center">
                  <bold>4<sup>th </sup>Year Medical</bold>
                </td>
                <td align="center">
                  <bold>ANU</bold>
                </td>
                <td align="center">
                  <bold>Chinese</bold>
                </td>
                <td align="center">
                  <bold>2<sup>nd </sup>vs 4<sup>th </sup>Year Medical</bold>
                </td>
                <td align="center">
                  <bold>ANU vs Chinese</bold>
                </td>
              </tr>
              <tr>
                <td/>
                <td colspan="4">
                  <hr/>
                </td>
                <td/>
                <td/>
              </tr>
              <tr>
                <td/>
                <td align="center">
                  <italic>n = 101</italic>
                </td>
                <td align="center">
                  <italic>n = 81</italic>
                </td>
                <td align="center">
                  <italic>n = 38</italic>
                </td>
                <td align="center">
                  <italic>n = 162</italic>
                </td>
                <td align="center">p value<sup>a</sup></td>
                <td align="center">p value<sup>a</sup></td>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td align="left">Cancer %</td>
                <td align="center">77</td>
                <td align="center">56</td>
                <td align="center">84</td>
                <td align="center">85</td>
                <td align="center">0.003</td>
                <td align="center">1.000</td>
              </tr>
              <tr>
                <td align="left">Heart disease and stroke %</td>
                <td align="center">96</td>
                <td align="center">91</td>
                <td align="center">92</td>
                <td align="center">49</td>
                <td align="center">0.315</td>
                <td align="center">&lt; 0.001</td>
              </tr>
              <tr>
                <td align="left">Brain, behavioural and mental health disorders %</td>
                <td align="center">61</td>
                <td align="center">85</td>
                <td align="center">53</td>
                <td align="center">24</td>
                <td align="center">0.001</td>
                <td align="center">0.001</td>
              </tr>
              <tr>
                <td align="left">Diabetes %</td>
                <td align="center">25</td>
                <td align="center">36</td>
                <td align="center">37</td>
                <td align="center">51</td>
                <td align="center">0.145</td>
                <td align="center">0.177</td>
              </tr>
              <tr>
                <td align="left">Lung and chest disease %</td>
                <td align="center">56</td>
                <td align="center">52</td>
                <td align="center">16</td>
                <td align="center">15</td>
                <td align="center">0.640</td>
                <td align="center">1.000</td>
              </tr>
              <tr>
                <td align="left">Accidental injuries %</td>
                <td align="center">36</td>
                <td align="center">10</td>
                <td align="center">37</td>
                <td align="center">28</td>
                <td align="center">&lt; 0.001</td>
                <td align="center">0.409</td>
              </tr>
              <tr>
                <td align="left">Infectious disease %</td>
                <td align="center">8</td>
                <td align="center">0</td>
                <td align="center">3</td>
                <td align="center">33</td>
                <td align="center">0.026</td>
                <td align="center">&lt; 0.001</td>
              </tr>
              <tr>
                <td align="left">Muscle or joint diseases %</td>
                <td align="center">10</td>
                <td align="center">40</td>
                <td align="center">5</td>
                <td align="center">4</td>
                <td align="center">&lt; 0.001</td>
                <td align="center">1.000</td>
              </tr>
              <tr>
                <td align="left">Non-accidental injuries %</td>
                <td align="center">2</td>
                <td align="center">4</td>
                <td align="center">5</td>
                <td align="center">22</td>
                <td align="center">0.802</td>
                <td align="center">0.030</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <p><sup>a</sup>Adjusted alpha = 0.05/9 = 0.006.</p>
            <p>* Data were missing for 6% of the valid sample (n = 25/407).</p>
          </table-wrap-foot>
        </table-wrap>
        <p>There also appeared to be a training effect, with significantly more fourth year medical students nominating "<italic>brain, behavioural and mental health disorders</italic>" as a major health problem than second year medical students.</p>
        <p>When asked about specific illnesses and injuries, rather than broad disease categories, a similar pattern of responses was observed with significant group differences observed in both sets of analyses (see Table <xref ref-type="table" rid="T3">3</xref>). For example, just over half of the Chinese students nominated "<italic>heart attack or other heart disease</italic>" as a main cause of death or disability, compared to more than 90% of ANU students. There was a trend towards a difference between the medical student groups in nominating "<italic>depression</italic>" as a specific illness causing death or disability, the proportion increasing with mental health training.</p>
        <table-wrap position="float" id="T3">
          <label>Table 3</label>
          <caption>
            <p>Specific illnesses or injuries students nominated as the main causes of death or disability in Australia (N = 380*)</p>
          </caption>
          <table frame="hsides" rules="groups">
            <thead>
              <tr>
                <td/>
                <td align="center">
                  <bold>2<sup>nd </sup>Year Medical</bold>
                </td>
                <td align="center">
                  <bold>4<sup>th </sup>Year Medical</bold>
                </td>
                <td align="center">
                  <bold>ANU</bold>
                </td>
                <td align="center">
                  <bold>Chinese</bold>
                </td>
                <td align="center">
                  <bold>2<sup>nd </sup>vs 4<sup>th </sup>Year Medical</bold>
                </td>
                <td align="center">
                  <bold>ANU vs Chinese</bold>
                </td>
              </tr>
              <tr>
                <td/>
                <td colspan="6">
                  <hr/>
                </td>
              </tr>
              <tr>
                <td/>
                <td align="center">
                  <italic>n = 103</italic>
                </td>
                <td align="center">
                  <italic>n = 81</italic>
                </td>
                <td align="center">
                  <italic>n = 37</italic>
                </td>
                <td align="center">
                  <italic>n = 159</italic>
                </td>
                <td align="center">p value<sup>a</sup></td>
                <td align="center">p value<sup>a</sup></td>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td align="left">Heart attack or other heart disease %</td>
                <td align="center">93</td>
                <td align="center">91</td>
                <td align="center">92</td>
                <td align="center">57</td>
                <td align="center">0.850</td>
                <td align="center">&lt; 0.001</td>
              </tr>
              <tr>
                <td align="left">Depression %</td>
                <td align="center">67</td>
                <td align="center">84</td>
                <td align="center">30</td>
                <td align="center">19</td>
                <td align="center">0.014</td>
                <td align="center">0.215</td>
              </tr>
              <tr>
                <td align="left">Stroke or other brain disease %</td>
                <td align="center">71</td>
                <td align="center">53</td>
                <td align="center">46</td>
                <td align="center">24</td>
                <td align="center">0.020</td>
                <td align="center">0.013</td>
              </tr>
              <tr>
                <td align="left">Diabetes %</td>
                <td align="center">31</td>
                <td align="center">63</td>
                <td align="center">38</td>
                <td align="center">45</td>
                <td align="center">&lt; 0.001</td>
                <td align="center">0.523</td>
              </tr>
              <tr>
                <td align="left">Lung cancer %</td>
                <td align="center">39</td>
                <td align="center">14</td>
                <td align="center">73</td>
                <td align="center">42</td>
                <td align="center">&lt; 0.001</td>
                <td align="center">0.001</td>
              </tr>
              <tr>
                <td align="left">Road traffic accidents %</td>
                <td align="center">49</td>
                <td align="center">16</td>
                <td align="center">35</td>
                <td align="center">38</td>
                <td align="center">&lt; 0.001</td>
                <td align="center">0.860</td>
              </tr>
              <tr>
                <td align="left">Alcohol abuse %</td>
                <td align="center">28</td>
                <td align="center">46</td>
                <td align="center">27</td>
                <td align="center">34</td>
                <td align="center">0.021</td>
                <td align="center">0.538</td>
              </tr>
              <tr>
                <td align="left">Alzheimer's disease or other dementias %</td>
                <td align="center">22</td>
                <td align="center">22</td>
                <td align="center">19</td>
                <td align="center">21</td>
                <td align="center">1.000</td>
                <td align="center">0.914</td>
              </tr>
              <tr>
                <td align="left">Asthma %</td>
                <td align="center">20</td>
                <td align="center">22</td>
                <td align="center">11</td>
                <td align="center">21</td>
                <td align="center">0.904</td>
                <td align="center">0.246</td>
              </tr>
              <tr>
                <td align="left">Osteoarthritis %</td>
                <td align="center">22</td>
                <td align="center">44</td>
                <td align="center">16</td>
                <td align="center">3</td>
                <td align="center">0.002</td>
                <td align="center">0.003</td>
              </tr>
              <tr>
                <td align="left">HIV infection or AIDS %</td>
                <td align="center">3</td>
                <td align="center">0</td>
                <td align="center">8</td>
                <td align="center">38</td>
                <td align="center">0.336</td>
                <td align="center">0.001</td>
              </tr>
              <tr>
                <td align="left">Colon or rectum (bowel) cancer %</td>
                <td align="center">18</td>
                <td align="center">12</td>
                <td align="center">16</td>
                <td align="center">16</td>
                <td align="center">0.450</td>
                <td align="center">1.000</td>
              </tr>
              <tr>
                <td align="left">Suicide or self-harm %</td>
                <td align="center">3</td>
                <td align="center">11</td>
                <td align="center">8</td>
                <td align="center">25</td>
                <td align="center">0.053</td>
                <td align="center">0.042</td>
              </tr>
              <tr>
                <td align="left">Emphysema or chronic bronchitis %</td>
                <td align="center">28</td>
                <td align="center">20</td>
                <td align="center">0</td>
                <td align="center">7</td>
                <td align="center">0.253</td>
                <td align="center">0.211</td>
              </tr>
              <tr>
                <td align="left">Lung or other chest infections %</td>
                <td align="center">31</td>
                <td align="center">7</td>
                <td align="center">5</td>
                <td align="center">9</td>
                <td align="center">&lt; 0.001</td>
                <td align="center">0.729</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <p><sup>a </sup>Adjusted alpha = 0.05/15 = 0.003.</p>
            <p>* Data were missing for 7% of the valid sample (n = 27/407).</p>
          </table-wrap-foot>
        </table-wrap>
        <sec>
          <title>Mental health problems</title>
          <p>For the specific question related to mental health problems, differences with regard to depression recognition were apparent (see Table <xref ref-type="table" rid="T4">4</xref>). The highest proportion nominating "<italic>depressive illness</italic>" was in the fourth year medical student group (94%), ranging down to only 17% for the ethnic Chinese students. However, the responses from the medical students were very similar. The proportions of ANU students nominating "<italic>depressive illness</italic>" and "<italic>alcohol abuse or addiction</italic>" were significantly higher than in the Chinese student group, but the situation was reversed when considering "<italic>anxiety, neurosis or panic disorder</italic>".</p>
          <table-wrap position="float" id="T4">
            <label>Table 4</label>
            <caption>
              <p>Mental health problems students nominated as the main causes of death or disability in Australia (N = 384*)</p>
            </caption>
            <table frame="hsides" rules="groups">
              <thead>
                <tr>
                  <td/>
                  <td align="center">
                    <bold>2<sup>nd </sup>Year Medical</bold>
                  </td>
                  <td align="center">
                    <bold>4<sup>th </sup>Year Medical</bold>
                  </td>
                  <td align="center">
                    <bold>ANU</bold>
                  </td>
                  <td align="center">
                    <bold>Chinese</bold>
                  </td>
                  <td align="center">
                    <bold>2<sup>nd </sup>vs 4<sup>th </sup>Year Medical</bold>
                  </td>
                  <td align="center">
                    <bold>ANU vs Chinese</bold>
                  </td>
                </tr>
                <tr>
                  <td/>
                  <td colspan="4">
                    <hr/>
                  </td>
                  <td/>
                  <td/>
                </tr>
                <tr>
                  <td/>
                  <td align="center">
                    <italic>n = 103</italic>
                  </td>
                  <td align="center">
                    <italic>n = 82</italic>
                  </td>
                  <td align="center">
                    <italic>n = 37</italic>
                  </td>
                  <td align="center">
                    <italic>n = 162</italic>
                  </td>
                  <td align="center">p value<sup>a</sup></td>
                  <td align="center">p value<sup>a</sup></td>
                </tr>
              </thead>
              <tbody>
                <tr>
                  <td align="left">Depressive illness %</td>
                  <td align="center">86</td>
                  <td align="center">94</td>
                  <td align="center">51</td>
                  <td align="center">17</td>
                  <td align="center">0.154</td>
                  <td align="center">&lt; 0.001</td>
                </tr>
                <tr>
                  <td align="left">Drug abuse or addiction %</td>
                  <td align="center">25</td>
                  <td align="center">33</td>
                  <td align="center">62</td>
                  <td align="center">46</td>
                  <td align="center">0.325</td>
                  <td align="center">0.104</td>
                </tr>
                <tr>
                  <td align="left">Alcohol abuse or addiction %</td>
                  <td align="center">51</td>
                  <td align="center">61</td>
                  <td align="center">49</td>
                  <td align="center">18</td>
                  <td align="center">0.202</td>
                  <td align="center">&lt; 0.001</td>
                </tr>
                <tr>
                  <td align="left">Dementia, Alzheimer's disease or other brain damage %</td>
                  <td align="center">45</td>
                  <td align="center">44</td>
                  <td align="center">27</td>
                  <td align="center">34</td>
                  <td align="center">1.000</td>
                  <td align="center">0.538</td>
                </tr>
                <tr>
                  <td align="left">Schizophrenia or other psychoses %</td>
                  <td align="center">29</td>
                  <td align="center">28</td>
                  <td align="center">16</td>
                  <td align="center">34</td>
                  <td align="center">1.000</td>
                  <td align="center">0.056</td>
                </tr>
                <tr>
                  <td align="left">Anxiety, neurosis or panic disorder %</td>
                  <td align="center">23</td>
                  <td align="center">18</td>
                  <td align="center">11</td>
                  <td align="center">41</td>
                  <td align="center">0.517</td>
                  <td align="center">0.001</td>
                </tr>
                <tr>
                  <td align="left">Eating disorder %</td>
                  <td align="center">12</td>
                  <td align="center">6</td>
                  <td align="center">22</td>
                  <td align="center">19</td>
                  <td align="center">0.297</td>
                  <td align="center">0.840</td>
                </tr>
                <tr>
                  <td align="left">Manic depressive illness %</td>
                  <td align="center">11</td>
                  <td align="center">2</td>
                  <td align="center">22</td>
                  <td align="center">18</td>
                  <td align="center">0.059</td>
                  <td align="center">0.771</td>
                </tr>
              </tbody>
            </table>
            <table-wrap-foot>
              <p><sup>a </sup>Adjusted alpha = 0.05/8 = 0.006.</p>
              <p>* Data were missing for 6% of the valid sample (n = 23/407).</p>
            </table-wrap-foot>
          </table-wrap>
        </sec>
      </sec>
      <sec>
        <title>Perceptions regarding people with depression</title>
        <p>There was a substantial degree of variation in recognition of common symptoms of depression (see Table <xref ref-type="table" rid="T5">5</xref>). A significantly greater proportion of ANU students than Chinese students recognised "<italic>feeling overwhelmed</italic>" as a typical sign of depression. It is of interest to note that there were also some shifts in responses between the second and fourth year medical students, for instance a greater recognition following mental health training of fatigue as a typical symptom of depression.</p>
        <table-wrap position="float" id="T5">
          <label>Table 5</label>
          <caption>
            <p>Signs or symptoms typifying a person with depression as nominated by Australian students (N = 394*)</p>
          </caption>
          <table frame="hsides" rules="groups">
            <thead>
              <tr>
                <td/>
                <td align="center">
                  <bold>2<sup>nd </sup>Year Medical</bold>
                </td>
                <td align="center">
                  <bold>4<sup>th </sup>Year Medical</bold>
                </td>
                <td align="center">
                  <bold>ANU</bold>
                </td>
                <td align="center">
                  <bold>Chinese</bold>
                </td>
                <td align="center">
                  <bold>2<sup>nd </sup>vs 4<sup>th </sup>Year Medical</bold>
                </td>
                <td align="center">
                  <bold>ANU vs Chinese</bold>
                </td>
              </tr>
              <tr>
                <td/>
                <td colspan="4">
                  <hr/>
                </td>
                <td/>
                <td/>
              </tr>
              <tr>
                <td/>
                <td align="center">
                  <italic>n = 103</italic>
                </td>
                <td align="center">
                  <italic>n = 82</italic>
                </td>
                <td align="center">
                  <italic>n = 37</italic>
                </td>
                <td align="center">
                  <italic>n = 172</italic>
                </td>
                <td align="center">p value<sup>a</sup></td>
                <td align="center">p value<sup>a</sup></td>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td align="left">Being sad, down or miserable %</td>
                <td align="center">71</td>
                <td align="center">82</td>
                <td align="center">46</td>
                <td align="center">50</td>
                <td align="center">0.125</td>
                <td align="center">0.790</td>
              </tr>
              <tr>
                <td align="left">Sleep disturbance %</td>
                <td align="center">60</td>
                <td align="center">79</td>
                <td align="center">38</td>
                <td align="center">21</td>
                <td align="center">0.009</td>
                <td align="center">0.048</td>
              </tr>
              <tr>
                <td align="left">Being unhappy or depressed %</td>
                <td align="center">54</td>
                <td align="center">55</td>
                <td align="center">35</td>
                <td align="center">31</td>
                <td align="center">1.000</td>
                <td align="center">0.750</td>
              </tr>
              <tr>
                <td align="left">Feeling tired all the time %</td>
                <td align="center">31</td>
                <td align="center">55</td>
                <td align="center">38</td>
                <td align="center">24</td>
                <td align="center">0.002</td>
                <td align="center">0.121</td>
              </tr>
              <tr>
                <td align="left">Thinking "Life is not worth living" %</td>
                <td align="center">33</td>
                <td align="center">29</td>
                <td align="center">35</td>
                <td align="center">32</td>
                <td align="center">0.700</td>
                <td align="center">0.858</td>
              </tr>
              <tr>
                <td align="left">Thinking "I'm worthless" %</td>
                <td align="center">40</td>
                <td align="center">34</td>
                <td align="center">19</td>
                <td align="center">29</td>
                <td align="center">0.524</td>
                <td align="center">0.292</td>
              </tr>
              <tr>
                <td align="left">Thinking "I'm a failure" %</td>
                <td align="center">43</td>
                <td align="center">11</td>
                <td align="center">24</td>
                <td align="center">31</td>
                <td align="center">&lt; 0.001</td>
                <td align="center">0.514</td>
              </tr>
              <tr>
                <td align="left">Having no confidence %</td>
                <td align="center">29</td>
                <td align="center">16</td>
                <td align="center">32</td>
                <td align="center">29</td>
                <td align="center">0.051</td>
                <td align="center">0.835</td>
              </tr>
              <tr>
                <td align="left">Feeling frustrated %</td>
                <td align="center">7</td>
                <td align="center">1</td>
                <td align="center">22</td>
                <td align="center">37</td>
                <td align="center">0.137</td>
                <td align="center">0.105</td>
              </tr>
              <tr>
                <td align="left">Feeling overwhelmed %</td>
                <td align="center">28</td>
                <td align="center">13</td>
                <td align="center">51</td>
                <td align="center">11</td>
                <td align="center">0.025</td>
                <td align="center">&lt; 0.001</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <p><sup>a </sup>Adjusted alpha = 0.05/10 = 0.005.</p>
            <p>* Data were missing for 3% of the valid sample (n = 13/407).</p>
          </table-wrap-foot>
        </table-wrap>
      </sec>
      <sec>
        <title>Common behaviours and experiences</title>
        <p>When asked about the typical behaviours and experiences of people with depression, there were some differences among the student groups (see Table <xref ref-type="table" rid="T6">6</xref>). Most notably, withdrawal was recognised as a typical behaviour by over two-thirds of the ANU students, but less than a third of the Chinese students. Otherwise the responses in these two groups were largely similar. In terms of possible training effects, the only significant difference between the medical student groups was for "<italic>lack of self care</italic>", fewer fourth year students nominating this behaviour. Suicidal ideation or behaviour was also less frequently nominated as typical of people with depression following training.</p>
        <table-wrap position="float" id="T6">
          <label>Table 6</label>
          <caption>
            <p>Typical behaviours and experiences of people with depression as nominated by Australian students (N = 394*)</p>
          </caption>
          <table frame="hsides" rules="groups">
            <thead>
              <tr>
                <td/>
                <td align="center">
                  <bold>2<sup>nd </sup>Year Medical</bold>
                </td>
                <td align="center">
                  <bold>4<sup>th </sup>Year Medical</bold>
                </td>
                <td align="center">
                  <bold>ANU</bold>
                </td>
                <td align="center">
                  <bold>Chinese</bold>
                </td>
                <td align="center">
                  <bold>2<sup>nd </sup>vs 4<sup>th </sup>Year Medical</bold>
                </td>
                <td align="center">
                  <bold>ANU vs Chinese</bold>
                </td>
              </tr>
              <tr>
                <td/>
                <td colspan="4">
                  <hr/>
                </td>
                <td/>
                <td/>
              </tr>
              <tr>
                <td/>
                <td align="center">
                  <italic>n = 103</italic>
                </td>
                <td align="center">
                  <italic>n = 82</italic>
                </td>
                <td align="center">
                  <italic>n = 37</italic>
                </td>
                <td align="center">
                  <italic>n = 172</italic>
                </td>
                <td align="center">p value<sup>a</sup></td>
                <td align="center">p value<sup>a</sup></td>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td align="left">Be unable to concentrate or have difficulty thinking %</td>
                <td align="center">62</td>
                <td align="center">78</td>
                <td align="center">41</td>
                <td align="center">35</td>
                <td align="center">0.030</td>
                <td align="center">0.644</td>
              </tr>
              <tr>
                <td align="left">Stop doing things they enjoy %</td>
                <td align="center">63</td>
                <td align="center">65</td>
                <td align="center">32</td>
                <td align="center">18</td>
                <td align="center">0.952</td>
                <td align="center">0.081</td>
              </tr>
              <tr>
                <td align="left">Withdraw from close family and friends %</td>
                <td align="center">52</td>
                <td align="center">42</td>
                <td align="center">70</td>
                <td align="center">28</td>
                <td align="center">0.228</td>
                <td align="center">&lt; 0.001</td>
              </tr>
              <tr>
                <td align="left">Have relationship or family <italic>problems </italic>%</td>
                <td align="center">37</td>
                <td align="center">44</td>
                <td align="center">27</td>
                <td align="center">34</td>
                <td align="center">0.415</td>
                <td align="center">0.509</td>
              </tr>
              <tr>
                <td align="left">Stop going out %</td>
                <td align="center">38</td>
                <td align="center">39</td>
                <td align="center">32</td>
                <td align="center">26</td>
                <td align="center">0.993</td>
                <td align="center">0.566</td>
              </tr>
              <tr>
                <td align="left">Become dependent on alcohol, drugs or sedatives %</td>
                <td align="center">19</td>
                <td align="center">37</td>
                <td align="center">41</td>
                <td align="center">38</td>
                <td align="center">0.014</td>
                <td align="center">0.900</td>
              </tr>
              <tr>
                <td align="left">Have suicidal thoughts or behaviours %</td>
                <td align="center">46</td>
                <td align="center">26</td>
                <td align="center">35</td>
                <td align="center">29</td>
                <td align="center">0.008</td>
                <td align="center">0.595</td>
              </tr>
              <tr>
                <td align="left">Not get things done at school/work %</td>
                <td align="center">28</td>
                <td align="center">38</td>
                <td align="center">35</td>
                <td align="center">26</td>
                <td align="center">0.217</td>
                <td align="center">0.366</td>
              </tr>
              <tr>
                <td align="left">Lack of self care (e.g. have a change in their personal hygiene habits) %</td>
                <td align="center">33</td>
                <td align="center">12</td>
                <td align="center">14</td>
                <td align="center">21</td>
                <td align="center">0.002</td>
                <td align="center">0.422</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <p><sup>a</sup>Adjusted alpha = 0.05/9 = 0.006.</p>
            <p>* Data were missing for 3% of the valid sample (n = 13/407).</p>
          </table-wrap-foot>
        </table-wrap>
        <p>When asked to estimate the proportion of people who will experience depression in their lives, there was a significant difference between the non-medical student groups in the proportion correctly nominating "one in five" (51% of the ANU students and 23% of the Chinese students), but not between the medical students (49% second year and 60% of fourth year students; see Table <xref ref-type="table" rid="T7">7</xref>).</p>
        <table-wrap position="float" id="T7">
          <label>Table 7</label>
          <caption>
            <p>Students perceptions of the approximate proportion of people who experience depression at some point in their lives (N = 391*)</p>
          </caption>
          <table frame="hsides" rules="groups">
            <thead>
              <tr>
                <td/>
                <td align="center">
                  <bold>2<sup>nd </sup>Year Medical</bold>
                </td>
                <td align="center">
                  <bold>4<sup>th </sup>Year Medical</bold>
                </td>
                <td align="center">
                  <bold>ANU</bold>
                </td>
                <td align="center">
                  <bold>Chinese</bold>
                </td>
                <td align="center">
                  <bold>2<sup>nd </sup>vs 4<sup>th </sup>Year Medical</bold>
                </td>
                <td align="center">
                  <bold>ANU vs Chinese</bold>
                </td>
              </tr>
              <tr>
                <td/>
                <td colspan="4">
                  <hr/>
                </td>
                <td/>
                <td/>
              </tr>
              <tr>
                <td/>
                <td align="center">
                  <italic>n = 103</italic>
                </td>
                <td align="center">
                  <italic>n = 82</italic>
                </td>
                <td align="center">
                  <italic>n = 37</italic>
                </td>
                <td align="center">
                  <italic>n = 169</italic>
                </td>
                <td align="center">p value</td>
                <td align="center">p value</td>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td align="left">One in 50 people %</td>
                <td align="center">4</td>
                <td align="center">1</td>
                <td align="center">11</td>
                <td align="center">17</td>
                <td/>
                <td/>
              </tr>
              <tr>
                <td align="left">One in 20 people %</td>
                <td align="center">18</td>
                <td align="center">13</td>
                <td align="center">22</td>
                <td align="center">27</td>
                <td/>
                <td/>
              </tr>
              <tr>
                <td align="left">One in 10 people %</td>
                <td align="center">28</td>
                <td align="center">26</td>
                <td align="center">16</td>
                <td align="center">22</td>
                <td/>
                <td/>
              </tr>
              <tr>
                <td align="left">One in 5 people %</td>
                <td align="center">49</td>
                <td align="center">60</td>
                <td align="center">51</td>
                <td align="center">23</td>
                <td align="center">0.171</td>
                <td align="center">0.001</td>
              </tr>
              <tr>
                <td align="left">Don't know %</td>
                <td align="center">1</td>
                <td align="center">0</td>
                <td align="center">0</td>
                <td align="center">11</td>
                <td/>
                <td/>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <p>* Data were missing for 4% of the valid sample (n = 16/407).</p>
          </table-wrap-foot>
        </table-wrap>
      </sec>
      <sec>
        <title>Help seeking</title>
        <p>Students were asked to rate how likely they would be to seek help from a list of health professionals (see Table <xref ref-type="table" rid="T8">8</xref>). There were no significant differences between the medical student groups. The most notable difference between the ANU and ethnic Chinese students was the proportion reporting they would be probably or definitely likely to seek help from a pharmacist, the proportion being seven times higher in the Chinese group.</p>
        <table-wrap position="float" id="T8">
          <label>Table 8</label>
          <caption>
            <p>Proportion of Australian students who reported being probably or definitely likely to seek professional help if they thought they were experiencing depression (N = 345*)</p>
          </caption>
          <table frame="hsides" rules="groups">
            <thead>
              <tr>
                <td/>
                <td align="center">
                  <bold>2<sup>nd </sup>Year Medical</bold>
                </td>
                <td align="center">
                  <bold>4<sup>th </sup>Year Medical</bold>
                </td>
                <td align="center">
                  <bold>ANU</bold>
                </td>
                <td align="center">
                  <bold>Chinese</bold>
                </td>
                <td align="center">
                  <bold>2<sup>nd </sup>vs 4<sup>th </sup>Year Medical</bold>
                </td>
                <td align="center">
                  <bold>ANU vs Chinese</bold>
                </td>
              </tr>
              <tr>
                <td/>
                <td colspan="4">
                  <hr/>
                </td>
                <td/>
                <td/>
              </tr>
              <tr>
                <td/>
                <td align="center">
                  <italic>n = 90</italic>
                </td>
                <td align="center">
                  <italic>n = 78</italic>
                </td>
                <td align="center">
                  <italic>n = 37</italic>
                </td>
                <td align="center">
                  <italic>n = 140</italic>
                </td>
                <td align="center">p value<sup>a</sup></td>
                <td align="center">p value<sup>a</sup></td>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td align="left">Counsellor %</td>
                <td align="center">54</td>
                <td align="center">46</td>
                <td align="center">53</td>
                <td align="center">58</td>
                <td align="center">0.359</td>
                <td align="center">0.719</td>
              </tr>
              <tr>
                <td align="left">General or family doctor %</td>
                <td align="center">82</td>
                <td align="center">89</td>
                <td align="center">47</td>
                <td align="center">67</td>
                <td align="center">0.358</td>
                <td align="center">0.048</td>
              </tr>
              <tr>
                <td align="left">Pharmacist %</td>
                <td align="center">8</td>
                <td align="center">3</td>
                <td align="center">6</td>
                <td align="center">43</td>
                <td align="center">0.250</td>
                <td align="center">&lt; 0.001</td>
              </tr>
              <tr>
                <td align="left">Psychiatrist %</td>
                <td align="center">51</td>
                <td align="center">65</td>
                <td align="center">43</td>
                <td align="center">55</td>
                <td align="center">0.085</td>
                <td align="center">0.301</td>
              </tr>
              <tr>
                <td align="left">Psychologist %</td>
                <td align="center">59</td>
                <td align="center">56</td>
                <td align="center">44</td>
                <td align="center">69</td>
                <td align="center">0.897</td>
                <td align="center">0.011</td>
              </tr>
              <tr>
                <td align="left">Social worker %</td>
                <td align="center">11</td>
                <td align="center">11</td>
                <td align="center">31</td>
                <td align="center">48</td>
                <td align="center">1.000</td>
                <td align="center">0.092</td>
              </tr>
              <tr>
                <td align="left">Welfare officer %</td>
                <td align="center">2</td>
                <td align="center">1</td>
                <td align="center">26</td>
                <td align="center">42</td>
                <td align="center">1.000</td>
                <td align="center">0.115</td>
              </tr>
              <tr>
                <td align="left">No one/wouldn't seek help %</td>
                <td align="center">32</td>
                <td align="center">33</td>
                <td align="center">47</td>
                <td align="center">42</td>
                <td align="center">1.000</td>
                <td align="center">0.790</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <p><sup>a </sup>Adjusted alpha = 0.05/8 = 0.006.</p>
            <p>* Data were missing for 8% of the valid sample (n = 29/374).</p>
          </table-wrap-foot>
        </table-wrap>
        <p>Students were then asked about seeking help from non-professional sources. Again, there were no significant differences between second and fourth year medical students. A greater proportion of Chinese students than ANU students indicated they were likely to seek help from non-professionals (such as acupuncturists, religious persons, naturopaths or herbalists, personal trainers and traditional healers; see Table <xref ref-type="table" rid="T9">9</xref>).</p>
        <table-wrap position="float" id="T9">
          <label>Table 9</label>
          <caption>
            <p>Proportion of Australian students who reported being probably or definitely likely to seek non-professional help if they thought they were experiencing depression (N = 350*)</p>
          </caption>
          <table frame="hsides" rules="groups">
            <thead>
              <tr>
                <td/>
                <td align="center">
                  <bold>2<sup>nd </sup>Year Medical</bold>
                </td>
                <td align="center">
                  <bold>4<sup>th </sup>Year Medical</bold>
                </td>
                <td align="center">
                  <bold>ANU</bold>
                </td>
                <td align="center">
                  <bold>Chinese</bold>
                </td>
                <td align="center">
                  <bold>2<sup>nd </sup>vs 4<sup>th </sup>Year Medical</bold>
                </td>
                <td align="center">
                  <bold>ANU vs Chinese</bold>
                </td>
              </tr>
              <tr>
                <td/>
                <td colspan="4">
                  <hr/>
                </td>
                <td/>
                <td/>
              </tr>
              <tr>
                <td/>
                <td align="center">
                  <italic>n = 91</italic>
                </td>
                <td align="center">
                  <italic>n = 78</italic>
                </td>
                <td align="center">
                  <italic>n = 37</italic>
                </td>
                <td align="center">
                  <italic>n = 144</italic>
                </td>
                <td align="center">p value<sup>a</sup></td>
                <td align="center">p value<sup>a</sup></td>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td align="left">Acupuncturist %</td>
                <td align="center">5</td>
                <td align="center">4</td>
                <td align="center">6</td>
                <td align="center">34</td>
                <td align="center">1.000</td>
                <td align="center">0.002</td>
              </tr>
              <tr>
                <td align="left">Clergy, priest or other religious person %</td>
                <td align="center">23</td>
                <td align="center">14</td>
                <td align="center">11</td>
                <td align="center">44</td>
                <td align="center">0.235</td>
                <td align="center">0.001</td>
              </tr>
              <tr>
                <td align="left">Family %</td>
                <td align="center">89</td>
                <td align="center">87</td>
                <td align="center">71</td>
                <td align="center">84</td>
                <td align="center">0.873</td>
                <td align="center">0.140</td>
              </tr>
              <tr>
                <td align="left">Friends %</td>
                <td align="center">88</td>
                <td align="center">87</td>
                <td align="center">83</td>
                <td align="center">88</td>
                <td align="center">1.000</td>
                <td align="center">0.659</td>
              </tr>
              <tr>
                <td align="left">Naturopath or herbalist %</td>
                <td align="center">9</td>
                <td align="center">5</td>
                <td align="center">11</td>
                <td align="center">42</td>
                <td align="center">0.522</td>
                <td align="center">0.002</td>
              </tr>
              <tr>
                <td align="left">Personal trainer, exercise manager or relaxation instructor %</td>
                <td align="center">26</td>
                <td align="center">32</td>
                <td align="center">19</td>
                <td align="center">55</td>
                <td align="center">0.504</td>
                <td align="center">&lt; 0.001</td>
              </tr>
              <tr>
                <td align="left">Traditional healer %</td>
                <td align="center">7</td>
                <td align="center">3</td>
                <td align="center">6</td>
                <td align="center">35</td>
                <td align="center">0.369</td>
                <td align="center">0.001</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <p><sup>a </sup>Adjusted alpha = 0.05/7 = 0.007.</p>
            <p>* Data were missing for 6% of the valid sample (n = 24/374).</p>
          </table-wrap-foot>
        </table-wrap>
        <p>Students were asked to rate the perceived helpfulness or harmfulness of various common treatments for depression (see Table <xref ref-type="table" rid="T10">10</xref>). There were no significant differences between the medical students in terms of the proportion nominating treatments as helpful. However, differences emerged between the non-medical students (ANU and ethnic Chinese). Over two-thirds of the Chinese students (72%) rated "<italic>reading self-help books</italic>" as helpful, compared with only 39% of ANU students. More ANU students (70%) thought antidepressant medications would be helpful than did Chinese students (46%). Similarly, there was trend towards a difference regarding the helpfulness of "<italic>having an occasional alcoholic drink</italic>", with 33% of Chinese students considering this helpful, compared with only 13% of ANU students.</p>
        <table-wrap position="float" id="T10">
          <label>Table 10</label>
          <caption>
            <p>Students perceptions of the helpfulness of specific treatments for depression (N = 342*)</p>
          </caption>
          <table frame="hsides" rules="groups">
            <thead>
              <tr>
                <td/>
                <td align="center">
                  <bold>2<sup>nd </sup>Year Medical</bold>
                </td>
                <td align="center">
                  <bold>4<sup>th </sup>Year Medical</bold>
                </td>
                <td align="center">
                  <bold>ANU</bold>
                </td>
                <td align="center">
                  <bold>Chinese</bold>
                </td>
                <td align="center">
                  <bold>2<sup>nd </sup>vs 4<sup>th </sup>Year Medical</bold>
                </td>
                <td align="center">
                  <bold>ANU vs Chinese</bold>
                </td>
              </tr>
              <tr>
                <td/>
                <td colspan="4">
                  <hr/>
                </td>
                <td/>
                <td/>
              </tr>
              <tr>
                <td/>
                <td align="center">
                  <italic>n = 91</italic>
                </td>
                <td align="center">
                  <italic>n = 78</italic>
                </td>
                <td align="center">
                  <italic>n = 36</italic>
                </td>
                <td align="center">
                  <italic>n = 133</italic>
                </td>
                <td align="center">p value<sup>a</sup></td>
                <td align="center">p value<sup>a</sup></td>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td align="left">Becoming more physically active %</td>
                <td align="center">99</td>
                <td align="center">100</td>
                <td align="center">97</td>
                <td align="center">84</td>
                <td align="center">1.000</td>
                <td align="center">0.063</td>
              </tr>
              <tr>
                <td align="left">Changing your diet %</td>
                <td align="center">71</td>
                <td align="center">55</td>
                <td align="center">71</td>
                <td align="center">63</td>
                <td align="center">0.069</td>
                <td align="center">0.547</td>
              </tr>
              <tr>
                <td align="left">Having an occasional alcoholic drink %</td>
                <td align="center">17</td>
                <td align="center">21</td>
                <td align="center">13</td>
                <td align="center">33</td>
                <td align="center">0.676</td>
                <td align="center">0.044</td>
              </tr>
              <tr>
                <td align="left">Reading about people with similar problems and how they have dealt with them %</td>
                <td align="center">85</td>
                <td align="center">88</td>
                <td align="center">65</td>
                <td align="center">75</td>
                <td align="center">0.796</td>
                <td align="center">0.303</td>
              </tr>
              <tr>
                <td align="left">Reading self-help book(s) %</td>
                <td align="center">59</td>
                <td align="center">69</td>
                <td align="center">39</td>
                <td align="center">72</td>
                <td align="center">0.273</td>
                <td align="center">0.001</td>
              </tr>
              <tr>
                <td align="left">Taking antidepressant medications %</td>
                <td align="center">92</td>
                <td align="center">99</td>
                <td align="center">70</td>
                <td align="center">46</td>
                <td align="center">0.115</td>
                <td align="center">0.029</td>
              </tr>
              <tr>
                <td align="left">Taking natural remedies (e.g. vitamins) %</td>
                <td align="center">26</td>
                <td align="center">28</td>
                <td align="center">42</td>
                <td align="center">51</td>
                <td align="center">0.992</td>
                <td align="center">0.500</td>
              </tr>
              <tr>
                <td align="left">Taking sleeping tablets or sedatives %</td>
                <td align="center">24</td>
                <td align="center">12</td>
                <td align="center">14</td>
                <td align="center">31</td>
                <td align="center">0.092</td>
                <td align="center">0.117</td>
              </tr>
              <tr>
                <td align="left">Using brief counselling therapies (e.g. cognitive and/or behavioural therapies) %</td>
                <td align="center">100</td>
                <td align="center">96</td>
                <td align="center">82</td>
                <td align="center">68</td>
                <td align="center">0.184</td>
                <td align="center">0.178</td>
              </tr>
              <tr>
                <td align="left">Using long-term counselling %</td>
                <td align="center">94</td>
                <td align="center">87</td>
                <td align="center">77</td>
                <td align="center">66</td>
                <td align="center">0.156</td>
                <td align="center">0.352</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <p><sup>a </sup>Adjusted alpha = 0.05/10 = 0.005.</p>
            <p>* Data were missing for 9% of the valid sample (n = 32/374).</p>
          </table-wrap-foot>
        </table-wrap>
      </sec>
      <sec>
        <title>Discrimination and stigma</title>
        <p>When asked about the perceived likelihood of discrimination if they, or someone close to them, experienced depression, the only difference in response amongst the medical students was regarding "<italic>a government or other public welfare agency</italic>", with a quarter of second year medical students believing this was definitely or probably likely, compared with 42% of fourth year medical students (see Table <xref ref-type="table" rid="T11">11</xref>). There was greater disparity in the perceived likelihood of discrimination between the non-medical groups. Only 7% of ANU students felt that discrimination was definitely or probably likely within the context of a public or private hospital, compared with 44% of Chinese students. Similarly, only 4% of ANU students felt that discrimination was likely from a "<italic>doctor or other health professional</italic>" compared with 37% of the Chinese students.</p>
        <table-wrap position="float" id="T11">
          <label>Table 11</label>
          <caption>
            <p>Proportion of Australian students who reported discrimination was probably or definitely likely from various persons or organisations if they, or someone close to them was experiencing depression (N = 298*)</p>
          </caption>
          <table frame="hsides" rules="groups">
            <thead>
              <tr>
                <td/>
                <td align="center">
                  <bold>2<sup>nd </sup>Year Medical</bold>
                </td>
                <td align="center">
                  <bold>4<sup>th </sup>Year Medical</bold>
                </td>
                <td align="center">
                  <bold>ANU</bold>
                </td>
                <td align="center">
                  <bold>Chinese</bold>
                </td>
                <td align="center">
                  <bold>2<sup>nd </sup>vs 4<sup>th </sup>Year Medical</bold>
                </td>
                <td align="center">
                  <bold>ANU vs Chinese</bold>
                </td>
              </tr>
              <tr>
                <td/>
                <td colspan="4">
                  <hr/>
                </td>
                <td/>
                <td/>
              </tr>
              <tr>
                <td/>
                <td align="center">
                  <italic>n = 69</italic>
                </td>
                <td align="center">
                  <italic>n = 70</italic>
                </td>
                <td align="center">
                  <italic>n = 29</italic>
                </td>
                <td align="center">
                  <italic>n = 130</italic>
                </td>
                <td align="center">p value<sup>a</sup></td>
                <td align="center">p value<sup>a</sup></td>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td align="left">A bank, insurance company or other financial institution %</td>
                <td align="center">42</td>
                <td align="center">50</td>
                <td align="center">54</td>
                <td align="center">44</td>
                <td align="center">0.426</td>
                <td align="center">0.476</td>
              </tr>
              <tr>
                <td align="left">A government or other public welfare agency %</td>
                <td align="center">25</td>
                <td align="center">42</td>
                <td align="center">19</td>
                <td align="center">39</td>
                <td align="center">0.049</td>
                <td align="center">0.073</td>
              </tr>
              <tr>
                <td align="left">A public or private hospital %</td>
                <td align="center">17</td>
                <td align="center">25</td>
                <td align="center">7</td>
                <td align="center">44</td>
                <td align="center">0.308</td>
                <td align="center">0.001</td>
              </tr>
              <tr>
                <td align="left">Other people who don't know you well %</td>
                <td align="center">94</td>
                <td align="center">88</td>
                <td align="center">89</td>
                <td align="center">66</td>
                <td align="center">0.379</td>
                <td align="center">0.048</td>
              </tr>
              <tr>
                <td align="left">Your doctor or other health professional %</td>
                <td align="center">7</td>
                <td align="center">18</td>
                <td align="center">4</td>
                <td align="center">37</td>
                <td align="center">0.120</td>
                <td align="center">0.002</td>
              </tr>
              <tr>
                <td align="left">Your employer %</td>
                <td align="center">72</td>
                <td align="center">77</td>
                <td align="center">67</td>
                <td align="center">67</td>
                <td align="center">0.621</td>
                <td align="center">1.000</td>
              </tr>
              <tr>
                <td align="left">Your family %</td>
                <td align="center">18</td>
                <td align="center">19</td>
                <td align="center">21</td>
                <td align="center">42</td>
                <td align="center">1.000</td>
                <td align="center">0.052</td>
              </tr>
              <tr>
                <td align="left">Your friends %</td>
                <td align="center">24</td>
                <td align="center">22</td>
                <td align="center">21</td>
                <td align="center">43</td>
                <td align="center">1.000</td>
                <td align="center">0.042</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <p><sup>a </sup>Adjusted alpha = 0.05/8 = 0.006.</p>
            <p>* Data were missing for 12% of the valid sample (n = 41/339).</p>
          </table-wrap-foot>
        </table-wrap>
        <p>Students were asked whether they agreed or disagreed with statements concerning people with severe depression (see Table <xref ref-type="table" rid="T12">12</xref>). There were no significant differences between attitudes towards people with severe depression between the medical student groups. In contrast, 48% of Chinese students agreed with the statement "<italic>have themselves to blame</italic>", compared with 7% of ANU students; and 39% of Chinese students agreed with the statement that people with severe depression "<italic>shouldn't have children in case they pass on the illness</italic>" compared with none of the ANU students.</p>
        <table-wrap position="float" id="T12">
          <label>Table 12</label>
          <caption>
            <p>Proportion of Australian students who agreed or strongly agreed with statements regarding people with severe depression (N = 298*)</p>
          </caption>
          <table frame="hsides" rules="groups">
            <thead>
              <tr>
                <td align="left">
                  <bold>People with depression...</bold>
                </td>
                <td align="center">
                  <bold>2<sup>nd </sup>Year Medical</bold>
                </td>
                <td align="center">
                  <bold>4<sup>th </sup>Year Medical</bold>
                </td>
                <td align="center">
                  <bold>ANU</bold>
                </td>
                <td align="center">
                  <bold>Chinese</bold>
                </td>
                <td align="center">
                  <bold>2<sup>nd </sup>vs 4<sup>th </sup>Year Medical</bold>
                </td>
                <td align="center">
                  <bold>ANU vs Chinese</bold>
                </td>
              </tr>
              <tr>
                <td/>
                <td colspan="4">
                  <hr/>
                </td>
                <td/>
                <td/>
              </tr>
              <tr>
                <td/>
                <td align="center">
                  <italic>n = 70</italic>
                </td>
                <td align="center">
                  <italic>n = 70</italic>
                </td>
                <td align="center">
                  <italic>n = 30</italic>
                </td>
                <td align="center">
                  <italic>n = 128</italic>
                </td>
                <td align="center">p value<sup>a</sup></td>
                <td align="center">p value<sup>a</sup></td>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td align="left">Are dangerous to others %</td>
                <td align="center">5</td>
                <td align="center">3</td>
                <td align="center">22</td>
                <td align="center">37</td>
                <td align="center">0.987</td>
                <td align="center">0.222</td>
              </tr>
              <tr>
                <td align="left">Are hard to talk to %</td>
                <td align="center">72</td>
                <td align="center">66</td>
                <td align="center">60</td>
                <td align="center">68</td>
                <td align="center">0.554</td>
                <td align="center">0.668</td>
              </tr>
              <tr>
                <td align="left">Are often artistic or creative people when they are well %</td>
                <td align="center">53</td>
                <td align="center">45</td>
                <td align="center">65</td>
                <td align="center">54</td>
                <td align="center">0.583</td>
                <td align="center">0.564</td>
              </tr>
              <tr>
                <td align="left">Are often very productive people when they are well %</td>
                <td align="center">94</td>
                <td align="center">90</td>
                <td align="center">80</td>
                <td align="center">55</td>
                <td align="center">0.690</td>
                <td align="center">0.068</td>
              </tr>
              <tr>
                <td align="left">Have themselves to blame %</td>
                <td align="center">6</td>
                <td align="center">1</td>
                <td align="center">7</td>
                <td align="center">48</td>
                <td align="center">0.362</td>
                <td align="center">&lt; 0.001</td>
              </tr>
              <tr>
                <td align="left">Often make good employees when they are well %</td>
                <td align="center">93</td>
                <td align="center">90</td>
                <td align="center">77</td>
                <td align="center">60</td>
                <td align="center">0.843</td>
                <td align="center">0.316</td>
              </tr>
              <tr>
                <td align="left">Often perform poorly as parents %</td>
                <td align="center">51</td>
                <td align="center">45</td>
                <td align="center">42</td>
                <td align="center">53</td>
                <td align="center">0.650</td>
                <td align="center">0.460</td>
              </tr>
              <tr>
                <td align="left">Often try even harder to contribute to their families or work when they are well %</td>
                <td align="center">77</td>
                <td align="center">81</td>
                <td align="center">77</td>
                <td align="center">64</td>
                <td align="center">0.879</td>
                <td align="center">0.371</td>
              </tr>
              <tr>
                <td align="left">Shouldn't have children in case they pass on the illness %</td>
                <td align="center">0</td>
                <td align="center">1</td>
                <td align="center">0</td>
                <td align="center">39</td>
                <td align="center">1.000</td>
                <td align="center">&lt; 0.001</td>
              </tr>
              <tr>
                <td align="left">Should pull themselves together %</td>
                <td align="center">16</td>
                <td align="center">18</td>
                <td align="center">23</td>
                <td align="center">41</td>
                <td align="center">0.975</td>
                <td align="center">0.143</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <p><sup>a </sup>Adjusted alpha = 0.05/10 = 0.005.</p>
            <p>* Data were missing for 12% of the valid sample (n = 41/339).</p>
          </table-wrap-foot>
        </table-wrap>
      </sec>
      <sec>
        <title>K10 and SPHERE</title>
        <p>As shown in Table <xref ref-type="table" rid="T13">13</xref>, more than half of the students were experiencing medium or high levels of psychological distress (as measured by the K10) during the 30 days prior to participation in the study.</p>
        <table-wrap position="float" id="T13">
          <label>Table 13</label>
          <caption>
            <p>Levels of current psychological distress as measured by the K10 and the SPHERE (N = 309*)</p>
          </caption>
          <table frame="hsides" rules="groups">
            <thead>
              <tr>
                <td/>
                <td/>
                <td align="center">
                  <bold>2<sup>nd </sup>Year Medical</bold>
                </td>
                <td align="center">
                  <bold>4<sup>th </sup>Year Medical</bold>
                </td>
                <td align="center">
                  <bold>ANU</bold>
                </td>
                <td align="center">
                  <bold>Chinese</bold>
                </td>
                <td align="center">
                  <bold>2<sup>nd </sup>vs 4<sup>th </sup>Year Medical</bold>
                </td>
                <td align="center">
                  <bold>ANU vs Chinese</bold>
                </td>
              </tr>
              <tr>
                <td/>
                <td/>
                <td colspan="4">
                  <hr/>
                </td>
                <td/>
                <td/>
              </tr>
              <tr>
                <td/>
                <td/>
                <td align="center">
                  <italic>n = 77</italic>
                </td>
                <td align="center">
                  <italic>n = 71</italic>
                </td>
                <td align="center">
                  <italic>n = 35</italic>
                </td>
                <td align="center">
                  <italic>n = 126</italic>
                </td>
                <td align="center">
                  <bold>p value</bold>
                </td>
                <td align="center">
                  <bold>p value</bold>
                </td>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td align="left">
                  <bold>K10</bold>
                </td>
                <td align="left">low or no psychological distress %</td>
                <td align="center">48</td>
                <td align="center">52</td>
                <td align="center">55</td>
                <td align="center">24</td>
                <td/>
                <td/>
              </tr>
              <tr>
                <td/>
                <td align="left">medium or high psychological distress %</td>
                <td align="center">53</td>
                <td align="center">48</td>
                <td align="center">45</td>
                <td align="center">76</td>
                <td align="center">0.687</td>
                <td align="center">0.002</td>
              </tr>
              <tr>
                <td align="left">
                  <bold>SPHERE</bold>
                </td>
                <td align="left">Any PSYCH-6 disorder %</td>
                <td align="center">31</td>
                <td align="center">25</td>
                <td align="center">26</td>
                <td align="center">56</td>
                <td align="center">0.547</td>
                <td align="center">0.003</td>
              </tr>
              <tr>
                <td/>
                <td align="left">Any SOMA-6 disorder %</td>
                <td align="center">26</td>
                <td align="center">20</td>
                <td align="center">46</td>
                <td align="center">56</td>
                <td align="center">0.450</td>
                <td align="center">0.355</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <p>K10 = Kessler Psychological Distress scale, SPHERE = Somatic and Psychological HEalth REport, PSYCH-6 disorder = a total score of two or more for the six SPHERE psychological items indicating strong psychological symptoms, SOMA-6 = a total score of three or more for the six SPHERE somatic items indicating strong somatic symptoms.</p>
            <p>* Data were missing for 7% of the valid sample (n = 24/333).</p>
          </table-wrap-foot>
        </table-wrap>
        <p>A significantly greater proportion of the Chinese students showed medium or high levels of psychological distress on the K10 than the ANU students, whereas there was no difference between the medical student groups. Consistent with this, the Chinese students indicated experiencing substantial psychological and somatic symptoms as measured by the SPHERE, with substantial psychological symptoms being significantly more prevalent than in the ANU students.</p>
      </sec>
    </sec>
    <sec>
      <title>Discussion</title>
      <p>The IDLS has been developed specifically to track understanding of depression as a general health condition. For the IDLS to be useful within ethnically diverse communities or groups of health professionals over time, it should first be sensitive to likely baseline differences between relevant groups residing in the same country. While there is little published research regarding the specifics of cross-cultural differences regarding attitudes and beliefs around depression, studies published to date suggest attitudes to mental illness in general differ between Asian and western cultures [<xref ref-type="bibr" rid="B18">18</xref>,<xref ref-type="bibr" rid="B19">19</xref>]. The study reported here demonstrates that the IDLS does detect clear differences between medical students in second and fourth year courses, and between non-medical students from ethnic Chinese backgrounds and other undergraduates residing in Australia. These differences are obvious across all the key areas (depression within the context of major general health problems and major mental health problems, common psychological symptoms of depression, attitudes to the use of evidence-based treatments, patterns of health care utilisation and expectations of discrimination).</p>
      <p>The basic utility of the instrument for potential use in wider epidemiological, cross-cultural, longitudinal or interventional studies is given preliminary support by the current results. However, it must be noted that convenience samples were utilised in this study, thus limiting the conclusions that can be drawn. The effect of health training on responses would ideally be confirmed by a longitudinal study, sampling the same individuals prior to and following mental health training. Another limitation was the age difference within each of the comparison student groups. While there did not appear to be a systematic effect with increasing age, the study would warrant repetition in age matched samples. While we acknowledge that a small proportion of the Chinese students had a medical or health care background, and that a small proportion of the other students (medical or from ANU) were Chinese, this would most probably reduce the likelihood of finding differences attributable to culture or training. As the instrument has been designed in consultation with professional leaders in a wide range of Asia-Pacific countries, we now encourage utilisation of at least the English version of the instrument in relevant studies among English-literate groups within those countries. A second set of studies will now address the utility of translated versions of the instrument for use in other population groups not literate in English within those countries.</p>
      <p>Within the Australia setting, the differences detected between the student groups examined are perhaps unexpected and worthy of further comment. Specific health care training clearly has an association with increasing recognition of the general health burden due to depression. This association also appears to increase with the degree of that training and exposure to direct clinical experience of mental disorders (i.e. fourth versus second year medical students). The importance of medical courses increasing their commitment to this style of teaching in Australia and across the region needs to be emphasised [<xref ref-type="bibr" rid="B20">20</xref>,<xref ref-type="bibr" rid="B21">21</xref>]. Secondly, those students from ethnic Chinese backgrounds in Australia have markedly different knowledge and attitudes towards depression. This does not simply reflect an unwillingness to discuss such difficulties as the relevant self-report instruments indicate moderately high levels of psychological distress among this cohort. The lack of recognition of depression as a general health problem, the tendency to recognise features more typically conceptualised as anxiety, the greater reliance on pharmacists and alternative practitioners rather than traditional medical services and the expectation of greater discrimination all appear to be consistent with attitudes expressed within other ethnic Chinese groups not residing in Australia [<xref ref-type="bibr" rid="B22">22</xref>,<xref ref-type="bibr" rid="B23">23</xref>]. Such effects have major implications for current public awareness and health literacy interventions in Australia [<xref ref-type="bibr" rid="B4">4</xref>,<xref ref-type="bibr" rid="B7">7</xref>]. While we are recording substantial shifts in public attitudes among the broad Australian public [<xref ref-type="bibr" rid="B12">12</xref>], we may need to deal more effectively with those specific attitudes held by key ethnic groups or those who have recently arrived in our country.</p>
    </sec>
    <sec>
      <title>Conclusion</title>
      <p>The IDLS does detect significant differences in understanding of depression among groups from different ethnic backgrounds and between those who differ in terms of prior health training. These results provide preliminary support for the suitability of the IDLS for use in a wider international context.</p>
    </sec>
    <sec>
      <title>Abbreviations</title>
      <p>ANU- The Australian National University; </p>
      <p>DALYs- Disability Adjusted Life Years; </p>
      <p>GUPI- General-practice Users' Perceived-need Inventory; </p>
      <p>IDLS-  International Depression Literacy Survey; </p>
      <p>SEBoD-  "Reducing the <underline>S</underline>ocial and <underline>E</underline>conomic <underline>B</underline>urdens <underline>o</underline>f <underline>D</underline>epression" in Asia; </p>
      <p>SPHERE-  Somatic and Psychological HEalth Report.</p>
    </sec>
    <sec>
      <title>Competing interests</title>
      <p>The author(s) declare that they have no competing interests.</p>
    </sec>
    <sec>
      <title>Authors' contributions</title>
      <p>IBH designed the survey and drafted the manuscript. TAD participated in the survey design and drafting the manuscript. GML participated in the survey design, performed the statistical analysis and participated in drafting the manuscript. YR participated in carrying out the study surveys and drafting the manuscript. MLH participated in carrying out and coordination of the study. MIB participated in statistical analysis and drafting the manuscript.</p>
      <p>All authors read and approved the final manuscript.</p>
    </sec>
    <sec>
      <title>Pre-publication history</title>
      <p>The pre-publication history for this paper can be accessed here:</p>
      <p>
        <ext-link ext-link-type="uri" xlink:href="http://www.biomedcentral.com/1471-244X/7/48/prepub"/>
      </p>
    </sec>
    <sec sec-type="supplementary-material">
      <title>Supplementary Material</title>
      <supplementary-material content-type="local-data" id="S1">
        <caption>
          <title>Additional file 1</title>
          <p>IDLS vn1.2.pdf. Version 1.2 of the International Depression Literacy Survey (IDLS) is linked to this manuscript. The authors encourage the use of the instrument, and would appreciate your feedback (contact Professor Ian Hickie; <email>ianh@med.usyd.edu.au</email>).</p>
        </caption>
        <media xlink:href="1471-244X-7-48-S1.pdf" mimetype="application" mime-subtype="pdf">
          <caption>
            <p>Click here for file</p>
          </caption>
        </media>
      </supplementary-material>
    </sec>
  </body>
  <back>
    <ack>
      <sec>
        <title>Acknowledgements</title>
        <p>We would like to thank all the students who participated in the survey.</p>
      </sec>
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</metadata></record><record><header><identifier>oai:pubmedcentral.nih.gov:2080628</identifier><datestamp>2007-11-17</datestamp><setSpec>jbracppni</setSpec><setSpec>pmc-open</setSpec></header><metadata><article xmlns="http://dtd.nlm.nih.gov/2.0/xsd/archivearticle" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://dtd.nlm.nih.gov/archiving/2.3/xsd/archivearticle.xsd" article-type="research-article">
  <front>
    <journal-meta>
      <journal-id journal-id-type="nlm-ta">J Brachial Plex Peripher Nerve Inj</journal-id>
      <journal-title>Journal of Brachial Plexus and Peripheral Nerve Injury</journal-title>
      <issn pub-type="epub">1749-7221</issn>
      <publisher>
        <publisher-name>BioMed Central</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="pmc">2080628</article-id>
      <article-id pub-id-type="publisher-id">1749-7221-2-18</article-id>
      <article-id pub-id-type="pmid">17883873</article-id>
      <article-id pub-id-type="doi">10.1186/1749-7221-2-18</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Case Report</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Functioning transferred free muscle innervated by part of the vascularized ulnar nerve connecting the contralateral cervical seventh root to themedian nerve: case report</article-title>
      </title-group>
      <contrib-group>
        <contrib id="A1" corresp="yes" contrib-type="author">
          <name>
            <surname>Kakinoki</surname>
            <given-names>Ryosuke</given-names>
          </name>
          <xref ref-type="aff" rid="I1">1</xref>
          <email>kakinoki@kuhp.kyoto-u.ac.jp</email>
        </contrib>
        <contrib id="A2" contrib-type="author">
          <name>
            <surname>Ikeguchi</surname>
            <given-names>Ryosuke</given-names>
          </name>
          <xref ref-type="aff" rid="I1">1</xref>
          <email>ikeguchi@kuhp.kyoto-u.ac.jp</email>
        </contrib>
        <contrib id="A3" contrib-type="author">
          <name>
            <surname>Nakayama</surname>
            <given-names>Ken</given-names>
          </name>
          <xref ref-type="aff" rid="I1">1</xref>
          <email>ken102419naka@yahoo.co.jp</email>
        </contrib>
        <contrib id="A4" contrib-type="author">
          <name>
            <surname>Nakamura</surname>
            <given-names>Takashi</given-names>
          </name>
          <xref ref-type="aff" rid="I1">1</xref>
          <email>ntaka@kuhp.kyoto-u.ac.jp</email>
        </contrib>
      </contrib-group>
      <aff id="I1"><label>1</label>Department of Orthopedic Surgery &amp; Rehabilitation Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan</aff>
      <pub-date pub-type="collection">
        <year>2007</year>
      </pub-date>
      <pub-date pub-type="epub">
        <day>21</day>
        <month>9</month>
        <year>2007</year>
      </pub-date>
      <volume>2</volume>
      <fpage>18</fpage>
      <lpage>18</lpage>
      <ext-link ext-link-type="uri" xlink:href="http://www.JBPPNI.com/content/2/1/18"/>
      <history>
        <date date-type="received">
          <day>3</day>
          <month>5</month>
          <year>2007</year>
        </date>
        <date date-type="accepted">
          <day>21</day>
          <month>9</month>
          <year>2007</year>
        </date>
      </history>
      <permissions>
        <copyright-statement>Copyright © 2007 Kakinoki et al; licensee BioMed Central Ltd.</copyright-statement>
        <copyright-year>2007</copyright-year>
        <copyright-holder>Kakinoki et al; licensee BioMed Central Ltd.</copyright-holder>
        <license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/2.0">
          <p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/2.0"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>
          <!--<rdf xmlns="http://web.resource.org/cc/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1" xmlns:dcterms="http://purl.org/dc/terms"><Work xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" rdf:about=""><license rdf:resource="http://creativecommons.org/licenses/by/2.0"/><dc:type rdf:resource="http://purl.org/dc/dcmitype/Text"/><dc:author>
               Kakinoki
               Ryosuke
               
               kakinoki@kuhp.kyoto-u.ac.jp
            </dc:author><dc:title>
            Functioning transferred free muscle innervated by part of the vascularized ulnar nerve connecting the contralateral cervical seventh root to themedian nerve: case report
         </dc:title><dc:date>2007</dc:date><dcterms:bibliographicCitation>Journal of Brachial Plexus and Peripheral Nerve Injury 2(1): 18-. (2007)</dcterms:bibliographicCitation><dc:identifier type="sici">1749-7221(2007)2:1&#x0003c;18&#x0003e;</dc:identifier><dcterms:isPartOf>urn:ISSN:1749-7221</dcterms:isPartOf><License rdf:about="http://creativecommons.org/licenses/by/2.0"><permits rdf:resource="http://web.resource.org/cc/Reproduction" xmlns=""/><permits rdf:resource="http://web.resource.org/cc/Distribution" xmlns=""/><requires rdf:resource="http://web.resource.org/cc/Notice" xmlns=""/><requires rdf:resource="http://web.resource.org/cc/Attribution" xmlns=""/><permits rdf:resource="http://web.resource.org/cc/DerivativeWorks" xmlns=""/></License></Work></rdf>-->
        </license>
      </permissions>
      <abstract>
        <sec>
          <title>Background</title>
          <p>The limited nerve sources available for the reconstruction and restoration of upper extremity function is the biggest obstacle in the treatment of brachial plexus injury (BPI). We used part of a transplanted vascularized ulnar nerve as a motor source of a free muscle graft.</p>
        </sec>
        <sec>
          <title>Case presentation</title>
          <p>A 21-year-old man with a left total brachial plexus injury had received surgical intercostal nerve transfer to the musculocutaneous nerve and a spinal accessory nerve transfer to the suprascapular nerve in another hospital previously. He received transplantation of a free vascularized gracilis muscle, innervated by a part of the transplanted vascularized ulnar nerve connecting the contralateral healthy cervical seventh nerve root (CC7) to the median nerve, and recovered wrist motion and sensation in the palm. At the final examination, the affected wrist could be flexed dorsally by the transplanted muscle, and touch sensation had recovered up to the base of each finger. When his left index and middle fingers were touched or scrubbed, he felt just a mild tingling pain in his right middle fingertip.</p>
        </sec>
        <sec>
          <title>Conclusion</title>
          <p>Part of the transplanted vascularized ulnar nerve connected to the contralateral healthy cervical seventh nerve root can be used successfully as a motor source and may be available in the treatment of patients with BPI with scanty motor sources.</p>
        </sec>
      </abstract>
    </article-meta>
  </front>
  <body>
    <sec>
      <title>Background</title>
      <p>The limited nerve sources available for the reconstruction and restoration of upper extremity function is the biggest obstacle in the treatment of brachial plexus injury (BPI). Recently, there have been several techniques invented to solve this. One is the use of the contralateral healthy cervical seventh nerve root (CC7) reported by Gu et al. in 1992 [<xref ref-type="bibr" rid="B1">1</xref>]. They used this as a donor nerve to reconstruct the median nerve function of the affected arm. Another is the use of a part of the ulnar nerve transfer for reinnervation of the biceps brachii muscle for the treatment of upper type BPI reported by Oberlin et al. in 1994 [<xref ref-type="bibr" rid="B2">2</xref>]. Several authors have reported excellent outcomes for nerve recovery with the use of these techniques without leaving functional loss of the donor nerves [<xref ref-type="bibr" rid="B3">3</xref>-<xref ref-type="bibr" rid="B7">7</xref>].</p>
      <p>We describe a 21-year-old patient with BPI who received a vascularized free gracilis muscle transfer [<xref ref-type="bibr" rid="B8">8</xref>] innervated by a part of the vascularized ulnar nerve connecting CC7 to the affected median nerve. This successfully restored wrist motion and sensation to the palm.</p>
    </sec>
    <sec>
      <title>Case presentation</title>
      <p>A 21-year-old man sustained contusion injuries to both lungs and the brain in a motorcycle accident. He was transferred to a hospital, where he was treated for the lung and brain injuries. As his consciousness recovered, his left arm was found to be completely paralyzed. He was diagnosed as having a total left BPI, and underwent surgery for this three months after the injury. During surgery, the left third, fourth and fifth intercostal nerves were transferred to the left musculocutaneous nerve [<xref ref-type="bibr" rid="B9">9</xref>], the sixth and seventh intercostal nerves to the left thoracodorsal nerve, and the left accessory nerve to the left suprascapular nerve [<xref ref-type="bibr" rid="B10">10</xref>] (Fig. <xref ref-type="fig" rid="F1">1</xref>).</p>
      <fig position="float" id="F1">
        <label>Figure 1</label>
        <caption>
          <p><bold>Scheme of the operative procedures of this case</bold>. Left third to fifth intercostal nerves (1) were transferred to the left musculocutaneous nerve (2) and the left accessory nerve (3) was connected to the ipsilateral suprascapular nerve (4). 
These procedures had been done previously in another hospital. The left ulnar nerve (5), vascularized by the superior ulnar collateral vessels and ulnar vessels, was transplanted between the right seventh cervical nerve root (CC7) and left median nerve (6) (the first stage of the surgery). 
A vascularized gracilis muscle (G) was harvested from the right thigh and transplanted to the left arm. The muscle, innervated by part of the vascularized ulnar nerve (7) and nourished by the transverse cervical vessels, was connected to the clavicle and the extensor carpi radialis brevis tendon (9) (the second stage of the surgery). 8, anterior branch of the obturator nerve; B. biceps brachii muscle; BR, brachioradialis muscle.</p>
        </caption>
        <graphic xlink:href="1749-7221-2-18-1"/>
      </fig>
      <p>Twelve months after the BPI surgery performed in the previous hospital, he visited our clinic complaining of complete loss of sensation and motor function distal to the left elbow joint. Reasonable recovery of the shoulder and elbow joints was seen from a physical examination. The left elbow flexion range was 100° against gravity and the abduction and flexion ranges of the left shoulder against gravity were 80° and 85°, respectively. However, the elbow extension was M0 according to the Medical Research Council Scale (MRCS) and the range of left shoulder extension was 15°, which was mostly achieved by motion of the left scapula. No active motion was observed in the left wrist and fingers. The patient demonstrated complete numbness in the area innervated by the left C5-T1 nerve roots. He had slight stiffness in the MP joints of the left index finger to the little finger, and started rehabilitation exercises to soften the joints. No other joints of his left upper extremity showed restriction of the range of motion in the passive movement. Elbow flexion was recovered to M4 level according to MRCS at 15 months after surgery thanks to muscle-strengthening exercises.</p>
      <p>Eighteen months after the injury, he underwent reconstructive surgery to his left wrist and hand. As the first step of the reconstruction, the CC7 was transferred to the median nerve through a vascularized ulnar nerve taken from the affected arm. The left ulnar nerve was elevated based on the superior ulnar collateral vessels, including the ulnar vessels distally. A monitor skin flap (2.5 × 1 cm) supplied by perforators arising from the ulnar vessels was also harvested from the distal third of the forearm together with the ulnar nerve. The ulnar nerve and vessels were sectioned at the wrist level distally. The ulnar nerve was also sectioned just proximal to the insertion of the superior ulnar collateral vessels into the ulnar nerve in the upper arm level proximally (Fig. <xref ref-type="fig" rid="F2">2</xref>). The median nerve was sectioned at the same level of the proximal section of the ulnar nerve. The proximal stump of the transected ulnar nerve segment was approximated to the distal stump of the median nerve. The distal stump of the ulnar nerve segment including the ulnar vessels was transferred to the right neck through a subcutaneous tunnel and approximated the posterosuperior portion of the right seventh cervical nerve root as described by Songcharoen et al. [<xref ref-type="bibr" rid="B5">5</xref>] (Fig. <xref ref-type="fig" rid="F3">3</xref>). The distal stump of the ulnar artery accompanying the transplanted ulnar nerve segment was approximated to the transverse cervical artery in the right neck followed by ligation of the distal stumps of the ulnar veins. After surgery, the monitor flap survived completely. The patient showed transient paresthesia in the tips of right index and middle fingers, which lasted for two months. Grip strength was not affected. The sensory recovery of the affected limb was rapid, and touch sensation was restored to the midpalm level of the affected hand by four months after the CC7 transfer.</p>
      <fig position="float" id="F2">
        <label>Figure 2</label>
        <caption>
          <p><bold>The harvested vascularized ulnar nerve</bold>. The ulnar nerve, vascularized by the superior ulnar collateral vessels proximally (1), was harvested containing the ulnar vessels (2) distally. A monitor flap (F) was taken attached to the ulnar vessels.</p>
        </caption>
        <graphic xlink:href="1749-7221-2-18-2"/>
      </fig>
      <fig position="float" id="F3">
        <label>Figure 3</label>
        <caption>
          <p><bold>Preparation of the donor C7 root</bold>. The contralateral healthy seventh cervical nerve root was divided into the posterosuperior (1) and anteroinferior (2) portions. The posterosuperior portion was sectioned and connected to the vascularized ulnar nerve.</p>
        </caption>
        <graphic xlink:href="1749-7221-2-18-3"/>
      </fig>
      <p>As the second stage of the reconstruction, the free vascularized gracilis muscle taken from the right medial thigh was transplanted to the left upper arm four months after the CC7 transfer. The proximal stump of the gracilis was joined to the clavicle with bone anchors and to the trapezius with 1-0 Ethicon sutures. The distal stump of the transplanted muscle was passed under the brachioradialis muscle, stretched maximally and sutured to the extensor carpi radialis brevis tendon in interlacing fashion, maintaining the shoulder joint at 60° abduction and 30° flexion, and the elbow joint at 45° flexion. The tension of the transplanted muscle was set higher than normal, because a slight flexion contracture of the elbow joint would help the patient bend the elbow joint. The medial circumflex femoral vessels of the transplanted gracilis muscle were approximated to the left transverse cervical vessels, as the thoracoacromial vessels were not suitable to microvascular anastomosis because of severe scarring. In the left anterior axillary area, two funiculi of the ulnar nerve (about 10% thickness of the original nerve) were separated from the vascularized ulnar nerve–having been transplanted in the previous operation–and taken proximally for about 1.5 cm. The proximally based partial ulnar nerve stump was approximated to the anterior branch of the obturator nerve innervating the free gracilis muscle (Fig. <xref ref-type="fig" rid="F4">4</xref>). The stump size of the two funiculi of the ulnar nerve matched that of the branch of the obturator nerve. The distance between the site of the neurorraphy and the entrance of the obturator nerve to the gracilis muscle belly was about 3 cm.</p>
      <fig position="float" id="F4">
        <label>Figure 4</label>
        <caption>
          <p><bold>Par of the vascularized ulnar nerve transfer</bold>. Two funiculi (1) were harvested from the vascularized ulnar nerve (2) and connected to the obturator nerve (3) innervating the transplanted gracilis muscle (F).</p>
        </caption>
        <graphic xlink:href="1749-7221-2-18-4"/>
      </fig>
      <p>Postoperative recovery was uneventful. After the muscle graft operation, the patient's sensation in the left palm was not compromised and showed continuous further recovery, even though almost 10% of the nerve fibers had been taken to innervate the transplanted muscle. Contraction of the transplanted muscle was observed eight months after the transplantation. Fifteen months after the muscle graft, the dorsiflexion of the left wrist was 35° against gravity with the elbow joint held fully extended (approximately at a 30° -flexion position) when the patient applied forces to the flexor muscles of his right wrist and ulnar fingers (mainly, right and little fingers). His right fist formation and slight palmar wrist flexion was synchronously accompanied by the dorsiflexion of his left wrist (Fig. <xref ref-type="fig" rid="F5">5A</xref> and <xref ref-type="fig" rid="F5">5B</xref>). The left elbow joint was restricted in extension after the muscle transplantation; the active range of the joint was -30° in extension and 130° in flexion. The flexion force of the joint was augmented by the muscle transplantation and recovered to an M5 level. Recovery of touch sensation advanced to the base of the index and middle fingers and thumb. The sensation in the left palm was S2 on the MRCS. When the tips of the fingers and thumb were touched or scrubbed, he did not recognized it as a sensation of his left digits but as a weak tingling pain at his right middle fingertip. The sign of motor recovery of the left median nerve has not been observed yet.</p>
      <fig position="float" id="F5">
        <label>Figure 5</label>
        <caption>
          <p><bold>A and B -Dorsiflexion of the wrist after 15 months after the free gracilis muscle transfer</bold>. Fifteen months after the muscle graft, the dorsiflexion of the left wrist was 35° against gravity with the elbow joint held at a 30° -flexion position when the patient tensed the flexor muscles of his right wrist and fingers. A: Dorsiflexion of the left wrist with synchronous flexion of the right wrist and fingers. B: Palmar flexion of the wrist by the gravity.</p>
        </caption>
        <graphic xlink:href="1749-7221-2-18-5"/>
      </fig>
      <p>As the final stage of the reconstruction, we plan to perform biceps brachii muscle transfer to the triceps muscle to stabilize the elbow joint, tenodesis at the wrist and arthrodesis of the thumb to obtain pinch function. The patient has not yet agreed to final operation, because he is completely satisfied with the improved muscle strength of the elbow flexion and is worried about possible loss of elbow flexion strength after the biceps brachii muscle transfer.</p>
    </sec>
    <sec>
      <title>Discussion</title>
      <p>This patient with BPI involving the total brachial plexus had undergone intercostal nerve transfer [<xref ref-type="bibr" rid="B9">9</xref>] to the musculocutaneous nerve and a spinal accessory nerve transfer [<xref ref-type="bibr" rid="B10">10</xref>] to the suprascapular nerve in a previous hospital. We restored sensation of the palm and motion of the wrist to the patient by transplantation of a vascularized ulnar nerve between the CC7 and the median nerve and a free vascularized gracilis muscle innervated by a part of the transplanted vascularized ulnar nerve. Nineteen months after our first operation, the affected wrist was flexed dorsally by the transplanted muscle innervated by a part of the vascularized nerve connecting to the CC7 and touch sensation recovered up to the base of each fingers.</p>
      <p>Several authors have reported excellent outcomes of the sensory and motor recovery of the median nerve using a vascularized nerve transfer connected to the CC7 [<xref ref-type="bibr" rid="B1">1</xref>,<xref ref-type="bibr" rid="B3">3</xref>,<xref ref-type="bibr" rid="B5">5</xref>,<xref ref-type="bibr" rid="B7">7</xref>]. Poor motor recovery is to be expected in muscles denervated for more than six months, and skin sensation does not recover if it has been denervated for a long time, because its muscle fibers or sensory organs become too atrophied [<xref ref-type="bibr" rid="B11">11</xref>,<xref ref-type="bibr" rid="B12">12</xref>]. In our patient, median nerve reconstruction was performed 16 months after the original injury. Excellent recovery of the sensory and motor function of the median nerve could not be expected in this patient, even with CC7 transfer to the median nerve. Thus, it was controversial whether this patient had a valid indication for a CC7 transfer to reconstruct the median nerve. Moreover, for this patient no motor source was available without the vascularized nerve connecting CC7. The intercostal nerves and the accessory nerve had already been used to restore elbow flexion and shoulder mobility. The patient had left phrenic nerve palsy. The patient had no chance of motor recovery without using a free functioning muscle transfer, as no muscles in the affected arm would function even after the neurotization because of the prolonged loss of innervation. Therefore, we decided to perform a CC7 transfer to the median nerve, expecting it to serve as the motor source of a free functioning muscle transfer as well as for recovery of the sensation of the hand. Because a movable hand lacking sensation is no more harmful than a totally paralyzed hand, we reached a consensus with the patient before surgery that the free gracilis muscle transfer would not be done if the sensory recovery of the median nerve was poor. Actually, the patient showed more rapid and better sensory recovery in the median nerve than we had expected before the CC7 operation. Four months after the operation, the patient recognized touch sensation up to the midpalm level of the hand. The sensory recovery of this patient was extremely faster than that reported by previous authors [<xref ref-type="bibr" rid="B1">1</xref>,<xref ref-type="bibr" rid="B3">3</xref>,<xref ref-type="bibr" rid="B5">5</xref>,<xref ref-type="bibr" rid="B7">7</xref>]. Although there may be different opinions [<xref ref-type="bibr" rid="B7">7</xref>], one possible explanation of the rapid nerve recovery through the CC7 operation in this patient is that the nerve recovery in the transplanted ulnar nerve might have been accelerated by sufficient vascular supply supercharged by the accompanying ulnar artery connected to the transverse cervical artery in the right neck. Most previous authors performed CC7 operations without supercharging the ulnar vessels accompanying the transplanted ulnar nerve [<xref ref-type="bibr" rid="B1">1</xref>,<xref ref-type="bibr" rid="B3">3</xref>,<xref ref-type="bibr" rid="B5">5</xref>]. In addition, the patient was still 22 years old when he had the CC7 operation. His youth might have also contributed to his rapid sensory recovery of his affected median nerve.</p>
      <p>Several surgeons have treated patients with upper BPI using a part of the ulnar nerve transferred to the biceps brachii branch of the musculocutaneous nerve and have demonstrated rapid reinnervation of the biceps brachii muscles without leaving any functional loss in the donor ulnar nerve [<xref ref-type="bibr" rid="B2">2</xref>,<xref ref-type="bibr" rid="B4">4</xref>,<xref ref-type="bibr" rid="B6">6</xref>,<xref ref-type="bibr" rid="B10">10</xref>]. Oberlin et al. reported that no functional loss should occur in the ulnar nerve after partial ulnar transfer, because the nerve fibers are still mixed and their locations are not distributed functionally at the midarm level [<xref ref-type="bibr" rid="B2">2</xref>]. In our patient, no regression of the sensation of the affected hand was observed after a part of the vascularized nerve was transferred to a branch innervating the free transplanted muscle. A part of the transplanted ulnar nerve was taken in the subclavicular region and joined to the obturator nerve of the transplanted gracilis muscle. The ulnar nerve was sectioned just above the insertion of the superior ulnar collateral vessels to the ulnar nerve, and the distal portion of the nerve was reflected proximally in the CC7 operation. Thus, the portion where a part of the transplanted ulnar nerve had been harvested was almost the same as where a part of the ulnar nerve had been taken in Oberlin's original procedure [<xref ref-type="bibr" rid="B2">2</xref>]. Because the nerve fibers had not been distributed functionally in the portion where a part of the transplanted ulnar nerve was taken, the palmar sensation in this patient after harvesting a part of the transplanted nerve may not have been compromised.</p>
      <p>In conclusion, part of the transplanted vascularized ulnar nerve connected to the contralateral healthy cervical seventh nerve root can be used successfully as a motor source and may be available in the treatment of patients with BPI with scanty motor sources.</p>
    </sec>
    <sec>
      <title>Competing interests</title>
      <p>The author(s) declare that they have no competing interests.</p>
    </sec>
    <sec>
      <title>Authors' contributions</title>
      <p>RK was responsible to this patient for the whole treatment of the brachial plexus injury and performed the surgery as a main surgeon. RI and KN assisted RK in the surgery. TN supervised the surgery and gave several suggestions to complete this manuscript. All authors read and approved the final manuscript.</p>
    </sec>
  </body>
  <back>
    <ack>
      <sec>
        <title>Acknowledgements</title>
        <p>We obtained the patient's permission to submit this article to Journal of Brachial Plexus and peripheral nerve injury.</p>
      </sec>
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  </back>
</article>

</metadata></record><record><header><identifier>oai:pubmedcentral.nih.gov:2080629</identifier><datestamp>2007-11-17</datestamp><setSpec>bmcem</setSpec><setSpec>pmc-open</setSpec></header><metadata><article xmlns="http://dtd.nlm.nih.gov/2.0/xsd/archivearticle" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://dtd.nlm.nih.gov/archiving/2.3/xsd/archivearticle.xsd" article-type="research-article">
  <front>
    <journal-meta>
      <journal-id journal-id-type="nlm-ta">BMC Emerg Med</journal-id>
      <journal-title>BMC Emergency Medicine</journal-title>
      <issn pub-type="epub">1471-227X</issn>
      <publisher>
        <publisher-name>BioMed Central</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="pmc">2080629</article-id>
      <article-id pub-id-type="publisher-id">1471-227X-7-17</article-id>
      <article-id pub-id-type="pmid">17937796</article-id>
      <article-id pub-id-type="doi">10.1186/1471-227X-7-17</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Prehospital score for acute disease: a community-based observational study in Japan</article-title>
      </title-group>
      <contrib-group>
        <contrib id="A1" equal-contrib="yes" contrib-type="author">
          <name>
            <surname>Toyoda</surname>
            <given-names>Yasuhiro</given-names>
          </name>
          <xref ref-type="aff" rid="I1">1</xref>
          <email>ytoyoda@pbhel.med.osaka-u.ac.jp</email>
        </contrib>
        <contrib id="A2" equal-contrib="yes" contrib-type="author">
          <name>
            <surname>Matsuo</surname>
            <given-names>Yoshio</given-names>
          </name>
          <xref ref-type="aff" rid="I2">2</xref>
          <xref ref-type="aff" rid="I3">3</xref>
          <email>kch-25_q9q9@kch.city.kishiwada.osaka.jp</email>
        </contrib>
        <contrib id="A3" equal-contrib="yes" contrib-type="author">
          <name>
            <surname>Tanaka</surname>
            <given-names>Hiroyuki</given-names>
          </name>
          <xref ref-type="aff" rid="I3">3</xref>
          <email>ertanaka@tokyo-med.ac.jp</email>
        </contrib>
        <contrib id="A4" equal-contrib="yes" contrib-type="author">
          <name>
            <surname>Fujiwara</surname>
            <given-names>Hidekazu</given-names>
          </name>
          <xref ref-type="aff" rid="I4">4</xref>
          <email>kishiwada-kyukyu@tvk.zaq.ne.jp</email>
        </contrib>
        <contrib id="A5" equal-contrib="yes" contrib-type="author">
          <name>
            <surname>Takatorige</surname>
            <given-names>Toshio</given-names>
          </name>
          <xref ref-type="aff" rid="I1">1</xref>
          <email>takatorige@pnhel.med.osaka-u.ac.jp</email>
        </contrib>
        <contrib id="A6" corresp="yes" contrib-type="author">
          <name>
            <surname>Iso</surname>
            <given-names>Hiroyasu</given-names>
          </name>
          <xref ref-type="aff" rid="I1">1</xref>
          <email>iso@pbhel.med.osaka-u.ac.jp</email>
        </contrib>
      </contrib-group>
      <aff id="I1"><label>1</label>Public Health, Department of Social and Environmental Medicine, Graduate School of Medicine, Osaka University, Osaka, Japan</aff>
      <aff id="I2"><label>2</label>Emergency Division, Kishiwada Tokushukai Hospital, Kishiwada, Japan</aff>
      <aff id="I3"><label>3</label>Emergency Division, Kishiwada City Hospital, Kishiwada, Japan</aff>
      <aff id="I4"><label>4</label>Kishiwada City Fire Department, Kishiwada, Japan</aff>
      <pub-date pub-type="collection">
        <year>2007</year>
      </pub-date>
      <pub-date pub-type="epub">
        <day>15</day>
        <month>10</month>
        <year>2007</year>
      </pub-date>
      <volume>7</volume>
      <fpage>17</fpage>
      <lpage>17</lpage>
      <ext-link ext-link-type="uri" xlink:href="http://www.biomedcentral.com/1471-227X/7/17"/>
      <history>
        <date date-type="received">
          <day>18</day>
          <month>5</month>
          <year>2007</year>
        </date>
        <date date-type="accepted">
          <day>15</day>
          <month>10</month>
          <year>2007</year>
        </date>
      </history>
      <permissions>
        <copyright-statement>Copyright © 2007 Toyoda et al.; licensee BioMed Central Ltd.</copyright-statement>
        <copyright-year>2007</copyright-year>
        <copyright-holder>Toyoda et al.; licensee BioMed Central Ltd.</copyright-holder>
        <license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/2.0">
          <p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/2.0"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>
          <!--<rdf xmlns="http://web.resource.org/cc/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1" xmlns:dcterms="http://purl.org/dc/terms"><Work xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" rdf:about=""><license rdf:resource="http://creativecommons.org/licenses/by/2.0"/><dc:type rdf:resource="http://purl.org/dc/dcmitype/Text"/><dc:author>
               Toyoda
               Yasuhiro
               
               ytoyoda@pbhel.med.osaka-u.ac.jp
            </dc:author><dc:title>
            Prehospital score for acute disease: a community-based observational study in Japan
         </dc:title><dc:date>2007</dc:date><dcterms:bibliographicCitation>BMC Emergency Medicine 7(1): 17-. (2007)</dcterms:bibliographicCitation><dc:identifier type="sici">1471-227X(2007)7:1&#x0003c;17&#x0003e;</dc:identifier><dcterms:isPartOf>urn:ISSN:1471-227X</dcterms:isPartOf><License rdf:about="http://creativecommons.org/licenses/by/2.0"><permits rdf:resource="http://web.resource.org/cc/Reproduction" xmlns=""/><permits rdf:resource="http://web.resource.org/cc/Distribution" xmlns=""/><requires rdf:resource="http://web.resource.org/cc/Notice" xmlns=""/><requires rdf:resource="http://web.resource.org/cc/Attribution" xmlns=""/><permits rdf:resource="http://web.resource.org/cc/DerivativeWorks" xmlns=""/></License></Work></rdf>-->
        </license>
      </permissions>
      <abstract>
        <sec>
          <title>Background</title>
          <p>Ambulance usage in Japan has increased consistently because it is free under the national health insurance system. The introduction of refusal for ambulance transfer is being debated nationally. The purpose of the present study was to investigate the relationship between prehospital data and hospitalization outcome for acute disease patients, and to develop a simple prehospital evaluation tool using prehospital data for Japan's emergency medical service system.</p>
        </sec>
        <sec sec-type="methods">
          <title>Methods</title>
          <p>The subjects were 9,160 consecutive acute disease patients aged ≥ 15 years who were transferred to hospital by Kishiwada City Fire Department ambulance between July 2004 and March 2006. The relationship between prehospital data (age, systolic blood pressure, pulse rate, respiration rate, level of consciousness, SpO<sub>2 </sub>level and ability to walk) and outcome (hospitalization or non-hospitalization) was analyzed using logistic regression models. The prehospital score component of each item of prehospital data was determined by beta coefficients. Eligible patients were scored retrospectively and the distribution of outcome was examined. For patients transported to the two main hospitals, outcome after hospitalization was also confirmed.</p>
        </sec>
        <sec>
          <title>Results</title>
          <p>A total of 8,330 (91%) patients were retrospectively evaluated using a prehospital score with a maximum value of 14. The percentage of patients requiring hospitalization rose from 9% with score = 0 to 100% with score = 14. With a cut-off point score ≥ 2, the sensitivity, specificity, positive predictive value and negative predictive value were 97%, 16%, 39% and 89%, respectively. Among the 6,498 patients transported to the two main hospitals, there were no deaths at scores ≤ 1 and the proportion of non-hospitalization was over 90%. The proportion of deaths increased rapidly at scores ≥ 11.</p>
        </sec>
        <sec>
          <title>Conclusion</title>
          <p>The prehospital score could be a useful tool for deciding the refusal of ambulance transfer in Japan's emergency medical service system.</p>
        </sec>
      </abstract>
    </article-meta>
  </front>
  <body>
    <sec>
      <title>Background</title>
      <p>The Japanese national emergency medical service system has been established since 1963 and enables those in need of urgent medical treatment to summon an ambulance by calling the free national emergency telephone number '119'. Approximately 78% of ambulances are staffed by emergency life-saving technicians, who were introduced in 1991. Prior to that, emergency medical technicians played a major role in prehospital settings but were only allowed to perform basic life support procedures such as external chest compression and ventilation with a bag valve mask. Emergency life-saving technicians, by contrast, are permitted to perform endotracheal intubation, defibrillation, intravenous infusion of Ringer's solution, and administration of epinephrine. However, these treatments are allowed only for cardiopulmonary arrest patients. In addition, they are not permitted to carry out additional life-saving interventions and clinical tests such as needle thoracostomy, cricothyroidotomy, 12-lead electrocardiograms, blood glucose measurements and administration of drugs other than epinephrine. Furthermore, the frequency with which vital signs are taken at the scene is still low in Japan; 25% for blood pressure and 27% for SpO<sub>2 </sub>[<xref ref-type="bibr" rid="B1">1</xref>]. As a result, prehospital care in Japan is very limited compared with to in western countries [<xref ref-type="bibr" rid="B2">2</xref>-<xref ref-type="bibr" rid="B5">5</xref>].</p>
      <p>Meanwhile, the Japanese national medical insurance system and free ambulance call-outs have resulted in a lack of concern over ambulance usage. This usage has increased consistently by over 5 million cases per year since 2004. According to national data, 51% of these were mild cases that did not require hospitalization [<xref ref-type="bibr" rid="B1">1</xref>]. In addition, the rapid aging of society, with more than 19% of the population aged over 65 years in 2004 [<xref ref-type="bibr" rid="B6">6</xref>], has promoted an increase in ambulance usage, especially for acute disease [<xref ref-type="bibr" rid="B7">7</xref>,<xref ref-type="bibr" rid="B8">8</xref>].</p>
      <p>In this situation, refusal of ambulance transfer for mild cases is being debated nationally. The fire and disaster management agency established a 'Committee for demand of ambulance usage' in 2006. For appropriate ambulance usage for hospitalization, a simple triage tool to decide the refusal of ambulance usage would be useful.</p>
      <p>The purpose of this study was to investigate the relationship between prehospital data and hospitalization outcome for acute disease patients aged ≥ 15 years, and to develop a simple tool for deciding the refusal of ambulance usage based primarily on vital signs.</p>
    </sec>
    <sec sec-type="methods">
      <title>Methods</title>
      <sec>
        <title>Study setting</title>
        <p>This study was conducted in Kishiwada City, Osaka Prefecture, Japan, which has a population of about 200,000 and an area of 72 km<sup>2</sup>. Kishiwada City Fire Department controls the emergency medical service system. A total of 17,293 patients were transferred by the Kishiwada City Fire Department ambulances between July 2004 and March 2006. The subjects in the present study were 9,160 consecutive acute disease patients aged ≥ 15 years during this period.</p>
        <p>All ambulances in Kishiwada carry at least one emergency life-saving technician who records prehospital data such as patient age, vital signs, chief complaint and simple physical examinations, taken at the scene or in the ambulance. Since April 2004, prehospital data have been entered into the computer database by the captain of each ambulance, who has the emergency life-saving technician national license. Approximately 80% of emergency patients are transferred to the two main hospitals; Kishiwada City Hospital and Kishiwada Tokushukai Hospital. Five or more clinical physicians, four or more emergency nurses, one or more radiology technicians, one or more clinical laboratory technicians and one or more pharmacists reside in these hospitals over each 24-hour period. These hospitals are certificated as emergency hospitals by the Japan Acute Medicine Association.</p>
      </sec>
      <sec>
        <title>Study design and protocol</title>
        <p>We investigated the relationship between prehospital data and hospitalization outcome for the acute disease patients transported by the Kishiwada City Fire Department ambulances, using a multivariable logistic regression model, and developed the prehospital score by the beta coefficients of significant variables.</p>
        <p>The following prehospital data collected by emergency personnel, including emergency life-saving technicians, were extracted from the database: age, systolic blood pressure, pulse rate, consciousness level, SpO<sub>2 </sub>and ability to walk. These are routinely taken at the scene or in the ambulance and are relatively objective.</p>
        <p>The outcome was reported as hospitalization or non-hospitalization. The chief of the emergency section of Kishiwada City Fire Department, a trained emergency life-saving technician, confirmed the hospitalization outcome and the final diagnosis by the attending physicians using FAX or telephone. Deaths in the emergency room were regarded as hospitalization. In addition, the outcome after hospitalization was confirmed for patients transferred to the two main hospitals (Kishiwada City Hospital and Kishiwada Tokushukai Hospital), i.e. 71% of the total number of subjects.</p>
        <p>The continuous variables – age, systolic blood pressure, pulse rate and SpO<sub>2 </sub>– were converted to categorical variables for practical use. We decided the reference of each continuous variable according to normal clinical range. Systolic blood pressure levels were categorized as &lt;80, 90–99, 100–149 (reference), 150–159, 160–169, 170–179, 180–189, 190–199, and ≥ 200 mmHg; pulse rates were categorized as &lt;50, 50–59, 60–89 (reference), 90–99, 100–109, 110–119, and ≥ 120 beats per min; SpO<sub>2 </sub>was categorized into &lt;95% (hypoxic) and ≥ 95% (normal). Patients with capillary circulation failure whose SpO<sub>2 </sub>levels could not be measured were also regarded as hypoxic. Ages were categorized as 15–59, 60–69, 70–79, 80–89 and ≥ 90 years; the consciousness level was categorized according to the Japan Coma Scale (JCS) as 0, I, II and III; the ability to walk was categorized as "yes" or "no". Cases in which the emergency life-saving technician advised the patient not to walk were regarded as "no". The major category of the Japan Coma Scale (JCS), a widely used criterion for evaluation of consciousness in Japan, was used in the present study. The scale is 0 = alert, I = awake without stimulation, II = awake with stimulation, III = not awake with stimulation [<xref ref-type="bibr" rid="B9">9</xref>]. When multiple data were available for each patient, the initial data were used for analyses.</p>
        <p>The prehospital score was determined as a simple integer (0, 1, 2 or 3) for practical use on the basis of the beta coefficient for each independent variable. The total score was obtained from the sum of all items of prehospital data.</p>
        <p>Eligible patients were retrospectively scored and the distributions of all scores for the hospitalized and non-hospitalized groups were examined. The proportion hospitalized was calculated and related to the total score. Moreover, for patients transported to the two main hospitals (Kishiwada City Hospital and Kishiwada Tokushukai Hospital), the proportions (1) non-hospitalized, (2) discharged after hospitalization, (3) transported to another hospital and (4) died in the emergency room or after hospitalization were related to the total score.</p>
        <p>The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for predicting hospitalization were calculated at each score point, and the area under the receiver operating characteristic (ROC) curve was determined with 95% confidence intervals.</p>
        <p>The statistical analysis package SPSS 12.0J for Windows (SPSS Japan inc., Tokyo, Japan) was used for data analyses. All p-values were two-tailed, and p-values &lt; 0.05 were considered statistically significant.</p>
      </sec>
      <sec>
        <title>Ethical approval</title>
        <p>Prehospital and outcome data did not include personal information. The present study was approved by the ethical committee of the Graduate School of Medicine, Osaka University, Japan.</p>
      </sec>
    </sec>
    <sec>
      <title>Results</title>
      <sec>
        <title>Multivariable logistic regression and development of prehospital score</title>
        <p>From a total of 9,169 patients, complete data were available for 8,330 (91%), which were used for the analyses. Of these, 36% (3,002) were hospitalized. The mean age (± SD) of the hospitalization group was 70 ± 16 years while that of the non-hospitalization group was 58 ± 20 years.</p>
        <p>Table <xref ref-type="table" rid="T1">1</xref> shows the beta coefficient and multivariable odds ratios for the components of prehospital score. All independent variables – age, systolic blood pressure, pulse rate, level of consciousness, SpO<sub>2 </sub>and ability to walk – were statistically significant in predicting hospital outcome.</p>
        <table-wrap position="float" id="T1">
          <label>Table 1</label>
          <caption>
            <p>Multivariable odds ratios of hospitalization in relation to prehospital score</p>
          </caption>
          <table frame="hsides" rules="groups">
            <thead>
              <tr>
                <td align="left">Prehospital data</td>
                <td align="center">No. of hospitalization/patients</td>
                <td align="center">beta coefficient</td>
                <td align="center">OR (95%CI)</td>
                <td align="center">Prehospital Score</td>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td align="left">Age, y</td>
                <td/>
                <td/>
                <td/>
                <td/>
              </tr>
              <tr>
                <td align="left">&lt;60</td>
                <td align="center">639/3,101</td>
                <td align="center">0</td>
                <td align="left">1</td>
                <td align="center">0</td>
              </tr>
              <tr>
                <td align="left">60–69</td>
                <td align="center">513/1,465</td>
                <td align="center">0.53</td>
                <td align="left">1.69(1.45–1.97)*</td>
                <td align="center">2</td>
              </tr>
              <tr>
                <td align="left">70–79</td>
                <td align="center">939/2,098</td>
                <td align="center">0.83</td>
                <td align="left">2.30(2.01–2.64)*</td>
                <td align="center">2</td>
              </tr>
              <tr>
                <td align="left">80–89</td>
                <td align="center">730/1,363</td>
                <td align="center">1.04</td>
                <td align="left">2.82(2.42–3.29)*</td>
                <td align="center">3</td>
              </tr>
              <tr>
                <td align="left">&gt;=90</td>
                <td align="center">181/303</td>
                <td align="center">1.15</td>
                <td align="left">3.16(2.41–4.13)*</td>
                <td align="center">3</td>
              </tr>
              <tr>
                <td/>
                <td/>
                <td/>
                <td/>
                <td/>
              </tr>
              <tr>
                <td align="left">Systolic blood pressure, mmHg</td>
                <td/>
                <td/>
                <td/>
                <td/>
              </tr>
              <tr>
                <td align="left">&lt;80</td>
                <td align="center">239/277</td>
                <td align="center">0.93</td>
                <td align="left">2.53(1.63–3.94)*</td>
                <td align="center">2</td>
              </tr>
              <tr>
                <td align="left">80–89</td>
                <td align="center">96/185</td>
                <td align="center">0.55</td>
                <td align="left">1.73(1.25–2.41)*</td>
                <td align="center">2</td>
              </tr>
              <tr>
                <td align="left">90–99</td>
                <td align="center">158/428</td>
                <td align="center">-0.05</td>
                <td align="left">0.95(0.75–1.20)</td>
                <td align="center">0</td>
              </tr>
              <tr>
                <td align="left">100–149</td>
                <td align="center">1,489/4,512</td>
                <td align="center">0</td>
                <td align="left">1</td>
                <td align="center">0</td>
              </tr>
              <tr>
                <td align="left">150–159</td>
                <td align="center">236/767</td>
                <td align="center">-0.14</td>
                <td align="left">0.87(0.73–1.05)</td>
                <td align="center">0</td>
              </tr>
              <tr>
                <td align="left">160–169</td>
                <td align="center">223/659</td>
                <td align="center">-0.04</td>
                <td align="left">0.97(0.80–1.23)</td>
                <td align="center">0</td>
              </tr>
              <tr>
                <td align="left">170–179</td>
                <td align="center">134/479</td>
                <td align="center">-0.01</td>
                <td align="left">0.99(0.80–1.23)</td>
                <td align="center">0</td>
              </tr>
              <tr>
                <td align="left">180–189</td>
                <td align="center">134/397</td>
                <td align="center">-0.09</td>
                <td align="left">0.91(0.72–1.16)</td>
                <td align="center">0</td>
              </tr>
              <tr>
                <td align="left">190–199</td>
                <td align="center">81/215</td>
                <td align="center">0.14</td>
                <td align="left">1.15(0.84–1.56)</td>
                <td align="center">0</td>
              </tr>
              <tr>
                <td align="left">&gt;=200</td>
                <td align="center">182/411</td>
                <td align="center">0.37</td>
                <td align="left">1.45(1.15–1.81)*</td>
                <td align="center">1</td>
              </tr>
              <tr>
                <td/>
                <td/>
                <td/>
                <td/>
                <td/>
              </tr>
              <tr>
                <td align="left">Pulse, per min</td>
                <td/>
                <td/>
                <td/>
                <td/>
              </tr>
              <tr>
                <td align="left">&lt;50</td>
                <td align="center">208/235</td>
                <td align="center">0.92</td>
                <td align="left">2.51(1.52–4.13)*</td>
                <td align="center">2</td>
              </tr>
              <tr>
                <td align="left">50–59</td>
                <td align="center">90/273</td>
                <td align="center">-0.03</td>
                <td align="left">0.97(0.73–1.29)</td>
                <td align="center">0</td>
              </tr>
              <tr>
                <td align="left">60–89</td>
                <td align="center">1,265/4,238</td>
                <td align="center">0</td>
                <td align="left">1</td>
                <td align="center">0</td>
              </tr>
              <tr>
                <td align="left">90–99</td>
                <td align="center">447/1,372</td>
                <td align="center">0.09</td>
                <td align="left">1.10(0.95–1.27)</td>
                <td align="center">0</td>
              </tr>
              <tr>
                <td align="left">100–109</td>
                <td align="center">366/954</td>
                <td align="center">0.23</td>
                <td align="left">1.26(1.07–1.49)*</td>
                <td align="center">1</td>
              </tr>
              <tr>
                <td align="left">110–119</td>
                <td align="center">245/541</td>
                <td align="center">0.52</td>
                <td align="left">1.67(1.37–2.05)*</td>
                <td align="center">2</td>
              </tr>
              <tr>
                <td align="left">120–129</td>
                <td align="center">218/437</td>
                <td align="center">0.63</td>
                <td align="left">1.88(1.50–2.35)*</td>
                <td align="center">2</td>
              </tr>
              <tr>
                <td align="left">&gt;=130</td>
                <td align="center">163/280</td>
                <td align="center">0.71</td>
                <td align="left">2.02(1.53–2.67)*</td>
                <td align="center">2</td>
              </tr>
              <tr>
                <td/>
                <td/>
                <td/>
                <td/>
                <td/>
              </tr>
              <tr>
                <td align="left">Consciousness, JCS</td>
                <td/>
                <td/>
                <td/>
                <td/>
              </tr>
              <tr>
                <td align="left">0</td>
                <td align="center">1,990/6,699</td>
                <td align="center">0</td>
                <td align="left">1</td>
                <td align="center">0</td>
              </tr>
              <tr>
                <td align="left">I</td>
                <td align="center">485/942</td>
                <td align="center">0.51</td>
                <td align="left">1.67(1.44–1.94)*</td>
                <td align="center">2</td>
              </tr>
              <tr>
                <td align="left">II</td>
                <td align="center">188/283</td>
                <td align="center">1.09</td>
                <td align="left">2.98(2.27–3.90)*</td>
                <td align="center">3</td>
              </tr>
              <tr>
                <td align="left">III</td>
                <td align="center">339/406</td>
                <td align="center">1.35</td>
                <td align="left">3.84(2.82–5.23)*</td>
                <td align="center">3</td>
              </tr>
              <tr>
                <td/>
                <td/>
                <td/>
                <td/>
                <td/>
              </tr>
              <tr>
                <td align="left">Saturation O<sub>2</sub>, %</td>
                <td/>
                <td/>
                <td/>
                <td/>
              </tr>
              <tr>
                <td align="left">&gt;=95</td>
                <td align="center">1,804/6,571</td>
                <td align="center">0</td>
                <td align="left">1</td>
                <td align="center">0</td>
              </tr>
              <tr>
                <td align="left">&lt;95</td>
                <td align="center">1,198/1,759</td>
                <td align="center">0.99</td>
                <td align="left">2.69(2.36–3.06)*</td>
                <td align="center">2</td>
              </tr>
              <tr>
                <td/>
                <td/>
                <td/>
                <td/>
                <td/>
              </tr>
              <tr>
                <td align="left">Ability to walk</td>
                <td/>
                <td/>
                <td/>
                <td/>
              </tr>
              <tr>
                <td align="left">yes</td>
                <td align="center">389/2,228</td>
                <td align="center">0</td>
                <td align="left">1</td>
                <td align="center">0</td>
              </tr>
              <tr>
                <td align="left">no</td>
                <td align="center">2,613/6,102</td>
                <td align="center">0.73</td>
                <td align="left">2.08(1.82–2.37)*</td>
                <td align="center">2</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <p>CI; Confidence Interval JCS; Japan coma scale OR; Odds ratio</p>
            <p>P value for logistic regression analysis ; *P &lt; 0.01</p>
          </table-wrap-foot>
        </table-wrap>
        <p>The prehospital score component was equated to 1, 2 or 3 when the beta coefficient was &lt;0.5, 0.5–1.0 or ≥ 1.0, respectively. The total score calculated by adding the six component scores to give a value from 0 to 14.</p>
      </sec>
      <sec>
        <title>Results of retrospective scoring</title>
        <p>The distribution of total scores for the hospitalization and non-hospitalization groups is shown in Figure <xref ref-type="fig" rid="F1">1</xref>; the hospitalization group follows an approximately normal distribution, while the non-hospitalization group is skewed with most patients receiving a low score. The modal score of the hospitalization group was 4 while that of the non-hospitalization group was 2.</p>
        <fig position="float" id="F1">
          <label>Figure 1</label>
          <caption>
            <p><bold>The number of patients according to prehospital score</bold>. The modal score of the hospitalization group was 4 while that of the non-hospitalization group was 2 (n = 8,330).</p>
          </caption>
          <graphic xlink:href="1471-227X-7-17-1"/>
        </fig>
        <p>Figure <xref ref-type="fig" rid="F2">2</xref> shows the proportion and 95% confidence interval of hospitalization in relation to total score. A linear relationship was observed between the score and the proportion hospitalized: 9% of patients with a score of 0 required hospitalization, and this increased to 100% for those with a score of 13.</p>
        <fig position="float" id="F2">
          <label>Figure 2</label>
          <caption>
            <p><bold>The proportion hospitalized (with 95% confidence intervals) in relation to prehospital score</bold>. A linear relationship was observed between the score and the proportion hospitalized (n = 8,330).</p>
          </caption>
          <graphic xlink:href="1471-227X-7-17-2"/>
        </fig>
        <p>Among the 102 patients requiring hospitalization with a total score ≤ 1, 55 (51%) were diagnosed with digestive disease, including 10 with gastrointestinal bleeding, 5 with cholangitis, 6 with pancreatitis and 7 with appendicitis. This contrasts with the overall proportion of digestive disease of 19%. In addition, 16 patients (15%) were diagnosed with psychiatric disease and 12 (7%) with cerebral disease. This compares with overall proportions of 7% for psychiatric disease and 19% for cerebral disease. Only 14 patients were not hospitalized despite a high total score (≥ 11). These included 4 patients suffering from a hypoglycemic attack, 7 with loss of consciousness and suspected vasovagal syncope, 2 with atrial arrhythmia and 1 with malignancy. Among the 165 patients who died in the emergency room, one had a total score of 4, three scored 7, one scored 8, seven scored 9 and the remainder scored ≥ 10. Those patients scoring 4–9 rapidly underwent cardiopulmonary arrest following headache, chest pain, dyspnea, fatigue and loss of consciousness.</p>
        <p>Figure <xref ref-type="fig" rid="F3">3</xref> shows the proportions of patients transported to the two main hospitals who were non-hospitalized, discharged after hospitalization, transferred to another hospital or died (n = 6,498, 71% of the subjects). The proportion non-hospitalized declined, and the proportions discharged after hospitalization, transferred to another hospital or died all increased linearly, between scores 2 and 10. At score 0 or 1, there were no deaths and the proportion non-hospitalized was over 90%. The proportion discharged after hospitalization was higher than the proportion who died at scores ≤ 10. The proportion who died increased rapidly at scores ≥ 11 and exceeded 80% at scores ≥ 12. Among these 6,498 patients, 14 with total scores ≤ 3 died after hospitalization, including 7 with malignancy, 3 with liver cirrhosis and 2 with cardiovascular disease.</p>
        <fig position="float" id="F3">
          <label>Figure 3</label>
          <caption>
            <p><bold>Outcome proportions in relation to prehospital score</bold>. The outcome proportions including after hospitalization were calculated for patients transported to the two main hospitals. The proportion discharged after hospitalization was higher than the proportion who died at scores ≤ 10, and <italic>vice versa </italic>at scores ≥ 11 (n = 6,498).</p>
          </caption>
          <graphic xlink:href="1471-227X-7-17-3"/>
        </fig>
      </sec>
      <sec>
        <title>Sensitivity and specificity of prehospital score</title>
        <p>Figure <xref ref-type="fig" rid="F4">4</xref> shows the ROC curve; the area under the curve is 0.75 (95% confidence interval 0.74–0.76, n = 8,330). When that was set at ≥ 2, the sensitivity, specificity, PPV and NPV were 97%, 16%, 39% and 89%, respectively (Table <xref ref-type="table" rid="T2">2</xref>).</p>
        <fig position="float" id="F4">
          <label>Figure 4</label>
          <caption>
            <p><bold>ROC curve for prehospital score to predict hospitalization</bold>. The area under the curve was 0.75 (95% confidence intervals 0.74–0.76, n = 8,330).</p>
          </caption>
          <graphic xlink:href="1471-227X-7-17-4"/>
        </fig>
        <table-wrap position="float" id="T2">
          <label>Table 2</label>
          <caption>
            <p>Screening parameters according to each cut-off point of prehospital score</p>
          </caption>
          <table frame="hsides" rules="groups">
            <thead>
              <tr>
                <td align="left">Cut off point</td>
                <td align="left">%Sensitivity</td>
                <td align="left">%Specificity</td>
                <td align="left">%PPV</td>
                <td align="left">%NPV</td>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td align="left">&gt;=1</td>
                <td align="left">97.1</td>
                <td align="left">13.4</td>
                <td align="left">38.7</td>
                <td align="left">89.1</td>
              </tr>
              <tr>
                <td align="left">&gt;=2</td>
                <td align="left">96.5</td>
                <td align="left">15.9</td>
                <td align="left">39.3</td>
                <td align="left">89.0</td>
              </tr>
              <tr>
                <td align="left">&gt;=3</td>
                <td align="left">86.6</td>
                <td align="left">43.2</td>
                <td align="left">46.2</td>
                <td align="left">85.1</td>
              </tr>
              <tr>
                <td align="left">&gt;=4</td>
                <td align="left">83.4</td>
                <td align="left">50.0</td>
                <td align="left">48.3</td>
                <td align="left">84.1</td>
              </tr>
              <tr>
                <td align="left">&gt;=5</td>
                <td align="left">67.0</td>
                <td align="left">70.8</td>
                <td align="left">56.4</td>
                <td align="left">79.2</td>
              </tr>
              <tr>
                <td align="left">&gt;=6</td>
                <td align="left">55.5</td>
                <td align="left">81.8</td>
                <td align="left">63.2</td>
                <td align="left">76.5</td>
              </tr>
              <tr>
                <td align="left">&gt;=7</td>
                <td align="left">42.8</td>
                <td align="left">89.9</td>
                <td align="left">70.6</td>
                <td align="left">73.6</td>
              </tr>
              <tr>
                <td align="left">&gt;=8</td>
                <td align="left">31.3</td>
                <td align="left">95.1</td>
                <td align="left">78.2</td>
                <td align="left">71.1</td>
              </tr>
              <tr>
                <td align="left">&gt;=9</td>
                <td align="left">22.2</td>
                <td align="left">97.9</td>
                <td align="left">85.8</td>
                <td align="left">69.1</td>
              </tr>
              <tr>
                <td align="left">&gt;=10</td>
                <td align="left">14.1</td>
                <td align="left">99.3</td>
                <td align="left">91.8</td>
                <td align="left">67.2</td>
              </tr>
              <tr>
                <td align="left">&gt;=11</td>
                <td align="left">10.1</td>
                <td align="left">99.9</td>
                <td align="left">95.6</td>
                <td align="left">66.3</td>
              </tr>
              <tr>
                <td align="left">&gt;=12</td>
                <td align="left">6.0</td>
                <td align="left">100</td>
                <td align="left">98.9</td>
                <td align="left">65.4</td>
              </tr>
              <tr>
                <td align="left">&gt;=13</td>
                <td align="left">5.0</td>
                <td align="left">100</td>
                <td align="left">100</td>
                <td align="left">65.1</td>
              </tr>
              <tr>
                <td align="left">&gt;=14</td>
                <td align="left">2.0</td>
                <td align="left">100</td>
                <td align="left">100</td>
                <td align="left">64.4</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <p>PPV: Positive predictive value</p>
            <p>NPV: Negative predictive value</p>
            <p>CI: Confidence interval</p>
          </table-wrap-foot>
        </table-wrap>
      </sec>
    </sec>
    <sec>
      <title>Discussion</title>
      <p>This study is an investigation of the relationship between prehospital data and requirement for hospitalization in acute disease patients aged ≥ 15 years; it also details the development of a simple triage assessment tool. Age, systolic blood pressure, pulse rate, level of consciousness, SpO<sub>2</sub>level and ability to walk were found to be statistically significant predictors for hospitalization requirement. A prehospital score ranging from 0 to 14 was developed on the basis of the multivariable analysis results.</p>
      <p>In western countries, prehospital triage guidelines are based on patient symptoms for acute disease [<xref ref-type="bibr" rid="B10">10</xref>-<xref ref-type="bibr" rid="B16">16</xref>], but these are inappropriate for use in Japan as emergency life-saving technicians can only perform limited medical treatments.</p>
      <p>There has been only one prehospital triage tool for acute disease and trauma in Japan: the prehospital severity and urgency criterion, produced by the Japan Foundation for Ambulance Service Development in 2004 [<xref ref-type="bibr" rid="B17">17</xref>]. However, this criterion is complex to use because it is based on 10 categories: trauma, burn, intoxication, consciousness disorder, chest pain, dyspnea, gastrointestinal bleeding, abdominal pain, pregnancy, and infancy; it requires approximately 20 items to be checked. In practice, this criterion is not used because of its complexity. Moreover, criteria based on chief complaints are of little use for cases with complaints outside those 10 categories, such as paralysis or headache [<xref ref-type="bibr" rid="B11">11</xref>].</p>
      <p>In contrast, the prehospital score of the present study is a simple to use, comprehensive triage tool for acute disease. Furthermore, emergency personnel without emergency life-saving technician licences could use this scoring system because of its simplicity.</p>
      <p>Sensitivity, specificity, PPV and NPV are barometers for the utility of a triage tool. As under-triage is less desirable than over-triage, sensitivity is more important than specificity. When we set the cut-off point at total score ≥ 2, sensitivity and specificity were respectively 97% (2,900/3,002) and 16% (841/5,328). Furthermore, we can also predict the likelihood of death as 0% and 100% when the score is low (≤ 1) or high (≥ 12), respectively.</p>
      <p>If ambulance transfer is refused for patients with score ≤ 1, 16% (841/5,328) of cases of inappropriate ambulance usage would be avoided. On the other hand, this decision made 3.5% (102/3,002) into under-triage cases.</p>
      <p>Previous studies in western countries have reported prehospital guidelines for predicting the requirement for admission to the emergency department (sensitivity = 90% and specificity = 37%) [<xref ref-type="bibr" rid="B11">11</xref>] and a prehospital protocol for predicting the critical event during transport (sensitivity = 95% and specificity = 33%) [<xref ref-type="bibr" rid="B12">12</xref>]. These studies relied on detailed protocols according to symptoms. Although simple comparison with our study is difficult because of differences in the medical systems, our scoring system showed higher sensitivity and lower specificity. To avoid under-triage, lower specificity might be inevitable.</p>
      <p>However, this study is not without its limitations. First, the scoring system did not include information other than the six fundamental elements. For example, the chief complaint is often strongly associated with outcome: chest pain, paralysis, hematemesis or melena. Patients with gastrointestinal bleeding usually require hospitalization, yet 10 patients in this study with gastrointestinal bleeding scored ≤ 1. Moreover, 4 cerebral infarction cases, 1 myocardial infarction case, 1 pneumothorax case and 1 tuberculosis case scored ≤ 1. These cases needed rapid transfer to an emergency hospital. If low-scoring (&lt;=1) patients with chest pain, paralysis, hematemesis or melena were considered as indicating ambulance usage, 17% (17/102) of under-triage cases could be avoided. Since our purpose is to develop a simple triage tool that would be useful for ambulance refusal for Japan emergency personnel regardless of emergency life-saving technician licence, an additional assessment for chief complaints would be necessary for practical use. However, sensitivity and specificity did not change substantially when these chief complaints were taken into account (97% and 15%, respectively).</p>
      <p>Second, the scoring system was mainly based on patient vital signs, but did not include body temperature or respiration rate. The method for measuring body temperature in the prehospital setting is not standardized; some are measured by tympanic temperature, others by axillary temperature. Therefore, we did not use body temperature. The inclusion of respiration rate in the regression model excluded 15% of the subject data and did not improve the predictive value for hospitalization (sensitivity = 97% and specificity = 15%).</p>
      <p>Third, the proportion of emergency hospitalization in Kishiwada City is substantially lower than the national average: 36% compared with 49%. Criteria for hospitalization vary according to areas and hospitals. Furthermore, we could not obtain complete data for 9% of patients in Kishiwada City. Therefore, the external validity of the prehospital score is uncertain.</p>
      <p>Fourth, we had no follow-up data on patients who were not hospitalized. Some might be misdiagnosed in the emergency room and not hospitalized at that time, but would then be hospitalized after a few days.</p>
      <p>Despite these limitations, the present study suggests that a simple score based on 6 fundamental elements enables us to decide whether ambulance transfer is indicated with 97% sensitivity and 16% specificity. In the near future, refusal of ambulance transfer for mild patients may be allowed in Japan. Our prehospital score could be a tool for deciding transfer refusal by emergency personnel.</p>
    </sec>
    <sec>
      <title>Conclusion</title>
      <p>We have developed a prehospital score, a simple acute disease triage tool for Japan's emergency medical service system. Further research on validity would be necessary.</p>
    </sec>
    <sec>
      <title>Competing interests</title>
      <p>The author(s) declare that they have no competing interests.</p>
    </sec>
    <sec>
      <title>Authors' contributions</title>
      <p>YM, HT and HF were involved in the acquisition of data. YT was involved in data analysis and drafting the manuscript. TT and HI provided statistical advice on study design and critical revision of the manuscript. All authors read and approved the final manuscript</p>
    </sec>
    <sec>
      <title>Pre-publication history</title>
      <p>The pre-publication history for this paper can be accessed here:</p>
      <p>
        <ext-link ext-link-type="uri" xlink:href="http://www.biomedcentral.com/1471-227X/7/17/prepub"/>
      </p>
    </sec>
  </body>
  <back>
    <ack>
      <sec>
        <title>Acknowledgements</title>
        <p>The authors thank the staff of Kishiwada City Fire Department who recorded the prehospital data. This study was supported by the Grant-in-Aid for Scientific Research, Ministry of Education, Culture, Sports, Science and Technology, Japan (Grant number: 18659149).</p>
      </sec>
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</metadata></record><record><header><identifier>oai:pubmedcentral.nih.gov:2080630</identifier><datestamp>2007-11-17</datestamp><setSpec>bmchsr</setSpec><setSpec>pmc-open</setSpec></header><metadata><article xmlns="http://dtd.nlm.nih.gov/2.0/xsd/archivearticle" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://dtd.nlm.nih.gov/archiving/2.3/xsd/archivearticle.xsd" article-type="research-article">
  <front>
    <journal-meta>
      <journal-id journal-id-type="nlm-ta">BMC Health Serv Res</journal-id>
      <journal-title>BMC Health Services Research</journal-title>
      <issn pub-type="epub">1472-6963</issn>
      <publisher>
        <publisher-name>BioMed Central</publisher-name>
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      <article-id pub-id-type="pmc">2080630</article-id>
      <article-id pub-id-type="publisher-id">1472-6963-7-136</article-id>
      <article-id pub-id-type="pmid">17764549</article-id>
      <article-id pub-id-type="doi">10.1186/1472-6963-7-136</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Development of a complex intervention to test the effectiveness of peer support in type 2 diabetes</article-title>
      </title-group>
      <contrib-group>
        <contrib id="A1" corresp="yes" contrib-type="author">
          <name>
            <surname>Paul</surname>
            <given-names>Gillian</given-names>
          </name>
          <xref ref-type="aff" rid="I1">1</xref>
          <email>gpaul@tcd.ie</email>
        </contrib>
        <contrib id="A2" contrib-type="author">
          <name>
            <surname>Smith</surname>
            <given-names>Susan M</given-names>
          </name>
          <xref ref-type="aff" rid="I1">1</xref>
          <email>susmith@tcd.ie</email>
        </contrib>
        <contrib id="A3" contrib-type="author">
          <name>
            <surname>Whitford</surname>
            <given-names>David</given-names>
          </name>
          <xref ref-type="aff" rid="I2">2</xref>
          <email>dwhitford@rcsi.ie</email>
        </contrib>
        <contrib id="A4" contrib-type="author">
          <name>
            <surname>O'Kelly</surname>
            <given-names>Fergus</given-names>
          </name>
          <xref ref-type="aff" rid="I3">3</xref>
          <email>feokelly@tcd.ie</email>
        </contrib>
        <contrib id="A5" contrib-type="author">
          <name>
            <surname>O'Dowd</surname>
            <given-names>Tom</given-names>
          </name>
          <xref ref-type="aff" rid="I1">1</xref>
          <email>todowd@tcd.ie</email>
        </contrib>
      </contrib-group>
      <aff id="I1"><label>1</label>Department of Public Health and Primary Care, Trinity College, Dublin 2, Ireland</aff>
      <aff id="I2"><label>2</label>Department of General Practice, RCSI, Dublin 2, Ireland</aff>
      <aff id="I3"><label>3</label>Trinity College-Eastern Regional General Practice Training Programme, Health Services Executive, Dublin 2, Ireland</aff>
      <pub-date pub-type="collection">
        <year>2007</year>
      </pub-date>
      <pub-date pub-type="epub">
        <day>31</day>
        <month>8</month>
        <year>2007</year>
      </pub-date>
      <volume>7</volume>
      <fpage>136</fpage>
      <lpage>136</lpage>
      <ext-link ext-link-type="uri" xlink:href="http://www.biomedcentral.com/1472-6963/7/136"/>
      <history>
        <date date-type="received">
          <day>13</day>
          <month>3</month>
          <year>2007</year>
        </date>
        <date date-type="accepted">
          <day>31</day>
          <month>8</month>
          <year>2007</year>
        </date>
      </history>
      <permissions>
        <copyright-statement>Copyright © 2007 Paul et al; licensee BioMed Central Ltd.</copyright-statement>
        <copyright-year>2007</copyright-year>
        <copyright-holder>Paul et al; licensee BioMed Central Ltd.</copyright-holder>
        <license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/2.0">
          <p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/2.0"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>
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               Paul
               Gillian
               
               gpaul@tcd.ie
            </dc:author><dc:title>
            Development of a complex intervention to test the effectiveness of peer support in type 2 diabetes
         </dc:title><dc:date>2007</dc:date><dcterms:bibliographicCitation>BMC Health Services Research 7(1): 136-. (2007)</dcterms:bibliographicCitation><dc:identifier type="sici">1472-6963(2007)7:1&#x0003c;136&#x0003e;</dc:identifier><dcterms:isPartOf>urn:ISSN:1472-6963</dcterms:isPartOf><License rdf:about="http://creativecommons.org/licenses/by/2.0"><permits rdf:resource="http://web.resource.org/cc/Reproduction" xmlns=""/><permits rdf:resource="http://web.resource.org/cc/Distribution" xmlns=""/><requires rdf:resource="http://web.resource.org/cc/Notice" xmlns=""/><requires rdf:resource="http://web.resource.org/cc/Attribution" xmlns=""/><permits rdf:resource="http://web.resource.org/cc/DerivativeWorks" xmlns=""/></License></Work></rdf>-->
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      <abstract>
        <sec>
          <title>Background</title>
          <p>Diabetes is a chronic illness which requires the individual to assume responsibility for their own care with the aim of maintaining glucose and blood pressure levels as close to normal as possible. Traditionally self management training for diabetes has been delivered in a didactic setting. In recent times alternatives to the traditional delivery of diabetes care have been investigated, for example, the concept of peer support which emphasises patient rather than professional domination. The aim of this paper is to describe the development of a complex intervention of peer support in type 2 diabetes for a randomised control trial in a primary care setting.</p>
        </sec>
        <sec sec-type="methods">
          <title>Methods</title>
          <p>The Medical Research Council (MRC) framework for the development and evaluation of complex interventions for randomised control trials (RCT) was used as a theoretical guide to designing the intervention.</p>
          <p>The first three phases (Preclinical Phase, Phase 1, Phase 2) of this framework were examined in depth. The Preclinical Phase included a review of the literature relating to type 2 diabetes and peer support. In Phase 1 the theoretical background and qualitative data from 4 focus groups were combined to define the main components of the intervention. The preliminary intervention was conducted in Phase 2. This was a pilot study conducted in two general practices and amongst 24 patients and 4 peer supporters. Focus groups and semi structured interviews were conducted to collect additional qualitative data to inform the development of the intervention.</p>
        </sec>
        <sec>
          <title>Results</title>
          <p>The four components of the intervention were identified from the Preclinical Phase and Phase 1. They are: 1. Peer supporters; 2. Peer supporter training; 3. Retention and support for peer supporters; 4.Peer support meetings. The preliminary intervention was implemented in the Phase 2. Findings from this phase allowed further modeling of the intervention, to produce the definitive intervention.</p>
        </sec>
        <sec>
          <title>Conclusion</title>
          <p>The MRC framework was instrumental in the development of a robust intervention of peer support of type 2 diabetes in primary care.</p>
        </sec>
        <sec>
          <title>Trial registration</title>
          <p>Current Controlled Trials ISRCTN42541690</p>
        </sec>
      </abstract>
    </article-meta>
  </front>
  <body>
    <sec>
      <title>Background</title>
      <p>Diabetes is a chronic illness which requires the individual to assume responsibility for their own care with the aim of maintaining glucose and blood pressure levels as close to normal as possible [<xref ref-type="bibr" rid="B1">1</xref>]. Maintaining optimal glucose and blood pressure levels reduces the risk of diabetes related complications [<xref ref-type="bibr" rid="B2">2</xref>,<xref ref-type="bibr" rid="B3">3</xref>]. Treatment of diabetes involves psychological, social and physical adjustments to an individual's lifestyle [<xref ref-type="bibr" rid="B1">1</xref>]. This can be confusing and overwhelming for people with diabetes [<xref ref-type="bibr" rid="B4">4</xref>]. They have to make a complex range of lifestyle modifications sometimes without necessarily noticing any tangible effects [<xref ref-type="bibr" rid="B4">4</xref>]. Emotional and quality of life issues need to be attended to as well as physical issues [<xref ref-type="bibr" rid="B4">4</xref>].</p>
      <p>Diabetes self management training has traditionally been delivered in a didactic setting with emphasis on imparting knowledge. However this approach has been shown to be ineffective in individual behaviour change and improving metabolic control [<xref ref-type="bibr" rid="B5">5</xref>]. In recent times alternatives to the traditional delivery of diabetes care have been investigated, for example, the concept of peer support which emphasises patient rather than professional domination [<xref ref-type="bibr" rid="B1">1</xref>]. Peer support could be implemented to complement existing diabetes care. Structured care for people with type 2 diabetes in general practice is not yet well established in the Republic of Ireland [<xref ref-type="bibr" rid="B6">6</xref>]. Prevalence of diabetes amongst people over 40 years of age attending 41 general practices in the Republic of Ireland reported a prevalence of type 2 diabetes of 9.2% indicating similar prevalence figures to other European countries [<xref ref-type="bibr" rid="B6">6</xref>]. The usual care of patients with type 2 diabetes in the Republic of Ireland is outlined in Figure <xref ref-type="fig" rid="F1">1</xref>.</p>
      <fig position="float" id="F1">
        <label>Figure 1</label>
        <caption>
          <p>Usual care in the general practice setting for people with type 2 diabetes [31, 32].</p>
        </caption>
        <graphic xlink:href="1472-6963-7-136-1"/>
      </fig>
      <p>Testing a complex intervention such as peer support presents a challenge to researchers. Complex health interventions are built up of several components which may include organisational and delivery methods [<xref ref-type="bibr" rid="B7">7</xref>,<xref ref-type="bibr" rid="B8">8</xref>]. The fact that they involve a number of separate components presents difficulties in isolating the "active ingredient" of the intervention that is effective [<xref ref-type="bibr" rid="B8">8</xref>,<xref ref-type="bibr" rid="B9">9</xref>]. Therefore it is recommended that a complex intervention for an RCT should be carefully planned and designed [<xref ref-type="bibr" rid="B10">10</xref>]. To guide researchers, the UK Medical Research Council (MRC) devised a five phase framework for developing and evaluating RCT's of complex interventions [<xref ref-type="bibr" rid="B8">8</xref>]. The framework is comprised of five phases [<xref ref-type="bibr" rid="B8">8</xref>]. The Pre-clinical phase involves establishing a theoretical basis to support the intervention. Phase 1, modelling, involves developing an understanding of the intervention and its possible effects. At this point the components of the intervention are delineated. These first two phases are often interrelated. Phase 2, the exploratory trial, is crucial. This is a test of the feasibility of key components of the intervention. Phase 3 is the definitive RCT. Finally long term implementation of the intervention is examined in Phase 4. A flowchart of the methodology of the application of the framework is presented in Figure <xref ref-type="fig" rid="F2">2</xref>.</p>
      <fig position="float" id="F2">
        <label>Figure 2</label>
        <caption>
          <p>A flowchart of the methodology of the application of the framework.</p>
        </caption>
        <graphic xlink:href="1472-6963-7-136-2"/>
      </fig>
      <p>This framework has been utilised in a variety of RCT's that have evaluated complex interventions in primary care [<xref ref-type="bibr" rid="B7">7</xref>,<xref ref-type="bibr" rid="B11">11</xref>-<xref ref-type="bibr" rid="B13">13</xref>]. These RCT's examine professionally led interventions for example a behaviour change intervention delivered by primary care practitioners to patients with coronary heart disease [<xref ref-type="bibr" rid="B10">10</xref>]. This paper is the first to examine the development of a complex intervention involving peer support.</p>
      <p>We describe below, the application of the first three phases of the MRC framework which led to the development of the intervention of peer support in type 2 diabetes based in primary care. The definitive intervention is currently being tested in a cluster RCT, the peer support in diabetes study (Table <xref ref-type="table" rid="T1">1</xref>).</p>
      <table-wrap position="float" id="T1">
        <label>Table 1</label>
        <caption>
          <p>Summary of study</p>
        </caption>
        <table frame="hsides" rules="groups">
          <thead>
            <tr>
              <td align="center">
                <bold>The peer support in diabetes study</bold>
              </td>
            </tr>
          </thead>
          <tbody>
            <tr>
              <td align="left">• <bold>Aims</bold></td>
            </tr>
            <tr>
              <td align="left">To determine whether a peer support programme for patients with type 2 diabetes improves biophysical and psychosocial outcomes and whether it is an acceptable, cost effective intervention in a primary care setting</td>
            </tr>
            <tr>
              <td align="left">• <bold>Design</bold></td>
            </tr>
            <tr>
              <td align="left">Cluster randomised controlled trial.</td>
            </tr>
            <tr>
              <td align="left">• <bold>Participants</bold></td>
            </tr>
            <tr>
              <td align="left">420 patients with type 2 diabetes recruited from 20 general practices<break/>30 peer supporters, also patients with type 2 diabetes, from 10 intervention general practices.</td>
            </tr>
            <tr>
              <td align="left">• <bold>Primary Outcomes</bold></td>
            </tr>
            <tr>
              <td align="left">Blood pressure<break/>Total cholesterol<break/>HBA1c<break/>Well being score [14]</td>
            </tr>
          </tbody>
        </table>
      </table-wrap>
    </sec>
    <sec>
      <title>Aims</title>
      <sec>
        <title>Preclinical phase</title>
        <p>The aim of the Preclinical Phase was to review the theoretical basis of peer support and to identify evidence to support the concept.</p>
        <sec>
          <title>Phase 1</title>
          <p>The aim of Phase 1 was to combine the theoretical basis from the Preclinical Phase with qualitative work to define the components of the intervention.</p>
        </sec>
      </sec>
      <sec>
        <title>Phase 2</title>
        <p>The aim of Phase 2 was to conduct a pilot study to test the feasibility of the intervention.</p>
      </sec>
    </sec>
    <sec sec-type="methods">
      <title>Methods</title>
      <sec>
        <title>Preclinical phase</title>
        <p>The Preclinical Phase involved conducting a literature search using CINHAL, Medline and the Cochrane Library. Key words included RCT, diabetes, type 2 diabetes, primary care, community health workers, lay health workers, chronic illness, voluntary workers and peer support workers. The literature retrieved was examined in depth and the concept of peer support was explored. Themes for components of the intervention evolved from reviewing this literature.</p>
        <sec>
          <title>Phase 1</title>
          <p>In Phase 1, the modelling phase, the theoretical basis from the Preclinical Phase was combined firstly with information from interviews with experts in the area of health psychology, diabetes and volunteering and secondly with qualitative data from focus groups with patients with type 2 diabetes and practice staff. Two focus groups (6 patients in each group) were conducted with patients in the two participating general practices. The topic guide included the meaning of the term peer support; the nature of support for people with type 2 diabetes; and an exploration of how peer support differs from professional support. Two focus groups (4 in each group) were conducted with practice staff from the two participating general practices. The topic guide included the definition of peer support; advantages and disadvantages of peer support; and training and support for peer supporters. The focus groups were conducted by a moderator and an observer. Each focus group was taped and the discussions then transcribed and analysed. Descriptive phenomenology was the theoretical framework used for the analysis of the qualitative data. This qualitative research tradition seeks to understand the lived experience of individuals [<xref ref-type="bibr" rid="B15">15</xref>]. The combination of information from the Preclinical and this Phase 1 led to the unravelling of four critical components of the preliminary intervention.</p>
        </sec>
        <sec>
          <title>Phase 2</title>
          <p>Phase 2, the exploratory trial/pilot study, involved testing the preliminary intervention. Two general practices were selected. Both are training practices attached to a university post graduate training scheme. One was a small single handed practice and the other a large group practice. Both had a practice nurse and used computerised records. Neither practices had structured diabetes care clinics. Practice staff compiled a register of patients with type 2 diabetes. Twenty two patients and four peer supporters from the two practices were purposefully selected to participate. The peer supporters, who were selected by the GPs, attended two evening training sessions conducted by the research team. The preliminary intervention was delivered in both practices- each peer supporter facilitated three peer group meetings with participating patients over a period of four months. Quantitative data were collected from participants prior to and following the meetings and was analysed using JMP IN statistical package. Qualitative research was also conducted in Phase 2 following the preliminary intervention; two focus groups with five patients each and one focus group with four peer supporters. The topic guide for these focus groups included feedback from the peer group meetings; how peer support differs from support from GPs and practice nurses; and positive and negative aspects of peer support. In addition to these themes the peer supporters were asked about training and ongoing support for peer supporters. The qualitative methodology used was the same as that for phase 1. In addition, three semi-structured interviews with practice staff were conducted following the preliminary intervention. The discussions were based around the logistics of holding the group meetings in the general practices; and recruitment, retention and support for the peer supporters.</p>
        </sec>
      </sec>
    </sec>
    <sec>
      <title>Ethical approval</title>
      <p>Ethical approval has been obtained from the Ethics Committee of the Irish College of General Practitioners (Protocol No.: REC0904-11; 01/12/04)</p>
    </sec>
    <sec>
      <title>Results</title>
      <sec>
        <title>Preclinical phase</title>
        <p>Theoretical and empirical evidence for peer support was identified in the literature search.</p>
        <p>Peer support within the healthcare context is defined as "the provision of emotional, appraisal, and informational assistance by a created social network member who possesses experiential knowledge of a specific behaviour or stressor and similar characteristics as the target population, to address a health-related issue of a potentially or actually stressed focal person" [<xref ref-type="bibr" rid="B16">16</xref>]. This definition of peer support falls within the social support model, that is defined as the process through which social relationships might promote health and well-being [<xref ref-type="bibr" rid="B17">17</xref>]. Within the social support model, the direct effect model would postulate that peer support could reduce feelings of isolation and loneliness, provide information about access to health services or the benefits of behaviours that positively improve health and well-being and encourage more positive health practices [<xref ref-type="bibr" rid="B16">16</xref>].</p>
        <p>The logic behind peer support programmes is that peers have a greater understanding of the target population's situation than other naturally embedded social networks [<xref ref-type="bibr" rid="B16">16</xref>]. During times of need or in stressful situations individuals often turn to social contacts and relationships for support to supplement the care given by the health services [<xref ref-type="bibr" rid="B16">16</xref>].</p>
        <p>Members of their own social network may not be able to offer appropriate support for various reasons. For example they may lack experience and knowledge of the stressful life event; they may feel uncomfortable about the issue or are too upset to provide support [<xref ref-type="bibr" rid="B18">18</xref>].</p>
        <p>Peer support groups provide individuals with a unique support system where they can gain understanding and feel a sense of belonging. As the group evolves attachments are formed and expressions of caring and genuine concern from the group provides emotional support [<xref ref-type="bibr" rid="B18">18</xref>].</p>
        <p>Peer support was found to be successful in some health care settings. It has improved outcomes in diverse health settings such as maternal child health development[<xref ref-type="bibr" rid="B19">19</xref>], neonatal mortality [<xref ref-type="bibr" rid="B20">20</xref>,<xref ref-type="bibr" rid="B21">21</xref>] and cardiac surgery [<xref ref-type="bibr" rid="B22">22</xref>].</p>
        <p>Peer support workers also known as lay health workers are defined in a Cochrane review as "any health worker carrying out functions related to health care delivery; trained in some way in the context of the intervention; having no formal professional or paraprofessional certificated or degree tertiary education" (page 1) [<xref ref-type="bibr" rid="B23">23</xref>]. Training for peer support workers should incorporate exploration of the skills required to use experiential knowledge and peer's appreciation and understanding of the target group [<xref ref-type="bibr" rid="B16">16</xref>]. However Giblin warns against too much specific training, as this may destruct the concept of "peerness" [<xref ref-type="bibr" rid="B24">24</xref>]. In addition to peer support benefiting recipients, peer supporters have reported benefits from their role [<xref ref-type="bibr" rid="B25">25</xref>-<xref ref-type="bibr" rid="B27">27</xref>].</p>
        <p>Qualitative research conducted for the Diabetes National Service Framework revealed that people with diabetes felt it would be helpful to meet others in similar circumstances. Peers were viewed as an under-utilised, helpful, source of information and support [<xref ref-type="bibr" rid="B28">28</xref>]. However there are no reported randomised controlled trials of peer support in type 2 diabetes. The literature review highlighted the need for a careful consideration of an underlying theoretical framework and the importance of exploratory qualitative work with individuals with type 2 diabetes in the context within which the study was planned.</p>
      </sec>
      <sec>
        <title>Phase 1</title>
        <p>In Phase 1, issues raised in the interviews with experts included the identification of social support as a theoretical framework for the study. In addition, experts working in the volunteering sector highlighted the importance of continuing support for the peer supporters to sustain the programme over time.</p>
        <p>The patients involved in the exploratory qualitative work expressed enthusiasm for the idea of peer support.</p>
        <p>FG1.5 "I thought it would be a good idea for me because from the point of view of the diet it could help me keep me on track. Hearing others ideas and sharing them and so on"</p>
        <p>They reported a tendency to turn to peers for advice but felt that a structured support network would be more helpful.</p>
        <p>FG2.3 "Very helpful because you are going into a hospital, seeing a doctor, but you are not seeing other people who have it like ourselves"</p>
        <p>They had a preference for group rather than individual meetings. Both patients and practice staff felt that peer supporters required specific training that should include the basics of treatment for diabetes and managing a group. However there was a consensus that medical questions from group members should be referred to the GP or practice nurse.</p>
        <p>FG7.2 "It is very important for the peer supporters to know their boundaries. They are not doctors"</p>
        <p>The work in the Preclinical Phase and in phase 1 led to the identification of four preliminary intervention components:</p>
        <p>1. Peer supporters</p>
        <p>2. Peer supporter training</p>
        <p>3. Retention and support for peer supporters</p>
        <p>4. Peer support meetings</p>
        <sec>
          <title>Phase 2</title>
          <p>Phase 2, the exploratory trial/pilot study, involved testing the following preliminary intervention in two general practices:</p>
        </sec>
        <sec>
          <title>1. Peer supporters</title>
          <p>The GPs and practice nurses in each practice were asked to select two patients with type 2 diabetes who would be suitable for the role of peer supporter. All four peer supporters recruited by the GPs and practice nurses had type 2 diabetes for over a year and were compliant to their treatment regime. Further peer supporter characteristics are presented in Table <xref ref-type="table" rid="T2">2</xref>. Findings from the semi structured interviews indicated that the GP's and practice nurses felt they should identify the peer supporters within their own practices.</p>
          <table-wrap position="float" id="T2">
            <label>Table 2</label>
            <caption>
              <p>Personal characteristic of the patients and peer supporters that participated in the study</p>
            </caption>
            <table frame="hsides" rules="groups">
              <thead>
                <tr>
                  <td/>
                  <td align="left">
                    <bold>Patient participants</bold>
                  </td>
                  <td align="left">
                    <bold>Peer supporters</bold>
                  </td>
                </tr>
              </thead>
              <tbody>
                <tr>
                  <td align="left">Male</td>
                  <td align="left">13 (59%)</td>
                  <td align="left">4 (100%)</td>
                </tr>
                <tr>
                  <td align="left">Mean age (yrs)</td>
                  <td align="left">66</td>
                  <td align="left">65</td>
                </tr>
                <tr>
                  <td align="left">Mean yrs since diagnosis of type 2 diabetes</td>
                  <td align="left">4</td>
                  <td align="left">7</td>
                </tr>
                <tr>
                  <td align="left">Entitled to medical card</td>
                  <td align="left">14 (64%)</td>
                  <td align="left">2 (50%)</td>
                </tr>
                <tr>
                  <td align="left">Smoker</td>
                  <td align="left">3 (14%)</td>
                  <td align="left">0 (0%)</td>
                </tr>
              </tbody>
            </table>
          </table-wrap>
        </sec>
        <sec>
          <title>2. Peer supporter training</title>
          <p>Two evening training sessions were organised for the peer supporters. The content of these sessions included the role of the peer supporter, basics of diabetes, lifestyle and medication issues, communication skills, managing groups, confidentiality, role play and support for the peer supporters. The sessions were interactive and informal. They were given a handbook that covered issues raised in the training session. The focus group with the peer supporters revealed that the peer supporters found the training informative and pitched at the correct level. They valued the handbook and referred to it on several occasions during the course of the exploratory trial.</p>
        </sec>
        <sec>
          <title>3. Retention and support for peer supporters</title>
          <p>A support system for the peer supporters was implemented. This consisted of the project manager contacting each peer supporter after each group session. This was to allow the peer supporter to debrief and discuss any problems that arose during the course of the meeting. The peer supporters reported that they appreciated this contact.</p>
          <p>FG5.6 "Someone out there behind you...Someone behind you saying well how did it go, so you are not left"</p>
        </sec>
        <sec>
          <title>4. Peer support meetings</title>
          <p>Patients were allocated, by GPs and PNs, to each peer supporter within each practice. Three meetings per group were organised and two groups met in the evening and the other two met during the day. Eighty per cent of patients went to two or three group meetings. Feedback in the focus groups with the peer supporters and patients was positive. Both patients and peer supporters reflected that they enjoyed meeting other people with type 2 diabetes. Exchanging practical information, comparing each others situations, conversing in lay terms and general support amongst the group were identified as particularly positive elements of the group meetings.</p>
          <p>FG5.4 "I think there is a common thing here in that the people are not looking for a theoretical understanding of it, you know they don't want to know the Latin. What everybody I think is striving for is kinda practical things"</p>
          <p>FG5.4 "the mood was terrific there were delighted to be together they took a lot out of it, there were happy"</p>
          <p>Patients and peer supporters agreed that more structure in the group meetings would enhance the peer support experience, for example having a set theme for each meeting. Peer supporters suggested a system of 'frequently asked questions' in order to answer any queries that the group members had identified during a meeting.</p>
          <p>FG7.4"after the meeting, somebody should put in their questions into the centre and somebody should answer them and bring it back to the group"</p>
          <p>Some peer supporters were anxious to have more professional involvement while others pointed out that this would just reproduce some of the services they currently accessed.</p>
        </sec>
      </sec>
      <sec>
        <title>The definitive intervention</title>
        <p>Following the exploratory phase we finalised the study protocol. The definitive intervention is as follows:</p>
        <sec>
          <title>1. Peer supporters</title>
          <p>Potential peer supporters are identified by GPs and practice nurses in the intervention practices. Peer supporters are recruited and trained at a ratio of approximately one peer supporter to seven/eight patients with type 2 diabetes. They are eligible to be trained if they meet the inclusion criteria outlined in Table <xref ref-type="table" rid="T3">3</xref>.</p>
          <table-wrap position="float" id="T3">
            <label>Table 3</label>
            <caption>
              <p>Summary of the development of the intervention</p>
            </caption>
            <table frame="hsides" rules="groups">
              <thead>
                <tr>
                  <td align="left">
                    <bold>INTERVENTION COMPONENT</bold>
                  </td>
                  <td align="left">
                    <bold>PRECLINICAL</bold>
                  </td>
                  <td align="left">
                    <bold>PHASE 1</bold>
                  </td>
                  <td align="left">
                    <bold>PHASE 2</bold>
                  </td>
                  <td align="left">
                    <bold>DEFINITIVE INTERVENTION</bold>
                  </td>
                </tr>
              </thead>
              <tbody>
                <tr>
                  <td align="left">
                    <bold>Peer supporters</bold>
                  </td>
                  <td align="left">No formal professional training</td>
                  <td align="left">To be selected by GPs and PNs</td>
                  <td align="left">4 peer supporters identified by GPs and PNs</td>
                  <td align="left">Inclusion criteria:<break/>• Identified by GPs and PNs<break/>• Have type 2 diabetes for 1 year min<break/>• Adherent to diabetes regieme<break/>• Understand concept of confidentiality<break/>• Liaise with PN/GP if unanticipated problems</td>
                </tr>
                <tr>
                  <td/>
                  <td/>
                  <td align="left">Inclusion/exclusion criteria considered</td>
                  <td/>
                  <td/>
                </tr>
                <tr>
                  <td align="left">
                    <bold>Peer support training</bold>
                  </td>
                  <td align="left">Non specific training</td>
                  <td align="left">2 training sessions</td>
                  <td align="left">2 training sessions- interactive</td>
                  <td align="left">• 2 training sessions conducted by PN and GP<break/>• Conducted locally<break/>• Training sessions focused on materials to be used at group meetings<break/>• Resource pack/handbook</td>
                </tr>
                <tr>
                  <td/>
                  <td/>
                  <td align="left">Content: basics of diabetes, lifestyle and medication issues, communication skills</td>
                  <td align="left">Peer supporters handbook</td>
                  <td/>
                </tr>
                <tr>
                  <td align="left">
                    <bold>Retention and support for peer supporters</bold>
                  </td>
                  <td/>
                  <td align="left">Support for peer supporters vital</td>
                  <td align="left">Project manager contacted peer supporters following each meeting</td>
                  <td align="left">Structures in place to ensure retention of peer supporters:<break/>• Feasible time commitment to the project<break/>• Outline of responsibilities/peer support policy<break/>• Adequate training<break/>• Resource pack<break/>• Contact details and explicit support from the project team and GP/practice nurse<break/>• Telephone call from project manager following each session<break/>• Annual social event/education session<break/>• Travel and related expenses</td>
                </tr>
                <tr>
                  <td/>
                  <td/>
                  <td align="left">Volunteer (no formal payment)</td>
                  <td align="left">Support from each other at training sessions and focus group following intervention</td>
                  <td/>
                </tr>
                <tr>
                  <td align="left">
                    <bold>Peer meetings</bold>
                  </td>
                  <td/>
                  <td align="left">7 patients per group</td>
                  <td align="left">Duration 1–1.5 hours</td>
                  <td align="left">• 9 peer support meetings per group in 2 years of intervention, held in general practice<break/>• 7 patients per group<break/>• 10 minute structured component for beginning of each meeting<break/>• Any unanswered questions (FAQ) feedback to research team at the end of each session and answers discussed at next session</td>
                </tr>
                <tr>
                  <td/>
                  <td/>
                  <td align="left">3 meetings</td>
                  <td align="left">Meeting held in general practice</td>
                  <td/>
                </tr>
                <tr>
                  <td/>
                  <td/>
                  <td/>
                  <td align="left">Frequently asked questions (FAQ)</td>
                  <td/>
                </tr>
              </tbody>
            </table>
          </table-wrap>
        </sec>
        <sec>
          <title>2. Peer supporter training</title>
          <p>The peer supporters attend two evening training sessions, which are conducted by a GP and nurse on the research team. Topics covered in Session 1 included: introduction to the project; role of the peer supporter; basics of type 2 diabetes and complications of type 2 diabetes. Session 2 covered the following topics: lifestyle and medication issues; communication skills and working with groups; dealing with difficult group members; role play and confidentiality.</p>
          <p>The two sessions focus on the materials to be used during the group meetings (described below) and peer supporters receive a resource pack with a manual and resource material to support these training sessions.</p>
        </sec>
        <sec>
          <title>3. Retention and support of peer supporters</title>
          <p>Retention of peer supporters is crucial to the study. Structures are in place to ensure peer support workers are supported in the role (See Table <xref ref-type="table" rid="T3">3</xref>)</p>
        </sec>
        <sec>
          <title>4. Peer support meetings</title>
          <p>Peer support meetings are held in the general practice premises at a convenient time for practice staff, peer supporters and participants. The intervention consists of nine peer support meetings held over two years; at month 1, month 2 and every 3 months thereafter. There is a defined ten to fifteen minute structured component for each meeting available to the peer supporters (see Table <xref ref-type="table" rid="T4">4</xref> for a summary of the meeting content). At the end of each meeting there is general discussion and the group identifies and records any questions regarding the meeting focus. These are fed back to the research team who compile written answers based on the feedback from all groups, which are presented and discussed at the start of the next meeting.</p>
          <table-wrap position="float" id="T4">
            <label>Table 4</label>
            <caption>
              <p>Summary of content of meetings</p>
            </caption>
            <table frame="hsides" rules="groups">
              <thead>
                <tr>
                  <td align="left">
                    <bold>
                      <italic>SESSION 1- INTRODUCTION</italic>
                    </bold>
                  </td>
                  <td align="left">
                    <bold>
                      <italic>SESSION 2- HEART AND VASCULAR DISEASE</italic>
                    </bold>
                  </td>
                </tr>
              </thead>
              <tbody>
                <tr>
                  <td align="left">• Introduction to each other<break/>• What is peer support?<break/>• Ground rules<break/>• Discussion on course content (9 sessions)<break/>• Video/DVD 15 mins<break/>• Entitlements in diabetes<break/>• Identifying a substitute peer supporter<break/>• Contact details for the group</td>
                  <td align="left">• Why is it so important?<break/>• How you can reduce your risk of heart disease and other vascular complication<break/>◦ Hypothetical individual and what they would advise them to do<break/>Questions relating to heart disease including blood pressure and cholesterol medication and taking tablets</td>
                </tr>
                <tr>
                  <td colspan="2">
                    <hr/>
                  </td>
                </tr>
                <tr>
                  <td align="left">
                    <bold>
                      <italic>SESSION 3- BLOOD SUGAR LEVELS</italic>
                    </bold>
                  </td>
                  <td align="left">
                    <bold>
                      <italic>SESSION 4- HEALTHY EATING</italic>
                    </bold>
                  </td>
                </tr>
                <tr>
                  <td align="left">• Information on hypo/hyperglycaemia<break/>• Blood sugar testing<break/>Questions on blood sugar levels<break/>What to do when you are sick</td>
                  <td align="left">Discussion of healthy 'eating plate'<break/>• Laminated picture of the 'healthy plate'<break/>Healthy eating quiz and discussion of answers<break/>Questions on healthy eating in diabetes</td>
                </tr>
                <tr>
                  <td colspan="2">
                    <hr/>
                  </td>
                </tr>
                <tr>
                  <td align="left">
                    <bold>
                      <italic>SESSION 5- MEDICATION</italic>
                    </bold>
                  </td>
                  <td align="left">
                    <bold>
                      <italic>SESSION 6- EXERCISE</italic>
                    </bold>
                  </td>
                </tr>
                <tr>
                  <td align="left">• Control of type 2 diabetes<break/>◦Diet<break/>◦Tablets<break/>◦Insulin<break/>Questions regarding medication including side effects</td>
                  <td align="left">• Importance of exercise<break/>• Use of a pedometer<break/>◦each person will be given a pedometer<break/>Questions about exercise<break/>Maybe arrange a walk in locality</td>
                </tr>
                <tr>
                  <td colspan="2">
                    <hr/>
                  </td>
                </tr>
                <tr>
                  <td align="left">
                    <bold>
                      <italic>SESSION 7- FOOT CARE</italic>
                    </bold>
                  </td>
                  <td align="left">
                    <bold>
                      <italic>SESSION 8-EYE AND KIDNEY COMPLICATIONS</italic>
                    </bold>
                  </td>
                </tr>
                <tr>
                  <td align="left">• Why foot care matters in diabetes<break/>• Discussion on how to check feet<break/>◦Laminated sheet to cover all aspects of foot care<break/>Questions relating to the feet<break/>Information on local chiropody services</td>
                  <td align="left">• What happens to the eyes and kidneys in diabetes<break/>• Importance of good blood pressure and blood sugar control in order to prevent complications<break/>Questions relating to eye and kidney disease</td>
                </tr>
                <tr>
                  <td colspan="2">
                    <hr/>
                  </td>
                </tr>
                <tr>
                  <td align="left">
                    <bold>
                      <italic>SESSION 9- LIVING WITH DIABETES</italic>
                    </bold>
                  </td>
                  <td/>
                </tr>
                <tr>
                  <td align="left">This is intended to be a relatively open session in which the group can discuss any remaining concerns and consider whether they would like to continue to meet<break/>Importance of follow up data collection</td>
                  <td/>
                </tr>
              </tbody>
            </table>
          </table-wrap>
          <p>It became evident to the research team during the Preclinical Phase and Phase 2 that monitoring the delivery of the intervention was crucial. We therefore decided to include a process evaluation and an assessment of treatment fidelity of the definitive intervention. The process evaluation will map the actual implementation of the intervention. Data from peer supporter log diaries of each meeting and the project manager's record of contact with the peer supporters will be recorded and analysed.</p>
          <p>The assessment of treatment fidelity will monitor the reliability and validity of the intervention. The Bellg framework will be used. It consists of five treatment fidelity strategies: Treatment design, Training procedures, Delivery of treatment, Receipt of treatment and Enactment of treatment skills [<xref ref-type="bibr" rid="B29">29</xref>].</p>
        </sec>
      </sec>
    </sec>
    <sec>
      <title>Discussion</title>
      <sec>
        <title>Summary</title>
        <p>Designing complex interventions that are pragmatic enough to be applied to real life situations is challenging [<xref ref-type="bibr" rid="B10">10</xref>]. We found the MRC framework very useful in guiding the design and the preliminary testing of the intervention of peer support in type 2 diabetes. The Preclinical Phase explored the existing evidence on the topic of peer support. In Phase 1 the utility of qualitative methods as specified in the MRC framework, and meetings with experts in the field, was invaluable for the early development of the intervention. The preliminary intervention for the proposed RCT was tested in the pilot study in Phase 2. This allowed us to observe the logistics of introducing the preliminary intervention into the primary care setting.</p>
      </sec>
      <sec>
        <title>Methodological issues</title>
        <p>After considering several theoretical models and discussing this issue with experts in health psychology and voluntary organisations we selected social support as a theoretical framework for the study. This led to the reassessment of the study outcomes and, in addition to the biophysical outcomes, we added the psychosocial outcomes of wellbeing, self care, self efficacy and social support.</p>
        <p>Best practice in randomisation is to randomise following baseline data collection. This avoids introducing bias in terms of patient recruitment and data collection if control practices become demotivated during the baseline data collection phase. Following the exploratory work in phase two, consultation with members of the research team highlighted difficulties with this approach. In order to facilitate the purposive recruitment of peer supporters from the patient register in intervention general practices prior to random selection of patients, it was decided that practices would have to be randomised prior to baseline data collection and randomisation of patients and the beginning of the intervention.</p>
        <p>The MRC framework emphasises the importance of monitoring the delivery of the RCT intervention [<xref ref-type="bibr" rid="B8">8</xref>]. The review of the literature on conducting randomised controlled trials in the Preclinical Phase and the pilot study in phase two led to our decision to include an assessment of treatment fidelity and a process evaluation in the study protocol. This will allow for the monitoring of the process of implementation of the intervention and also assess the validity and reliability of the intervention. The incorporation of these elements will add depth to our understanding of the final results of the randomised controlled trial. For example, we will be in a position to address any potential questions such as whether the intervention was experienced as intended by the participating intervention patients. In addition, we will be able to consider the relative effectiveness of the intervention in relation to the extent of exposure to peer support. This process will also facilitate reproducibility of the intervention if the trial finds that it is effective as there will be a clear and detailed description of the intervention as it occurred in practice settings.</p>
      </sec>
      <sec>
        <title>Intervention issues</title>
        <p>The qualitative work in Phase 1 and Phase 2 allowed us to identify details of the intervention components that needed further development. In particular the structure of the group sessions and support for peer supporters was developed further. The idea of having a focus to each session and a system of frequently asked questions came from the patients and peer supporters and was incorporated into the definitive intervention. A guide for each session was devised. This guide is designed to be flexible and does not have to be strictly adhered to, so as not to destroy the concept of peer led meetings. Unlike the peer led educational interventions such as the Chronic Disease Self-Management Programme (CDSMP)[<xref ref-type="bibr" rid="B30">30</xref>] devised by Kate Lorig the intervention in this study focused more on social support than education. There is a clear need to distinguish between interventions that are genuinely peer led compared to professionally led support or educational interventions. As some of the peer supporters emphasised, professionally led interventions would just duplicate some of the services that they currently access.</p>
        <p>Consultation with a volunteering expert led to further development of support mechanisms for the peer supporters. The support given in the pilot study, which involved telephone contact after meetings was identified as crucial by the peer supporters and so was developed further for the definitive intervention. We also plan to hold an annual social meeting to facilitate communication between peer supporters from difference practices. The travel allowance for peer supporters has also been modified so that it is given in stages throughout the intervention.</p>
      </sec>
    </sec>
    <sec>
      <title>Conclusion</title>
      <p>The MRC framework was instrumental in the development of a robust intervention of peer support in type 2 diabetes in primary care. The intervention of peer support was considered in depth incorporating an analysis of current literature, qualitative work with those who would be both experiencing, delivering and administering the peer support system and finally an analysis of how the intervention would run in the pilot study. It enabled a clear and detailed understanding of the components of the intervention and how each should be documented and tested during the definitive study. The effectiveness of this intervention is now being tested in a cluster randomised controlled trial involving twenty general practices and 420 patients with type 2 diabetes.</p>
    </sec>
    <sec>
      <title>Competing interests</title>
      <p>The author(s) declare that they have no competing interests.</p>
    </sec>
    <sec>
      <title>Authors' contributions</title>
      <p>All authors reviewed and approved the final version of this manuscript. GP, SMS, TOD and DW designed the study, prepared the protocol and participated in writing this paper. GP conceptualized and drafted the paper, and conducted the data collection. FOK prepared the protocol and participated in writing the paper.</p>
    </sec>
    <sec>
      <title>Pre-publication history</title>
      <p>The pre-publication history for this paper can be accessed here:</p>
      <p>
        <ext-link ext-link-type="uri" xlink:href="http://www.biomedcentral.com/1472-6963/7/136/prepub"/>
      </p>
    </sec>
  </body>
  <back>
    <ack>
      <sec>
        <title>Acknowledgements</title>
        <p>The authors would like to thank all the participants for their time and feedback. Also the hard work and enthusiasm of the staff in the two participating practices was very much appreciated.</p>
      </sec>
    </ack>
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</metadata></record><record><header><identifier>oai:pubmedcentral.nih.gov:2080631</identifier><datestamp>2007-11-17</datestamp><setSpec>bmchsr</setSpec><setSpec>pmc-open</setSpec></header><metadata><article xmlns="http://dtd.nlm.nih.gov/2.0/xsd/archivearticle" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://dtd.nlm.nih.gov/archiving/2.3/xsd/archivearticle.xsd" article-type="research-article">
  <front>
    <journal-meta>
      <journal-id journal-id-type="nlm-ta">BMC Health Serv Res</journal-id>
      <journal-title>BMC Health Services Research</journal-title>
      <issn pub-type="epub">1472-6963</issn>
      <publisher>
        <publisher-name>BioMed Central</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="pmc">2080631</article-id>
      <article-id pub-id-type="publisher-id">1472-6963-7-147</article-id>
      <article-id pub-id-type="pmid">17880689</article-id>
      <article-id pub-id-type="doi">10.1186/1472-6963-7-147</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Potential drug-drug and drug-disease interactions in prescriptions for ambulatory patients over 50 years of age in family medicine clinics in Mexico City</article-title>
      </title-group>
      <contrib-group>
        <contrib id="A1" corresp="yes" contrib-type="author">
          <name>
            <surname>Doubova (Dubova)</surname>
            <given-names>Svetlana Vladislavovna</given-names>
          </name>
          <xref ref-type="aff" rid="I1">1</xref>
          <email>svetlana.doubova@imss.gob.mx</email>
        </contrib>
        <contrib id="A2" contrib-type="author">
          <name>
            <surname>Reyes-Morales</surname>
            <given-names>Hortensia</given-names>
          </name>
          <xref ref-type="aff" rid="I1">1</xref>
          <email>hortensia.reyes@imss.gob.mx</email>
        </contrib>
        <contrib id="A3" contrib-type="author">
          <name>
            <surname>Torres-Arreola</surname>
            <given-names>Laura del Pilar</given-names>
          </name>
          <xref ref-type="aff" rid="I1">1</xref>
          <email>laura.torres@imss.gob.mx</email>
        </contrib>
        <contrib id="A4" contrib-type="author">
          <name>
            <surname>Suárez-Ortega</surname>
            <given-names>Magdalena</given-names>
          </name>
          <xref ref-type="aff" rid="I1">1</xref>
          <email>magdalena.suarez@imss.gob.mx</email>
        </contrib>
      </contrib-group>
      <aff id="I1"><label>1</label>Epidemiology and Health Services Research Unit. National Medical Center Century XXI, Mexican Institute of Social Security, Mexico City, Mexico</aff>
      <pub-date pub-type="collection">
        <year>2007</year>
      </pub-date>
      <pub-date pub-type="epub">
        <day>19</day>
        <month>9</month>
        <year>2007</year>
      </pub-date>
      <volume>7</volume>
      <fpage>147</fpage>
      <lpage>147</lpage>
      <ext-link ext-link-type="uri" xlink:href="http://www.biomedcentral.com/1472-6963/7/147"/>
      <history>
        <date date-type="received">
          <day>17</day>
          <month>5</month>
          <year>2007</year>
        </date>
        <date date-type="accepted">
          <day>19</day>
          <month>9</month>
          <year>2007</year>
        </date>
      </history>
      <permissions>
        <copyright-statement>Copyright © 2007 Doubova (Dubova) et al; licensee BioMed Central Ltd.</copyright-statement>
        <copyright-year>2007</copyright-year>
        <copyright-holder>Doubova (Dubova) et al; licensee BioMed Central Ltd.</copyright-holder>
        <license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/2.0">
          <p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/2.0"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>
          <!--<rdf xmlns="http://web.resource.org/cc/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1" xmlns:dcterms="http://purl.org/dc/terms"><Work xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" rdf:about=""><license rdf:resource="http://creativecommons.org/licenses/by/2.0"/><dc:type rdf:resource="http://purl.org/dc/dcmitype/Text"/><dc:author>
               Doubova (Dubova)
               Vladislavovna
               Svetlana
               
               svetlana.doubova@imss.gob.mx
            </dc:author><dc:title>
            Potential drug-drug and drug-disease interactions in prescriptions for ambulatory patients over 50 years of age in family medicine clinics in Mexico City
         </dc:title><dc:date>2007</dc:date><dcterms:bibliographicCitation>BMC Health Services Research 7(1): 147-. (2007)</dcterms:bibliographicCitation><dc:identifier type="sici">1472-6963(2007)7:1&#x0003c;147&#x0003e;</dc:identifier><dcterms:isPartOf>urn:ISSN:1472-6963</dcterms:isPartOf><License rdf:about="http://creativecommons.org/licenses/by/2.0"><permits rdf:resource="http://web.resource.org/cc/Reproduction" xmlns=""/><permits rdf:resource="http://web.resource.org/cc/Distribution" xmlns=""/><requires rdf:resource="http://web.resource.org/cc/Notice" xmlns=""/><requires rdf:resource="http://web.resource.org/cc/Attribution" xmlns=""/><permits rdf:resource="http://web.resource.org/cc/DerivativeWorks" xmlns=""/></License></Work></rdf>-->
        </license>
      </permissions>
      <abstract>
        <sec>
          <title>Background</title>
          <p>In Mexico, inappropriate prescription of drugs with potential interactions causing serious risks to patient health has been little studied. Work in this area has focused mainly on hospitalized patients, with only specific drug combinations analyzed; moreover, the studies have not produced conclusive results. In the present study, we determined the frequency of potential drug-drug and drug-disease interactions in prescriptions for ambulatory patients over 50 years of age, who used Mexican Institute of Social Security (IMSS) family medicine clinics. In addition, we aimed to identify the associated factors for these interactions.</p>
        </sec>
        <sec sec-type="methods">
          <title>Methods</title>
          <p>We collected information on general patient characteristics, medical histories, and medication (complete data). The study included 624 ambulatory patients over 50 years of age, with non-malignant pain syndrome, who made ambulatory visits to two IMSS family medicine clinics in Mexico City. The patients received 7-day prescriptions for non-opioid analgesics. The potential interactions were identified by using the Thompson Micromedex program. Data were analyzed using descriptive, bivariate and multiple logistic regression analyses.</p>
        </sec>
        <sec>
          <title>Results</title>
          <p>The average number of prescribed drugs was 5.9 ± 2.5. About 80.0% of patients had prescriptions implying one or more potential drug-drug interactions and 3.8% of patients were prescribed drug combinations with interactions that should be avoided. Also, 64.0% of patients had prescriptions implying one or more potential drug disease interactions. The factors significantly associated with having one or more potential interactions included: taking 5 or more medicines (adjusted Odds Ratio (OR): 4.34, 95%CI: 2.76–6.83), patient age 60 years or older (adjusted OR: 1.66, 95% CI: 1.01–2.74) and suffering from cardiovascular diseases (adjusted OR: 7.26, 95% CI: 4.61–11.44).</p>
        </sec>
        <sec>
          <title>Conclusion</title>
          <p>The high frequency of prescription of drugs with potential drug interactions showed in this study suggests that it is common practice in primary care level. To lower the frequency of potential interactions it could be necessary to make a careful selection of therapeutic alternatives, and in cases without other options, patients should be continuously monitored to identify adverse events.</p>
        </sec>
      </abstract>
    </article-meta>
  </front>
  <body>
    <sec>
      <title>Background</title>
      <p>During the last decades in Mexico, as elsewhere, the population has aged, causing an increase in the level of chronic degenerative diseases and a consequent increment in medication. Polypharmacy is now common, and carries a high risk of drug-drug interactions and drug-disease interactions. These may cause adverse effects, or the therapeutic effects of the combined medicines may change, with serious consequences for health. In the United States 25% of ambulatory patients taking drug combinations were at risk for clinically important interactions [<xref ref-type="bibr" rid="B1">1</xref>]. Furthermore, it has been reported that about 40% of hospitalized patients had at least one potential drug-disease interaction [<xref ref-type="bibr" rid="B2">2</xref>]; a large study including 70,203 outpatient visits by patients aged 65 and older found that 2.6% ofvisits with at least one prescription had one or more of the 50 inappropriate drug-disease combinations examined [<xref ref-type="bibr" rid="B3">3</xref>]. A European study of 1601 ambulatory elderly patients, taking an average of seven different drugs, found that 46.0% were at risk for at least one clinically important potential drug-drug interaction [<xref ref-type="bibr" rid="B4">4</xref>]. It has been shown that inappropriate prescription combinations increase with patient age, are more frequent in men, rise in line with the Charlson co-morbidity index [<xref ref-type="bibr" rid="B5">5</xref>], and increase as the number of prescribed drugs increases [<xref ref-type="bibr" rid="B2">2</xref>,<xref ref-type="bibr" rid="B3">3</xref>,<xref ref-type="bibr" rid="B6">6</xref>-<xref ref-type="bibr" rid="B8">8</xref>]. It is possible that other risk factors for potential interactions exist, and these should be identified to establish successful methods for improving prescription practices.</p>
      <p>Adverse consequences of drug interactions have been shown in various studies. Drug-drug interactions cause 4.8% of hospitalizations attributed to drugs in the elderly [<xref ref-type="bibr" rid="B9">9</xref>-<xref ref-type="bibr" rid="B11">11</xref>]. In most cases they are erroneously interpreted as patient deterioration because of illness, poor adherence to prescribed treatment, or infection [<xref ref-type="bibr" rid="B12">12</xref>].</p>
      <p>In Mexico, inappropriate prescription of drugs with potential interactions causing serious risks to patient health has been little studied. Work in this area has focused mainly on hospitalized patients, with only specific drug combinations analyzed [<xref ref-type="bibr" rid="B13">13</xref>]; moreover, the studies have not produced conclusive results [<xref ref-type="bibr" rid="B14">14</xref>,<xref ref-type="bibr" rid="B15">15</xref>].</p>
      <p>In the present study, we sought to determine the frequency of potential drug-drug and drug-disease interactions in prescriptions of ambulatory patients over 50 years of age, who attended to Mexican Institute of Social Security (IMSS) family medicine clinics. In addition, we aimed at identifying factors associated to them.</p>
    </sec>
    <sec sec-type="methods">
      <title>Methods</title>
      <p>The present study is a secondary data analysis from the Educational Strategy Study (ESS) involving both doctors and patients over 50 years of age, focused on improving utilization of non-opioid analgesics in primary care study and carried out during 2006 in two large IMSS family medicine clinics (FMC) located in Mexico City.</p>
      <p>IMSS is the largest medical institution in Mexico that provides health care for more than 53 million of Mexicans. The provision of services is divided into three levels, where the Family Medicine Clinic is the primary care level. IMSS FMC range from 2 to 40 examining rooms; the clinics included in the study had 32 examining rooms, which means 64 family doctors working in the morning and evening shifts (32 in each);. These clinics were selected by convenience and are similar in organization to the rest of those that constitute IMSS primary care system. Cross-sectional data from 624 ambulatory patients over 50 years of age who made visits to 127 family doctors (96% of all family doctors) were collected. On average, five patients seen by each family doctor were included consecutively. The patients studied suffered from non-malignant pain syndrome and received prescriptions of non-opioid analgesics for 7 days or more. The variables analyzed were general characteristics of the patient (age, marital status, literacy), medical history (number of chronic diseases, number of medicines prescribed), and complete information about all oral and injected drugs prescribed by the doctors during the consultation (including occasional drugs and those that were prescribed for regular use, besides the prescription of non-opioid analgesics described as inclusion criteria). All patients were personally interviewed immediately after the visit and the information from the electronic medical record and from the electronic prescription was registered. Most of information (diagnosis and prescriptions) was obtained through personal interview and additional data were obtained from the electronic medical charts and the electronic prescriptions.</p>
      <p>The International Classification of Disease, version 10 (ICD-10) [<xref ref-type="bibr" rid="B16">16</xref>], and the Anatomical Therapeutic Chemical classification system [<xref ref-type="bibr" rid="B17">17</xref>] served to codify the data. To look for potential interactions every combination of prescribed drugs was analyzed by using the Thompson Micromedex program [<xref ref-type="bibr" rid="B18">18</xref>]. Drug-drug interactions were sorted by clinical relevance using the Classification System of the Department of Pharmacology, Hospital Huddinge, Stockholm, Sweden [<xref ref-type="bibr" rid="B19">19</xref>]. In this classification, drug interactions are rated A and B when they are not of clinical importance (type A), or the effect of the interaction has not yet been established (type B). One interaction of type C can cause possible changes in the therapeutic effects, or may cause adverse effects, but can be avoided adjusting the individual drug doses. A potential drug-drug interaction of type D indicates a potential for severe adverse effects; individual dose adjustment is difficult in these cases. For this paper, only drug-drug interactions of type C and D were detected and analyzed. Using the Zhan Classification all drug-disease interactions were classified as being of low, moderate or high clinical significance [<xref ref-type="bibr" rid="B3">3</xref>].</p>
      <p>The IMSS Ethics Committee approved the ESS (registration number: 2005-785-185).</p>
      <sec>
        <title>Statistical analysis</title>
        <p>All collected data regarding medications prescribed were included in the analysis. The descriptive analysis included absolute and relative frequencies of categorical variables. A bivariate analysis to ascertain potential factors associated with drug-drug and drug-disease interaction was performed using the chi-square test for categorical variables. To evaluate the risk factors related to the presence of drug-drug interactions in prescription mixes, a multiple logistic regression analysis by using the backward stepwise method was performed; the correlation terms and interactions among selected variables were also explored, and goodness of fit test was assessed for the best model. Variables that were explored in the bivariate analysis were: gender (female), marital status (single), age (≥ 60 years of age), literacy (only elementary school o less), number of chronic conditions, diagnosis (cardiovascular, gastrointestinal, endocrine, genital and urinary, neurological, mental, infection disease, as well as musculoskeletal and joint disorders), and number of drugs prescribed (≥ 5). Only statistically significant associations and plausible variables were considered for the logistic regression model.</p>
        <p>All <italic>P</italic>-values were obtained from two-tailed tests and the significance level selected was <italic>P </italic>= 0.05. The programs SPSS 10.0 for Windows (SPSS Inc, Chicago, IL), and the statistics package of STATA Corporation (College Station, TX) were used to analyze data.</p>
      </sec>
    </sec>
    <sec>
      <title>Results</title>
      <p>The median age of patients was 69 years (range 50–94 years). Most (78.7%) were women, 63.9% were housewives and more than half were single, divorced or widowed. The average number of chronic diseases per patient was 3.4 ± 1.5 and the most frequent illnesses were degenerative joint disease, hypertension, chronic gastritis, diabetes mellitus and dyslipidemia (Table <xref ref-type="table" rid="T1">1</xref>). The total number of medicines prescribed to the 624 patients was 3,739 with an average of 5.9 ± 2.5 drugs per patient. The most frequent drugs prescribed were active on the alimentary tract, or affected general metabolism (drugs combating gastrointestinal diseases were the most commonly prescribed drugs). The next most common class of drugs was active on the cardiovascular system; drugs addressing muscle-skeletal system problems were next in prescription frequency, and, finally, drugs active on the nervous system. In this final group paracetamol was the main drug consumed (Table <xref ref-type="table" rid="T2">2</xref>).</p>
      <table-wrap position="float" id="T1">
        <label>Table 1</label>
        <caption>
          <p>General patient characteristics and medical history</p>
        </caption>
        <table frame="hsides" rules="groups">
          <thead>
            <tr>
              <td align="left">
                <bold>Characteristics</bold>
              </td>
              <td align="center">n = 624 <break/><bold>n (%)</bold></td>
            </tr>
          </thead>
          <tbody>
            <tr>
              <td align="left">
                <bold>General patient characteristics</bold>
              </td>
              <td/>
            </tr>
            <tr>
              <td align="left">Female</td>
              <td align="center">491 (78.7)</td>
            </tr>
            <tr>
              <td align="left">Lives without couple (Single, Divorced, Widow)</td>
              <td align="center">320 (51.3)</td>
            </tr>
            <tr>
              <td align="left">
                <bold>Occupation</bold>
              </td>
              <td/>
            </tr>
            <tr>
              <td align="left"> Housewife</td>
              <td align="center">399 (63.9)</td>
            </tr>
            <tr>
              <td align="left"> Retired-pensioner</td>
              <td align="center">119 (19.0)</td>
            </tr>
            <tr>
              <td align="left"> Services</td>
              <td align="center">16 (2.6)</td>
            </tr>
            <tr>
              <td align="left"> Unskilled worker</td>
              <td align="center">38 (6.0)</td>
            </tr>
            <tr>
              <td align="left"> Clerk</td>
              <td align="center">48 (7.7)</td>
            </tr>
            <tr>
              <td align="left"> Professionals</td>
              <td align="center">4 (0.6)</td>
            </tr>
            <tr>
              <td align="left"><bold>Age, years, </bold>Median (range)</td>
              <td align="center">69 (50–94)</td>
            </tr>
            <tr>
              <td align="left"><bold>Education, years, </bold>Median (range)</td>
              <td align="center">6 (0–22)</td>
            </tr>
            <tr>
              <td align="left">
                <bold>Medical History</bold>
              </td>
              <td/>
            </tr>
            <tr>
              <td align="left">
                <bold>Cardiovascular disease</bold>
              </td>
              <td align="center">446 (71.5)</td>
            </tr>
            <tr>
              <td align="left"> Myocardial</td>
              <td align="center">123 (19.7)</td>
            </tr>
            <tr>
              <td align="left"> Hypertension</td>
              <td align="center">420 (67.3)</td>
            </tr>
            <tr>
              <td align="left"> Peripheral vascular</td>
              <td align="center">64 (10.3)</td>
            </tr>
            <tr>
              <td align="left">
                <bold>Pulmonary disease</bold>
              </td>
              <td align="center">39 (6.3)</td>
            </tr>
            <tr>
              <td align="left">
                <bold>Gastrointestinal disease</bold>
              </td>
              <td align="center">253 (40.5)</td>
            </tr>
            <tr>
              <td align="left"> Chronic Gastro-duodenitis/ulcer disease</td>
              <td align="center">225 (36.1)</td>
            </tr>
            <tr>
              <td align="left"> Others: inflammatory bowel, liver disease etc.</td>
              <td align="center">49 (7.9)</td>
            </tr>
            <tr>
              <td align="left">
                <bold>Genito-urinary disease</bold>
              </td>
              <td align="center">47 (7.5)</td>
            </tr>
            <tr>
              <td align="left"> Renal disease with renal insufficiency</td>
              <td align="center">40 (6.4)</td>
            </tr>
            <tr>
              <td align="left"> Prostate disease</td>
              <td align="center">7 (1.1)</td>
            </tr>
            <tr>
              <td align="left">
                <bold>Musculoskeletal and joint disorders</bold>
              </td>
              <td align="center">597 (95.7)</td>
            </tr>
            <tr>
              <td align="left"> Osteoarthritis</td>
              <td align="center">565 (90.5)</td>
            </tr>
            <tr>
              <td align="left"> Rheumatoid arthritis</td>
              <td align="center">16 (2.6)</td>
            </tr>
            <tr>
              <td align="left"> Gout</td>
              <td align="center">11 (1.8)</td>
            </tr>
            <tr>
              <td align="left">
                <bold>Endocrine, alimentary and metabolic disease</bold>
              </td>
              <td align="center">313 (50.2)</td>
            </tr>
            <tr>
              <td align="left"> Diabetes mellitus</td>
              <td align="center">184 (29.5)</td>
            </tr>
            <tr>
              <td align="left"> Thyroid gland disease</td>
              <td align="center">22 (3.5)</td>
            </tr>
            <tr>
              <td align="left"> Hyperlipidemia</td>
              <td align="center">155 (24.8)</td>
            </tr>
            <tr>
              <td align="left"> Obesity</td>
              <td align="center">39 (6.3)</td>
            </tr>
            <tr>
              <td align="left">
                <bold>Neurological disease</bold>
              </td>
              <td align="center">51 (8.2)</td>
            </tr>
            <tr>
              <td align="left">
                <bold>Mental disease</bold>
              </td>
              <td align="center">33 (5.2)</td>
            </tr>
            <tr>
              <td align="left">
                <bold>Hematological disease</bold>
              </td>
              <td align="center">17 (2.7)</td>
            </tr>
            <tr>
              <td align="left">
                <bold>Ophthalmological disease</bold>
              </td>
              <td align="center">26 (4.2)</td>
            </tr>
            <tr>
              <td align="left">
                <bold>Dermatological disease</bold>
              </td>
              <td align="center">14 (2.3)</td>
            </tr>
            <tr>
              <td align="left">
                <bold>Infections and parasitic disease</bold>
              </td>
              <td align="center">118 (18.9)</td>
            </tr>
            <tr>
              <td align="left"> Respiratory infections</td>
              <td align="center">47 (7.5)</td>
            </tr>
            <tr>
              <td align="left"> Gastrointestinal infections</td>
              <td align="center">6 (1.0)</td>
            </tr>
            <tr>
              <td align="left"> Genito-urinary infections</td>
              <td align="center">43 (6.8)</td>
            </tr>
            <tr>
              <td align="left"> Mycosis</td>
              <td align="center">28 (4.5)</td>
            </tr>
            <tr>
              <td align="left">
                <bold>Trauma</bold>
              </td>
              <td align="center">10 (1.6)</td>
            </tr>
            <tr>
              <td/>
              <td align="center"><bold>Mean </bold>± <bold>SD*</bold></td>
            </tr>
            <tr>
              <td align="left">
                <bold>Disease number</bold>
              </td>
              <td align="center">3.6 ± 1.5</td>
            </tr>
            <tr>
              <td align="left"> Chronic disease</td>
              <td align="center">3.4 ± 1.5</td>
            </tr>
            <tr>
              <td colspan="2">
                <hr/>
              </td>
            </tr>
            <tr>
              <td align="left"> Acute disease and trauma</td>
              <td align="center">0.2 ± 0.4</td>
            </tr>
          </tbody>
        </table>
        <table-wrap-foot>
          <p>*SD: Standard deviation</p>
        </table-wrap-foot>
      </table-wrap>
      <table-wrap position="float" id="T2">
        <label>Table 2</label>
        <caption>
          <p>Prescribed drugs</p>
        </caption>
        <table frame="hsides" rules="groups">
          <thead>
            <tr>
              <td align="left">
                <bold>Anatomical Therapeutic Chemical groups*</bold>
              </td>
              <td align="center"><bold>Medications</bold><break/>n = 3739<break/><bold>n (%)</bold></td>
              <td align="center"><bold>Patients</bold><break/>n = 624<break/><bold>n (%)</bold></td>
            </tr>
          </thead>
          <tbody>
            <tr>
              <td align="left">
                <bold>Alimentary tract and metabolism</bold>
              </td>
              <td align="center">990 (26.5)</td>
              <td align="center">495 (79.3)</td>
            </tr>
            <tr>
              <td align="left"> Drugs used in diabetes</td>
              <td align="center">250 (6.7)</td>
              <td align="center">179 (28.7)</td>
            </tr>
            <tr>
              <td align="left"> Drugs for gastrointestinal disease**</td>
              <td align="center">437 (11.7)</td>
              <td align="center">332 (53.2)</td>
            </tr>
            <tr>
              <td align="left"> Vitamins</td>
              <td align="center">236 (6.3)</td>
              <td align="center">209 (33.5)</td>
            </tr>
            <tr>
              <td align="left"> Mineral supplements</td>
              <td align="center">88 (2.4)</td>
              <td align="center">87 (13.9)</td>
            </tr>
            <tr>
              <td align="left">
                <bold>Blood and blood forming organs</bold>
              </td>
              <td align="center">253 (6.8)</td>
              <td align="center">247 (39.6)</td>
            </tr>
            <tr>
              <td align="left">
                <bold>Cardiovascular system</bold>
              </td>
              <td align="center">929 (24.8)</td>
              <td align="center">470 (75.3)</td>
            </tr>
            <tr>
              <td align="left">
                <bold>Dermatologicals</bold>
              </td>
              <td align="center">81 (2.1)</td>
              <td align="center">66 (10.6)</td>
            </tr>
            <tr>
              <td align="left">
                <bold>Genitourinary system and sex hormones</bold>
              </td>
              <td align="center">20 (0.5)</td>
              <td align="center">20 (3.2)</td>
            </tr>
            <tr>
              <td align="left">
                <bold>Systemic hormonal preparations</bold>
              </td>
              <td align="center">29 (0.8)</td>
              <td align="center">27 (4.3)</td>
            </tr>
            <tr>
              <td align="left">
                <bold>Antiinfectives for systemic use</bold>
              </td>
              <td align="center">158 (4.2)</td>
              <td align="center">149 (23.9)</td>
            </tr>
            <tr>
              <td align="left">
                <bold>Musculoskeletal system</bold>
              </td>
              <td align="center">680 (18.2)</td>
              <td align="center">569 (91.2)</td>
            </tr>
            <tr>
              <td align="left"> Non-steroidal anti-inflammatory drugs</td>
              <td align="center">611 (16.3)</td>
              <td align="center">560 (89.8)</td>
            </tr>
            <tr>
              <td align="left"> Others drugs for the musculoskeletal system</td>
              <td align="center">69 (1.8)</td>
              <td align="center">61 (9.8)</td>
            </tr>
            <tr>
              <td align="left">
                <bold>Nervous system</bold>
              </td>
              <td align="center">380 (10.2)</td>
              <td align="center">298 (47.8)</td>
            </tr>
            <tr>
              <td align="left"> Analgesics and antipyretics (Paracetamol)</td>
              <td align="center">229 (36.7)</td>
              <td align="center">229 (36.7)</td>
            </tr>
            <tr>
              <td align="left"> Other nervous system drugs***</td>
              <td align="center">152 (4.1)</td>
              <td align="center">119 (19.1)</td>
            </tr>
            <tr>
              <td align="left">
                <bold>Respiratory system</bold>
              </td>
              <td align="center">117 (3.1)</td>
              <td align="center">81 (13.0)</td>
            </tr>
            <tr>
              <td align="left">
                <bold>Sensory organs</bold>
              </td>
              <td align="center">102 (2.7)</td>
              <td align="center">56 (9.0)</td>
            </tr>
            <tr>
              <td/>
              <td/>
              <td/>
            </tr>
            <tr>
              <td align="left"><bold>Mean number of prescribed drugs</bold>, Mean ± SD****</td>
              <td/>
              <td align="center">5.9 ± 2.5</td>
            </tr>
            <tr>
              <td align="left">
                <bold>Number of prescribed drugs</bold>
              </td>
              <td/>
              <td align="center">
                <bold>n (%)</bold>
              </td>
            </tr>
            <tr>
              <td align="left">2</td>
              <td/>
              <td align="center">22 (3.5)</td>
            </tr>
            <tr>
              <td align="left">3–4</td>
              <td/>
              <td align="center">168 (26.9)</td>
            </tr>
            <tr>
              <td align="left">5–6</td>
              <td/>
              <td align="center">210 (33.7)</td>
            </tr>
            <tr>
              <td align="left">≥ 7</td>
              <td/>
              <td align="center">224 (35.9)</td>
            </tr>
          </tbody>
        </table>
        <table-wrap-foot>
          <p>*Anatomical Therapeutic Chemical classification system (ATC)</p>
          <p>**A02–A09 in the ATC</p>
          <p>***N01; N02A and C; N03–N07 in the ATC</p>
          <p>****SD: Standard deviation</p>
        </table-wrap-foot>
      </table-wrap>
      <p>About 80% of patients had prescriptions for one or more combinations in the potential drug-drug interaction class. The most frequent drug interactions were type C, such as combinations of non-steroidal anti-inflammatory drugs (NSAIDs) with antihypertensive drugs (40.4%), and with low doses of acetylsalicylic acid (ASA) (34.0%). 3.8% of patients were prescribed drug combinations with interactions that should be avoided, and two patients were prescribed drugs with two potential type D interactions. Also, 400 patients (64.0%) had one or more potential drug-disease interactions of moderate clinical significance, given that the medicines prescribed could cause either light or moderate adverse effects. The most frequent were NSAIDs in patients with hypertension and/or chronic heart failure; β-blocking agents in patients with diabetes mellitus, and NSAIDs in patients with chronic renal failure (Table <xref ref-type="table" rid="T3">3</xref>) When analyzing both classes of potential interactions we did not find statistically significant differences in patient gender, marital status or education.</p>
      <table-wrap position="float" id="T3">
        <label>Table 3</label>
        <caption>
          <p>Potential drug-drug and drug-disease interactions</p>
        </caption>
        <table frame="hsides" rules="groups">
          <thead>
            <tr>
              <td align="left">
                <bold>Interactions</bold>
              </td>
              <td align="center"><bold>Patients</bold><break/>n = 624<break/><bold>n (%)</bold></td>
            </tr>
          </thead>
          <tbody>
            <tr>
              <td align="left">
                <bold>Potential drug-drug interactions</bold>
              </td>
              <td align="center">
                <bold>492 (78.8)</bold>
              </td>
            </tr>
            <tr>
              <td align="left">
                <bold>Number of potential drug-drug interactions*</bold>
              </td>
              <td/>
            </tr>
            <tr>
              <td align="left"> 1</td>
              <td align="center">154 (24.7)</td>
            </tr>
            <tr>
              <td align="left"> 2</td>
              <td align="center">92 (14.7)</td>
            </tr>
            <tr>
              <td align="left"> 3–4</td>
              <td align="center">154 (24.7)</td>
            </tr>
            <tr>
              <td align="left"> ≥ 5</td>
              <td align="center">92 (14.7)</td>
            </tr>
            <tr>
              <td align="left">
                <bold>Type D</bold>
              </td>
              <td align="center">
                <bold>24 (3.8)</bold>
              </td>
            </tr>
            <tr>
              <td align="left"> ACE* inhibitors + potassium-sparing diuretics (or potassium supplementation)</td>
              <td align="center">11 (1.8)</td>
            </tr>
            <tr>
              <td align="left"> NSAID*+ Methotrexate</td>
              <td align="center">5 (0.8)</td>
            </tr>
            <tr>
              <td align="left"> NSAID* +anticoagulants (or glucocorticoids)</td>
              <td align="center">5 (0.8)</td>
            </tr>
            <tr>
              <td align="left"> β blocking agents + Verapamil (or Fluoxetin)</td>
              <td align="center">3 (0.4)</td>
            </tr>
            <tr>
              <td align="left">
                <bold>Type C</bold>
              </td>
              <td align="center">
                <bold>468 (75.0)</bold>
              </td>
            </tr>
            <tr>
              <td align="left"> ACE* inhibitors + NSAID*</td>
              <td align="center">252 (40.4)</td>
            </tr>
            <tr>
              <td align="left"> NSAID*+ low dose ASA*</td>
              <td align="center">212 (34.0)</td>
            </tr>
            <tr>
              <td align="left"> NSAID*+ sulfonylureas</td>
              <td align="center">128 (20.5)</td>
            </tr>
            <tr>
              <td align="left"> ACE* inhibitors + low dose ASA*</td>
              <td align="center">130 (20.8)</td>
            </tr>
            <tr>
              <td align="left"> β blocking agents + NSAID*</td>
              <td align="center">107 (17.1)</td>
            </tr>
            <tr>
              <td align="left"> NSAID* + Diuretics</td>
              <td align="center">105 (16.8)</td>
            </tr>
            <tr>
              <td align="left"> ACE* inhibitors + glybenclamide</td>
              <td align="center">68 (10.9)</td>
            </tr>
            <tr>
              <td align="left"> NSAID*+ other NSAID*</td>
              <td align="center">51 (8.2)</td>
            </tr>
            <tr>
              <td align="left"> ACE* inhibitors + thiazide diuretics</td>
              <td align="center">47 (7.6)</td>
            </tr>
            <tr>
              <td align="left"> Pravastatin + bezafibrate</td>
              <td align="center">35 (5.6)</td>
            </tr>
            <tr>
              <td align="left"> Pentoxiyilline + antihypertensives</td>
              <td align="center">37 (5.9)</td>
            </tr>
            <tr>
              <td align="left"> Metformin+ ranitidine</td>
              <td align="center">40 (6.5)</td>
            </tr>
            <tr>
              <td align="left"> Glibenclamide + antimycotics or cotrimoxazole</td>
              <td align="center">24 (3.9)</td>
            </tr>
            <tr>
              <td align="left"> Furosemide + ACE* inhibitors</td>
              <td align="center">21 (3.4)</td>
            </tr>
            <tr>
              <td align="left"> ACE* inhibitors + antiacids</td>
              <td align="center">19 (3.1)</td>
            </tr>
            <tr>
              <td align="left"> Alendronate + NSAIDs*</td>
              <td align="center">18 (2.9)</td>
            </tr>
            <tr>
              <td align="left"> Insulin + antihypertensive</td>
              <td align="center">18 (2.9)</td>
            </tr>
            <tr>
              <td align="left"> Pentoxifylline + hypoglycemic agents</td>
              <td align="center">14 (2.2)</td>
            </tr>
            <tr>
              <td align="left"> Acetaminophen + carbamazepin</td>
              <td align="center">14 (2.2)</td>
            </tr>
            <tr>
              <td align="left"> Ranitidine + azole type of antimycotics</td>
              <td align="center">11 (1.8)</td>
            </tr>
            <tr>
              <td align="left"> Others</td>
              <td align="center">61 (9.4)</td>
            </tr>
            <tr>
              <td align="left">
                <bold>Potential drug-disease interactions</bold>
              </td>
              <td align="center">400 (64.1)</td>
            </tr>
            <tr>
              <td align="left">
                <bold>Number of potential drug-disease interactions</bold>
              </td>
              <td/>
            </tr>
            <tr>
              <td align="left"> 1</td>
              <td align="center">346 (55.4)</td>
            </tr>
            <tr>
              <td align="left"> ≥ 2</td>
              <td align="center">54 (8.7)</td>
            </tr>
            <tr>
              <td align="left">NSAIDs* in patients with hypertension and/or chronic heart failure</td>
              <td align="center">384 (61.5)</td>
            </tr>
            <tr>
              <td align="left">β blocking agents in patients with diabetes mellitus</td>
              <td align="center">31 (5.0)</td>
            </tr>
            <tr>
              <td align="left">NSAIDs* in patients with chronic renal insufficiency</td>
              <td align="center">18 (2.9)</td>
            </tr>
            <tr>
              <td align="left">NSAIDs* in patients with previous peptic ulcer</td>
              <td align="center">8 (1.3)</td>
            </tr>
            <tr>
              <td align="left">Thiazides diuretics in patients with gout</td>
              <td align="center">7 (1.1)</td>
            </tr>
            <tr>
              <td align="left">Metformin in patients with chronic renal insufficiency or congestive heart failure</td>
              <td align="center">6 (1.0)</td>
            </tr>
            <tr>
              <td align="left">β blocking agents in patients with peripheral vascular disease</td>
              <td align="center">4 (0.6)</td>
            </tr>
            <tr>
              <td align="left">β blocking agents in patients with asthma/COPD*</td>
              <td align="center">3 (0.5)</td>
            </tr>
            <tr>
              <td align="left">Others</td>
              <td align="center">5 (1.0)</td>
            </tr>
          </tbody>
        </table>
        <table-wrap-foot>
          <p>*ACE: angiotensin-converting enzyme; ASA: acetylsalicylic acid; COPD: chronic obstructive pulmonary disease; NSAID: Non-steroidal anti-inflammatory drugs.</p>
        </table-wrap-foot>
      </table-wrap>
      <p>Table <xref ref-type="table" rid="T4">4</xref> shows bivariate analysis of the relationship between the characteristics of patient and prescription, and potential drug-drug interactions. The variables found significant (p &lt; 0.05) were, patient older than sixty years, 3 or more diseases, cardiovascular disease, endocrine, alimentary and metabolic disease and receiving five or more medicines.</p>
      <table-wrap position="float" id="T4">
        <label>Table 4</label>
        <caption>
          <p>Relationship between patient's and prescription's characteristics and potential drug-drug interactions</p>
        </caption>
        <table frame="hsides" rules="groups">
          <thead>
            <tr>
              <td align="left">
                <bold>Variables</bold>
              </td>
              <td align="center">
                <bold>Patients without potential drug-drug interactions in their prescription</bold>
                <break/>
                <bold>n = 132</bold>
              </td>
              <td align="center">
                <bold>Patients with at least one potential drug-drug interactions in their prescription</bold>
                <break/>
                <bold>n = 492</bold>
              </td>
            </tr>
          </thead>
          <tbody>
            <tr>
              <td align="left">Gender (female)</td>
              <td align="center">105 (79.5)</td>
              <td align="center">386 (78.5)</td>
            </tr>
            <tr>
              <td align="left">Civil status (single)</td>
              <td align="center">61 (46.2)</td>
              <td align="center">259 (52.6)</td>
            </tr>
            <tr>
              <td align="left">Did not work</td>
              <td align="center">102 (77.3)</td>
              <td align="center">416 (84.6)</td>
            </tr>
            <tr>
              <td align="left">Literacy (only elementary school o less)</td>
              <td align="center">67 (54.9)</td>
              <td align="center">266 (62.9)</td>
            </tr>
            <tr>
              <td align="left">Patient age ≥ 60*</td>
              <td align="center">87 (65.9)</td>
              <td align="center">406 (82.5)</td>
            </tr>
            <tr>
              <td align="left">Number of disease ≥ 3*</td>
              <td align="center">73 (55.3)</td>
              <td align="center">396 (80.5)</td>
            </tr>
            <tr>
              <td align="left">Cardiovascular disease*</td>
              <td align="center">43 (32.6)</td>
              <td align="center">403 (81.9)</td>
            </tr>
            <tr>
              <td align="left">Musculoskeletal and joint disorders</td>
              <td align="center">126 (95.5)</td>
              <td align="center">471(95.7)</td>
            </tr>
            <tr>
              <td align="left">Gastrointestinal disease</td>
              <td align="center">48 (36.4)</td>
              <td align="center">205 (41.7)</td>
            </tr>
            <tr>
              <td align="left">Endocrine, alimentary and metabolic disease*</td>
              <td align="center">38 (28.8)</td>
              <td align="center">275 (55.9)</td>
            </tr>
            <tr>
              <td align="left">Pulmonary disease</td>
              <td align="center">8 (6.0)</td>
              <td align="center">31 (6.3)</td>
            </tr>
            <tr>
              <td align="left">Mental disease</td>
              <td align="center">12 (9.1)</td>
              <td align="center">21 (4.3)</td>
            </tr>
            <tr>
              <td align="left">Neurological disease</td>
              <td align="center">11 (8.3)</td>
              <td align="center">40 (8.1)</td>
            </tr>
            <tr>
              <td align="left">Infections and parasitic disease</td>
              <td align="center">30 (22.7)</td>
              <td align="center">88 (17.9)</td>
            </tr>
            <tr>
              <td align="left">Number of medicines ≥ 5*</td>
              <td align="center">50 (37.9)</td>
              <td align="center">383 (77.8)</td>
            </tr>
          </tbody>
        </table>
        <table-wrap-foot>
          <p>*p &lt; 0.05</p>
        </table-wrap-foot>
      </table-wrap>
      <p>The factors significantly associated with having one or more potential drug-drug interactions in the logistic regression model included: taking five or more medicines (adjusted odds ratio (aOR): 4.34, 95%CI: 2.76–6.83), patient age of 60 years or older (aOR: 1.66, 95% CI: 1.01–2.74) and suffering from cardiovascular diseases (aOR: 7.26, 95% CI: 4.61–11.44) (Table <xref ref-type="table" rid="T5">5</xref>); the adjustment variables were: number of disease ≥ 3 and endocrine, alimentary and metabolic disease.</p>
      <table-wrap position="float" id="T5">
        <label>Table 5</label>
        <caption>
          <p>Factors related to the potential drug-drug interactions</p>
        </caption>
        <table frame="hsides" rules="groups">
          <thead>
            <tr>
              <td align="left">
                <bold>Variables</bold>
              </td>
              <td align="center">
                <bold>Odds ratio</bold>
              </td>
              <td align="center">
                <bold>95% Confidence intervals</bold>
              </td>
              <td align="center">
                <bold>Adjusted Odds Ratio</bold>
              </td>
              <td align="center">
                <bold>95% Confidence intervals</bold>
              </td>
            </tr>
          </thead>
          <tbody>
            <tr>
              <td align="left">Patient age ≥ 60</td>
              <td align="center">2.44*</td>
              <td align="center">1.59 – 3.75</td>
              <td align="center">1.66*</td>
              <td align="center">1.01 – 2.74</td>
            </tr>
            <tr>
              <td align="left">Cardiovascular disease</td>
              <td align="center">9.37*</td>
              <td align="center">6.09 – 14.41</td>
              <td align="center">7.26*</td>
              <td align="center">4.61 – 11.44</td>
            </tr>
            <tr>
              <td align="left">Number of medicines ≥ 5</td>
              <td align="center">5.76*</td>
              <td align="center">3.82 – 8.69</td>
              <td align="center">4.34*</td>
              <td align="center">2.76 – 6.83</td>
            </tr>
          </tbody>
        </table>
        <table-wrap-foot>
          <p>Adjustment variables: number of disease ≥ 3 and endocrine, alimentary and metabolic disease. </p>
          <p>Goodness of fit &gt; 0.05</p>
          <p>*<italic>P </italic>&lt; 0.05</p>
        </table-wrap-foot>
      </table-wrap>
      <p>The bivariate analysis of the factors associated with drug-disease interaction did not show any statistically significant association; therefore, a logistic regression analysis was not performed for these interactions.</p>
    </sec>
    <sec>
      <title>Discussion</title>
      <p>Various studies have shown that potential drug-drug and drug disease interactions are frequent when patients receive multiple prescriptions. This is true for both ambulatory and hospitalized patients, and, in many cases, causes adverse effects and changes in therapeutic efficacies of the combined medicines, with consequent poor control of the diseases under treatment [<xref ref-type="bibr" rid="B1">1</xref>-<xref ref-type="bibr" rid="B4">4</xref>,<xref ref-type="bibr" rid="B6">6</xref>-<xref ref-type="bibr" rid="B12">12</xref>].</p>
      <p>In the present study, we found that the frequency of potential drug-drug interactions in prescriptions of family doctors working in primary care clinics in Mexico City was almost 80.0%; this is higher than the frequency in Europe [<xref ref-type="bibr" rid="B4">4</xref>] (46.0%) and in the United States [<xref ref-type="bibr" rid="B1">1</xref>] (25.0%) in ambulatory patients over 59 years of age. The rates we found may be unique for the sample and may not be fully representative of Mexican population situation. The higher prevalence of potential drug-drug and drug-disease interactions in this study compared to others studies is likely attributable to the characteristics of the study sample (older adults with very high prevalence – nearly 90.0% – of NSAID utilization) among other reasons.</p>
      <p>The frequency of type D interactions (which should be avoided) was smaller (3.8%) in our work, when compared with other studies (the type D frequency was 10.0% in the European study) [<xref ref-type="bibr" rid="B4">4</xref>]. The three combinations with drug-drug potential interactions that were found most frequently in our work are among those reported by Bjorkman [<xref ref-type="bibr" rid="B4">4</xref>]. These drug interactions are of type C and, without dose adjustment and patient monitoring, such interactions may antagonize drug effects on vascular tone and may result in increases in blood pressure (angiotensin-converting enzyme (ACE) inhibitors + NSAIDs, ACE inhibitors + low doses of ASA) [<xref ref-type="bibr" rid="B20">20</xref>] or may increase gastrointestinal adverse effects (NSAIDs + low doses of ASA) [<xref ref-type="bibr" rid="B21">21</xref>]. These finding coincide with the literature review performed by Becker et al., in which it was reported that drugs most often responsible for hospital admissions were NSAIDs and cardiovascular drugs, and the most common causes for such admissions were gastrointestinal tract bleeding and hyper- or hypotension [<xref ref-type="bibr" rid="B11">11</xref>].</p>
      <p>Other authors have reported that both types C and D show similar hospitalization frequencies [<xref ref-type="bibr" rid="B10">10</xref>]. Therefore, medical doctors must be familiar with both interaction types.</p>
      <p>We found that not only potential drug-drug, but also drug-disease interactions, were frequent in prescriptions. The frequency of the latter (64.0%) found in the present work is greater than reported in either hospitalized patients [<xref ref-type="bibr" rid="B2">2</xref>] or ambulatory patients [<xref ref-type="bibr" rid="B3">3</xref>].</p>
      <p>The most frequent were interactions involving NSAIDs that were prescribed to patients with hypertension and/or chronic heart failure, and prescriptions of NSAIDs and ACE inhibitors. Although this finding was influenced by patient inclusion criteria, it shows that the flaws in the knowledge of prescribers regarding interactions of this group of drugs. In such cases, other therapeutic options should be considered to avoid potential drug interactions, like using paracetamol to manage osteoarthritis in patients with hypertension being treated with ACE inhibitors.</p>
      <p>In general, our findings agree with other studies reporting that the risk of potential drug-drug interactions increases with each new prescription issued and with the aging of the patient [<xref ref-type="bibr" rid="B2">2</xref>,<xref ref-type="bibr" rid="B3">3</xref>,<xref ref-type="bibr" rid="B6">6</xref>-<xref ref-type="bibr" rid="B8">8</xref>]. In line with this, we found that patient age of 60 years or older and taking 5 or more medicines increases the risk of such potential interactions. Polypharmacy is an important problem in older people that has been reported as a frequent event all over the world [<xref ref-type="bibr" rid="B3">3</xref>,<xref ref-type="bibr" rid="B4">4</xref>,<xref ref-type="bibr" rid="B22">22</xref>,<xref ref-type="bibr" rid="B23">23</xref>]. In our sample, the patients took an average of 5.9 drugs, and those 60 years or older took an average of 6.1 drugs (37.3% of them took 7 or more medicines).</p>
      <p>Within the context of this study, there exists limited published local information regarding the average number of drugs that a patient older than fifty years gets prescribed. Previous studies have been carried out in specific groups of older patients, such as community-dwelling elderly hospitalized due to inappropriate drug prescriptions [<xref ref-type="bibr" rid="B24">24</xref>], in nursing home residents [<xref ref-type="bibr" rid="B25">25</xref>] and in patients with hypertension [<xref ref-type="bibr" rid="B26">26</xref>]. For example, in hospitalized elderly patients, the average number of drugs consumed was 6.0 [<xref ref-type="bibr" rid="B24">24</xref>], and in nursing home residents was 2.8 [<xref ref-type="bibr" rid="B25">25</xref>], and in the study addressing patients with hypertension [<xref ref-type="bibr" rid="B26">26</xref>] aged 60 years and older, only 1.9% were taking three or more hypertensive drugs; yet, in this study the consumption of other drugs was not analyzed. Further studies should be advisable to gain in depth knowledge about the average number of drugs that family doctors prescribe to the elderly in Mexico.</p>
      <p>Furthermore, we found that having a cardiovascular disease increases seven-fold the risk of potential drug-disease interactions. This means, as has been recommended in prior studies from other countries, that doctors need to pay more attention to drug prescription and patient monitoring when treating older individuals [<xref ref-type="bibr" rid="B2">2</xref>,<xref ref-type="bibr" rid="B3">3</xref>,<xref ref-type="bibr" rid="B6">6</xref>,<xref ref-type="bibr" rid="B7">7</xref>] also, the patients with cardiovascular diseases deserve more attention. It is necessary to consider interventions to reduce the drug interaction problem. Computer-based access to information on all prescriptions dispensed, and automated doctor alerts on the most frequent potential drug interactions encountered, would be most helpful. These tools are effective in reducing inappropriate prescriptions, and doctor acceptance in other populations has been reported [<xref ref-type="bibr" rid="B27">27</xref>,<xref ref-type="bibr" rid="B28">28</xref>]. Alternatives such as programs of continuous medical education, or pharmaceutical support, may also be considered. It has been found, however, that even pharmacists cannot detect all potential drug interactions because their number rises dramatically as the number of medicines prescribed increases [<xref ref-type="bibr" rid="B29">29</xref>].</p>
      <p>Among the limitations of this study is that it only permits an approximation to problem of drug interactions in family medicine practice. The patients' group studied was very limited (all patients had non-malignant pain syndrome). We believe that some drug interactions may be more frequent in such patients. For example, we found that the most frequent potential drug-disease interaction involved the use of NSAIDs in patients with hypertension. In patients with acute or infectious disease is possible that other interactions would be found more frequently. Also, in this cross-sectional study we did not determine any possible relationship between drug-drug nor drug-disease interactions and the health status of the population studied.</p>
      <p>It is possible to conclude that the high frequency of prescription of drugs with potential drug interactions is common in primary care level; the easiest way to reduce the frequency of them is to decrease the number of medicines prescribed. Nevertheless, sometimes it is difficult to reduce the number of drugs prescribed for patients with multiple chronic conditions; therefore, to lower the frequency of potential interactions it could be necessary to make a careful selection of therapeutic alternatives, and in cases without other options, patients should be continuously monitored to identify adverse events.</p>
    </sec>
    <sec>
      <title>Competing interests</title>
      <p>The author(s) declare that they have no competing interests.</p>
    </sec>
    <sec>
      <title>Authors' contributions</title>
      <p>SVD, HRM contributed in the conception and design of the study, literature review and statistical analysis. LPTA reviewed for important intellectual content. MSO contributed in data management. All authors participated in the interpretation of data and read and approved the final version to be published.</p>
    </sec>
    <sec>
      <title>Pre-publication history</title>
      <p>The pre-publication history for this paper can be accessed here:</p>
      <p>
        <ext-link ext-link-type="uri" xlink:href="http://www.biomedcentral.com/1472-6963/7/147/prepub"/>
      </p>
    </sec>
  </body>
  <back>
    <ack>
      <sec>
        <title>Acknowledgements</title>
        <p>The study was supported by grants from the Research Promotion Fund of the Mexican Institute of Social Security (FOFOI IMSS-2005/1/I/201).</p>
      </sec>
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</metadata></record><record><header><identifier>oai:pubmedcentral.nih.gov:2080632</identifier><datestamp>2007-11-17</datestamp><setSpec>rr</setSpec><setSpec>pmc-open</setSpec></header><metadata><article xmlns="http://dtd.nlm.nih.gov/2.0/xsd/archivearticle" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://dtd.nlm.nih.gov/archiving/2.3/xsd/archivearticle.xsd" article-type="research-article">
  <front>
    <journal-meta>
      <journal-id journal-id-type="nlm-ta">Respir Res</journal-id>
      <journal-title>Respiratory Research</journal-title>
      <issn pub-type="ppub">1465-9921</issn>
      <issn pub-type="epub">1465-993X</issn>
      <publisher>
        <publisher-name>BioMed Central</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="pmc">2080632</article-id>
      <article-id pub-id-type="publisher-id">1465-9921-8-71</article-id>
      <article-id pub-id-type="pmid">17916230</article-id>
      <article-id pub-id-type="doi">10.1186/1465-9921-8-71</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>LPS induces IL-10 production by human alveolar macrophages via MAPKinases- and Sp1-dependent mechanisms</article-title>
      </title-group>
      <contrib-group>
        <contrib id="A1" contrib-type="author">
          <name>
            <surname>Chanteux</surname>
            <given-names>Hugues</given-names>
          </name>
          <xref ref-type="aff" rid="I1">1</xref>
          <email>hugues.chanteux@ucb-group.com</email>
        </contrib>
        <contrib id="A2" contrib-type="author">
          <name>
            <surname>Guisset</surname>
            <given-names>Amélie C</given-names>
          </name>
          <xref ref-type="aff" rid="I1">1</xref>
          <email>amelie.guisset@mblg.ucl.ac.be</email>
        </contrib>
        <contrib id="A3" contrib-type="author">
          <name>
            <surname>Pilette</surname>
            <given-names>Charles</given-names>
          </name>
          <xref ref-type="aff" rid="I1">1</xref>
          <email>charles.pilette@pneu.ucl.ac.be</email>
        </contrib>
        <contrib id="A4" corresp="yes" contrib-type="author">
          <name>
            <surname>Sibille</surname>
            <given-names>Yves</given-names>
          </name>
          <xref ref-type="aff" rid="I1">1</xref>
          <email>sibille@mblg.ucl.ac.be</email>
        </contrib>
      </contrib-group>
      <aff id="I1"><label>1</label>Unit of microbiology, Université Catholique de Louvain, Av Hippocrate 54, B-1200 Brussels, Belgium</aff>
      <pub-date pub-type="ppub">
        <year>2007</year>
      </pub-date>
      <pub-date pub-type="epub">
        <day>4</day>
        <month>10</month>
        <year>2007</year>
      </pub-date>
      <volume>8</volume>
      <issue>1</issue>
      <fpage>71</fpage>
      <lpage>71</lpage>
      <ext-link ext-link-type="uri" xlink:href="http://respiratory-research.com/content/8/1/71"/>
      <history>
        <date date-type="received">
          <day>21</day>
          <month>9</month>
          <year>2006</year>
        </date>
        <date date-type="accepted">
          <day>4</day>
          <month>10</month>
          <year>2007</year>
        </date>
      </history>
      <permissions>
        <copyright-statement>Copyright © 2007 Chanteux et al; licensee BioMed Central Ltd.</copyright-statement>
        <copyright-year>2007</copyright-year>
        <copyright-holder>Chanteux et al; licensee BioMed Central Ltd.</copyright-holder>
        <license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/2.0">
          <p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/2.0"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>
          <!--<rdf xmlns="http://web.resource.org/cc/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1" xmlns:dcterms="http://purl.org/dc/terms"><Work xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" rdf:about=""><license rdf:resource="http://creativecommons.org/licenses/by/2.0"/><dc:type rdf:resource="http://purl.org/dc/dcmitype/Text"/><dc:author>
               Chanteux
               Hugues
               
               hugues.chanteux@ucb-group.com
            </dc:author><dc:title>
            LPS induces IL-10 production by human alveolar macrophages via MAPKinases- and Sp1-dependent mechanisms
         </dc:title><dc:date>2007</dc:date><dcterms:bibliographicCitation>Respiratory Research 8(1): 71-. (2007)</dcterms:bibliographicCitation><dc:identifier type="sici">1465-9921(2007)8:1&#x0003c;71&#x0003e;</dc:identifier><dcterms:isPartOf>urn:ISSN:1465-9921</dcterms:isPartOf><License rdf:about="http://creativecommons.org/licenses/by/2.0"><permits rdf:resource="http://web.resource.org/cc/Reproduction" xmlns=""/><permits rdf:resource="http://web.resource.org/cc/Distribution" xmlns=""/><requires rdf:resource="http://web.resource.org/cc/Notice" xmlns=""/><requires rdf:resource="http://web.resource.org/cc/Attribution" xmlns=""/><permits rdf:resource="http://web.resource.org/cc/DerivativeWorks" xmlns=""/></License></Work></rdf>-->
        </license>
      </permissions>
      <abstract>
        <sec>
          <title>Background</title>
          <p>IL-10 is a cytokine mainly produced by macrophages that plays key roles in tolerance to inhaled antigens and in lung homeostasis. Its regulation in alveolar macrophages (HAM), the resident lung phagocytes, remains however unknown.</p>
        </sec>
        <sec sec-type="methods">
          <title>Methods</title>
          <p>The present study investigated the role of intracellular signalling and transcription factors controlling the production of IL-10 in LPS-activated HAM from normal nonsmoking volunteers.</p>
        </sec>
        <sec>
          <title>Results</title>
          <p>LPS (1–1000 pg/ml) induced <italic>in vitro </italic>IL-10 production by HAM, both at mRNA and protein levels. LPS also activated the phosphorylation of ERK, p38 and JNK MAPkinases (immunoblots) and Sp-1 nuclear activity (EMSA). Selective inhibitors of MAPKinases (respectively PD98059, SB203580 and SP600125) and of Sp-1 signaling (mithramycin) decreased IL-10 expression in HAM. In addition, whilst not affecting IL-10 mRNA degradation, the three MAPKinase inhibitors completely abolished Sp-1 activation by LPS in HAM.</p>
        </sec>
        <sec>
          <title>Conclusion</title>
          <p>These results demonstrate for the first time that expression of IL-10 in lung macrophages stimulated by LPS depends on the concomitant activation of ERK, p38 and JNK MAPKinases, which control downstream signalling to Sp-1 transcription factor. This study further points to Sp-1 as a key signalling pathway for IL-10 expression in the lung.</p>
        </sec>
      </abstract>
    </article-meta>
  </front>
  <body>
    <sec>
      <title>Background</title>
      <p>Strategically located on the alveolar surface, alveolar macrophages represent highly specialized macrophages that function primarily in lung defence against inhaled particle matter, microorganisms and environmental toxins. Among microorganisms, gram-negative bacteria and more precisely, the lipopolysaccharide (LPS) component of the outer cell wall, is a very potent activator of macrophages. LPS binds to LPS-binding protein and is delivered to the cell surface receptor CD14, before being transferred to the transmembrane signaling receptor toll-like receptor 4 (TLR4) and its accessory protein MD2 [<xref ref-type="bibr" rid="B1">1</xref>]. LPS stimulation activates several intracellular signaling pathways including the three mitogen-activated protein kinase (MAPK) pathways: extracellular signal-regulated kinases (ERK) 1 and 2, c-Jun N-terminal kinase (JNK) and p38. These signalling pathways in turn activate a variety of transcription factors which coordinate the induction of many genes encoding inflammatory mediators as well as anti-inflammatory cytokines.</p>
      <p>The control of inflammatory responses is critical to the host to allow resolution and avoid tissue damage. IL-10 is a key anti-inflammatory factor and pleiotropic cytokine produced by a variety of cell types among which monocytes/macrophages are the main sources [<xref ref-type="bibr" rid="B2">2</xref>]. IL-10 mediates the inhibition of pro-inflammatory cytokines such as TNF-α, IL-8, IL-6, IL-1β, IL-12 [<xref ref-type="bibr" rid="B3">3</xref>-<xref ref-type="bibr" rid="B7">7</xref>]. IL-10 has also been shown to inhibit antigen-presenting cell function, including the maturation of dendritic cells [<xref ref-type="bibr" rid="B8">8</xref>] and the expression of MHC class II and co-stimulatory molecules [<xref ref-type="bibr" rid="B9">9</xref>,<xref ref-type="bibr" rid="B10">10</xref>]. IL-10 gene regulation can occur both at the transcriptional and posttranscriptional levels [<xref ref-type="bibr" rid="B11">11</xref>]. Several studies have shown that the transcription factor Sp1 plays an important role in IL-10 transcription (an Sp1 responsive element in the IL-10 promoter is localized at -89 to -78) [<xref ref-type="bibr" rid="B12">12</xref>-<xref ref-type="bibr" rid="B14">14</xref>]. Moreover, detailed studies showed that p38 mitogen-activated protein regulates LPS-induced activation of Sp1 in THP-1, a human monocytic cell line [<xref ref-type="bibr" rid="B14">14</xref>]. The STAT3 transcription factor may also bind to an element in the IL-10 promoter gene and the use of a dominant negative form of STAT3 was able to decrease IL-10 transcription [<xref ref-type="bibr" rid="B15">15</xref>]. More recently, the protooncogene c-Maf has been shown to be an essential transcription factor for IL-10 gene expression in macrophages [<xref ref-type="bibr" rid="B16">16</xref>] while a role for C/EBP in cooperation with Sp1 has also been suggested [<xref ref-type="bibr" rid="B17">17</xref>]. However, the intracellular signalling pathways governing IL-10 gene regulation in human alveolar macrophages are poorly understood. Thus, alveolar macrophages are the main source of IL-10 in the alveoli where they play an important role to control lung homeostasis. One study on human alveolar macrophages [<xref ref-type="bibr" rid="B18">18</xref>] showed that activation of PKC decreases IL-10 production whereas activation of protein phosphatases PP1 and PP2A enhance IL-10 secretion. In the present work, we evaluate the ability of human alveolar macrophages to produce IL-10 upon LPS stimulation and the role of MAPkinases (ERK, p38 and JNK) and Sp1 transcription factor as intracellular signals leading to IL-10 expression.</p>
    </sec>
    <sec sec-type="methods">
      <title>Methods</title>
      <sec>
        <title>Reagents</title>
        <p>LPS from <italic>Salmonella typhimurium</italic>, PMSF, Nonidet, DTT, BSA, Tween 20, Thiazolyl Blue Tetrazolium Bromide and Actinomycin D were purchased from Sigma (Sigma Chemical Co., St Louis, MO). PD98059, SB203580 were purchased from BioMol (Plymouth Meeting, PA) and SP600125 from AG Scientific (San Diego, CA). Anti-CD14 was purchased from R&amp;D Systems (Abingdon, UK). All other reagents were from VWR International (Darmstadt, Germany).</p>
      </sec>
      <sec>
        <title>Isolation of Human Alveolar Macrophages (HAM)</title>
        <p>HAM were obtained from bronchoalveolar lavages from normal non smoking volunteers as previously described [<xref ref-type="bibr" rid="B19">19</xref>]. Briefly, the lavage fluid was passed through a layer of sterile gauze to remove gross mucus and then centrifuged at 500 <italic>g </italic>for 10 min at 4°C to separate cells from fluid. The cell pellet was washed twice in complete culture medium : RPMI 1640 medium (Cambrex Corporation, East Rutherford, NJ) supplemented with 10% decomplemented (30 min at 56°C) FCS, 2 mM L-glutamine, 100 U/ml penicillin and 100 μg/ml streptomycin. HAM were &gt;95% pure with less than 1% of neutrophils and monocytes. HAM were allowed to adhere during 30 min and non-adherent cells were removed by two washes.</p>
      </sec>
      <sec>
        <title>Nuclear extract and Electrophoretic Mobility Shif Assay (EMSA)</title>
        <p>Nuclear extracts were prepared from HAM as described by Carter with minor modifications as reported previously [<xref ref-type="bibr" rid="B19">19</xref>]. 1.10<sup>6 </sup>HAM were washed in cold PBS and collected in 400 μl of ice-cold EMSA lysis buffer (10 mM HEPES pH 7.9, 10 mM KCl, 2 mM MgCl<sub>2</sub>, 2 mM EDTA, 1 mM DTT, 1 mM PMSF) supplemented with 10 μg/ml of each protease inhibitors (leupeptin, aprotinin, pepstatin, trypsin inhibitor) and then incubated on ice for 10 min. Nonidet (NP-40) 10% was added to lyse the cells which were vortexed and centrifuged 1 min at 4°C at 13000 rpm. Nuclei were resuspended in 25 μl of extraction buffer (50 mM Hepes pH 7.9, 10% glycerol, 50 mM KCl, 300 mM NaCl, 0,1 mM EDTA, 1 mM DTT, 0.5 mM phenylmethylsulfonylfluoride and protease inhibitors) for 30 min on ice. The nuclear suspension was then centrifuged 3 min at 13000 rpm and supernatant stored at -70°C until use. Proteins were assayed using the Blue coomassie method. Sp1 consensus oligonucleotides (5'-ATTCGATCG<bold>GGGCGG</bold>GGCGAGC-3') were purchased from Invitrogen Life Technologies (Carlsbad, CA) and were 3' biotinylated using Biotin 3' End DNA Labeling Kit (Pierce, Rockford, IL) following manufacturer's instructions. EMSA was performed using the LightShift Chemiluminescent EMSA kit (Pierce, Rockford, IL). Briefly, 2, 5 μg of nuclear extract was incubated at room temperature during 20 min with 20 fmol of biotinylated double-stranded oligonucleotide in presence of 50 ng of salmon sperm and reaction buffer. The protein-DNA complexes were separated on a 7% non-denaturating polyacrylamide gel and bands were visualized using Biorad Chemidocs XRS apparatus (Bio-Rad Laboratories, Hercules, CA).</p>
      </sec>
      <sec>
        <title>RNA extraction and real-time PCR</title>
        <p>Total RNA was extracted from 10<sup>6 </sup>HAM using TRIzol reagent (Invitrogen) and 2 μg of total RNA was used to generate first strand cDNA synthesis using Superscript II (Invitrogen/Life Technologies, Carlsbad, CA). The reaction mix containing 1 μg of RNA, poly-dT, and 10 mM dNTP mix was diluted to 24 μl in sterile water, heated to 65°C for 5 min, and chilled on ice for 1 min. First strand synthesis was then performed in 50 μl total reaction volume by adding 50 mM Tris (pH 8.3), 75 mM KCl, 3 mM MgCl<sub>2</sub>, 20 mM DTT, 40 U of RNaseout, and 200 U of Superscript II reverse-transcriptase enzyme (Invitrogen) at 42°C for 1 h. The reaction was inactivated by heating at 72°C for 10 min. cDNA was stored at -20°C until amplification. The quantitative PCR was performed by real-time PCR on a Lightcycler System (Roche Applied Science, Basel, Switzerland) using predevelopped primers set for human IL-10 (Search LC, GmbH Heidelberg, Germany). PCR conditions were those described in manufacturer's instruction. The reaction mix contains 5 μl cDNA, 1 mM of primers, water and Master mix (Faststart DNA Master plus Sybr Green I-Roche Applied Science) in a final volume of 20 μl. β-actin primers were designed following sequence published in GenBank (access number : <ext-link ext-link-type="gen" xlink:href="M10277">M10277</ext-link>) in two different exons. They were synthesized by Life technologies : sense : 5'-gtgacattaaggagaagctgtgcta-3' (position : 2294–2317), antisense : 5'-cttcatgatggagttgaaggtagtt-3' (position : 2588–2612). PCR conditions were : denaturation at 95°C, 10 s – hybridization, 60°C, 5 s – elongation, 72°C, 7 s. After amplification step, a melting curve is performed to ensure that only one product has been amplified. Moreover, separation of the products on 2% agarose gel confirmed the size of the amplicon.</p>
      </sec>
      <sec>
        <title>IL-10 ELISA</title>
        <p>IL-10 was assayed in the supernatant by ELISA using a pair of antibodies (BD Biosciences, San Diego, CA) following manufacturer's instructions. The sensitivity of the ELISA was 1.5 pg/ml.</p>
      </sec>
      <sec>
        <title>Western-Blot analysis</title>
        <p>5 × 10<sup>5 </sup>HAM were collected in 200 μl Laemmli sample buffer and heated at 100°C, 5 min to denature proteins. 20 μl of protein lysate was loaded onto a 12% SDS-PAGE gel and run at 180 V for 1 h. Cell proteins were then transferred to nitrocellulose (Hybond-C, Amersham Biosciences, UK) membrane at 70 mA for 1 h 30 at room temperature. Membrane was blocked with 5% BSA in TTBS (Tris-Buffered saline with 0.1% Tween 20) for 1 h at room temperature, washed, and then incubated with the primary Ab 1/1000(anti-phospho ERK, anti-phospho p38 or anti-phospho JNK – Cell Signaling Technology, Beverly, MA) overnight at 4°C. The blots were washed 3 × 5 min with TTBS and incubated for 1 h with HRP-conjugated anti-rabbit IgG Ab 1/2000(Cell Signaling Technology, Beverly, MA). Immunoreactive bands were revealed using a chemiluminescent substrate (ECL, Amersham Biosciences, UK) and chemiluminescence was detected with chemidoc XRS apparatus. The intensity of each blot was measured with the densitometry program Quantity One (Bio-Rad Laboratories, Hercules, CA).</p>
      </sec>
      <sec>
        <title>IL-10 mRNA degradation assay</title>
        <p>1 × 10<sup>6 </sup>HAM/well were stimulated with LPS (1 μg/ml) for 16 h, translation was stopped by using Actinomycin D (2.5 μg/ml) and then, PD98059, SB203580 or medium (25 μM) was added for various time periods. HAM were collected for RNA extraction and real time PCR for IL-10 mRNA was performed.</p>
      </sec>
      <sec>
        <title>MTT assay</title>
        <p>2.5 × 10<sup>5 </sup>HAM/well were incubated with PD98059, SB203580, SP600125 (25 μM) or medium for 24 h. Supernatants were discarded and 100 μl of Thiazolyl Blue Tetrazolium Bromide (MTT, 1 mg/ml) was added to the cells for 1 h. DMSO was then used to stop the reaction and optical density was read at 550 nm.</p>
      </sec>
      <sec>
        <title>Statistical analysis</title>
        <p>Comparisons were performed using two-tailed paired t test or Mann-Wittney U test as appropriate. All analyses were performed using a statistics software package (GraphPad Prism, PA, USA). p values &lt; 0.05 were considered as statistically significant.</p>
      </sec>
    </sec>
    <sec>
      <title>Results</title>
      <sec>
        <title>LPS induces IL-10 secretion in human alveolar macrophages</title>
        <p>In a first series of experiments, we evaluated the ability of HAM to release IL-10 after LPS stimulation. Figure <xref ref-type="fig" rid="F1">1</xref> panel A shows the production of IL-10 overtime. The release of IL-10 begins after 6 h of incubation and reaches a maximum at 24 h. Moreover, IL-10 production is dose-dependent and linear in the range of LPS concentration between 1 ng/ml and 1 μg/ml (Figure <xref ref-type="fig" rid="F1">1</xref>, panel B). The time-course of IL-10 induction by LPS was confirmed at gene level by real time PCR (Figure <xref ref-type="fig" rid="F1">1</xref>, panel C).</p>
        <fig position="float" id="F1">
          <label>Figure 1</label>
          <caption>
            <p><bold>Time and dose dependency of IL-10 production in HAM stimulated by LPS</bold>. HAM were stimulated with LPS (1 μg/ml) and supernatant were collected after different incubation time and assayed for IL-10 content by ELISA for Panel A and by real time PCR for Panel C. Panel B: HAM were stimulated for 24 hours with increasing concentration of LPS and supernatant were assayed for IL-10 by ELISA.</p>
          </caption>
          <graphic xlink:href="1465-9921-8-71-1"/>
        </fig>
        <p>To check if IL-10 production is CD14 dependent, we used an anti-CD14 blocking antibody. Preincubation of HAM with a neutralizing anti-CD14 (10 μg/ml) totally inhibits LPS-induced IL-10 (data not shown).</p>
      </sec>
      <sec>
        <title>Activation of MAPkinases by LPS</title>
        <p>It is well-known that LPS activates ERK, p38 and JNK MAPkinases. The ability of LPS to induce the phosphorylation of ERK, p38 and JNK in human alveolar macrophages was evaluated by western-blotting. As shown on Figure <xref ref-type="fig" rid="F2">2</xref>, LPS triggers ERK, p38 and JNK phosphorylation in a time- and dose-dependent fashion. Panel A shows that both ERK and p38 MAPkinases reached a maximum of phosporylation at a concentration of 100 ng/ml and are not activated at concentration below 100 pg/ml. Concerning JNK MAPkinase, phosphorylation is dose-dependent in the range of concentration between 0.1 and 10 ng/ml. Experiments of time-dependence show that both ERK and p38 are rapidly phosphorylated (within 5 min) and reached a maximum of activation after 15–30 min followed by a progressive decline and come-back to the basal state after 90 and 120 min for ERK and p38 respectively (panel B). JNK phosphorylation is also rapid (within 5 minutes) and reached its maximum at 15 min but returns to its basal state within 60 min.</p>
        <fig position="float" id="F2">
          <label>Figure 2</label>
          <caption>
            <p><bold>Activation of MAP kinases in HAM stimulated by LPS</bold>. Panel A: HAM were stimulated 30 min with increasing doses of LPS and phosphorylated ERK, p38 and JNK were detected by Western-blotting as described in Materials and Methods. Panel B: HAM were incubated with LPS (1 μg/ml) during different time and phosphorylated ERK, p38 and JNK were detected by Western-blotting. Below the blots, the graph represents the phosphorylated MAP kinases to β-actin ratio obtained by densitometric analysis of each bands using Quantity One Sotware.</p>
          </caption>
          <graphic xlink:href="1465-9921-8-71-2"/>
        </fig>
      </sec>
      <sec>
        <title>MAPkinases are crucial for IL-10 production</title>
        <p>Since we have shown that the three MAPkinases were activated following LPS stimulation, we therefore evaluated the precise role of each MAPkinase in the production of IL-10. To this aim, PD98059, SB203580 and SP600125, three specific inhibitors of ERK, p38 and JNK respectively were used. First, the specificity of each inhibitor was checked by western-blot (Figure <xref ref-type="fig" rid="F3">3</xref>) and cell toxicity was assessed by the MTT assay (Table <xref ref-type="table" rid="T1">1</xref>). No significant cytotoxicity was observed for the three inhibitors at 25 μM while 50 μM of SB or SP induced a 30–35% reduction in MTT reduction (Table <xref ref-type="table" rid="T1">1</xref>). Pre-treatment of HAM with PD98059 (50 μM) clearly inhibits LPS-induced ERK activation and was without significant effect on p38 and JNK phosphorylation (Figure <xref ref-type="fig" rid="F3">3</xref>). SB203580 (25 μM) partially inhibits LPS-induced p38 phosphorylation without affecting ERK and JNK activation while SP600125 (50 μM) is able to prevent the phosphorylation of JNK MAPkinase after LPS stimulation without affecting ERK phosphorylation. In the latter conditions, phosphorylation of p38 MAPkinase is slightly increased. Having shown that these three inhibitors were specific of each MAPkinase, we used them to evaluate the involvment of MAPkinases in the production of IL-10. As shown on Figure <xref ref-type="fig" rid="F4">4</xref>, PD98059, SB203580 and SP600125 dose-dependently inhibit LPS-induced IL-10 in HAM. At the maximum concentration (50 μM), SB203580 totally inhibits IL-10 production (more than 99% of inhibition) whereas PD98059 is slightly less active (80% of inhibition). The specific inhibitor of JNK MAPkinase, SP600125, at its maximal concentration, only reduced IL-10 production by 50%.</p>
        <table-wrap position="float" id="T1">
          <label>Table 1</label>
          <caption>
            <p>MTT-based cytotoxicity assay of MAPk inhibitors in HAM. HAM were incubated for 24 h with PD98059, SB203580, SP600125 or medium at different concentrations, and cell viability was assessed by using the MTT reduction assay, as described in Methods. Results are mean ± SD of one representative experiment in triplicates (expressed as % of control); *p value &lt; 0.05 (one sample t-test).</p>
          </caption>
          <table frame="hsides" rules="groups">
            <thead>
              <tr>
                <td align="center">
                  <bold>Concentration of inhibitors</bold>
                </td>
                <td align="center">
                  <bold>PD98059</bold>
                </td>
                <td align="center">
                  <bold>SB203580</bold>
                </td>
                <td align="center">
                  <bold>SP600125</bold>
                </td>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td align="center">
                  <bold>1 μM</bold>
                </td>
                <td align="center">96.2 ± 20.26</td>
                <td align="center">92.7 ± 14.2</td>
                <td align="center">92.6 ± 19.5</td>
              </tr>
              <tr>
                <td align="center">
                  <bold>5 μM</bold>
                </td>
                <td align="center">93.4 ± 14</td>
                <td align="center">85.3 ± 34.6</td>
                <td align="center">104.9 ± 33.5</td>
              </tr>
              <tr>
                <td align="center">
                  <bold>10 μM</bold>
                </td>
                <td align="center">79.9 ± 14.2</td>
                <td align="center">104.1 ± 15.7</td>
                <td align="center">110.1 ± 11</td>
              </tr>
              <tr>
                <td align="center">
                  <bold>25 μM</bold>
                </td>
                <td align="center">122.3 ± 6.9</td>
                <td align="center">82.8 ± 7.2</td>
                <td align="center">89.3 ± 9</td>
              </tr>
              <tr>
                <td align="center">
                  <bold>50 μM</bold>
                </td>
                <td align="center">104.6 ± 20.6</td>
                <td align="center">66.2 ± 10.1*</td>
                <td align="center">65.2 ± 9*</td>
              </tr>
            </tbody>
          </table>
        </table-wrap>
        <fig position="float" id="F3">
          <label>Figure 3</label>
          <caption>
            <p><bold>Inhibition of MAPkinases activation by PD98059, SB203580, SP600125</bold>. HAM were preincubated during 1 h with inhibitors (50 μM) and then stimulated 30 min with LPS (1 μg/ml). Levels of phosphorylated ERK, p38 and JNK MAP kinases were evaluated by Western-blot analysis. Each bands was normalised by performing phospho MAP kinase to β-actin ratio as by the graph representing the densitometric analysis.</p>
          </caption>
          <graphic xlink:href="1465-9921-8-71-3"/>
        </fig>
        <fig position="float" id="F4">
          <label>Figure 4</label>
          <caption>
            <p><bold>Effect of specific MAP kinase inhibitors on the production of IL-10 in HAM</bold>. HAM were preincubated (1 h) with increasing concentrations of inhibitors and then were stimulated with LPS (1 μg/ml) during 24 h. Supernatants were assayed to determine the production of IL-10 by ELISA.</p>
          </caption>
          <graphic xlink:href="1465-9921-8-71-4"/>
        </fig>
      </sec>
      <sec>
        <title>Role of Sp1 transcription factor in the production of IL-10</title>
        <p>Sp1 transcription factor is one of the main transcription factor regulating IL-10 transcription in monocytes/macrophages. In order to evaluate the involvement of Sp1 in IL-10 production in HAM, we first used mithramycin as a specific inhibitor of Sp1. As shown on Figure <xref ref-type="fig" rid="F5">5</xref>, mithramycin dose-dependently inhibits LPS-induced IL-10 production in HAM with a maximal inhibition at 500 nM. Secondly, we set up an EMSA assay to confirm that Sp1 was activated and that the inhibition observed with mithramycin was due to an effect on Sp1. Activation of Sp1 following LPS stimulation was assessed using a specific probe containing the consensus binding site for Sp1. Figure <xref ref-type="fig" rid="F6">6</xref> represents a representative EMSA gel where HAM have been activated by LPS during 2 h. As control, the free probe (without nuclear extract protein) shows no band whereas in the control and LPS-treated HAM, two bands (one major intense and one light) are found in both conditions whereas the light band is more present in LPS-treated HAM. To determine which of these bands is specific to Sp1, the following controls have been performed. First, an excess of cold probe totally switch off all the bands. Secondly, the use of a mutant probe (mutation in the consensus binding site of Sp1) gives only one band corresponding to the major band meaning that this band is a non-specific one. Thirdly, addition of an anti-Sp1 antibody decreased the light band and induces a super-shift. Therefore, we can conclude that the light band represents the complex Sp1/probe.</p>
        <fig position="float" id="F5">
          <label>Figure 5</label>
          <caption>
            <p><bold>Effect of mithramycin on IL-10 production in HAM</bold>. HAM were preincubated (1 h) with increasing concentration of mithramycin and were stimulated with LPS (1 μg/ml) during 24 h. Supernantants were assayed by ELISA to determine IL-10 production.</p>
          </caption>
          <graphic xlink:href="1465-9921-8-71-5"/>
        </fig>
        <fig position="float" id="F6">
          <label>Figure 6</label>
          <caption>
            <p><bold>EMSA analysis of Sp1 binding activity in nuclear proteins of HAM</bold>. Panel A : HAM were treated or not with LPS (1 μg/ml) during 2 h. Nuclear proteins were extracted following procedure described in Materials and Methods. Lane 1: free labelled probe only (without nuclear proteins) – Lane 2: Nuclear proteins from control HAM incubated with labelled probe specific for Sp1 – Lane 3: idem lane2 except that HAM were treated 2 h with LPS – Lane 4: idem lane 3 except that an excess of unlabelled (cold) probe was added in the binding reaction – Lane 5: idem lane 3 except that a mutant labelled probe (mutation in consensus binding site) is used instead of the specific labelled probe for Sp1 – Lane 6: idem lane 3 except that nuclear proteins were preincubated with a specific anti-Sp1 antibody before addition of the specific labelled probe. Panel B represents a quantitative analysis of a EMSA gel from HAM following stimulation by LPS. Data are mean ± SD from 6 experiments; *p value = 0.0411 (Mann-Whitney <italic>U </italic>test).</p>
          </caption>
          <graphic xlink:href="1465-9921-8-71-6"/>
        </fig>
        <p>Preliminary experiments have shown that maximum Sp1 activation following LPS stimulation is reached between 1 and 2 h (data not shown), and that LPS was up-regulating nuclear translocation of Sp1 (Figure <xref ref-type="fig" rid="F6">6B</xref>). In the following experiments, we have assessed the role of the three MAPkinases using their specific inhibitors in the activation of Sp1. Figure <xref ref-type="fig" rid="F7">7</xref> shows that PD98059, SB203580 and SP600125 alone did not influence the binding of Sp1 to the probe. However, in LPS-treated HAM, these three inhibitors decreased the activation of Sp1 induced by LPS.</p>
        <fig position="float" id="F7">
          <label>Figure 7</label>
          <caption>
            <p><bold>Sp1 binding activity in nuclear proteins of HAM</bold>. HAM were preincubated 1 h or not with inhibitors (50 μM for PD98059, SB203580 and SP600125 or 500 nM for mithramycin) and then stimulated with LPS (1 μg/ml) during 2 hours. Control HAM were HAM cultured with medium alone. Nuclear proteins were extracted as previously described and were then incubated in the binding buffer with specific labelled probe and then subjected to electrophoresis for separation of the complexes.</p>
          </caption>
          <graphic xlink:href="1465-9921-8-71-7"/>
        </fig>
      </sec>
      <sec>
        <title>Effects of MAPkinases and Sp1 inhibitors on IL-10 mRNA</title>
        <p>To further demonstrate the role of the MAPkinases and the Sp1 transcription factor in the production of IL-10, we performed quantitative assay of IL-10 mRNA using real-time PCR. This technique allows the precise quantification of mRNA using specific primers. Figure <xref ref-type="fig" rid="F8">8</xref> shows the relative quantification of IL-10 mRNA after different treatments. First, as positive control, LPS induced IL-10 mRNA production in HAM (Figure <xref ref-type="fig" rid="F8">8</xref>, panel A). Treatment of HAM with PD98059 (50 μM), SB203580 (50 μM), SP600125 (50 μM) or mithramycin (100 nM), decreased IL-10 mRNA induced by LPS. This inhibition is more pronounced for PD98059 (&gt;99% inhibition) and SB203580 (90% inhibition) inhibitors whereas mithramycin (75% inhibition) and SP600125 (45% inhibition) are less active.</p>
        <fig position="float" id="F8">
          <label>Figure 8</label>
          <caption>
            <p><bold>IL-10 mRNA in HAM stimulated with LPS</bold>. Panel A : HAM were preincubated 1 h with inhibitors (25 μM for PD98059, SB203580 and SP600125 or 100 nM for mithramycin) and then stimulated for 24 h with LPS. RNA was extracted as described in details in Materials and Methods. After reverse transcription, specific primers were used to amplify fragment of IL-10 mRNA and the relative abundance of IL-10 compared to β-actin is represented in the graph. Data are mean ± SD from 3 experiments; *p value &lt; 0.05 versus (One sample t test). Panel B: HAM were incubated with LPS (1 μg/ml) for 16 h, translation was stopped using Actinomycin D 2.5 μg/ml and inhibitors (PD98059 or SB203580, 25 μM) were added. IL-10 mRNA was assayed at different time points by real time PCR and corrected for β-actin mRNA.</p>
          </caption>
          <graphic xlink:href="1465-9921-8-71-8"/>
        </fig>
        <p>To assess a potential effect of PD and SB inhibitors on post-transcriptional mechanisms of regulation for IL-10 production, real time PCR for IL-10 mRNA was performed in HAM treated with Actinomycin D. Figure <xref ref-type="fig" rid="F8">8</xref>, panel B shows that both MAPK inhibitors did not affect significantly IL-10 mRNA degradation following LPS stimulation.</p>
      </sec>
    </sec>
    <sec>
      <title>Discussion</title>
      <p>Lung homeostasis relies on the equilibrium between the induction of efficient innate defensive responses to inhaled infectious microorganisms and equally effective mechanisms to downregulate the inflammatory response to initiate resolution and tissue repair. As a predominant immune effector cell in the airspaces, the alveolar macrophage is critical to these defence processes. Thus they produce a vast array of cytokines and inflammatory mediators in particular after LPS stimulation, including TNF-α and IL-10 as prototypic pro-inflammatory and anti-inflammatory cytokines, respectively. While the signaling events that mediate TNF-α in HAM have been extensively studied [<xref ref-type="bibr" rid="B20">20</xref>-<xref ref-type="bibr" rid="B23">23</xref>,<xref ref-type="bibr" rid="B19">19</xref>], those responsible for IL-10 production have not been well characterized.</p>
      <p>The present study is the first one showing that ERK, p38, JNK and Sp1 are involved and essential in LPS-induced IL-10 expression in HAM. These factors act at the transcriptional level, as IL-10 mRNA stability was not affected by MAPK inhibitors. It is well known that LPS drives intracellular signaling pathways such as MAPKs and NF-κB [<xref ref-type="bibr" rid="B23">23</xref>,<xref ref-type="bibr" rid="B24">24</xref>] to activate several pro-inflammatory genes including cyclooxygenase-2 [<xref ref-type="bibr" rid="B25">25</xref>], inducible nitric oxygen synthase [<xref ref-type="bibr" rid="B26">26</xref>], TNF-α and IL-1β [<xref ref-type="bibr" rid="B27">27</xref>]. In the present study, we found that in HAM the MAPK signaling pathways were also involved in LPS-induced gene activation of IL-10, a major anti-inflammatory factor. A recent study in murine macrophage raw 264.7 cells also reported that MAPKs were necessary in IL-10 expression by LPS [<xref ref-type="bibr" rid="B28">28</xref>] whereas other studies showed that only MAPK p38 was essential for IL-10 expression induced by LPS and other ligands [<xref ref-type="bibr" rid="B29">29</xref>-<xref ref-type="bibr" rid="B33">33</xref>]. Our study not only showed that all MAPKs were necessary but that they also played an important role in the downstream activation of Sp1 trancription factor.</p>
      <p>Sp1 is the founding member of a family of zinc finger transcription factors, which includes at least four Sp transcription factors [<xref ref-type="bibr" rid="B34">34</xref>,<xref ref-type="bibr" rid="B35">35</xref>]. Among the Sp transcription factors, Sp1 has been extensively studied [<xref ref-type="bibr" rid="B36">36</xref>] and is known to be widely expressed and to play a role in the regulation of a vast array of genes. Thus, while not excluding a role for other nuclear factors our data confirm previous studies showing that IL-10 gene expression is controlled by the transcription factor Sp1 [<xref ref-type="bibr" rid="B13">13</xref>,<xref ref-type="bibr" rid="B14">14</xref>,<xref ref-type="bibr" rid="B37">37</xref>] since mithramycin, an inhibitor of Sp1, almost completely abrogated LPS-induced IL-10 production at the mRNA and protein level. EMSA assay confirmed this observation as it showed that mithramycin decreased the activation of the nuclear protein Sp1 after LPS stimulation. Transfection of HAM by antisense oligonucleotides to Sp1 could not be used as another approach to confirm the role of Sp1 in IL-10 induction by LPS, as after the time period required to silence Sp1 expression (minimum 16–20 hrs) following 4 hrs-transfection, HAMs were not anymore responsive to LPS for IL-10 production (data not shown). Interestingly, inhibition of MAPKs by their specific inhibitors, also abolished LPS-induced Sp1 activation. These results are in accordance with previous studies [<xref ref-type="bibr" rid="B14">14</xref>,<xref ref-type="bibr" rid="B38">38</xref>-<xref ref-type="bibr" rid="B42">42</xref>] showing that Sp1 phosphorylation can be induced by ERK and p38 MAP kinases. In addition the present study also showed that JNK MAP kinase is also required for the activation of Sp1 induced by LPS. The three MAP kinases seem however to have different contributions to LPS-induced IL-10 in HAM, with a prominent role of p38 and ERK.</p>
      <p>IL-10 production by alveolar macrophages has been debated since some authors described the inability of alveolar macrophages to produce IL-10 [<xref ref-type="bibr" rid="B43">43</xref>-<xref ref-type="bibr" rid="B45">45</xref>]. Other investigators related this to a reduced production of IL-10 to allergic inflammation [<xref ref-type="bibr" rid="B46">46</xref>]. Our data clearly confirm IL-10 production by normal HAM [<xref ref-type="bibr" rid="B47">47</xref>-<xref ref-type="bibr" rid="B54">54</xref>], provide new information on the mechanisms involved in this production and complete the studies of Boehringer et al [<xref ref-type="bibr" rid="B18">18</xref>] who has studied the role of PP1 and PP2A in the regulation of LPS-induced IL-10 in HAM.</p>
    </sec>
    <sec>
      <title>Conclusion</title>
      <p>Our study demonstrates the contribution of MAP kinases to IL-10 expression in HAM upon endotoxin activation, indicating that ERK and p38 and to a lesser extent JNK are involved. In addition we show that ERK, p38 and JNK are able to trigger the phosphorylation of Sp1, the major transcription factor for the IL-10 gene. These findings are highly relevant to lung immunity, alveolar macrophages assuming front-line defense mechanisms and IL-10 representing a key factor for mucosal tolerance and resolution of inflammatory responses.</p>
    </sec>
    <sec>
      <title>Competing interests</title>
      <p>The author(s) declare that they have no competing interests.</p>
    </sec>
    <sec>
      <title>Authors' contributions</title>
      <p>HC supervised all the experiments, performed the data analysis and wrote the manuscript. AG carried out the experiments. CP was involved in the design of the study and in writing of the manuscript. YS was involved in the design of the study, writing of the manuscript and interpretation of the data. All authors read and approved the final manuscript.</p>
    </sec>
  </body>
  <back>
    <ack>
      <sec>
        <title>Acknowledgements</title>
        <p>The authors thank J.-P. Vaerman for gift of IgA. H.C. was Chargé de Recherche of the Belgian Fonds National de la Recherche Scientifique. This work was supported by the Belgian Fonds National de la Recherche Scientifique Médicale (grant N°3.4598.05F), by an FSR grant (N° 1324.2004) and by a grant from GSK.</p>
      </sec>
    </ack>
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</metadata></record><record><header><identifier>oai:pubmedcentral.nih.gov:2080633</identifier><datestamp>2007-11-17</datestamp><setSpec>bmcsb</setSpec><setSpec>pmc-open</setSpec></header><metadata><article xmlns="http://dtd.nlm.nih.gov/2.0/xsd/archivearticle" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://dtd.nlm.nih.gov/archiving/2.3/xsd/archivearticle.xsd" article-type="research-article">
  <front>
    <journal-meta>
      <journal-id journal-id-type="nlm-ta">BMC Struct Biol</journal-id>
      <journal-title>BMC Structural Biology</journal-title>
      <issn pub-type="epub">1472-6807</issn>
      <publisher>
        <publisher-name>BioMed Central</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="pmc">2080633</article-id>
      <article-id pub-id-type="publisher-id">1472-6807-7-55</article-id>
      <article-id pub-id-type="pmid">17725819</article-id>
      <article-id pub-id-type="doi">10.1186/1472-6807-7-55</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Dimerization of inositol monophosphatase <italic>Mycobacterium tuberculosis </italic>SuhB is not constitutive, but induced by binding of the activator Mg<sup>2+</sup></article-title>
      </title-group>
      <contrib-group>
        <contrib id="A1" equal-contrib="yes" contrib-type="author">
          <name>
            <surname>Brown</surname>
            <given-names>Alistair K</given-names>
          </name>
          <xref ref-type="aff" rid="I1">1</xref>
          <email>a.k.brown.1@bham.ac.uk</email>
        </contrib>
        <contrib id="A2" equal-contrib="yes" contrib-type="author">
          <name>
            <surname>Meng</surname>
            <given-names>Guoyu</given-names>
          </name>
          <xref ref-type="aff" rid="I1">1</xref>
          <xref ref-type="aff" rid="I4">4</xref>
          <email>ubcg54l@mail.cryst.bbk.ac.uk</email>
        </contrib>
        <contrib id="A3" equal-contrib="yes" contrib-type="author">
          <name>
            <surname>Ghadbane</surname>
            <given-names>Hemza</given-names>
          </name>
          <xref ref-type="aff" rid="I1">1</xref>
          <email>HXG597@bham.ac.uk</email>
        </contrib>
        <contrib id="A4" contrib-type="author">
          <name>
            <surname>Scott</surname>
            <given-names>David J</given-names>
          </name>
          <xref ref-type="aff" rid="I2">2</xref>
          <email>dj.scott@nottingham.ac.uk</email>
        </contrib>
        <contrib id="A5" contrib-type="author">
          <name>
            <surname>Dover</surname>
            <given-names>Lynn G</given-names>
          </name>
          <xref ref-type="aff" rid="I1">1</xref>
          <email>L.G.Dover@bham.ac.uk</email>
        </contrib>
        <contrib id="A6" contrib-type="author">
          <name>
            <surname>Nigou</surname>
            <given-names>Jérôme</given-names>
          </name>
          <xref ref-type="aff" rid="I3">3</xref>
          <email>jerome.nigou@ipbs.fr</email>
        </contrib>
        <contrib id="A7" corresp="yes" contrib-type="author">
          <name>
            <surname>Besra</surname>
            <given-names>Gurdyal S</given-names>
          </name>
          <xref ref-type="aff" rid="I1">1</xref>
          <email>G.Besra@bham.ac.uk</email>
        </contrib>
        <contrib id="A8" corresp="yes" contrib-type="author">
          <name>
            <surname>Fütterer</surname>
            <given-names>Klaus</given-names>
          </name>
          <xref ref-type="aff" rid="I1">1</xref>
          <email>K.Futterer@bham.ac.uk</email>
        </contrib>
      </contrib-group>
      <aff id="I1"><label>1</label>School of Biosciences, The University of Birmingham, Edgbaston, Birmingham B15 2TT, UK</aff>
      <aff id="I2"><label>2</label>National Centre for Macromolecular Hydrodynamics, School of Biosciences, University of Nottingham, Sutton Bonington, LE12 5RD, UK</aff>
      <aff id="I3"><label>3</label>Department of Molecular Mechanisms of Mycobacterial Infections, Institut de Pharmacologie et de Biologie Structurale, Centre National de la Recherche Scientifique Unité Mixte de Recherche 5089, Toulouse, France</aff>
      <aff id="I4"><label>4</label>Present address : School of Crystallography, Birkbeck College, Malet Street, London WC1E 7HX, UK</aff>
      <pub-date pub-type="collection">
        <year>2007</year>
      </pub-date>
      <pub-date pub-type="epub">
        <day>28</day>
        <month>8</month>
        <year>2007</year>
      </pub-date>
      <volume>7</volume>
      <fpage>55</fpage>
      <lpage>55</lpage>
      <ext-link ext-link-type="uri" xlink:href="http://www.biomedcentral.com/1472-6807/7/55"/>
      <history>
        <date date-type="received">
          <day>22</day>
          <month>6</month>
          <year>2007</year>
        </date>
        <date date-type="accepted">
          <day>28</day>
          <month>8</month>
          <year>2007</year>
        </date>
      </history>
      <permissions>
        <copyright-statement>Copyright © 2007 Brown et al; licensee BioMed Central Ltd.</copyright-statement>
        <copyright-year>2007</copyright-year>
        <copyright-holder>Brown et al; licensee BioMed Central Ltd.</copyright-holder>
        <license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/2.0">
          <p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/2.0"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>
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               Brown
               K
               Alistair
               
               a.k.brown.1@bham.ac.uk
            </dc:author><dc:title>
            Dimerization of inositol monophosphatase Mycobacterium tuberculosis SuhB is not constitutive, but induced by binding of the activator Mg2+
         </dc:title><dc:date>2007</dc:date><dcterms:bibliographicCitation>BMC Structural Biology 7(1): 55-. (2007)</dcterms:bibliographicCitation><dc:identifier type="sici">1472-6807(2007)7:1&#x0003c;55&#x0003e;</dc:identifier><dcterms:isPartOf>urn:ISSN:1472-6807</dcterms:isPartOf><License rdf:about="http://creativecommons.org/licenses/by/2.0"><permits rdf:resource="http://web.resource.org/cc/Reproduction" xmlns=""/><permits rdf:resource="http://web.resource.org/cc/Distribution" xmlns=""/><requires rdf:resource="http://web.resource.org/cc/Notice" xmlns=""/><requires rdf:resource="http://web.resource.org/cc/Attribution" xmlns=""/><permits rdf:resource="http://web.resource.org/cc/DerivativeWorks" xmlns=""/></License></Work></rdf>-->
        </license>
      </permissions>
      <abstract>
        <sec>
          <title>Background</title>
          <p>The cell wall of <italic>Mycobacterium tuberculosis </italic>contains a wide range of phosphatidyl inositol-based glycolipids that play critical structural roles and, in part, govern pathogen-host interactions. Synthesis of phosphatidyl inositol is dependent on free myo-inositol, generated through dephosphorylation of myo-inositol-1-phosphate by inositol monophosphatase (IMPase). Human IMPase, the putative target of lithium therapy, has been studied extensively, but the function of four IMPase-like genes in <italic>M. tuberculosis </italic>is unclear.</p>
        </sec>
        <sec>
          <title>Results</title>
          <p>We determined the crystal structure, to 2.6 Å resolution, of the IMPase <italic>M. tuberculosis </italic>SuhB in the apo form, and analysed self-assembly by analytical ultracentrifugation. Contrary to the paradigm of constitutive dimerization of IMPases, SuhB is predominantly monomeric in the absence of the physiological activator Mg<sup>2+</sup>, in spite of a conserved fold and apparent dimerization in the crystal. However, Mg<sup>2+ </sup>concentrations that result in enzymatic activation of SuhB decisively promote dimerization, with the inhibitor Li<sup>+ </sup>amplifying the effect of Mg<sup>2+</sup>, but failing to induce dimerization on its own.</p>
        </sec>
        <sec>
          <title>Conclusion</title>
          <p>The correlation of Mg<sup>2+</sup>-driven enzymatic activity with dimerization suggests that catalytic activity is linked to the dimer form. Current models of lithium inhibition of IMPases posit that Li<sup>+ </sup>competes for one of three catalytic Mg<sup>2+ </sup>sites in the active site, stabilized by a mobile loop at the dimer interface. Our data suggest that Mg<sup>2+</sup>/Li<sup>+</sup>-induced ordering of this loop may promote dimerization by expanding the dimer interface of SuhB. The dynamic nature of the monomer-dimer equilibrium may also explain the extended concentration range over which Mg<sup>2+ </sup>maintains SuhB activity.</p>
        </sec>
      </abstract>
    </article-meta>
  </front>
  <body>
    <sec>
      <title>Background</title>
      <p>The enzyme inositol monophosphatase (<italic>myo</italic>-inositol-1-phosphate phosphohydrolase, EC 3.1.3.25, IMPase) has attracted considerable scrutiny since the early 1980s. Then, it was discovered that low millimolar concentrations of Li<sup>+ </sup>inhibit IMPase-catalysed dephosphorylation of <italic>myo</italic>-inositol-1-phosphate [<xref ref-type="bibr" rid="B1">1</xref>], which could plausibly explain the marked decrease of <italic>myo</italic>-inositol in brain tissue following administration of lithium, a veteran therapeutic in manic depression treatment [<xref ref-type="bibr" rid="B2">2</xref>]. Inhibition of <italic>myo</italic>-inositol synthesis affects the phosphatidyl inositol second messenger pathway, which is linked to manic depression, and it is now widely accepted, though unproven, that IMPases constitute a major target of lithium therapy [<xref ref-type="bibr" rid="B3">3</xref>].</p>
      <p>The mycobacterial cell wall contains several lipid constituents based on the structure of phosphatidylinositol (PI), such as free PI, phosphatidylinositol-mannosides, lipomannan, and lipoarabinomannan [<xref ref-type="bibr" rid="B4">4</xref>]. In addition to their critical structural role, these lipids are significant as immunomodulatory factors in interactions of the tubercle bacillus with the host [<xref ref-type="bibr" rid="B5">5</xref>-<xref ref-type="bibr" rid="B7">7</xref>]. PI, an essential structural component, is synthesised by phosphatidylinositol synthase, <italic>M. tuberculosis </italic>PgsA, from CDP-diacylglycerol and <italic>myo</italic>-inositol [<xref ref-type="bibr" rid="B8">8</xref>]. In mycobacteria, the supply of <italic>myo</italic>-inositol to PI synthesis is thought to be maintained by <italic>de novo </italic>synthesis, which entails conversion of glucose-6-phosphate to inositol-1-phosphate, catalysed by inositol-1-phosphate synthase, and subsequent dephosphorylation of inositol-1-phosphate catalysed by an IMPase [<xref ref-type="bibr" rid="B9">9</xref>]. Thus, IMPase activity is a critical part of PI biosynthesis in mycobacteria. Indeed, growth of <italic>Mycobacterium smegmatis </italic>is accompanied by IMPase activity that dies off as growth reaches the stationary phase, while growth is retarded in the presence of lithium [<xref ref-type="bibr" rid="B10">10</xref>].</p>
      <p>The <italic>M. tuberculosis </italic>genome encodes four IMPase-like genes (Figure <xref ref-type="fig" rid="F1">1</xref>) [<xref ref-type="bibr" rid="B11">11</xref>,<xref ref-type="bibr" rid="B12">12</xref>], but little is known about the function of the corresponding proteins in terms of <italic>M. tuberculosis </italic>biology. The enzyme most closely related to human IMPase (25% identity), <italic>M. tuberculosis </italic>SuhB (Rv2701c), has been annotated as a 'putative extragenic suppressor protein' according to its homology to <italic>E. coli </italic>SuhB. The <italic>E. coli </italic>enzyme has been implicated in posttranscriptional control of gene expression [<xref ref-type="bibr" rid="B13">13</xref>], but no such function has to date been described for <italic>M. tuberculosis </italic>SuhB. According to the transposon mutagenesis study by Sassetti <italic>et al</italic>., Rv3137 is essential, SuhB is dispensable [<xref ref-type="bibr" rid="B14">14</xref>], and information on essentiality is as yet unavailable for CysQ and ImpA. <italic>In vitro </italic>analyses showed that <italic>M. tuberculosis </italic>CysQ hydrolyses inositol-1-phosphate, adenosine-monophosphate and fructose-1,6-bisphosphate [<xref ref-type="bibr" rid="B15">15</xref>]. In contrast, SuhB appears to be a <italic>bona fide </italic>IMPase with little or no activity towards fructose-1,6-bisphosphate. Still, SuhB also de-phosphorylates a series of polyol phosphates including glucitol-6-phosphate, glycerol-2-phosphate, and 2'-AMP, albeit with significantly reduced efficacy [<xref ref-type="bibr" rid="B12">12</xref>]. Like the human orthologue, SuhB is activated by Mg<sup>2+</sup>, and inhibited by lithium. Nevertheless, SuhB requires higher concentrations of Mg<sup>2+ </sup>for full activation (at ~6 mM), and activity persists over a much wider concentration range (~100 mM) of the activating ion before it becomes inhibitory [<xref ref-type="bibr" rid="B12">12</xref>]. In order to better understand potential functional differences between the mycobacterial and eukaryotic IMPases, we have determined the crystal structure of <italic>M. tuberculosis </italic>SuhB and characterised its self-assembly state in solution.</p>
      <fig position="float" id="F1">
        <label>Figure 1</label>
        <caption>
          <p><bold>Sequence comparison of <italic>M. tuberculosis </italic>IMPase-like proteins with human IMPase</bold>. Sequences were aligned based on the structural superimposition of SuhB and human IMPase using STRAP [53], and formatted using ESPript [54]. Secondary structure elements of SuhB are above the sequence, cylinders representing helices and arrows β-strands, coloured according to Fig. 2A. Full asterisks denote residues coordinating the catalytic Mg<sup>2+ </sup>sites, triangles indicate residues contacting inositol-1-phosphate in the simulated SuhB-substrate complex. Horizontal boxes indicate disordered parts of the sequence. The grey arrows indicate the positions of strands β1, β2 in the α1-α2 loop ('mobile loop') of human IMPase, with the open asterisk marking the critical lysine residue.</p>
        </caption>
        <graphic xlink:href="1472-6807-7-55-1"/>
      </fig>
    </sec>
    <sec>
      <title>Results</title>
      <sec>
        <title>Structure determination of SuhB</title>
        <p>The structure of M. tuberculosis SuhB was determined by molecular replacement to a resolution of 2.6 Å (Table <xref ref-type="table" rid="T1">1</xref>, Figure <xref ref-type="fig" rid="F2">2</xref>). The asymmetric unit of the crystal lattice contains three independent copies of the SuhB monomer forming two crystallographically distinct dimers: chains A and C associate as one dimer, whereas chain B forms an analogous dimer with one of its symmetry mates. The quality of the refined model is limited by several factors: first, a high Wilson B-factor (77.1 Å<sup>2</sup>) of the measured structure factor amplitudes is mirrored by a high average atomic displacement factor (78 Å<sup>2</sup>) (Table <xref ref-type="table" rid="T1">1</xref>); second, three disordered loop regions (see below) and mild disorder at either terminus leave 42 of 290 residues of the primary sequence unaccounted for (Figure <xref ref-type="fig" rid="F1">1</xref>); third, despite a nominal resolution of 2.6 Å and reasonably strong data in the high-resolution shell (Table <xref ref-type="table" rid="T1">1</xref>), structural details are less well defined by the (calculated) density than expected at this resolution. In order to counteract an unfavourable observables-to-parameter ratio, non-crystallographic symmetry (NCS) restraints were employed, leading to root mean square (RMS) deviations between NCS-related molecules of 0.05 Å for backbone and ≤ 0.42 Å for side chain atoms. Based on visual impression and real space R-factor, the electron density is best defined for subunits A and C, and worst for subunit B.</p>
        <table-wrap position="float" id="T1">
          <label>Table 1</label>
          <caption>
            <p>Crystallographic statistics</p>
          </caption>
          <table frame="hsides" rules="groups">
            <tbody>
              <tr>
                <td align="left">Beamline</td>
                <td align="left">ID14-2 (ESRF, Grenoble)</td>
              </tr>
              <tr>
                <td align="left">Wavelength (Å)</td>
                <td align="left">0.933</td>
              </tr>
              <tr>
                <td align="left">Space group</td>
                <td align="left"><italic>C</italic>222<sub>1</sub></td>
              </tr>
              <tr>
                <td align="left">Unit cell parameters</td>
                <td/>
              </tr>
              <tr>
                <td align="left">a, b, c (Å)</td>
                <td align="left">101.5, 185.4, 106.9</td>
              </tr>
              <tr>
                <td align="left">Resolution range (Å)</td>
                <td align="left">20–2.60 (2.69–2.60)<sup>a</sup></td>
              </tr>
              <tr>
                <td align="left">Unique reflections</td>
                <td align="left">30931 (3028)</td>
              </tr>
              <tr>
                <td align="left">Completeness (%)</td>
                <td align="left">98.7 (97.4)</td>
              </tr>
              <tr>
                <td align="left">&lt; I/σ(I) &gt;</td>
                <td align="left">24.5 (2.5)</td>
              </tr>
              <tr>
                <td align="left">Multiplicity</td>
                <td align="left">4.9 (3.8)</td>
              </tr>
              <tr>
                <td align="left">Rsym<sup>b </sup>(%)</td>
                <td align="left">6.8 (25.8)</td>
              </tr>
              <tr>
                <td align="left">Rcryst/Rfree<sup>c </sup>(%)</td>
                <td align="left">22.3/24.5</td>
              </tr>
              <tr>
                <td align="left">No. of non-hydrogen atoms</td>
                <td align="left">5466</td>
              </tr>
              <tr>
                <td align="left">Protein</td>
                <td align="left">5342</td>
              </tr>
              <tr>
                <td align="left">Solvent</td>
                <td align="left">124</td>
              </tr>
              <tr>
                <td align="left">Average B-factors (Å<sup>2</sup>)</td>
                <td align="left">78</td>
              </tr>
              <tr>
                <td align="left">Main chain – subunit A/B/C</td>
                <td align="left">68/89/72</td>
              </tr>
              <tr>
                <td align="left">Side-chain – subunit A/B/C</td>
                <td align="left">71/91/76</td>
              </tr>
              <tr>
                <td align="left">Solvent</td>
                <td align="left">81</td>
              </tr>
              <tr>
                <td align="left">Wilson B-factor</td>
                <td align="left">77.1</td>
              </tr>
              <tr>
                <td align="left">RMSD bonds (Å)</td>
                <td align="left">0.011</td>
              </tr>
              <tr>
                <td align="left">RMSD angles (°)</td>
                <td align="left">1.26</td>
              </tr>
              <tr>
                <td align="left">Ramachandran statistics<sup>d</sup></td>
                <td/>
              </tr>
              <tr>
                <td align="left">Core</td>
                <td align="left">91.4%</td>
              </tr>
              <tr>
                <td align="left">Allowed</td>
                <td align="left">7.9%</td>
              </tr>
              <tr>
                <td align="left">Generous</td>
                <td align="left">0.7%</td>
              </tr>
              <tr>
                <td align="left">Disallowed</td>
                <td align="left">None</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <p><sup>a </sup>Numbers in parenthesis refer to the outer resolution bin.</p>
            <p><sup>b </sup>Rsym = Σ<sub>h</sub>Σ<sub>i </sub>| I(h, i) - &lt; I(h) &gt;|/Σ<sub>h</sub>Σ<sub>i </sub>I(h, i), where I(h, i) is the intensity of the ith measurement of reflection h and &lt; I(h) &gt; is the mean value of I(h, i) for all i measurements.</p>
            <p><sup>c </sup>Rcryst = Σ<sub>hkl</sub>||Fo| - |Fc||/Σ |Fo|, where Fo is the observed structure-factor amplitude and Fc the calculated structure-factor amplitude. Rfree is calculated based on 5% of reflections not used in the refinement.</p>
            <p><sup>d </sup>The Ramachandran plot was calculated using <italic>PROCHECK </italic>[43]</p>
          </table-wrap-foot>
        </table-wrap>
        <fig position="float" id="F2">
          <label>Figure 2</label>
          <caption>
            <p><bold>Fold and crystal dimer of <italic>M. tuberculosis </italic>SuhB</bold>. (<bold>A</bold>) Stereo ribbon diagram of the SuhB monomer, with secondary structure elements coloured according to the penta-layered αβαβα-sandwich arrangement of IMPases (cf. Figure 1). (<bold>B</bold>) Dimer of SuhB formed by subunits A (blue, yellow) and C (lightblue, green). Selected secondary structure elements are labelled for ease of comparison with panel A. Grey spheres indicate boundaries of disordered loops, with corresponding residue numbers in black type. A (modelled) molecule of inositol-1-phosphate in ball-and-stick representation indicates the location of the active site(s) in both panels.</p>
          </caption>
          <graphic xlink:href="1472-6807-7-55-2"/>
        </fig>
        <p>Apart from minor discrepancies, the SuhB monomer is identical in fold to eukaryotic IMPases [<xref ref-type="bibr" rid="B16">16</xref>,<xref ref-type="bibr" rid="B17">17</xref>], with RMS deviations between Cα positions of superimposed backbone structures ranging from 1.09 Å to 1.15 Å (Table <xref ref-type="table" rid="T2">2</xref>). In order to more readily compare SuhB with related structures we denote secondary structure according to the recent report of the 1.4 Å-resolution structure of bovine IMPase (Figures <xref ref-type="fig" rid="F1">1</xref> and <xref ref-type="fig" rid="F2">2A</xref>) [<xref ref-type="bibr" rid="B17">17</xref>]. The IMPase fold is characterised by alternating layers of α-helices and β-sheets in an α-β-α-β-α sandwich arrangement (Figure <xref ref-type="fig" rid="F2">2A</xref>). Comparative studies established that IMPases share a structural scaffold with inositol polyphosphate-1-phosphatases (IPPases), fructose-1,6-biphosphatases (FBPases), 3'-phosphoadenosine-5'-phosphatases (PAPases) and 3'-phosphoadenosine-5'-phosphatase/inositol-1,4-bisphophatases (PIPases) (Table <xref ref-type="table" rid="T2">2</xref>), although on the amino acid sequence level the evolutionary relationship between these groups of enzymes is not obvious [<xref ref-type="bibr" rid="B18">18</xref>-<xref ref-type="bibr" rid="B20">20</xref>]. However, members of this super-family differ notably with respect to their assembly state: eukaryotic IPPases, PAPases and PIPases are monomeric [<xref ref-type="bibr" rid="B19">19</xref>,<xref ref-type="bibr" rid="B21">21</xref>,<xref ref-type="bibr" rid="B22">22</xref>], eukaryotic IMPases form homodimers as do a subset of dual activity IMPase/FBPases [<xref ref-type="bibr" rid="B16">16</xref>,<xref ref-type="bibr" rid="B17">17</xref>,<xref ref-type="bibr" rid="B23">23</xref>-<xref ref-type="bibr" rid="B25">25</xref>], whereas FBPases and the dual activity IMPase/FBPase of <italic>Thermotoga maritima </italic>form tetrameric assemblies [<xref ref-type="bibr" rid="B26">26</xref>,<xref ref-type="bibr" rid="B27">27</xref>].</p>
        <table-wrap position="float" id="T2">
          <label>Table 2</label>
          <caption>
            <p>Comparison of <italic>M. tuberculosis </italic>SuhB to selected members of the Mg<sup>2+</sup>-dependent/Li<sup>+</sup>-inhibited phosphomonoesterase family of proteins</p>
          </caption>
          <table frame="hsides" rules="groups">
            <thead>
              <tr>
                <td/>
                <td align="left" colspan="3">IMPase<sup>c</sup></td>
                <td align="left" colspan="2">FBPase</td>
                <td align="left" colspan="2">IMPase/FBPase</td>
                <td align="left">PAPase</td>
                <td align="left">IPPase</td>
                <td align="left">PiPase</td>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td align="left">PDB ID<sup>a</sup></td>
                <td align="left">
                  <ext-link ext-link-type="pdb" xlink:href="1IMA">1IMA</ext-link>
                </td>
                <td align="left">
                  <ext-link ext-link-type="pdb" xlink:href="2CZH">2CZH</ext-link>
                </td>
                <td align="left">
                  <ext-link ext-link-type="pdb" xlink:href="2BJI">2BJI</ext-link>
                </td>
                <td align="left">
                  <ext-link ext-link-type="pdb" xlink:href="1FBP">1FBP</ext-link>
                </td>
                <td align="left">
                  <ext-link ext-link-type="pdb" xlink:href="1DCU">1DCU</ext-link>
                </td>
                <td align="left">
                  <ext-link ext-link-type="pdb" xlink:href="1LBV">1LBV</ext-link>
                </td>
                <td align="left">
                  <ext-link ext-link-type="pdb" xlink:href="1DK4">1DK4</ext-link>
                </td>
                <td align="left">
                  <ext-link ext-link-type="pdb" xlink:href="1QGX">1QGX</ext-link>
                </td>
                <td align="left">
                  <ext-link ext-link-type="pdb" xlink:href="1INP">1INP</ext-link>
                </td>
                <td align="left">
                  <ext-link ext-link-type="pdb" xlink:href="1JP4">1JP4</ext-link>
                </td>
              </tr>
              <tr>
                <td colspan="11">
                  <hr/>
                </td>
              </tr>
              <tr>
                <td align="left">RMSD (Å)</td>
                <td align="left">1.09 (197)<sup>b</sup></td>
                <td align="left">1.12 (199)</td>
                <td align="left">1.15 (193)</td>
                <td align="left">1.61 (159)</td>
                <td align="left">1.88 (138)</td>
                <td align="left">1.23 (177)</td>
                <td align="left">1.13 (158)</td>
                <td align="left">1.28 (190)</td>
                <td align="left">1.41 (166)</td>
                <td align="left">1.40 (182)</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <p><sup>a</sup>References for the pdb entries cited in this table are provided in the supplementary information [see Additional file <xref ref-type="supplementary-material" rid="S3">3</xref>].</p>
            <p><sup>b</sup>Number of aligned Cα positions.</p>
            <p><sup>c</sup>IMPase (inositol-1-monophosphatase), FBP (fructose-1,6-bisphosphatase), PAPase (3'-phosphoadenosine-5'-phosphatase), IPPase (inositol-polyphosphate-1-phosphatase), PIPase (inositol-polyphosphate-1-phosphatase and 3'-phosphoadenosine-5'-phosphate phosphatase)</p>
          </table-wrap-foot>
        </table-wrap>
        <p>Eukaryotic adenosine-monophosphate (AMP)-regulated FBPases have been described in terms of two sub-domains. In this description, layers I and II of the α-β-α-β-α sandwich are equivalent to the AMP-binding sub-domain of porcine FBPase, and layers III to V correspond to the fructose-1,6-bisphosphate binding sub-domain (Figure <xref ref-type="fig" rid="F2">2A</xref>) [<xref ref-type="bibr" rid="B26">26</xref>]. The primary sequence runs sequentially through layers I and II of the 'AMP-binding' sub-domain, but meanders in the fructose-1,6-bisphosphate-binding sub-domain between layers III-V, with helices and strands alternating. This pattern is interrupted only for strands β12 and β13, which are not separated by a helix (Figures <xref ref-type="fig" rid="F1">1</xref>, <xref ref-type="fig" rid="F2">2A</xref>). The dimer observed in the crystal structure of SuhB is primarily mediated by helices α6 in layer V and the β-sheet in layer IV, which extends across the interface (Figure <xref ref-type="fig" rid="F2">2B</xref>). In contrast, strands in the sheet of layer II are oriented perpendicular to the plane of the dimer interface.</p>
        <p>Due to the absence of divalent metal ions and of substrate in the active site, the loop connecting helices α1 and α2 is disordered (residues 35–53 missing), as is much of the loop connecting strands β3 and β4 (residues 85–96 missing). Both features are consistent with the structure of the <italic>apo </italic>form of human IMPase (pdb entry <ext-link ext-link-type="pdb" xlink:href="1IMF">1IMF</ext-link>, [<xref ref-type="bibr" rid="B28">28</xref>]). Soaks of SuhB crystals in Mg<sup>2+</sup>- or Mn<sup>2+</sup>-containing cryoprotection buffers failed to induce ordering, or give rise to density peaks associated with metals sites known from the eukaryotic orthologues, which we attribute to the acidic pH (4.1–4.5) of the crystallisation buffer. Further disorder was seen in the hairpin loop connecting strands β12 and β13 (residues 254–259) in layer IV, while density for the β9-α6 loop was disjointed, yet indicating that the conformation of the loop between residues 183 and 186 differed markedly between subunits. As a consequence, side chains for residues Tyr183, Val185, Arg186 and Cys187 in this loop could not be built.</p>
      </sec>
      <sec>
        <title>Active Site</title>
        <p>The active site of SuhB is situated in a cavity carved out at the N-terminal end of helix α7, sandwiched between layers II and IV (Figure <xref ref-type="fig" rid="F2">2A</xref>). Due to the disordered α1-α2 loop – referred to as the 'mobile loop' [<xref ref-type="bibr" rid="B27">27</xref>] – the active site in SuhB appears wide open to solvent. Yet, it is anticipated that the α1-α2 loop will become ordered upon the enzyme binding metal ions and substrate. In this state the active site is anticipated to be effectively shielded from solvent, as is the case in the ligand-bound structure of human IMPase [<xref ref-type="bibr" rid="B29">29</xref>]. In SuhB, the α1-α2 loop has a 10-residue insertion relative to human IMPase (Figure <xref ref-type="fig" rid="F1">1</xref>). Hence, the exact conformation of this loop in the ordered state may well deviate from that of the human enzyme. Interestingly, alternative secondary structure conformations of this loop were observed within the tetramer of the structure of <italic>Thermotoga maritima </italic>IMPase/FBPase TM1415. While the mobile loop included a short helix in two subunits of the tetramer, it assumed a β-hairpin conformation in the other two subunits [<xref ref-type="bibr" rid="B27">27</xref>]. The mobile loop includes a lysine residue at position 36 (corresponding to residue 49 in SuhB, marked by I in Figure <xref ref-type="fig" rid="F1">1</xref>) that stabilizes the third of three catalytic metal sites through hydrogen bonds to two ordered water molecules. In SuhB, this lysine is conserved and parallels in the characteristics of Li<sup>+ </sup>inhibition between SuhB and human IMPase (see Discussion) suggest an equivalent pattern of interactions in the mycobacterial enzyme.</p>
        <p>Structural elements of the active site required for metal and substrate binding include the IMPase signature motif <sup>104</sup>DPXDGT<sup>109 </sup>(superscripts denote residue numbers of the SuhB sequence) between strand β4 and helix α4, the <sup>82</sup>GEEG<sup>85 </sup>motif at the 'tip' of the β3-β4 loop, the <sup>209</sup>G [ST]AA<sup>212 </sup>motif in the β10-α7 loop, in addition to Glu228 in β11 and the <sup>234</sup>WDXA<sup>237 </sup>motif in helix α8. All elements contributing to metal site coordination are contained within one subunit of the dimeric assembly. Compelling evidence for three sites occupied by Mg<sup>2+ </sup>was provided only recently by the 1.4 Å-structure of bovine IMPase [<xref ref-type="bibr" rid="B17">17</xref>]. This study, in conjunction with preceding structural studies on lithium-sensitive PAPase and lithium-insensitive IMPase/FBPases [<xref ref-type="bibr" rid="B21">21</xref>,<xref ref-type="bibr" rid="B24">24</xref>,<xref ref-type="bibr" rid="B25">25</xref>,<xref ref-type="bibr" rid="B27">27</xref>], provided strong support for a 3-metal catalytic reaction mechanism. When mapped onto the structure of SuhB, these three magnesium ion sites are coordinated by Glu83 (equivalent to residue 70 in human/bovine IMPase: h_70), Asp104 (h_90), Asp107 (h_93), Asp235 (h_220), in addition to the carbonyl of Ile106 (h_92). In a previous study we had shown that mutations to these sites in SuhB reduced activity dramatically [<xref ref-type="bibr" rid="B12">12</xref>]. Likewise, when activity was tested in the presence of various divalent cations, Mg<sup>2+ </sup>was the most potent activator of SuhB. These data and the high level of sequence conservation among active site residues justify the attempt to construct a model of inositol-1-phosphate in the active site of SuhB (Figure <xref ref-type="fig" rid="F3">3A</xref>) and to analyse potential differences in substrate-enzyme contacts.</p>
        <fig position="float" id="F3">
          <label>Figure 3</label>
          <caption>
            <p><bold>Stereo views of the active site</bold>. (<bold>A</bold>) Active site of subunit A of SuhB, with metal sites (beige) and inositol-1-phosphate (coloured by atom type, carbons in light grey) modelled based on superimposition with the structures of bovine (PDB:<ext-link ext-link-type="pdb" xlink:href="2BJI">2BJI</ext-link>, [17]) and human IMPase (PDB:<ext-link ext-link-type="pdb" xlink:href="1IMA">1IMA</ext-link>, [29]). Residues in contact with metal sites and substrate in the modelled complex are shown as sticks and numbered according to the SuhB sequence. Secondary structure elements are coloured as in Figure 2A. The loop in violet indicates the approximate position of the α1-α2 loop, based on the superposition with PDB:<ext-link ext-link-type="pdb" xlink:href="1IMA">1IMA</ext-link> [29]. (<bold>B</bold>) Bias-free difference density map of the β9-α6 loop in SuhB, calculated after simulated annealing of the model with residues 178–188 deleted and contoured at 2σ. The density is superimposed with <italic>apo </italic>SuhB (blue sticks) and human IMPase in complex with inositol-1-phosphate (light green, PDB:<ext-link ext-link-type="pdb" xlink:href="1IMA">1IMA</ext-link>, [29]). Putative (grey) and experimental (red) contact distances with substrate are indicated. (<bold>C</bold>) Active site of subunit C of SuhB with σ<sub>A</sub>-weighted Fo-Fc map contoured at 3σ, showing unexplained density around the putative substrate position and metal site 1.</p>
          </caption>
          <graphic xlink:href="1472-6807-7-55-3"/>
        </fig>
        <p>In our model of the SuhB-substrate complex, the phosphate moiety is positioned at the N-terminal end of helix α4, the helix dipole countering the charge of the phosphate (Figure <xref ref-type="fig" rid="F3">3A</xref>). Most contacts between enzyme and phosphate are through the three Mg<sup>2+ </sup>ions, with contact distances in the order of 2.15–2.3 Å, in agreement with the experimental structures of the eukaryotic IMPases [<xref ref-type="bibr" rid="B17">17</xref>,<xref ref-type="bibr" rid="B28">28</xref>,<xref ref-type="bibr" rid="B29">29</xref>]. In addition, the phosphate forms H-bond interactions with the amide nitrogen of Gly108 (h_94) and Thr109 (h_95) at the N-terminus of helix α4. The inositol moiety packs primarily against residues in the β9-α6 and β10-α7 loops with specificity-determining contacts provided by Glu228 (h_213) in strand β11, and Asp107 (h_93) in the β4-α4 loop (Figure <xref ref-type="fig" rid="F3">3A</xref>). All conserved side chains forming the metal binding sites or contacting inositol-1-phosphate are seen in essentially the same conformation as in the human/bovine enzyme, with the exception of Glu83: as a consequence of disorder in a large part of the β3-β4 loop, Glu83 (h_70) in subunit A points outward rather into the active site (Figure <xref ref-type="fig" rid="F3">3A</xref>).</p>
        <p>Significant discrepancies between the <italic>M. tuberculosis </italic>and the human enzyme are seen in the β9-α6 loop, which in human IMPase provides a contact surface, but no specificity-determining interactions with the inositol ring [<xref ref-type="bibr" rid="B29">29</xref>] (Figure <xref ref-type="fig" rid="F3">3B</xref>). The β9-α6 loop in SuhB is two residues shorter than in the human enzyme with weak sequence conservation (Figure <xref ref-type="fig" rid="F1">1</xref>). Although poorly ordered between residues 183–186, residues in proximity to the putative position of the inositol ring – Gly180, Phe181 and Gly182 – are well defined by density (Figure <xref ref-type="fig" rid="F3">3B</xref>). Interestingly, the carbonyl oxygen of Phe181 falls within H-bonding distance range of the C3 (2.9 Å) and C4 (3.3 Å) hydroxyls of the inositol ring, suggesting that the β9-α6 of SuhB may form specificity-determining contacts to the substrate that are not present in the human enzyme.</p>
        <p>A surprising observation was a patch of unexplained density in the active site that overlaps significantly with the modelled position of inositol-1-phosphate, while a second density peak coincides with the metal site 1 (Figure <xref ref-type="fig" rid="F3">3C</xref>) (in the numbering of ref. [<xref ref-type="bibr" rid="B17">17</xref>]). The latter is situated between the carbonyl oxygen of Ile106 and the carboxylate of Asp104 and corresponds to the high-affinity metal site [<xref ref-type="bibr" rid="B17">17</xref>]. The 'metal site 1' peak was present in all three active sites, whereas the density for the inositol-1-phosphate site was best defined in subunit C (Figure <xref ref-type="fig" rid="F3">3C</xref>). We consider it likely that the observed density represents a weakly-bound molecule of octyl β-D-glucopyranoside, a reagent used as an additive during crystallisation. Whether or not the density peak a metal site 1 represents a divalent cation could not be verified.</p>
      </sec>
      <sec>
        <title>Dimer interface and assembly state</title>
        <p>The present crystal structure comprises two apparent dimers of SuhB. One dimer is formed between the NCS-related subunits A and C, while the second dimer results from crystallographic symmetry, pairing two symmetry-related copies of subunit B. As a result of NCS restraints applied during the refinement no substantial difference between the two independent dimers is observed at the interface. The SuhB dimers also superimpose closely with the dimers of the human and bovine IMPase enzymes, whereby the dimer interface is formed by analogous secondary structure elements. These include helix α6, the strand β10, the β9-α 6 loop, helix α4, and the β10-α7 and α7-β11 loops. In the superposition, which is based on secondary structure matching, helices α6 of the two protomers are positioned opposite to each other (Figures <xref ref-type="fig" rid="F2">2B</xref>, <xref ref-type="fig" rid="F4">4A</xref>), contributing approximately 30% of the buried surface area (per monomer). It seems noteworthy that in SuhB the axes of these two helices are spaced 7.5 Å apart whereas in the eukaryotic enzymes that spacing is approximately 10 Å (Figure <xref ref-type="fig" rid="F4">4A</xref>). The discrepancy can be attributed to alanine residues 192 and 196 being positioned at the centre of this interface (Figure <xref ref-type="fig" rid="F4">4B</xref>), while the side chains of a leucine at position 176 occupy the corresponding space in human IMPase.</p>
        <fig position="float" id="F4">
          <label>Figure 4</label>
          <caption>
            <p><bold>Analysis of dimer interface</bold>. (<bold>A</bold>) Helices α6 after superimposition of the dimers of human IMPase (cyan) and SuhB (red) by secondary structure matching. The spacing of the helix axes is indicated in units of Å and the black oval indicates the position of the non-crystallographic 2-fold axis mapping the subunits onto each other. (<bold>B</bold>) The helix α6 interface in <italic>SuhB </italic>with side chains contributing to the contact surface indicated as sticks in cyan (subunit A) and yellow (subunit C). (<bold>C</bold>) Contact surface (magenta) of subunit A calculated and visualised using Swiss PDB Viewer [50]. The active site indicated by a molecule of inositol-1-phosphate (yellow sticks).</p>
          </caption>
          <graphic xlink:href="1472-6807-7-55-4"/>
        </fig>
        <p>The interface of the SuhB dimer buries a total of 2696 Å<sup>2 </sup>of solvent accessible surface, calculated using the <italic>PISA </italic>interface server [<xref ref-type="bibr" rid="B30">30</xref>,<xref ref-type="bibr" rid="B31">31</xref>], or 1348 Å<sup>2 </sup>per monomer. In terms of buried surface area hydrophobic interactions clearly dominate over H-bonds (12 contacts). Although the residues located at the interface include a number of polar and charged side chains (Figure <xref ref-type="fig" rid="F4">4C</xref>) only one ionic interaction is seen. In human IMPase distinctly more solvent accessible surface is buried in the interface (1675 Å<sup>2 </sup>per monomer). Contacts across the interface include 11 ionic interactions, while the number of H-bonds (13) is about the same as in SuhB. One factor explaining the difference in size of the interface, at least in part, is the disordered 'mobile loop' in SuhB. In the <italic>apo </italic>structure of human IMPase (<ext-link ext-link-type="pdb" xlink:href="1IMF">1IMF</ext-link> – [<xref ref-type="bibr" rid="B29">29</xref>]), the α1-α2 loop is also disordered, reducing the total of buried solvent accessible surface per monomer from 1675 Å<sup>2 </sup>to 1571 Å<sup>2</sup>. Thus disorder of this loop accounts partially for the observed discrepancy.</p>
        <p>The analysis of the dimer interface using the <italic>PISA </italic>server suggested that dimerisation of SuhB might not be constitutive. Based on molecular contacts at the interface, <italic>PISA </italic>calculates a 'complexation significance score' (CSS) that on a scale from 0 to 1 indicates the probability that a packing interface generated by crystal symmetry might represent a 'real' interface [<xref ref-type="bibr" rid="B31">31</xref>]. The CSS for the dimer interface of SuhB is 0.1, compared to a score of 1.0 for the dimer interface of human IMPase (with or without the α1-α2 loop in the ordered state), suggesting that dimerisation was merely due to crystal packing. We analysed self-association of SuhB by analytical ultracentrifugation (AUC) in sedimentation velocity mode. To our surprise, but consistent with the prediction by <italic>PISA</italic>, we found that SuhB is predominantly monomeric, with the peak at molecular weight 30,508 Da closely matching the calculated mass of the SuhB monomer (Figure <xref ref-type="fig" rid="F5">5</xref>). However, with increasing protein concentration a second peak at molecular weight of 54,160 Da appears, and this peak becomes more pronounced, at the expense of the main peak, when 1 mM Mg<sup>2+ </sup>is added to the buffer (Figure <xref ref-type="fig" rid="F5">5</xref>). We verified by SDS gel electrophoresis that the preparation of SuhB used in this experiment did not contain a contaminant that could explain the peak at 54,160 Da (data not shown).</p>
        <fig position="float" id="F5">
          <label>Figure 5</label>
          <caption>
            <p><bold>Analytical ultracentrifugation in sedimentation velocity mode demonstrates that SuhB is monomeric in the absence of Mg<sup>2+</sup></bold>. Main panel: Traces of the molecular weight distribution of <italic>M. tuberculosis </italic>SuhB in a sedimentation velocity experiment. Conditions analysed were 0.5 mg.ml<sup>-1 </sup>SuhB (solid triangle), 1.0 mg.ml<sup>-1 </sup>SuhB (open triangle),1.0 mg.ml<sup>-1 </sup>SuhB + 1 mM Mg<sup>2+ </sup>(open circle). The main peak is centred at 30,508 Da, the secondary peak at 54,160 Da. Inset: enlarged view of the region between 40,000 and 80,000 Da. Samples were centrifuged at 40,000 rpm, 4°C, for a minimum of 12 hours, in 20 mM Tris-HCl pH 7.9, 50 mM NaCl and MgCl<sub>2 </sub>as indicated.</p>
          </caption>
          <graphic xlink:href="1472-6807-7-55-5"/>
        </fig>
        <p>These data suggested that SuhB, at protein concentrations in the order of 1 mg.ml<sup>-1</sup>, exists in a monomer-dimer equilibrium, but that Mg<sup>2+</sup>, which is required for activity, might shift self assembly to the dimer state. The underestimate in molecular weight of the dimer peak is due to the fitting of a single frictional coefficient to two species that have differing frictional ratios. In addition, the appearance of two separate peaks in the molecular weight profile with increasing concentration indicates that the off-rate for dimerisation is slow compared with the time of sedimentation. Values for the off-rate for this regime are therefore estimated to be 10<sup>-5 </sup>&lt; k<sub>off </sub>&lt; 10<sup>-3 </sup>[<xref ref-type="bibr" rid="B32">32</xref>]. Analysing the sedimentation velocity of SuhB in the presence of increasing concentrations of Mg<sup>2+</sup>, confirmed that in the absence of Mg<sup>2+ </sup>the monomer form is strongly preferred (Figure <xref ref-type="fig" rid="F6">6A</xref>). Yet, as Mg<sup>2+ </sup>increases in concentration (at a protein concentration of 1.0 mg.ml<sup>-1</sup>) two features are observed: first, the dimer peak increases in height, at the expense of the monomer peak; second, the monomer and dimer peaks shift towards each other until, at 5 mM Mg<sup>2+</sup>, a broad skewed distribution of the sedimentation coefficient is observed (Figure <xref ref-type="fig" rid="F6">6A</xref>), suggesting a gradual transition from slow to fast exchange between the two assembly states due to an increase in the off-rate of dimerisation. Increasing the concentration of Mg<sup>2+ </sup>further, the dimer peak eventually becomes the dominant species in the c(<italic>S</italic>) distribution (Figure <xref ref-type="fig" rid="F6">6A</xref>).</p>
        <fig position="float" id="F6">
          <label>Figure 6</label>
          <caption>
            <p><bold>Dimerization of SuhB is induced by Mg<sup>2+</sup>, or Mg<sup>2+ </sup>and Li<sup>+</sup>, but not by Li<sup>+ </sup>alone</bold>. Traces of the sedimentation coefficient distribution recorded in sedimentation velocity experiments of <italic>M. tuberculosis </italic>SuhB. SuhB was at 1.0 mg.ml<sup>-1 </sup>in 20 mM Tris-HCl pH 7.9, 50 mM NaCl, plus MgCl<sub>2 </sub>or LiCl as indicated. Samples were centrifuged at 40,000 rpm at 4°C for at least 12 hours. The peak at 1.6 <italic>S </italic>corresponds to a molecular weight of 30,147 Da, the peak at 2.5 <italic>S </italic>corresponds to 50,116 Da.</p>
          </caption>
          <graphic xlink:href="1472-6807-7-55-6"/>
        </fig>
        <p>Next, we examined whether the inhibitor Li<sup>+ </sup>influenced dimerization. At an enzyme concentration of 1.0 mg.ml<sup>-1 </sup>and in the presence of 5 mM Mg<sup>2+</sup>, increasing concentrations of Li<sup>+ </sup>amplify the effect of Mg<sup>2+</sup>-induced dimerization, with the dimer peak becoming dominant over the monomer peak (Figure <xref ref-type="fig" rid="F6">6B</xref>). However on its own Li<sup>+ </sup>promotes dimerization only very weakly, if at all (Figure <xref ref-type="fig" rid="F6">6B</xref>). Furthermore the c(<italic>S</italic>) distribution obtained for 15 mM Mg<sup>2+ </sup>matches almost perfectly the one obtained in presence of 5 mM Mg<sup>2+ </sup>and 5 mM Li<sup>+</sup>. Calcium, which binds to IMPase on identical sites as Mg<sup>2+</sup>, but does not activate, strongly promotes dimerization, while EDTA reverses Mg<sup>2+</sup>-induced dimerization [see Additional file <xref ref-type="supplementary-material" rid="S1">1</xref>].</p>
      </sec>
    </sec>
    <sec>
      <title>Discussion</title>
      <p>The present crystal structure of <italic>M. tuberculosis </italic>SuhB confirms a highly conserved structural scaffold of IMPases in mycobacteria with respect to overall fold and active site geometry, in spite of a low level of overall sequence identity (25%) relative to human IMPase. The structural similarity correlates with similar biochemical characteristics – activation by magnesium, inhibition by lithium, specificity for inositol-1-phosphate and exclusion of fructose-1,6-bisphosphate as a substrate. It has been noted previously that the Mg<sup>2+</sup>-dependence of IMPase activity of SuhB resembles more closely that of the thermophilic species <italic>Thermotoga maritima</italic>, <italic>Archeoglobus fulgidus </italic>and <italic>Methanococcus jannaschii </italic>[<xref ref-type="bibr" rid="B12">12</xref>,<xref ref-type="bibr" rid="B25">25</xref>,<xref ref-type="bibr" rid="B33">33</xref>,<xref ref-type="bibr" rid="B34">34</xref>] in that activation is maintained over a concentration range of Mg<sup>2+ </sup>in the order of 100 mM, whereas in eukaryotic IMPases Mg<sup>2+ </sup>becomes inhibitory above 5 mM. Such comparison ignores, however, that unlike these thermophilic enzymes SuhB does not hydrolyze fructose-1,6-bisphosphate, and remains sensitive to Li<sup>+ </sup>(IC<sub>50 </sub>0.9 mM, [<xref ref-type="bibr" rid="B12">12</xref>]). Given that the active site of SuhB, in its 'non-mobile' part, displays the same highly conserved framework of side chains coordinating the three metal sites as the eukaryotic orthologues, we postulate that differences in Mg<sup>2+</sup>-dependence of activity between SuhB and eukaryotic IMPases must be linked on the one hand to structural differences in the mobile α1-α2 loop, and secondly to the apparent link between Mg<sup>2+</sup>-driven dimerization and activation of SuhB. In IMPases and the tetrameric IMPase/FBPases the α1-α2 loop, when ordered, stabilizes the third of the three catalytic metal sites through bridging water molecules [<xref ref-type="bibr" rid="B17">17</xref>,<xref ref-type="bibr" rid="B25">25</xref>,<xref ref-type="bibr" rid="B29">29</xref>]. The α1-α2 loop contributes significantly to the dimer interface. This is apparent when comparing the buried solvent-accessible surface in the dimer interface of human IMPase between the ordered and disordered state of the mobile loop. Thus, we anticipate that ordering of the α1-α2 loop in SuhB, which is 10 residues longer compared to human IMPase, will expand the dimer interface and help stabilize the dimer state. While SuhB is driven to the dimer state at high protein concentrations in the absence of metal ions, as was the case during crystallization, it is evident that Mg<sup>2+ </sup>strongly promotes dimerization at low concentrations. Lithium amplifies the Mg<sup>2+</sup>-induced effect, yet Li<sup>+ </sup>alone does not noticeably shift the monomer dimer equilibrium. These observations correlate with the characteristics of metal binding in the active site, which is known to promote ordering of the α1-α2 loop. According to <sup>7</sup>Li-NMR binding data, lithium occupies a single site per monomer in IMPase [<xref ref-type="bibr" rid="B35">35</xref>], and various indirect evidence points to Li<sup>+ </sup>displacing Mg<sup>2+ </sup>from either site 2 or site 3 [<xref ref-type="bibr" rid="B17">17</xref>,<xref ref-type="bibr" rid="B21">21</xref>,<xref ref-type="bibr" rid="B36">36</xref>,<xref ref-type="bibr" rid="B37">37</xref>]. A lysine residue in the mobile loop (Lys36 in human, open asterisk in Figure <xref ref-type="fig" rid="F1">1</xref>) that coordinates the third metal site via hydrogen bonds to bridging water molecules has been shown to critically influence Li<sup>+</sup>-sensitivity [<xref ref-type="bibr" rid="B37">37</xref>], and this lysine is conserved in SuhB (Lys49). Given that the α1-α2 loop is disordered, the present structure leaves open the precise geometry of this loop in the ordered state and whether Lys49 in SuhB coordinates the third metal site. Yet, lithium sensitivity of SuhB (IC<sub>50 </sub>0.9 mM, [<xref ref-type="bibr" rid="B12">12</xref>]), the debilitating effect on activity of the W234A mutation, and the loss of Li+ inhibition through the L81A mutation [<xref ref-type="bibr" rid="B12">12</xref>] – a mutation that removes a stabilising hydrophobic contact to the conserved Trp234 in the active site – hint that metal binding induces ordering of the α1-α2 loop in SuhB in a similar fashion as in the eukaryotic orthologues.</p>
      <p>Previously, size exclusion chromatography experiments with 1 mM EDTA present in the buffer had indicated that <italic>E. coli </italic>SuhB formed monomers and it had been inferred that the <italic>E. coli </italic>enzyme was active in the monomeric form [<xref ref-type="bibr" rid="B13">13</xref>]. The parallels between metal-dependent self-association and enzymatic activation in <italic>M. tuberculosis </italic>SuhB strongly suggest that dimerization is linked to loading of the three metal sites in the active site, and that phosphatase activity occurs in the dimer state, although we are not in a position to determine whether dimerization is required for activity. If dimerization were required for enzymatic activity of SuhB, this would at least in part explain the wide range of Mg<sup>2+ </sup>concentrations over which activity is maintained, as the transition to the dimer state is not complete up to at least 15 mM Mg<sup>2+</sup>. Several <italic>caveats </italic>go with this rationale. First, the comparison of the activity and AUC data is complicated by the fact that metal binding is cooperative with substrate binding [<xref ref-type="bibr" rid="B38">38</xref>] and inositol-1-phosphate was not present in the AUC experiments. Also, while dimerisation appears to correlate with loading of the metal positions in the active site, we cannot rule out the possibility that the dimer interface contains one or more metal binding sites, which could drive dimerisation. However, the present structure, in line with related IMPases, and a series of metal-soaking experiments with SuhB crystals provided no indication for such a site (data not shown).</p>
      <p>Crystal structures of eukaryotic IMPases, a refolding study and AUC analysis of human IMPase 2, in the absence of Mg<sup>2+</sup>, consistently indicate constitutive dimerization of the eukaryotic orthologue [<xref ref-type="bibr" rid="B16">16</xref>,<xref ref-type="bibr" rid="B17">17</xref>,<xref ref-type="bibr" rid="B23">23</xref>,<xref ref-type="bibr" rid="B39">39</xref>]. It is not clear what mechanistic purpose dimerization serves with respect to the enzymatic properties of IMPases, and why dimerization should be constitutive in eukarya, but not in bacteria. Unlike the tetrameric FBPases, which are regulated by an allosteric mechanism involving changes in the relative orientation of the subunits in the tetramer (see [<xref ref-type="bibr" rid="B40">40</xref>] and references therein), no regulatory mechanism for IMPase has been reported that invokes dimerization of the enzyme. Nevertheless, Mg<sup>2+ </sup>has been shown to moderately enhance thermal stability of <italic>M. tuberculosis </italic>SuhB, which correlates to some extent with phosphohydrolase activity of SuhB peaking at about 80°C [<xref ref-type="bibr" rid="B12">12</xref>]. While this latter property is mirrored by <italic>E. coli </italic>SuhB [<xref ref-type="bibr" rid="B13">13</xref>] and <italic>M. tuberculosis </italic>CysQ [<xref ref-type="bibr" rid="B15">15</xref>] it has not been tested whether at such high temperatures SuhB still discriminates between substrates. Thus, while dimerization may increase thermal stability, the functional role of Mg<sup>2+</sup>-induced dimerization of SuhB in the physiological regime of the tubercle bacillus is not clear.</p>
      <sec>
        <title>SuhB – a template for the other M. tuberculosis IMPases?</title>
        <p>The IMPase-like genes in M. tuberculosis display considerable sequence diversity relative to each other. In the multiple sequence alignment (Figure <xref ref-type="fig" rid="F1">1</xref>), SuhB and Rv3137 align with 30% sequence identity, while ImpA and CysQ score significantly lower (= 23%) relative to any sequence in Figure <xref ref-type="fig" rid="F1">1</xref> (Table <xref ref-type="table" rid="T3">3</xref>). Searching the PDB for homologues of known structure, using BLAST, showed that SuhB still represents the best template in terms of sequence identity, although the differences to the next nearest homologue are small (Table <xref ref-type="table" rid="T3">3</xref>). Based on the search results, one could speculate on the substrate specificities of the two uncharacterised gene products, Rv3137 and ImpA. The gene product with the most divergent sequence, CysQ, has been characterised as a dual IMPase/FBPase [<xref ref-type="bibr" rid="B15">15</xref>]. Consistent with this finding, searching the PDB with the CysQ sequence returns two dual activity enzymes, <italic>Rattus norvegicus </italic>3'-phosphoadenosine-5'-phosphate/inositol-1,4-bisphosphate phosphatase (RnPIP) [<xref ref-type="bibr" rid="B22">22</xref>], and <italic>T. maritima </italic>IMPase/FBPase TM1415 [<xref ref-type="bibr" rid="B18">18</xref>,<xref ref-type="bibr" rid="B27">27</xref>] as the closest homologues of known structure. Likewise, the search results mirror the close relationship of SuhB to the eukaryotic IMPases, which strongly prefer inositol-1-phosphate as substrate. Interestingly, the dual activity IMPase/FBPase TM1415 appears as the top hit for both ImpA and Rv3137 (Table <xref ref-type="table" rid="T3">3</xref>).</p>
        <table-wrap position="float" id="T3">
          <label>Table 3</label>
          <caption>
            <p>BLAST search for M. tuberculosis IMPase homologues of known structure</p>
          </caption>
          <table frame="hsides" rules="groups">
            <thead>
              <tr>
                <td/>
                <td align="left">SuhB</td>
                <td align="left">Rv3137</td>
                <td align="left">ImpA</td>
                <td align="left">CysQ</td>
                <td align="left">
                  <ext-link ext-link-type="pdb" xlink:href="1IMA">1IMA</ext-link>
                  <sup>a</sup>
                </td>
                <td align="left">
                  <ext-link ext-link-type="pdb" xlink:href="2BJI">2BJI</ext-link>
                </td>
                <td align="left">
                  <ext-link ext-link-type="pdb" xlink:href="1JP4">1JP4</ext-link>
                </td>
                <td align="left">
                  <ext-link ext-link-type="pdb" xlink:href="2P3N">2P3N</ext-link>
                </td>
                <td align="left">
                  <ext-link ext-link-type="pdb" xlink:href="1G0H">1G0H</ext-link>
                </td>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td align="left">SuhB</td>
                <td align="left">100</td>
                <td align="left">30</td>
                <td align="left">23</td>
                <td align="left">22</td>
                <td align="left">25</td>
                <td align="left">25</td>
                <td align="left">14</td>
                <td align="left">23</td>
                <td align="left">19</td>
              </tr>
              <tr>
                <td align="left">Rv3137</td>
                <td/>
                <td align="left">100</td>
                <td align="left">23</td>
                <td align="left">18</td>
                <td align="left">23</td>
                <td align="left">22</td>
                <td align="left">22</td>
                <td align="left">29</td>
                <td align="left">17</td>
              </tr>
              <tr>
                <td align="left">ImpA</td>
                <td/>
                <td/>
                <td align="left">100</td>
                <td align="left">13</td>
                <td align="left">15</td>
                <td align="left">16</td>
                <td align="left">12</td>
                <td align="left">22</td>
                <td align="left">20</td>
              </tr>
              <tr>
                <td align="left">CysQ</td>
                <td/>
                <td/>
                <td/>
                <td align="left">100</td>
                <td align="left">14</td>
                <td align="left">12</td>
                <td align="left">16</td>
                <td align="left">7</td>
                <td align="left">3</td>
              </tr>
              <tr>
                <td align="left"><ext-link ext-link-type="pdb" xlink:href="1IMA">1IMA</ext-link> (IMP human)</td>
                <td align="left">
                  <bold>2.0E-20</bold>
                </td>
                <td/>
                <td/>
                <td/>
                <td align="left">100</td>
                <td align="left">88</td>
                <td align="left">16</td>
                <td align="left">28</td>
                <td align="left">19</td>
              </tr>
              <tr>
                <td/>
                <td align="left">
                  <bold>(194)</bold>
                </td>
                <td/>
                <td/>
                <td/>
                <td/>
                <td/>
                <td/>
                <td/>
                <td/>
              </tr>
              <tr>
                <td align="left"><ext-link ext-link-type="pdb" xlink:href="2BJI">2BJI</ext-link> (IMP bovine)</td>
                <td align="left">
                  <bold>3.0E-21</bold>
                </td>
                <td align="left">
                  <bold>4.7E-07</bold>
                </td>
                <td/>
                <td/>
                <td/>
                <td align="left">100</td>
                <td align="left">19</td>
                <td align="left">28</td>
                <td align="left">20</td>
              </tr>
              <tr>
                <td/>
                <td align="left">
                  <bold>(194)</bold>
                </td>
                <td align="left">
                  <bold>(165)</bold>
                </td>
                <td/>
                <td/>
                <td/>
                <td/>
                <td/>
                <td/>
                <td/>
              </tr>
              <tr>
                <td align="left"><ext-link ext-link-type="pdb" xlink:href="1JP4">1JP4</ext-link> (PIPase_Rno)</td>
                <td/>
                <td/>
                <td/>
                <td align="left">
                  <bold>2.7E-05</bold>
                </td>
                <td/>
                <td/>
                <td align="left">100</td>
                <td align="left">18</td>
                <td align="left">15</td>
              </tr>
              <tr>
                <td/>
                <td/>
                <td/>
                <td/>
                <td align="left">
                  <bold>(169)</bold>
                </td>
                <td/>
                <td/>
                <td/>
                <td/>
                <td/>
              </tr>
              <tr>
                <td align="left"><ext-link ext-link-type="pdb" xlink:href="2P3N">2P3N</ext-link>(TM1415_Tma)</td>
                <td/>
                <td align="left">
                  <bold>9.5E-16</bold>
                </td>
                <td align="left">
                  <bold>4.0E-12</bold>
                </td>
                <td align="left">
                  <bold>8.7E-04</bold>
                </td>
                <td/>
                <td/>
                <td/>
                <td align="left">100</td>
                <td align="left">23</td>
              </tr>
              <tr>
                <td/>
                <td/>
                <td align="left">
                  <bold>(221)</bold>
                </td>
                <td align="left">
                  <bold>(247)</bold>
                </td>
                <td align="left">
                  <bold>(192)</bold>
                </td>
                <td/>
                <td/>
                <td/>
                <td/>
                <td/>
              </tr>
              <tr>
                <td align="left"><ext-link ext-link-type="pdb" xlink:href="1G0H">1G0H</ext-link> (MJ0109_Mja)</td>
                <td/>
                <td/>
                <td align="left">
                  <bold>6.3E-10</bold>
                </td>
                <td/>
                <td/>
                <td/>
                <td/>
                <td/>
                <td align="left">100</td>
              </tr>
              <tr>
                <td/>
                <td/>
                <td/>
                <td align="left">
                  <bold>(161)</bold>
                </td>
                <td/>
                <td/>
                <td/>
                <td/>
                <td/>
                <td/>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <p>Fields above the table diagonal give the %-identity in a <italic>STRAP</italic>-generated multiple sequence alignment. Fields in bold type give the E-values and (number of paired amino acid residues) of the two top hits in the <italic>BLAST </italic>search of the PDB [48].</p>
            <p><sup>a </sup>References for PDB entries:</p>
            <p><ext-link ext-link-type="pdb" xlink:href="1IMA">1IMA</ext-link> – human IMPase complexed with <italic>myo-</italic>inositol-1-phosphate [29]</p>
            <p><ext-link ext-link-type="pdb" xlink:href="2BJI">2BJI</ext-link> – bovine IMPase [17]</p>
            <p><ext-link ext-link-type="pdb" xlink:href="1JP4">1JP4</ext-link> – <italic>Rattus norvegicus </italic>3'-phosphoadenosine 5'-phosphate and inositol-1,4-bisphosphate phosphatase [22]</p>
            <p><ext-link ext-link-type="pdb" xlink:href="2P3N">2P3N</ext-link> – <italic>Thermotoga maritima </italic>TM1415 IMPase/FBPase [27]</p>
            <p><ext-link ext-link-type="pdb" xlink:href="1G0H">1G0H</ext-link> – <italic>Methanococcus jannaschii </italic>MJ0109 IMPase/FBPase [24].</p>
          </table-wrap-foot>
        </table-wrap>
        <p>Analysing the multiple sequence alignment that underlies Table <xref ref-type="table" rid="T3">3</xref> [see Additional file <xref ref-type="supplementary-material" rid="S2">2</xref>] more closely, it is interesting to note that enzymes that are specific for inositol-1-phosphate and exclude fructose-1,6-bisphosphate carry a glutamic acid or glutamine at position 228 (SuhB sequence; residue 213 in human IMPase), whereas Asp, His, Ser or Thr are found in enzymes that hydrolyze both substrates or are specific for fructose-1,6-bisphosphate. In the inositol-1-phosphate-bound structure of human IMPase [<xref ref-type="bibr" rid="B29">29</xref>], the corresponding residue, Glu213, forms hydrogen bonds to the C3 and C4 hydroxyls of the inositol ring. In addition to the H-bond between Asp93 (Asp107 in SuhB) and the C6-hydroxyl, these H-bonds are the only side chain-mediated, specificity-determining contacts between the inositol moiety and the enzyme. In the structural superimposition it is evident that an Asp (and likewise Ser, Thr or His) at this position is unlikely to confer selectivity as the distance between the terminal group of the side chain and the sugar hydroxyls becomes too large. Discrimination against fructose-1,6-bisphosphate is rooted primarily in steric clashes of the 6-phosphate the β9-α6 loop. As a result of deletions relative to human IMPase, a much shorter β9-α6 loop in FBPases and dual activity IMPase/FBPases provide the space to accommodate the second phosphate group. Thus, deletions in this region in addition to substitutions of Glu/Gln at position 228 could be indicative of dual specificity. Analysing the sequences of ImpA and Rv3137 in light of these considerations suggests that at least Rv3137 is restricted to inositol-1-phosphate, whereas the case is less clear cut for ImpA. The latter carries a Ser at the position corresponding to Glu228, but displays no significant deletion relative to SuhB between residues 150 and 190, whereas CysQ by the standards of both criteria falls into the category of the dual specificity enzymes, consistent with published biochemical data [<xref ref-type="bibr" rid="B15">15</xref>].</p>
      </sec>
    </sec>
    <sec>
      <title>Conclusion</title>
      <p>We have determined the structure of M. tuberculosis SuhB, providing a structural template for the four IMPase-like enzymes in this organism. While resembling eukaryotic IMPases in terms of structural scaffold, specificity for inositol-1-phosphate, requirement for Mg<sup>2+ </sup>and inhibition by Li<sup>+</sup>, SuhB clearly diverges from the paradigm of constitutive dimerization of <italic>bona fide </italic>IMPases. The present data support a model of Mg<sup>2+</sup>-dependent dimerization, where loading of the three catalytic metal sites in the active site induces ordering of the mobile loop, promoting dimerization likely by expanding the dimer interface. The active site of SuhB presents a highly conserved scaffold of side chains forming the metal- and substrate-binding site, yet additional specificity-determining contacts are expected with the weakly conserved β9-α6 loop. Sequence and structural comparisons lead us to predict that the essential gene product Rv3137 represents a bona fide IMPase, while such may or may not be the case for ImpA.</p>
    </sec>
    <sec sec-type="methods">
      <title>Methods</title>
      <sec sec-type="materials">
        <title>Materials</title>
        <p>Centricon YM-10 filtration units were obtained from Millipore. <italic>E. coli </italic>C41(DE3) [<xref ref-type="bibr" rid="B41">41</xref>], acquired from Avidis (France), was used for protein production in this study. Sparse matrix crystallisation screens were obtained from Molecular Dimensions Ltd. All other chemicals were reagent grade or better and obtained from Sigma-Aldrich.</p>
      </sec>
      <sec>
        <title>Expression, purification and crystallisation</title>
        <p>Recombinant proteins were generated and purified as described previously [<xref ref-type="bibr" rid="B12">12</xref>]. Purified His<sub>6</sub>-tagged SuhB, was dialyzed extensively against 20 mM sodium phosphate pH 7.5, 250 mM NaCl and purified further by size exclusion chromatography over a Sephacryl S200-HR matrix. Pure fractions were pooled and concentrated using Centricon YM-10 filter units. Crystals of SuhB were obtained by hanging drop vapour diffusion, mixing 1 μl of protein solution (40–50 mg.ml<sup>-1</sup>) with 1 μl of reservoir solution, screening against commercial sparse matrix screens (Structure Screen 1 and 2, Molecular Dimensions Ltd.) at 18°C. Initial crystals appeared in 30%(v/v)2-methyl-2, 4-pentanediol(MPD), 0.1 M tri-sodium citrate, pH 5.6, 0.2 M ammonium acetate. Optimization led to crystals approximately 0.3 mm in length at 10–14%(v/v) MPD, 0.1 M citric acid, pH 4.2, and 0.05%(w/v) octyl β-D-glucopyranoside. Crystals grew to their final size over 7–10 days. In preparation for X-ray data collection crystals were soaked in cryoprotectant , consisting of upto 30%(v/v) MPD, 125 mM NaCl, 0.1 M citric acid pH 4.2 and 0.05%(w/v) octyl β-D-glucopyranoside, increasing the MPD concentration in steps of 10%. Crystals were mounted in nylon loops and frozen in a 100 K nitrogen gas stream.</p>
      </sec>
      <sec>
        <title>X-ray data collection and crystallographic analysis</title>
        <p>X-ray diffraction data for SuhB were recorded on beamline ID14-EH2 at the European Synchrotron Radiation Facility (ESRF), Grenoble, France (Table <xref ref-type="table" rid="T1">1</xref>). Data were reduced using <italic>DENZO/SCALEPACK </italic>[<xref ref-type="bibr" rid="B42">42</xref>]. Patterson self-rotation analysis (<italic>POLARRFN </italic>– [<xref ref-type="bibr" rid="B43">43</xref>]) revealed a 3-fold non-crystallographic rotation axis parallel to the 2<sub>1</sub>-screw axis (resulting in an apparent 6-fold), consistent with three SuhB monomers per crystallographic asymmetric unit. Structure factor amplitudes were normalized (<italic>ECALC </italic>– [<xref ref-type="bibr" rid="B43">43</xref>]), and initial phases were obtained by molecular replacement (<italic>AMORE </italic>– [<xref ref-type="bibr" rid="B43">43</xref>]), using monomer coordinates of human IMPase (PDB:<ext-link ext-link-type="pdb" xlink:href="1IMA">1IMA</ext-link> – [<xref ref-type="bibr" rid="B29">29</xref>]) as a search model. While the Patterson cross-rotation search did not reveal clear solutions, the correct 3 orientations (peaks 4, 5 and 7) could be identified through comparing rotation angles between rotation function peaks with self-rotation peaks, which was confirmed through the subsequent translation search. The search model was stripped of non-conserved side chains and insertions, and built manually into MR-phased density (<italic>O </italic>– [<xref ref-type="bibr" rid="B44">44</xref>]). Search model bias was minimised by building into simulated annealing omit maps [<xref ref-type="bibr" rid="B45">45</xref>], followed by rounds of refinement (conjugate-gradient minimization, simulated annealing) in <italic>CNS </italic>ver 1.1 [<xref ref-type="bibr" rid="B46">46</xref>] and manual rebuilding, eventually leading to a model that fitted the data with an Rfree of ~30% (5% of reflections). Non-crystallographic symmetry restraints were introduced and the refinement was continued using <italic>REFMAC5 </italic>[<xref ref-type="bibr" rid="B47">47</xref>]. The final model contains 3 monomers covering SuhB residues 5–34, 54–85, 98–253, 260–286. Details of the refinement statistics are listed in Table <xref ref-type="table" rid="T1">1</xref>. Coordinates and structure factors have been deposited in the Protein Data Bank [<xref ref-type="bibr" rid="B48">48</xref>] [PDB:<ext-link ext-link-type="pdb" xlink:href="2Q74">2Q74</ext-link>].</p>
      </sec>
      <sec>
        <title>Molecular graphics</title>
        <p>Figures <xref ref-type="fig" rid="F2">2</xref>, <xref ref-type="fig" rid="F3">3</xref> and <xref ref-type="fig" rid="F4">4A,4B</xref> were prepared using <italic>PyMOL </italic>ver 0.97 [<xref ref-type="bibr" rid="B49">49</xref>]. Figure <xref ref-type="fig" rid="F4">4C</xref> was generated using <italic>Swiss PDB Viewer </italic>[<xref ref-type="bibr" rid="B50">50</xref>] and <italic>POV-Ray </italic>Version 3.6 [<xref ref-type="bibr" rid="B51">51</xref>].</p>
      </sec>
      <sec>
        <title>Analytical ultracentrifugation</title>
        <p>Sedimentation velocity experiments were performed using a Beckman Optima XL-A analytical ultracentrifuge equipped with absorbance optics. Protein samples were dialysed into storage buffer, as indicated in the figure legends (Figures <xref ref-type="fig" rid="F5">5</xref> and <xref ref-type="fig" rid="F6">6</xref>) and loaded into cells with two channel Epon centre pieces and quartz windows. Data were recorded at 40,000 rpm, 4°C. A total of 100 absorbance scans (280 nm) were recorded for each sample, representing the full extent of sedimentation of the sample. Data analysis was performed using the SEDFIT software fitting a single friction coefficient [<xref ref-type="bibr" rid="B52">52</xref>].</p>
      </sec>
    </sec>
    <sec>
      <title>Authors' contributions</title>
      <p>A.K.B., G.S.B. and K.F. designed the study. A.K.B. wrote the initial draft of the manuscript, and purified the protein. G.M. performed crystallisation experiments, data acquisition and contributed to crystallographic analysis and model building. A.K.B. and H.G. performed the AUC experiment, and with help from D.J.S., analysed the data, and prepared figures. L.G.D. together with J.N. designed and produced the expression plasmids, developed the purification protocol and contributed to data interpretation. K.F. solved the structure, contributed to design of figures, and edited the manuscript. All authors have read and approved the manuscript.</p>
    </sec>
    <sec sec-type="supplementary-material">
      <title>Supplementary Material</title>
      <supplementary-material content-type="local-data" id="S1">
        <caption>
          <title>Additional file 1</title>
          <p><bold>Supplementary Figure S1</bold>. This Figure shows traces of the sedimentation coefficient distribution recorded in sedimentation velocity experiments of <italic>M. tuberculosis </italic>SuhB. SuhB was at 1.0 mg.ml<sup>-1 </sup>in 20 mM Tris-HCl pH 7.9, 50 mM NaCl, plus MgCl<sub>2</sub>, LiCl, CaCl<sub>2 </sub>and EDTA as indicated. Samples were centrifuged at 40,000 rpm at 4°C for at least 12 hours.</p>
        </caption>
        <media xlink:href="1472-6807-7-55-S1.png" mimetype="image" mime-subtype="png">
          <caption>
            <p>Click here for file</p>
          </caption>
        </media>
      </supplementary-material>
      <supplementary-material content-type="local-data" id="S2">
        <caption>
          <title>Additional file 2</title>
          <p><bold>Supplementary Figure S2</bold>. This Figure shows a structure-based sequence alignment of IMPase-like proteins using <italic>STRAP </italic>[<xref ref-type="bibr" rid="B53">53</xref>] with formatting in <italic>ESPRIPT </italic>[<xref ref-type="bibr" rid="B54">54</xref>]. Sequence abbreviations (with pdb accession code in parentheses) are as follows: SuhB_Mtb – <italic>Mycobacterium tuberculosis </italic>SuhB ; Rv3137_Mtb – gene product Rv3131 of <italic>M. tuberculosis; </italic>ImpA_Mtb – <italic>M. tuberculosis </italic>ImpA; CysQ_Mtb – <italic>M. tuberculosis </italic>CysQ; IMPase_hum – human inositol monophosphatase (<ext-link ext-link-type="pdb" xlink:href="1IMA">1IMA</ext-link>); IMPase2_hum – human inositol monophosphatase 2 (<ext-link ext-link-type="pdb" xlink:href="2CZH">2CZH</ext-link>); IMPase_bov – bovine inositol monophosphatase (<ext-link ext-link-type="pdb" xlink:href="2BJI">2BJI</ext-link>); SuhB_Eco – <italic>Escherichia coli </italic>SuhB; MJ0109_Mja – <italic>Methanococcus jannaschii </italic>IMPase/FBPase MJ0109 (<ext-link ext-link-type="pdb" xlink:href="1DK4">1DK4</ext-link>); AF2372_Afu – <italic>Archeoglobus fulgidus </italic>IMPase/FBPase AF2372 (<ext-link ext-link-type="pdb" xlink:href="1LBV">1LBV</ext-link>); TM1415_Tma – <italic>Thermotoga maritima </italic>IMPase TM1415 (<ext-link ext-link-type="pdb" xlink:href="2P3N">2P3N</ext-link>); PIPase_Rno – <italic>Rattus norvegicus </italic>3'-phosphoadenosine 5'-phosphate and inositol 1,4-bisphosphate phosphatase (<ext-link ext-link-type="pdb" xlink:href="1JP4">1JP4</ext-link>). Secondary structure elements above the sequence refer to the crystal structure of <italic>M. tuberculosis </italic>SuhB.</p>
        </caption>
        <media xlink:href="1472-6807-7-55-S2.png" mimetype="image" mime-subtype="png">
          <caption>
            <p>Click here for file</p>
          </caption>
        </media>
      </supplementary-material>
      <supplementary-material content-type="local-data" id="S3">
        <caption>
          <title>Additional file 3</title>
          <p><bold>References for Table </bold><xref ref-type="table" rid="T2">2</xref>. This file contains references for PDB entries cited in Table <xref ref-type="table" rid="T2">2</xref> of the main text.</p>
        </caption>
        <media xlink:href="1472-6807-7-55-S3.pdf" mimetype="application" mime-subtype="pdf">
          <caption>
            <p>Click here for file</p>
          </caption>
        </media>
      </supplementary-material>
    </sec>
  </body>
  <back>
    <ack>
      <sec>
        <title>Acknowledgements</title>
        <p>We thank Tom Burton for his involvement in model building as part of an undergraduate summer project. We thank Tim Dafforn for access to the analytical ultracentrifuge, part of the Biosciences Biomolecular Characterisation Facility (BBCF), and J. Baz Jackson for valuable discussions. We thank ESRF Grenoble for access to the synchrotron and travel support, and ESRF staff for support during data acquisition. G.M. was supported by an Adrian Brown Scholarship. G.S.B. acknowledges support in the form of a Personal Research Chair from Mr. James Bardrick, as a former Lister Institute-Jenner Research Fellow, and the Medical Research Council.</p>
      </sec>
    </ack>
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      <aff id="I2"><label>2</label>Department of Mathematics and Statistics, McMaster University, 1280 Main Street West, Hamilton, ON, L8S 4K1, Canada</aff>
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          <month>9</month>
          <year>2007</year>
        </date>
      </history>
      <permissions>
        <copyright-statement>Copyright © 2007 Ismaila et al; licensee BioMed Central Ltd.</copyright-statement>
        <copyright-year>2007</copyright-year>
        <copyright-holder>Ismaila et al; licensee BioMed Central Ltd.</copyright-holder>
        <license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/2.0">
          <p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/2.0"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>
          <!--<rdf xmlns="http://web.resource.org/cc/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1" xmlns:dcterms="http://purl.org/dc/terms"><Work xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" rdf:about=""><license rdf:resource="http://creativecommons.org/licenses/by/2.0"/><dc:type rdf:resource="http://purl.org/dc/dcmitype/Text"/><dc:author>
               Ismaila
               S
               Afisi
               
               ismailas@mcmaster.ca
            </dc:author><dc:title>
            Comparison of Bayesian and frequentist approaches in modelling risk of preterm birth near the Sydney Tar Ponds, Nova Scotia, Canada
         </dc:title><dc:date>2007</dc:date><dcterms:bibliographicCitation>BMC Medical Research Methodology 7(1): 39-. (2007)</dcterms:bibliographicCitation><dc:identifier type="sici">1471-2288(2007)7:1&#x0003c;39&#x0003e;</dc:identifier><dcterms:isPartOf>urn:ISSN:1471-2288</dcterms:isPartOf><License rdf:about="http://creativecommons.org/licenses/by/2.0"><permits rdf:resource="http://web.resource.org/cc/Reproduction" xmlns=""/><permits rdf:resource="http://web.resource.org/cc/Distribution" xmlns=""/><requires rdf:resource="http://web.resource.org/cc/Notice" xmlns=""/><requires rdf:resource="http://web.resource.org/cc/Attribution" xmlns=""/><permits rdf:resource="http://web.resource.org/cc/DerivativeWorks" xmlns=""/></License></Work></rdf>-->
        </license>
      </permissions>
      <abstract>
        <sec>
          <title>Background</title>
          <p>This study compares the Bayesian and frequentist (non-Bayesian) approaches in the modelling of the association between the risk of preterm birth and maternal proximity to hazardous waste and pollution from the Sydney Tar Pond site in Nova Scotia, Canada.</p>
        </sec>
        <sec sec-type="methods">
          <title>Methods</title>
          <p>The data includes 1604 observed cases of preterm birth out of a total population of 17559 at risk of preterm birth from 144 enumeration districts in the Cape Breton Regional Municipality. Other covariates include the distance from the Tar Pond; the rate of unemployment to population; the proportion of persons who are separated, divorced or widowed; the proportion of persons who have no high school diploma; the proportion of persons living alone; the proportion of single parent families and average income. Bayesian hierarchical Poisson regression, quasi-likelihood Poisson regression and weighted linear regression models were fitted to the data.</p>
        </sec>
        <sec>
          <title>Results</title>
          <p>The results of the analyses were compared together with their limitations.</p>
        </sec>
        <sec>
          <title>Conclusion</title>
          <p>The results of the weighted linear regression and the quasi-likelihood Poisson regression agrees with the result from the Bayesian hierarchical modelling which incorporates the spatial effects.</p>
        </sec>
      </abstract>
    </article-meta>
  </front>
  <body>
    <sec>
      <title>Background</title>
      <p>Public awareness about potential environmental hazards has continued to grow in recent years. This concern has led to an increased demand for public health authorities and researchers to investigate potential clustering of diseases around putative sources of hazards [<xref ref-type="bibr" rid="B1">1</xref>-<xref ref-type="bibr" rid="B10">10</xref>]. Evidence of significant association between maternal proximity to hazardous waste sites and risk of low birth-weight and congenital anomalies has been reported in some studies [<xref ref-type="bibr" rid="B4">4</xref>-<xref ref-type="bibr" rid="B12">12</xref>], but other studies have reported otherwise [<xref ref-type="bibr" rid="B1">1</xref>,<xref ref-type="bibr" rid="B3">3</xref>,<xref ref-type="bibr" rid="B6">6</xref>,<xref ref-type="bibr" rid="B13">13</xref>-<xref ref-type="bibr" rid="B15">15</xref>]. Some studies have also shown that women exposed to PCB are at increased risk of giving birth to infants with low birth weight [<xref ref-type="bibr" rid="B16">16</xref>,<xref ref-type="bibr" rid="B17">17</xref>].</p>
      <p>An assessment of the effect of human exposure to particular substances can be complex because multiple chemicals are usually involved so it may be difficult to discern the specific agent responsible for a particular health concern [<xref ref-type="bibr" rid="B16">16</xref>-<xref ref-type="bibr" rid="B19">19</xref>]. Furthermore, extraneous factors, like cultural and socioeconomic, may confound the effect of direct exposure to a waste site [<xref ref-type="bibr" rid="B16">16</xref>-<xref ref-type="bibr" rid="B24">24</xref>]. Within the boundaries of these limitations, the theory of spatial modelling and its applications to waste landfills and risk of adverse health have been developed and extensively discussed [<xref ref-type="bibr" rid="B25">25</xref>-<xref ref-type="bibr" rid="B29">29</xref>]. Regression analysis is one of the most widely used methods in the modelling of disease risk associated with proximity to a point source [<xref ref-type="bibr" rid="B25">25</xref>]. The parameters of the regression model can be estimated using the Bayesian or the frequentist approaches with spatial data assumed to be available at the individual case level or as spatially aggregated counts in enumeration districts (ED) [<xref ref-type="bibr" rid="B25">25</xref>-<xref ref-type="bibr" rid="B27">27</xref>].</p>
      <p>In this paper, we focus on the comparison of the Bayesian and frequentist regression methods for aggregated counts. Specifically, we compare the Bayesian hierarchical Poisson regression, quasi-likelihood Poisson regression and weighted linear regression modelling approaches in answering the following two questions: 1) Is maternal proximity to hazardous waste and pollution from the Sydney Tar Pond sites associated with increased risk of preterm birth? 2) How much of the variation in preterm birth can be explained by socioeconomic inequalities across the study region?</p>
    </sec>
    <sec sec-type="methods">
      <title>Methods</title>
      <p>In the following subsections we provide a description of the study site, the data used for analyses and the theoretical framework of methods used to analyse the data.</p>
      <sec>
        <title>Tar Pond site in Sydney</title>
        <p>The history of the Tar Pond site in Sydney, Nova Scotia, and the health consequences are well documented [<xref ref-type="bibr" rid="B2">2</xref>,<xref ref-type="bibr" rid="B30">30</xref>]. The Tar Pond is a tidal estuary of 33 hectares in the Cape Breton regional municipality of Nova Scotia, Canada. This site, considered to be the most toxic site in Canada, is a result of over 100 years of steel manufacturing and other allied industries in the area. The byproducts from these industries include BTEX (benzene, toluene, ethylbenzene, and xylene), PAH (polycyclic aromatic hydrocarbons), PCB (polychlorinated biphenyl) and particulate laden with toxic metals, such as arsenic, lead and other heavy metals. This has led to the contamination of soil and other sources of natural water in the surrounding areas.</p>
      </sec>
      <sec>
        <title>Data description</title>
        <p>Cape Breton regional municipality is made up of 158 enumeration districts but aggregated counts of preterm birth were available from only 144 enumeration districts in the municipality. There were 1604 observed cases of preterm birth out of a total population of 17559 at risk of preterm birth. Other variables include the distance from the Tar Pond (<italic>d</italic>) and the following area-specific covariates; the proportion of persons who are separated, divorced or widowed (<italic>x</italic><sub>2</sub>); the proportion of persons who have no high school diploma (<italic>x</italic><sub>3</sub>); the proportion of people living alone (<italic>x</italic><sub>4</sub>); the proportion of single parent families (<italic>x</italic><sub>5</sub>) and average income (<italic>x</italic><sub>6</sub>). The covariates were selected based on the Pampalon and Raymond index [<xref ref-type="bibr" rid="B21">21</xref>] for health and welfare planning in Quebec. All area-specific covariates were extracted from the 1996 Canadian census data.</p>
      </sec>
      <sec>
        <title>Some theoretical background and context</title>
        <p>Let <italic>Y</italic><sub><italic>i </italic></sub>denote the number of observed cases of preterm birth, and <italic>N</italic><sub><italic>i </italic></sub>the population at risk in each enumeration district (ED). The expected counts (<italic>E</italic><sub><italic>i</italic></sub>) for each ED was calculated by multiplying <italic>N</italic><sub><italic>i </italic></sub>by the the Canada preterm birth rate of 7.1 per 100 live births in 1996 (source: Population and Public Health Branch, Health Canada). This rate is assumed fixed for 1996 and may have been calculated by including data from the Cape Breton regional municipality, but we will assume that the effect of this can be ignored. Hence, <italic>E</italic><sub><italic>i </italic></sub>is the expected number of preterm birth from all other sources of risk other than pollution from the Sydney Tar Pond. Preterm births only occur in females within the child-bearing age and the condition is not infectious. Hence, it is reasonable to assume that each case occurred independently. We also assumed that the risk is constant in each ED, so that</p>
        <p>
          <disp-formula id="bmcM1"><italic>Y</italic><sub><italic>i</italic></sub>|<italic>λ</italic><sub><italic>i </italic></sub>~ Poisson (<italic>E</italic><sub><italic>i</italic></sub><italic>λ</italic><sub><italic>i</italic></sub>) <italic>i </italic>= 1,..., <italic>n</italic>,</disp-formula>
        </p>
        <p>where <italic>λ</italic><sub><italic>i </italic></sub>denotes the relative risk of preterm birth for each ED compared to the whole country [<xref ref-type="bibr" rid="B31">31</xref>]. The maximum likelihood estimator of <italic>λ</italic><sub><italic>i </italic></sub>is the unadjusted standardized incidence ratio (SIR), the ratio of observed to expected within each ED [<xref ref-type="bibr" rid="B27">27</xref>,<xref ref-type="bibr" rid="B32">32</xref>]. We use a regression approach to adjust the crude SIR to improve its stability where the population at risk may be small [<xref ref-type="bibr" rid="B27">27</xref>,<xref ref-type="bibr" rid="B29">29</xref>,<xref ref-type="bibr" rid="B32">32</xref>,<xref ref-type="bibr" rid="B33">33</xref>].</p>
        <p>Based on the work of Morris and Wakefield [<xref ref-type="bibr" rid="B27">27</xref>], we define the null hypothesis that proximity to source does not influence risk by</p>
        <p>
          <disp-formula><italic>H</italic><sub>0 </sub>: <italic>λ</italic><sub><italic>i </italic></sub>= <italic>η </italic>for <italic>i </italic>= 1,..., <italic>n</italic>.</disp-formula>
        </p>
        <p>Now suppose (<italic>x</italic><sub>0</sub>, <italic>y</italic><sub>0</sub>) denotes the centroid of the Tar pond, (<italic>x</italic><sub><italic>i</italic></sub>, <italic>y</italic><sub><italic>i</italic></sub>) the centroid of each ED and <italic>d</italic><sub><italic>i </italic></sub>the distance between the two centroid. In the absence of an exposure measure that may be attached to each ED, Morris and Wakefield [<xref ref-type="bibr" rid="B27">27</xref>] define a natural additive distance/risk model by</p>
        <p>
          <disp-formula><italic>λ</italic><sub><italic>i </italic></sub>= <italic>η </italic>{1 + <italic>f</italic>(<italic>d</italic><sub><italic>i</italic></sub>; <italic>θ</italic>)}</disp-formula>
        </p>
        <p>where <italic>η </italic>is the background relative risk and <italic>f</italic>(<italic>d</italic><sub><italic>i</italic></sub>; <italic>θ</italic>) is a function of distance, such that <italic>f </italic>(<italic>d</italic><sub><italic>i</italic></sub>; <italic>θ</italic>) → 0 as <italic>d</italic><sub><italic>i </italic></sub>→ ∞. We will use a reparameterization of the form</p>
        <p>
          <disp-formula id="bmcM2"><italic>λ</italic><sub><italic>i </italic></sub>= <italic>η g</italic>(<italic>d</italic><sub><italic>i</italic></sub>; <italic>θ</italic>)</disp-formula>
        </p>
        <p>so that this model will be consistent with Bithell [<xref ref-type="bibr" rid="B34">34</xref>]. With this reparameterization, <italic>g</italic>(<italic>d</italic><sub><italic>i</italic></sub>; <italic>θ</italic>) → 1 as <italic>d</italic><sub><italic>i </italic></sub>→ ∞. Bithell [<xref ref-type="bibr" rid="B34">34</xref>] proposed the following distance functions as suitable forms for <italic>g</italic>(<italic>d</italic><sub><italic>i</italic></sub>).</p>
        <p>
          <disp-formula id="bmcM3"><italic>g</italic><sub>1</sub>(<italic>d</italic><sub><italic>i</italic></sub>) = exp(<italic>α</italic>/<italic>d</italic><sub><italic>i</italic></sub>)</disp-formula>
        </p>
        <p>
          <disp-formula id="bmcM4"><italic>g</italic><sub>2</sub>(<italic>d</italic><sub><italic>i</italic></sub>) = 1 + <italic>ξ </italic>exp(-<italic>d</italic><sub><italic>i</italic></sub>/<italic>β</italic>)</disp-formula>
        </p>
        <p>
          <disp-formula id="bmcM5"><italic>g</italic><sub>3</sub>(<italic>d</italic><sub><italic>i</italic></sub>) = 1 + <italic>ξ </italic>exp(-(<italic>d</italic><sub><italic>i</italic></sub>/<italic>γ</italic>)<sup>2</sup>)</disp-formula>
        </p>
        <p>
          <disp-formula id="bmcM6"><italic>g</italic><sub>4</sub>(<italic>d</italic><sub><italic>i</italic></sub>) = 1 + <italic>ξ</italic>/(1 + <italic>d</italic><sub><italic>i</italic></sub>/<italic>δ</italic>)</disp-formula>
        </p>
        <p>where <italic>α</italic>, <italic>β</italic>, <italic>γ</italic>, and <italic>δ </italic>represent decay rates. For <italic>g</italic><sub>2</sub>(<italic>d</italic><sub><italic>i</italic></sub>), <italic>g</italic><sub>3</sub>(<italic>d</italic><sub><italic>i</italic></sub>) and <italic>g</italic><sub>4</sub>(<italic>d</italic><sub><italic>i</italic></sub>), 1 + <italic>ξ </italic>is a measure of the ratio of relative risk at source to that at infinity. Other variants of the Bithell functions have also been proposed [<xref ref-type="bibr" rid="B35">35</xref>]. For simplicity, and following Datta <italic>et al. </italic>[<xref ref-type="bibr" rid="B32">32</xref>] and Bithell [<xref ref-type="bibr" rid="B34">34</xref>], we have chosen</p>
        <p>
          <disp-formula><italic>g</italic>(<italic>d</italic><sub><italic>i</italic></sub>; <italic>θ</italic>) = <italic>g</italic><sub>1 </sub>(<italic>d</italic><sub><italic>i</italic></sub>; <italic>θ</italic>) = exp(<italic>α</italic>/<italic>d</italic><sub><italic>i</italic></sub>).</disp-formula>
        </p>
        <p>We incorporated the area-level covariates (<italic>z</italic><sub><italic>i</italic></sub>) and a measure of the spread of the risk from the Tar pond through a generalized linear model of the form</p>
        <p>
          <disp-formula id="bmcM7">
            <mml:math id="M1" name="1471-2288-7-39-i1" overflow="scroll">
              <mml:semantics definitionURL="" encoding="">
                <mml:mrow>
                  <mml:mi>log</mml:mi>
                  <mml:mo>⁡</mml:mo>
                  <mml:msub>
                    <mml:mi>λ</mml:mi>
                    <mml:mi>i</mml:mi>
                  </mml:msub>
                  <mml:mo>=</mml:mo>
                  <mml:msub>
                    <mml:mi>α</mml:mi>
                    <mml:mi>o</mml:mi>
                  </mml:msub>
                  <mml:mo>+</mml:mo>
                  <mml:mi>log</mml:mi>
                  <mml:mo>⁡</mml:mo>
                  <mml:msub>
                    <mml:mi>g</mml:mi>
                    <mml:mn>1</mml:mn>
                  </mml:msub>
                  <mml:mo stretchy="false">(</mml:mo>
                  <mml:msub>
                    <mml:mi>d</mml:mi>
                    <mml:mi>i</mml:mi>
                  </mml:msub>
                  <mml:mo>;</mml:mo>
                  <mml:mi>θ</mml:mi>
                  <mml:mo stretchy="false">)</mml:mo>
                  <mml:mo>+</mml:mo>
                  <mml:msubsup>
                    <mml:mi>z</mml:mi>
                    <mml:mi>i</mml:mi>
                    <mml:mi>T</mml:mi>
                  </mml:msubsup>
                  <mml:mi>φ</mml:mi>
                  <mml:mo>=</mml:mo>
                  <mml:msub>
                    <mml:mi>α</mml:mi>
                    <mml:mi>o</mml:mi>
                  </mml:msub>
                  <mml:mo>+</mml:mo>
                  <mml:mfrac>
                    <mml:mi>α</mml:mi>
                    <mml:mrow>
                      <mml:msub>
                        <mml:mi>d</mml:mi>
                        <mml:mi>i</mml:mi>
                      </mml:msub>
                    </mml:mrow>
                  </mml:mfrac>
                  <mml:mo>+</mml:mo>
                  <mml:msubsup>
                    <mml:mi>z</mml:mi>
                    <mml:mi>i</mml:mi>
                    <mml:mi>T</mml:mi>
                  </mml:msubsup>
                  <mml:mi>φ</mml:mi>
                </mml:mrow>
                <mml:annotation encoding="MathType-MTEF">
 MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacH8akY=wiFfYdH8Gipec8Eeeu0xXdbba9frFj0=OqFfea0dXdd9vqai=hGuQ8kuc9pgc9s8qqaq=dirpe0xb9q8qiLsFr0=vr0=vr0dc8meaabaqaciaacaGaaeqabaqabeGadaaakeaacyGGSbaBcqGGVbWBcqGGNbWziiGacqWF7oaBdaWgaaWcbaGaemyAaKgabeaakiabg2da9iab=f7aHnaaBaaaleaacqWGVbWBaeqaaOGaey4kaSIagiiBaWMaei4Ba8Maei4zaCMaem4zaC2aaSbaaSqaaiabigdaXaqabaGccqGGOaakcqWGKbazdaWgaaWcbaGaemyAaKgabeaakiabcUda7iab=H7aXjabcMcaPiabgUcaRiabdQha6naaDaaaleaacqWGPbqAaeaacqWGubavaaGccqWFgpGzcqGH9aqpcqWFXoqydaWgaaWcbaGaem4Ba8gabeaakiabgUcaRmaalaaabaGae8xSdegabaGaemizaq2aaSbaaSqaaiabdMgaPbqabaaaaOGaey4kaSIaemOEaO3aa0baaSqaaiabdMgaPbqaaiabdsfaubaakiab=z8aMbaa@5E6A@</mml:annotation>
              </mml:semantics>
            </mml:math>
          </disp-formula>
        </p>
        <p>where <italic>α</italic><sub><italic>o </italic></sub>= log <italic>η</italic>. Hence, <italic>η </italic>= exp(<italic>α</italic><sub><italic>o</italic></sub>) is a measure of the overall inflation of risk in the region under study, <italic>α </italic>represents the decay rate and <italic>ϕ </italic>is a vector of parameters of the area-specific covariates. One of the problems associated with the use of equation (7) is overdispersion (heterogeneity or spatial dependency) [<xref ref-type="bibr" rid="B36">36</xref>]. In the frequentist framework, we have assessed spatial autocorrelation by using any of the Moran's I statistics [<xref ref-type="bibr" rid="B37">37</xref>]. Other alternatives include Geary's C statistic [<xref ref-type="bibr" rid="B38">38</xref>] and non-parametric rank-based method [<xref ref-type="bibr" rid="B39">39</xref>]. The Bayesian approach is discussed in the next section.</p>
      </sec>
      <sec>
        <title>Bayesian hierarchical modelling</title>
        <p>To model the data while accommodating the expected heterogeneity and also including the spatial components (location or relative position of data values) of the data, Bayesian hierarchical modelling [<xref ref-type="bibr" rid="B33">33</xref>,<xref ref-type="bibr" rid="B40">40</xref>,<xref ref-type="bibr" rid="B41">41</xref>] was used. The implementation of this modelling was done with WINBUGS and GeoBugs software [<xref ref-type="bibr" rid="B42">42</xref>] for modelling aggregated data with plots and convergence diagnostic tests done using the <bold>coda </bold>package in R [<xref ref-type="bibr" rid="B43">43</xref>]. The mean or median of the posterior distribution is used as a point estimate of disease risk for each area. The modelling is explained in the following three stages:</p>
        <sec>
          <title>First-stage: model</title>
          <p>We incorporated two measures of overdispersion, so that equation (7) becomes</p>
          <p>
            <disp-formula id="bmcM8">
              <mml:math id="M2" name="1471-2288-7-39-i2" overflow="scroll">
                <mml:semantics definitionURL="" encoding="">
                  <mml:mrow>
                    <mml:mi>log</mml:mi>
                    <mml:mo>⁡</mml:mo>
                    <mml:msub>
                      <mml:mi>λ</mml:mi>
                      <mml:mi>i</mml:mi>
                    </mml:msub>
                    <mml:mo>=</mml:mo>
                    <mml:msub>
                      <mml:mi>α</mml:mi>
                      <mml:mi>o</mml:mi>
                    </mml:msub>
                    <mml:mo>+</mml:mo>
                    <mml:mi>α</mml:mi>
                    <mml:mo>/</mml:mo>
                    <mml:msub>
                      <mml:mi>d</mml:mi>
                      <mml:mi>i</mml:mi>
                    </mml:msub>
                    <mml:mo>+</mml:mo>
                    <mml:msubsup>
                      <mml:mi>z</mml:mi>
                      <mml:mi>i</mml:mi>
                      <mml:mi>T</mml:mi>
                    </mml:msubsup>
                    <mml:mi>φ</mml:mi>
                    <mml:mo>+</mml:mo>
                    <mml:msub>
                      <mml:mi>V</mml:mi>
                      <mml:mi>i</mml:mi>
                    </mml:msub>
                    <mml:mo>+</mml:mo>
                    <mml:msub>
                      <mml:mi>U</mml:mi>
                      <mml:mi>i</mml:mi>
                    </mml:msub>
                  </mml:mrow>
                  <mml:annotation encoding="MathType-MTEF">
 MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacH8akY=wiFfYdH8Gipec8Eeeu0xXdbba9frFj0=OqFfea0dXdd9vqai=hGuQ8kuc9pgc9s8qqaq=dirpe0xb9q8qiLsFr0=vr0=vr0dc8meaabaqaciaacaGaaeqabaqabeGadaaakeaacyGGSbaBcqGGVbWBcqGGNbWziiGacqWF7oaBdaWgaaWcbaGaemyAaKgabeaakiabg2da9iab=f7aHnaaBaaaleaacqWGVbWBaeqaaOGaey4kaSIae8xSdeMaei4la8Iaemizaq2aaSbaaSqaaiabdMgaPbqabaGccqGHRaWkcqWG6bGEdaqhaaWcbaGaemyAaKgabaGaemivaqfaaOGae8NXdyMaey4kaSIaemOvay1aaSbaaSqaaiabdMgaPbqabaGccqGHRaWkcqWGvbqvdaWgaaWcbaGaemyAaKgabeaaaaa@4CB1@</mml:annotation>
                </mml:semantics>
              </mml:math>
            </disp-formula>
          </p>
          <p>where <italic>V</italic><sub><italic>i </italic></sub>are unstructured random effects included in the model to capture the effects of unknown or unmeasured area level covariates. Hence, exp(<italic>V</italic><sub><italic>i</italic></sub>) will be equal to the residual or unexplained relative risk in each ED after adjusting for known area-specific covariates. We have included <italic>U</italic><sub><italic>i </italic></sub>in the model to capture our belief that the unstructured random effects (<italic>V</italic><sub><italic>i</italic></sub>) may exhibit some spatial structure.</p>
        </sec>
        <sec>
          <title>Second-stage: overdispersion modelling</title>
          <p>We assume that the unstructured random effects which is a measure of heterogeneity is of the form</p>
          <p>
            <disp-formula>
              <mml:math id="M3" name="1471-2288-7-39-i3" overflow="scroll">
                <mml:semantics definitionURL="" encoding="">
                  <mml:mrow>
                    <mml:mtable>
                      <mml:mtr>
                        <mml:mtd>
                          <mml:mrow>
                            <mml:msub>
                              <mml:mi>V</mml:mi>
                              <mml:mi>i</mml:mi>
                            </mml:msub>
                            <mml:mover>
                              <mml:mrow>
                                <mml:munder>
                                  <mml:mo>~</mml:mo>
                                  <mml:mrow/>
                                </mml:munder>
                              </mml:mrow>
                              <mml:mrow>
                                <mml:mi>i</mml:mi>
                                <mml:mi>i</mml:mi>
                                <mml:mi>d</mml:mi>
                              </mml:mrow>
                            </mml:mover>
                            <mml:mi>N</mml:mi>
                            <mml:mo stretchy="false">(</mml:mo>
                            <mml:mn>0</mml:mn>
                            <mml:mo>,</mml:mo>
                            <mml:msubsup>
                              <mml:mi>σ</mml:mi>
                              <mml:mi>v</mml:mi>
                              <mml:mn>2</mml:mn>
                            </mml:msubsup>
                            <mml:mo stretchy="false">)</mml:mo>
                          </mml:mrow>
                        </mml:mtd>
                        <mml:mtd>
                          <mml:mrow>
                            <mml:mi>i</mml:mi>
                            <mml:mo>=</mml:mo>
                            <mml:mn>1</mml:mn>
                            <mml:mo>,</mml:mo>
                            <mml:mn>...</mml:mn>
                            <mml:mo>,</mml:mo>
                            <mml:mi>n</mml:mi>
                          </mml:mrow>
                        </mml:mtd>
                      </mml:mtr>
                    </mml:mtable>
                  </mml:mrow>
                  <mml:annotation encoding="MathType-MTEF">
 MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacH8akY=wiFfYdH8Gipec8Eeeu0xXdbba9frFj0=OqFfea0dXdd9vqai=hGuQ8kuc9pgc9s8qqaq=dirpe0xb9q8qiLsFr0=vr0=vr0dc8meaabaqaciaacaGaaeqabaqabeGadaaakeaafaqabeqacaaabaGaemOvay1aaSbaaSqaaiabdMgaPbqabaGcdaWfGaqaamaaxababaGaeiOFa4haleaaaeqaaaqabeaacqWGPbqAcqWGPbqAcqWGKbazaaGccqWGobGtcqGGOaakcqaIWaamcqGGSaaliiGacqWFdpWCdaqhaaWcbaGaemODayhabaGaeGOmaidaaOGaeiykaKcabaGaemyAaKMaeyypa0JaeGymaeJaeiilaWIaeiOla4IaeiOla4IaeiOla4IaeiilaWIaemOBa4gaaaaa@47BA@</mml:annotation>
                </mml:semantics>
              </mml:math>
            </disp-formula>
          </p>
          <p>where <inline-formula><mml:math id="M4" name="1471-2288-7-39-i4" overflow="scroll"><mml:semantics definitionURL="" encoding=""><mml:mrow><mml:msubsup><mml:mi>σ</mml:mi><mml:mi>v</mml:mi><mml:mn>2</mml:mn></mml:msubsup></mml:mrow><mml:annotation encoding="MathType-MTEF">
 MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacH8akY=wiFfYdH8Gipec8Eeeu0xXdbba9frFj0=OqFfea0dXdd9vqai=hGuQ8kuc9pgc9s8qqaq=dirpe0xb9q8qiLsFr0=vr0=vr0dc8meaabaqaciaacaGaaeqabaqabeGadaaakeaaiiGacqWFdpWCdaqhaaWcbaGaemODayhabaGaeGOmaidaaaaa@310A@</mml:annotation></mml:semantics></mml:math></inline-formula> is a measure of the between-area variability of the <italic>V</italic><sub><italic>i</italic></sub>. Next, we specify the spatial random effect to model the anticipated spatial dependence of the log of relative risk. For a detailed review on the modelling of the spatial variability see Wakefield <italic>et al. </italic>[<xref ref-type="bibr" rid="B26">26</xref>,<xref ref-type="bibr" rid="B41">41</xref>].</p>
          <p>We specified the Markov random field (MRF) model using the intrinsic conditional autoregressive (CAR) proposed by Besag <italic>et al. </italic>[<xref ref-type="bibr" rid="B40">40</xref>]. We define ED <italic>i </italic>and <italic>j </italic>as neighbours if they share a common boundary [<xref ref-type="bibr" rid="B31">31</xref>,<xref ref-type="bibr" rid="B40">40</xref>,<xref ref-type="bibr" rid="B41">41</xref>]. We also define the spatial weights {<italic>W</italic><sub><italic>ij </italic></sub>: <italic>i </italic>= 1,..., <italic>n</italic>} as a binary contiguity matrix in which <italic>W</italic><sub><italic>ij </italic></sub>= 1 for neighbours and <italic>W</italic><sub><italic>ij </italic></sub>= 0 otherwise. Furthermore, <italic>W</italic><sub><italic>ii </italic></sub>= 0 and the constraint <inline-formula><mml:math id="M5" name="1471-2288-7-39-i5" overflow="scroll"><mml:semantics definitionURL="" encoding=""><mml:mrow><mml:mstyle displaystyle="true"><mml:msubsup><mml:mo>∑</mml:mo><mml:mrow><mml:mi>i</mml:mi><mml:mo>=</mml:mo><mml:mn>1</mml:mn></mml:mrow><mml:mi>n</mml:mi></mml:msubsup><mml:mrow><mml:msub><mml:mi>U</mml:mi><mml:mi>i</mml:mi></mml:msub><mml:mo>=</mml:mo><mml:mn>0</mml:mn></mml:mrow></mml:mstyle></mml:mrow><mml:annotation encoding="MathType-MTEF">
 MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacH8akY=wiFfYdH8Gipec8Eeeu0xXdbba9frFj0=OqFfea0dXdd9vqai=hGuQ8kuc9pgc9s8qqaq=dirpe0xb9q8qiLsFr0=vr0=vr0dc8meaabaqaciaacaGaaeqabaqabeGadaaakeaadaaeWaqaaiabdwfavnaaBaaaleaacqWGPbqAaeqaaOGaeyypa0JaeGimaadaleaacqWGPbqAcqGH9aqpcqaIXaqmaeaacqWGUbGBa0GaeyyeIuoaaaa@381C@</mml:annotation></mml:semantics></mml:math></inline-formula> is imposed for identifiability.</p>
        </sec>
        <sec>
          <title>Third-stage: prior distributions</title>
          <p>At this stage all the parameters (<italic>α</italic><sub><italic>o</italic></sub>, <italic>α</italic>, <italic>ϕ</italic>, <inline-formula><mml:math id="M6" name="1471-2288-7-39-i6" overflow="scroll"><mml:semantics definitionURL="" encoding=""><mml:mrow><mml:msubsup><mml:mi>σ</mml:mi><mml:mi>v</mml:mi><mml:mrow><mml:mo>−</mml:mo><mml:mn>2</mml:mn></mml:mrow></mml:msubsup></mml:mrow><mml:annotation encoding="MathType-MTEF">
 MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacH8akY=wiFfYdH8Gipec8Eeeu0xXdbba9frFj0=OqFfea0dXdd9vqai=hGuQ8kuc9pgc9s8qqaq=dirpe0xb9q8qiLsFr0=vr0=vr0dc8meaabaqaciaacaGaaeqabaqabeGadaaakeaaiiGacqWFdpWCdaqhaaWcbaGaemODayhabaGaeyOeI0IaeGOmaidaaaaa@31F7@</mml:annotation></mml:semantics></mml:math></inline-formula> and <inline-formula><mml:math id="M7" name="1471-2288-7-39-i7" overflow="scroll"><mml:semantics definitionURL="" encoding=""><mml:mrow><mml:msubsup><mml:mi>σ</mml:mi><mml:mi>u</mml:mi><mml:mrow><mml:mo>−</mml:mo><mml:mn>2</mml:mn></mml:mrow></mml:msubsup></mml:mrow><mml:annotation encoding="MathType-MTEF">
 MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacH8akY=wiFfYdH8Gipec8Eeeu0xXdbba9frFj0=OqFfea0dXdd9vqai=hGuQ8kuc9pgc9s8qqaq=dirpe0xb9q8qiLsFr0=vr0=vr0dc8meaabaqaciaacaGaaeqabaqabeGadaaakeaaiiGacqWFdpWCdaqhaaWcbaGaemyDauhabaGaeyOeI0IaeGOmaidaaaaa@31F5@</mml:annotation></mml:semantics></mml:math></inline-formula>) of the model are assigned a prior distribution. <italic>α</italic><sub><italic>o </italic></sub>was assigned a flat prior which corresponds to a uniform distribution over the whole real line. <italic>α</italic>, and <italic>ϕ</italic><sub><italic>i</italic></sub>were assigned a normal (0, 10<sup>5</sup>). The choice of prior for <inline-formula><mml:math id="M8" name="1471-2288-7-39-i6" overflow="scroll"><mml:semantics definitionURL="" encoding=""><mml:mrow><mml:msubsup><mml:mi>σ</mml:mi><mml:mi>v</mml:mi><mml:mrow><mml:mo>−</mml:mo><mml:mn>2</mml:mn></mml:mrow></mml:msubsup></mml:mrow><mml:annotation encoding="MathType-MTEF">
 MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacH8akY=wiFfYdH8Gipec8Eeeu0xXdbba9frFj0=OqFfea0dXdd9vqai=hGuQ8kuc9pgc9s8qqaq=dirpe0xb9q8qiLsFr0=vr0=vr0dc8meaabaqaciaacaGaaeqabaqabeGadaaakeaaiiGacqWFdpWCdaqhaaWcbaGaemODayhabaGaeyOeI0IaeGOmaidaaaaa@31F7@</mml:annotation></mml:semantics></mml:math></inline-formula> and <inline-formula><mml:math id="M9" name="1471-2288-7-39-i7" overflow="scroll"><mml:semantics definitionURL="" encoding=""><mml:mrow><mml:msubsup><mml:mi>σ</mml:mi><mml:mi>u</mml:mi><mml:mrow><mml:mo>−</mml:mo><mml:mn>2</mml:mn></mml:mrow></mml:msubsup></mml:mrow><mml:annotation encoding="MathType-MTEF">
 MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacH8akY=wiFfYdH8Gipec8Eeeu0xXdbba9frFj0=OqFfea0dXdd9vqai=hGuQ8kuc9pgc9s8qqaq=dirpe0xb9q8qiLsFr0=vr0=vr0dc8meaabaqaciaacaGaaeqabaqabeGadaaakeaaiiGacqWFdpWCdaqhaaWcbaGaemyDauhabaGaeyOeI0IaeGOmaidaaaaa@31F5@</mml:annotation></mml:semantics></mml:math></inline-formula> is a very challenging one and it has to be done carefully. Many authors have favoured the use of gamma (a, b) for both <inline-formula><mml:math id="M10" name="1471-2288-7-39-i6" overflow="scroll"><mml:semantics definitionURL="" encoding=""><mml:mrow><mml:msubsup><mml:mi>σ</mml:mi><mml:mi>v</mml:mi><mml:mrow><mml:mo>−</mml:mo><mml:mn>2</mml:mn></mml:mrow></mml:msubsup></mml:mrow><mml:annotation encoding="MathType-MTEF">
 MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacH8akY=wiFfYdH8Gipec8Eeeu0xXdbba9frFj0=OqFfea0dXdd9vqai=hGuQ8kuc9pgc9s8qqaq=dirpe0xb9q8qiLsFr0=vr0=vr0dc8meaabaqaciaacaGaaeqabaqabeGadaaakeaaiiGacqWFdpWCdaqhaaWcbaGaemODayhabaGaeyOeI0IaeGOmaidaaaaa@31F7@</mml:annotation></mml:semantics></mml:math></inline-formula> and <inline-formula><mml:math id="M11" name="1471-2288-7-39-i7" overflow="scroll"><mml:semantics definitionURL="" encoding=""><mml:mrow><mml:msubsup><mml:mi>σ</mml:mi><mml:mi>u</mml:mi><mml:mrow><mml:mo>−</mml:mo><mml:mn>2</mml:mn></mml:mrow></mml:msubsup></mml:mrow><mml:annotation encoding="MathType-MTEF">
 MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacH8akY=wiFfYdH8Gipec8Eeeu0xXdbba9frFj0=OqFfea0dXdd9vqai=hGuQ8kuc9pgc9s8qqaq=dirpe0xb9q8qiLsFr0=vr0=vr0dc8meaabaqaciaacaGaaeqabaqabeGadaaakeaaiiGacqWFdpWCdaqhaaWcbaGaemyDauhabaGaeyOeI0IaeGOmaidaaaaa@31F5@</mml:annotation></mml:semantics></mml:math></inline-formula> because it is a conjugate prior in the normal model but the choice of <italic>a </italic>and <italic>b </italic>is what they have not agreed on [<xref ref-type="bibr" rid="B31">31</xref>-<xref ref-type="bibr" rid="B33">33</xref>,<xref ref-type="bibr" rid="B36">36</xref>,<xref ref-type="bibr" rid="B40">40</xref>,<xref ref-type="bibr" rid="B41">41</xref>]. In our case, we have assigned gamma (0.1, 0.1) to both <inline-formula><mml:math id="M12" name="1471-2288-7-39-i6" overflow="scroll"><mml:semantics definitionURL="" encoding=""><mml:mrow><mml:msubsup><mml:mi>σ</mml:mi><mml:mi>v</mml:mi><mml:mrow><mml:mo>−</mml:mo><mml:mn>2</mml:mn></mml:mrow></mml:msubsup></mml:mrow><mml:annotation encoding="MathType-MTEF">
 MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacH8akY=wiFfYdH8Gipec8Eeeu0xXdbba9frFj0=OqFfea0dXdd9vqai=hGuQ8kuc9pgc9s8qqaq=dirpe0xb9q8qiLsFr0=vr0=vr0dc8meaabaqaciaacaGaaeqabaqabeGadaaakeaaiiGacqWFdpWCdaqhaaWcbaGaemODayhabaGaeyOeI0IaeGOmaidaaaaa@31F7@</mml:annotation></mml:semantics></mml:math></inline-formula> and <inline-formula><mml:math id="M13" name="1471-2288-7-39-i7" overflow="scroll"><mml:semantics definitionURL="" encoding=""><mml:mrow><mml:msubsup><mml:mi>σ</mml:mi><mml:mi>u</mml:mi><mml:mrow><mml:mo>−</mml:mo><mml:mn>2</mml:mn></mml:mrow></mml:msubsup></mml:mrow><mml:annotation encoding="MathType-MTEF">
 MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacH8akY=wiFfYdH8Gipec8Eeeu0xXdbba9frFj0=OqFfea0dXdd9vqai=hGuQ8kuc9pgc9s8qqaq=dirpe0xb9q8qiLsFr0=vr0=vr0dc8meaabaqaciaacaGaaeqabaqabeGadaaakeaaiiGacqWFdpWCdaqhaaWcbaGaemyDauhabaGaeyOeI0IaeGOmaidaaaaa@31F5@</mml:annotation></mml:semantics></mml:math></inline-formula> and carry out sensitivity analysis with all the priors given in [<xref ref-type="bibr" rid="B31">31</xref>-<xref ref-type="bibr" rid="B33">33</xref>,<xref ref-type="bibr" rid="B36">36</xref>,<xref ref-type="bibr" rid="B40">40</xref>,<xref ref-type="bibr" rid="B41">41</xref>].</p>
          <p>The models were fitted using Markov Chain Monte Carlo (MCMC) simulation method [<xref ref-type="bibr" rid="B44">44</xref>]. Five separate chains starting from different initial values were run for each model. Convergence was assessed by visual examination of time series plots for each parameter and by carrying out the Gelman and Rubin diagnostic test [<xref ref-type="bibr" rid="B45">45</xref>] based on the ratio of between to within chain variances for each model. The time series plots with all the five chains superimposed were examined to see whether the chains were mixing well. Goodness of fit was examined using the Deviance Information Criterion (DIC) [<xref ref-type="bibr" rid="B46">46</xref>] which consists of two terms, one is a measure of goodness of fit and the other is a penalty for increasing model complexity so that smaller values of DIC indicate a better-fitting model.</p>
          <p>We defined a quantity <italic>ψ </italic>= <italic>σ</italic><sub><italic>u</italic></sub>/(<italic>σ</italic><sub><italic>u </italic></sub>+ <italic>σ</italic><sub><italic>v</italic></sub>) as a measure of the relative contribution of <italic>U</italic><sub><italic>i </italic></sub>and <italic>V</italic><sub><italic>i </italic></sub>to the total overdispersion [<xref ref-type="bibr" rid="B33">33</xref>]. So that as <italic>ψ </italic>→ 1, spatial variation dominates, while as <italic>ψ </italic>→ 0, spatial variation becomes negligible.</p>
        </sec>
      </sec>
      <sec>
        <title>Poisson regression</title>
        <p>For <italic>Y</italic><sub><italic>i </italic></sub>~ Poisson(<italic>μ</italic><sub><italic>i</italic></sub>), where <italic>μ</italic><sub><italic>i </italic></sub>= <italic>λ</italic><sub><italic>i</italic></sub>E<sub><italic>i </italic></sub>(<italic>i </italic>= 1,..., <italic>n</italic>), we assume the generalized linear model [<xref ref-type="bibr" rid="B47">47</xref>]. Four models were fitted for the log relative risk (log <italic>λ</italic><sub><italic>i </italic></sub>= log <italic>μ</italic><sub><italic>i </italic></sub>- log <italic>E</italic><sub><italic>i</italic></sub>) in terms of a constant, area-level covariates and the reciprocal of distance. The fitted models are:</p>
        <p>
          <disp-formula id="bmcM9">log <italic>λ</italic><sub><italic>i </italic></sub>= <italic>α</italic><sub><italic>o</italic></sub></disp-formula>
        </p>
        <p>
          <disp-formula id="bmcM10">log <italic>λ</italic><sub><italic>i </italic></sub>= <italic>α</italic><sub><italic>o </italic></sub>+ <italic>α</italic>/<italic>d</italic><sub><italic>i</italic></sub></disp-formula>
        </p>
        <p>
          <disp-formula id="bmcM11">log <italic>λ</italic><sub><italic>i </italic></sub>= <italic>α</italic><sub><italic>o </italic></sub>+ <italic>ϕ</italic><sub>1</sub><italic>x</italic><sub>1 </sub>+ <italic>ϕ</italic><sub>2</sub><italic>x</italic><sub>2 </sub>+ <italic>ϕ</italic><sub>3</sub><italic>x</italic><sub>3 </sub>+ <italic>ϕ</italic><sub>4</sub><italic>x</italic><sub>4 </sub>+ <italic>ϕ</italic><sub>5</sub><italic>x</italic><sub>5</sub></disp-formula>
        </p>
        <p>
          <disp-formula id="bmcM12">log <italic>λ</italic><sub><italic>i </italic></sub>= <italic>α</italic><sub><italic>o </italic></sub>+ <italic>α</italic>/<italic>d</italic><sub><italic>i </italic></sub>+ <italic>ϕ</italic><sub>1</sub><italic>x</italic><sub>1 </sub>+ <italic>ϕ</italic><sub>2</sub><italic>x</italic><sub>2 </sub>+ <italic>ϕ</italic><sub>3</sub><italic>x</italic><sub>3 </sub>+ <italic>ϕ</italic><sub>4</sub><italic>x</italic><sub>4 </sub>+ <italic>ϕ</italic><sub>5</sub><italic>x</italic><sub>5</sub></disp-formula>
        </p>
        <p>No random effects or spatial effects was included. In each of the fitted models, log <italic>E</italic><sub><italic>i </italic></sub>is used as an offset to account for variations in <italic>λ</italic><sub><italic>i </italic></sub>over the study region. The models were fitted using the quasi-likelihood approach to account for the overdispersion that might occur in the data set. The dispersion parameter, <italic>κ</italic>, was estimated by the mean of the Pearson <italic>χ</italic><sup>2 </sup>statistic.</p>
      </sec>
      <sec>
        <title>Weighted linear regression</title>
        <p>A weighted regression approach was carried out to account for the dispersion that might result from the violation of the constant variance assumption in the least squares approach. The last three models (equations 10, 11 and 12) were fitted using weighted least square regression by replacing <italic>λ</italic><sub><italic>i </italic></sub>with the SIR (<inline-formula><mml:math id="M14" name="1471-2288-7-39-i8" overflow="scroll"><mml:semantics definitionURL="" encoding=""><mml:mrow><mml:msub><mml:mover accent="true"><mml:mi>λ</mml:mi><mml:mo>^</mml:mo></mml:mover><mml:mi>i</mml:mi></mml:msub></mml:mrow><mml:annotation encoding="MathType-MTEF">
 MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacH8akY=wiFfYdH8Gipec8Eeeu0xXdbba9frFj0=OqFfea0dXdd9vqai=hGuQ8kuc9pgc9s8qqaq=dirpe0xb9q8qiLsFr0=vr0=vr0dc8meaabaqaciaacaGaaeqabaqabeGadaaakeaaiiGacuWF7oaBgaqcamaaBaaaleaacqWGPbqAaeqaaaaa@2FFE@</mml:annotation></mml:semantics></mml:math></inline-formula> = <italic>Y</italic><sub><italic>i</italic></sub><italic>/E</italic><sub><italic>i</italic></sub>). The weights (<italic>w</italic><sub><italic>i</italic></sub>) were set equal to <inline-formula><mml:math id="M15" name="1471-2288-7-39-i9" overflow="scroll"><mml:semantics definitionURL="" encoding=""><mml:mrow><mml:msub><mml:mi>E</mml:mi><mml:mi>i</mml:mi></mml:msub><mml:mo>/</mml:mo><mml:mstyle displaystyle="true"><mml:msubsup><mml:mo>∑</mml:mo><mml:mrow><mml:mi>i</mml:mi><mml:mo>=</mml:mo><mml:mn>1</mml:mn></mml:mrow><mml:mi>n</mml:mi></mml:msubsup><mml:mrow><mml:msub><mml:mi>E</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:mrow></mml:mstyle></mml:mrow><mml:annotation encoding="MathType-MTEF">
 MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacH8akY=wiFfYdH8Gipec8Eeeu0xXdbba9frFj0=OqFfea0dXdd9vqai=hGuQ8kuc9pgc9s8qqaq=dirpe0xb9q8qiLsFr0=vr0=vr0dc8meaabaqaciaacaGaaeqabaqabeGadaaakeaacqWGfbqrdaWgaaWcbaGaemyAaKgabeaakiabc+caVmaaqadabaGaemyrau0aaSbaaSqaaiabdMgaPbqabaaabaGaemyAaKMaeyypa0JaeGymaedabaGaemOBa4ganiabggHiLdaaaa@397D@</mml:annotation></mml:semantics></mml:math></inline-formula> so that the error sum of squares (<italic>Q</italic>) of the weighted linear regression can be written as</p>
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        </p>
        <p>Here, we have not included the spatial component of the model because we have seen that the SIR does not exhibit spatial dependency during our exploratory data analysis.</p>
      </sec>
    </sec>
    <sec>
      <title>Results</title>
      <p>In the following subsections, we explain the results of the exploratory data analysis and modelling.</p>
      <sec>
        <title>Exploratory data analysis</title>
        <p>Plot of unadjusted standardized incidence ratios (SIR) against distance in km from the Tar Pond is shown in Figure <xref ref-type="fig" rid="F1">1</xref>. From the plots, areas with SIR less than 1 indicate no risk or absolute risk reduction while SIR greater than 1 indicate high risk of preterm birth compared to the rest of Canada. All the high values of SIR occurred within the 20 km distance from the Tar Pond. There is some evidence of decrease in risk from source as we move further away but this will be tested statistically in the next sections. However, as explained earlier, care has to be taken when interpreting the crude SIR. To illustrate this, we plotted the SIR against the population at risk (see Figure <xref ref-type="fig" rid="F2">2</xref>). This graph clearly shows that areas with low population at risk tend to show high variability in SIR. We accounted for this by using the Poisson model regression for aggregated data.</p>
        <fig position="float" id="F1">
          <label>Figure 1</label>
          <caption>
            <p><bold>Plot of SIR against distance</bold>. Plot of unadjusted standardized incidence ratios against distance in km from the Tar Pond.</p>
          </caption>
          <graphic xlink:href="1471-2288-7-39-1"/>
        </fig>
        <fig position="float" id="F2">
          <label>Figure 2</label>
          <caption>
            <p><bold>Plot of SIR</bold>. Plot of SIR versus population at risk and other area-specific covariates.</p>
          </caption>
          <graphic xlink:href="1471-2288-7-39-2"/>
        </fig>
      </sec>
      <sec>
        <title>Area-specific risk</title>
        <p>Following Pampalon and Raymond [<xref ref-type="bibr" rid="B21">21</xref>], the following area-specific variables were considered for the analysis: the proportion of persons who have no high school diploma, the rate of unemployment, average income, the proportion of persons who are separated, divorced or widowed, the proportion of single parent families and the proportion of people living alone.</p>
        <p>Only five of the variables are available at all the 144 EDs with average income available only in 130 EDs. Hence, we could not compute an adequate measure of deprivation based on the method proposed by Pampalon and Raymond. We decided to assess the effect of each of the variables separately leaving out average income. Distance from the Tar Pond site and all the area-specific variables were plotted against SIR to assess the effect of each. The plots are given in Figure <xref ref-type="fig" rid="F2">2</xref>.</p>
        <p>As explained earlier, points below the dotted line indicate no risk or absolute risk reduction and vice versa. The plot of SIR and the rate of unemployment shows an upward trend with high unemployment rates associated with high SIR. A similar pattern is displayed by the plot of SIR against proportion of persons with no high school diploma. In the plot of the SIR against proportion of separated, divorced and widowed areas with low proportion of separated, divorced and widowed tend to have high SIR. A similar pattern is seen in the plot of SIR and proportion of people living alone. There is no obvious pattern in the plot of SIR against proportion of single parent families.</p>
      </sec>
      <sec>
        <title>Test for spatial dependency</title>
        <p>One of the objectives of this study is to check for any clustering of events around the Tar Pond that may be significant in explaining the variation in preterm birth rates. This was done by plotting the maps of all the variables (Figure <xref ref-type="fig" rid="F3">3</xref>, <xref ref-type="fig" rid="F4">4</xref>, <xref ref-type="fig" rid="F5">5</xref>, <xref ref-type="fig" rid="F6">6</xref>, <xref ref-type="fig" rid="F7">7</xref>, <xref ref-type="fig" rid="F8">8</xref>) and visually assessing whether there is any clustering, and by performing a formal test of clustering using the Moran I statistic [<xref ref-type="bibr" rid="B37">37</xref>].</p>
        <fig position="float" id="F3">
          <label>Figure 3</label>
          <caption>
            <p><bold>Map of SIR</bold>. A map showing the unadjusted standardized incidence ratios for preterm birth.</p>
          </caption>
          <graphic xlink:href="1471-2288-7-39-3"/>
        </fig>
        <fig position="float" id="F4">
          <label>Figure 4</label>
          <caption>
            <p><bold>Map of people living alone</bold>. A map showing the percentage of people living alone.</p>
          </caption>
          <graphic xlink:href="1471-2288-7-39-4"/>
        </fig>
        <fig position="float" id="F5">
          <label>Figure 5</label>
          <caption>
            <p><bold>Map of rate of unemployment</bold>. A map showing the rate of unemployment to population.</p>
          </caption>
          <graphic xlink:href="1471-2288-7-39-5"/>
        </fig>
        <fig position="float" id="F6">
          <label>Figure 6</label>
          <caption>
            <p><bold>Map of persons separated, divorced or widowed</bold>. A map showing the percentage of persons who are separated, divorced or widowed.</p>
          </caption>
          <graphic xlink:href="1471-2288-7-39-6"/>
        </fig>
        <fig position="float" id="F7">
          <label>Figure 7</label>
          <caption>
            <p><bold>Map of single parent families</bold>. A map showing the percentage of single parent families.</p>
          </caption>
          <graphic xlink:href="1471-2288-7-39-7"/>
        </fig>
        <fig position="float" id="F8">
          <label>Figure 8</label>
          <caption>
            <p><bold>Map of persons who have no high school diploma</bold>. A map showing the percentage of persons who have no high school diploma.</p>
          </caption>
          <graphic xlink:href="1471-2288-7-39-8"/>
        </fig>
        <p>The map of SIR (Figure <xref ref-type="fig" rid="F3">3</xref>) was examined to see whether there is a cluster of high SIR around the Tar Pond or a decrease in the SIR as we move further away from the Tar Pond but neither of the two is obvious from the map. The maps of all the area-covariates (Figure <xref ref-type="fig" rid="F4">4</xref>, <xref ref-type="fig" rid="F5">5</xref>, <xref ref-type="fig" rid="F6">6</xref>, <xref ref-type="fig" rid="F7">7</xref>, <xref ref-type="fig" rid="F8">8</xref>) were examined to assess whether there is any spatial pattern. The plot of percentage of people living alone shows a pattern with the highest proportion of people living alone occurring within the 20 km radius of the Tar Pond site. The plot of the rate of unemployment to population also shows that the unemployment to population ratio decreases as we move further away from the Tar Pond. Furthermore, the proportion of persons who have no high school diploma also displays some spatial pattern with some of the areas close to the Tar Pond having high proportion. Existence of spatial autocorrelation was also tested formally using the Moran I test. Results of the spatial autocorrelation analysis given in Table <xref ref-type="table" rid="T1">1</xref>, show the correlation, standard error, corresponding normal statistic and associated <italic>p</italic>-value. The results indicate that there is significant autocorrelation for all the covariates with the exception of SIR (<italic>p </italic>= 0.5387). However, a more confirmatory test is required. The result of the autocorrelation not being statistically significant could be due to different reasons (1) there is none; or (2) small populations which may give rise to high SIR [<xref ref-type="bibr" rid="B39">39</xref>].</p>
        <table-wrap position="float" id="T1">
          <label>Table 1</label>
          <caption>
            <p>Results of spatial autocorrelation analysis using Moran I statistics</p>
          </caption>
          <table frame="hsides" rules="groups">
            <thead>
              <tr>
                <td align="center">Variables</td>
                <td align="center">Correlation</td>
                <td align="center">Std. Error</td>
                <td align="center">Normal statistic</td>
                <td align="center">Normal <italic>p</italic>-value</td>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td align="center">SIR</td>
                <td align="center">-0.03798</td>
                <td align="center">0.05041</td>
                <td align="center">-0.6148</td>
                <td align="center">0.5387</td>
              </tr>
              <tr>
                <td align="center">
                  <italic>x</italic>
                  <sub>1</sub>
                </td>
                <td align="center">0.348</td>
                <td align="center">0.05041</td>
                <td align="center">7.043</td>
                <td align="center"><italic>p </italic>&lt; 0.0001</td>
              </tr>
              <tr>
                <td align="center">
                  <italic>x</italic>
                  <sub>2</sub>
                </td>
                <td align="center">0.4582</td>
                <td align="center">0.05041</td>
                <td align="center">9.229</td>
                <td align="center"><italic>p </italic>&lt; 0.0001</td>
              </tr>
              <tr>
                <td align="center">
                  <italic>x</italic>
                  <sub>3</sub>
                </td>
                <td align="center">0.1924</td>
                <td align="center">0.05041</td>
                <td align="center">3.955</td>
                <td align="center"><italic>p </italic>&lt; 0.0001</td>
              </tr>
              <tr>
                <td align="center">
                  <italic>x</italic>
                  <sub>4</sub>
                </td>
                <td align="center">0.4051</td>
                <td align="center">0.05041</td>
                <td align="center">8.174</td>
                <td align="center"><italic>p </italic>&lt; 0.0001</td>
              </tr>
              <tr>
                <td align="center">
                  <italic>x</italic>
                  <sub>5</sub>
                </td>
                <td align="center">0.2932</td>
                <td align="center">0.05041</td>
                <td align="center">5.955</td>
                <td align="center"><italic>p </italic>&lt; 0.0001</td>
              </tr>
            </tbody>
          </table>
        </table-wrap>
      </sec>
      <sec>
        <title>Bayesian analysis results</title>
        <p>The following four models were fitted using the five area covariates available at all the 144 EDs and a measure of proximity (<italic>d</italic><sub><italic>i</italic></sub>): Model 1 which contains no covariates and corresponds to the null model; Model 2 which contains the distance measure alone; Model 3 with deprivation covariates alone; and finally, Model 4 with distance and deprivation covariates.</p>
        <p>The Gelman Rubin Plots shows that the "shrinkage factor" for each parameter approaches 1. Hence, all chains have escaped the influence of their starting points. The autocorrelation plots shows that autocorrelation decrease rapidly from lag 1. On this basis, the first 2000 samples of each chain were discarded as 'burn-in'; each chain was run for a further 10,000 iterations, and posterior estimates were based on pooling the 5 × 10, 000 samples for each model. This gave Monte Carlo standard errors that are less than 1% of the posterior standard deviation for each parameter. All the plots including the posterior density of each parameter after convergence are provided as additional file <xref ref-type="supplementary-material" rid="S1">1</xref> (Bayesian diagnostic  plots). All the plots were produced with the <bold>coda </bold>package for R [<xref ref-type="bibr" rid="B43">43</xref>].</p>
        <p>Table <xref ref-type="table" rid="T2">2</xref> gives the summaries of the posterior distribution under each model. From Table <xref ref-type="table" rid="T2">2</xref>, we can see that estimates of <italic>α </italic>in both Models 2 and 4 are negative, and the 95% credible intervals contain zero which shows that there is no significant association between distance from the Tar Ponds and risk of preterm birth. The 95% credible interval for <italic>ϕ</italic><sub><italic>i </italic></sub>(<italic>i </italic>= 1,..., 5) in Models 3 and 4 also contain zero which shows that the change in risk cannot be explained by any of the socio-economic covariates. For each of the models, <italic>η</italic>, a measure of the overall risk, was found to be greater than 1 which is evidence that there is an increased risk of preterm birth in the entire Cape Breton region compared to the rest of Canada.</p>
        <table-wrap position="float" id="T2">
          <label>Table 2</label>
          <caption>
            <p>Bayesian posterior median (95% credible interval), summaries of model fit (DIC) and complexity (<italic>p</italic><sub><italic>D</italic></sub>)</p>
          </caption>
          <table frame="hsides" rules="groups">
            <thead>
              <tr>
                <td align="center">Nodes</td>
                <td align="center">Model 1</td>
                <td align="center">Model 2</td>
                <td align="center">Model 3</td>
                <td align="center">Model 4</td>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td align="center">
                  <italic>α</italic>
                </td>
                <td align="center">-</td>
                <td align="center">-0.097 (-0.326,0.120)</td>
                <td align="center">-</td>
                <td align="center">-0.087 (-0.317,0.130)</td>
              </tr>
              <tr>
                <td align="center">
                  <italic>α</italic>
                  <sub>
                    <italic>o</italic>
                  </sub>
                </td>
                <td align="center">0.246 (0.188,0.305)</td>
                <td align="center">0.268 (0.193,0.343)</td>
                <td align="center">0.241 (0.182,0.300)</td>
                <td align="center">0.260 (0.183,0.336)</td>
              </tr>
              <tr>
                <td align="center">
                  <italic>ϕ</italic>
                  <sub>1</sub>
                </td>
                <td align="center">-</td>
                <td align="center">-</td>
                <td align="center">-0.019 (-0.108,0.070)</td>
                <td align="center">-0.019 (-0.107,0.072)</td>
              </tr>
              <tr>
                <td align="center">
                  <italic>ϕ</italic>
                  <sub>2</sub>
                </td>
                <td align="center">-</td>
                <td align="center">-</td>
                <td align="center">-0.001 (-0.080,0.077)</td>
                <td align="center">0.001 (-0.079,0.080)</td>
              </tr>
              <tr>
                <td align="center">
                  <italic>ϕ</italic>
                  <sub>3</sub>
                </td>
                <td align="center">-</td>
                <td align="center">-</td>
                <td align="center">0.051 (-0.091,0.195)</td>
                <td align="center">0.049 (-0.092,0.189)</td>
              </tr>
              <tr>
                <td align="center">
                  <italic>ϕ</italic>
                  <sub>4</sub>
                </td>
                <td align="center">-</td>
                <td align="center">-</td>
                <td align="center">0.008 (-0.102,0.118)</td>
                <td align="center">0.008 (-0.101,0.116)</td>
              </tr>
              <tr>
                <td align="center">
                  <italic>ϕ</italic>
                  <sub>5</sub>
                </td>
                <td align="center">-</td>
                <td align="center">-</td>
                <td align="center">-0.002 (-0.093,0.090)</td>
                <td align="center">-0.002 (-0.092,0.090)</td>
              </tr>
              <tr>
                <td align="center">
                  <italic>ψ</italic>
                </td>
                <td align="center">0.557 (0.428,0.676)</td>
                <td align="center">0.559 (0.434,0.679)</td>
                <td align="center">0.555 (0.426,0.677)</td>
                <td align="center">0.558 (0.430,0.682)</td>
              </tr>
              <tr>
                <td align="center">
                  <italic>η</italic>
                </td>
                <td align="center">1.279 (1.207,1.356)</td>
                <td align="center">1.307 (1.212,1.409)</td>
                <td align="center">1.272 (1.200,1.349)</td>
                <td align="center">1.297 (1.201,1.400)</td>
              </tr>
              <tr>
                <td align="center">
                  <italic>σ</italic>
                  <sub>
                    <italic>u</italic>
                  </sub>
                </td>
                <td align="center">0.187 (0.125,0.281)</td>
                <td align="center">0.189 (0.127,0.283)</td>
                <td align="center">0.185 (0.124,0.282)</td>
                <td align="center">0.187 (0.126,0.287)</td>
              </tr>
              <tr>
                <td align="center">
                  <italic>σ</italic>
                  <sub>
                    <italic>v</italic>
                  </sub>
                </td>
                <td align="center">0.149 (0.109,0.204)</td>
                <td align="center">0.149 (0.110,0.204)</td>
                <td align="center">0.149 (0.108,0.204)</td>
                <td align="center">0.149 (0.108,0.203)</td>
              </tr>
              <tr>
                <td align="center">DIC</td>
                <td align="center">727.934</td>
                <td align="center">728.672</td>
                <td align="center">732.164</td>
                <td align="center">734.653</td>
              </tr>
              <tr>
                <td align="center">
                  <italic>p</italic>
                  <sub>
                    <italic>D</italic>
                  </sub>
                </td>
                <td align="center">38.419</td>
                <td align="center">39.208</td>
                <td align="center">42.915</td>
                <td align="center">41.094</td>
              </tr>
            </tbody>
          </table>
        </table-wrap>
        <p>The parameters, <italic>σ</italic><sub><italic>u </italic></sub>and <italic>σ</italic><sub><italic>v </italic></sub>change only slightly over the four models. From Table <xref ref-type="table" rid="T2">2</xref>, the 95% credible intervals for <italic>ψ </italic>for each model contain 0.5. Hence, there is no clear evidence that the spatial structure dominates the random effect in any of the models. From the results of Table <xref ref-type="table" rid="T2">2</xref>, the DIC increases as more variables are added into the model. Hence, Model 1 is better than all three other models. Finally, the posterior median of the relative risk of preterm birth were plotted against distance in km from the Tar pond. The plot is shown in Figure <xref ref-type="fig" rid="F9">9</xref>.</p>
        <fig position="float" id="F9">
          <label>Figure 9</label>
          <caption>
            <p><bold>Plot of posterior medians</bold>. Plot of the posterior medians of relative risk against distance from Tar Pond in km.</p>
          </caption>
          <graphic xlink:href="1471-2288-7-39-9"/>
        </fig>
        <p>A comparison of the plots with that of Figure <xref ref-type="fig" rid="F1">1</xref> shows there is a high relative risk (greater than 1) of preterm birth in almost all the enumeration districts. However, the risk is not as high in Figure <xref ref-type="fig" rid="F9">9</xref> as in Figure <xref ref-type="fig" rid="F1">1</xref>. The plots also show that there is no clear relationship between distance and risk. This result is consistent with the results of two of the studies conducted in this area using primary data [<xref ref-type="bibr" rid="B1">1</xref>,<xref ref-type="bibr" rid="B3">3</xref>]. They both concluded that a causal association between preterm births and maternal/residential proximity to the Tar Ponds could not be inferred from the statistical analysis. A map showing the posterior median of the relative risk of preterm births for Model 4 is shown in Figure <xref ref-type="fig" rid="F10">10</xref>.</p>
        <fig position="float" id="F10">
          <label>Figure 10</label>
          <caption>
            <p><bold>Map of posterior medians</bold>. A map showing the posterior median of the relative risk of preterm births for Model 4.</p>
          </caption>
          <graphic xlink:href="1471-2288-7-39-10"/>
        </fig>
      </sec>
      <sec>
        <title>Poisson regression analysis results</title>
        <p>The results of all four models are displayed in Table <xref ref-type="table" rid="T3">3</xref>. For each of the fitted models, <italic>κ </italic>was estimated to be approximately equal to 1, a condition that shows that there is no evidence of overdispersion. The Wald confidence intervals shown in Table <xref ref-type="table" rid="T3">3</xref> are based on the asymptotic normality of the parameter estimators. From the table, we can see that the estimated <italic>α </italic>in both Models 2 and 4 is negative, and the 95% Wald confidence intervals contain zero which is evidence that there is no decrease in risk as distance from Tar pond decreases.</p>
        <table-wrap position="float" id="T3">
          <label>Table 3</label>
          <caption>
            <p>Poisson regression parameter estimates (95% Wald CI), residual deviance and over-dispersion parameter</p>
          </caption>
          <table frame="hsides" rules="groups">
            <thead>
              <tr>
                <td align="center">Parameter</td>
                <td align="center">Model 1</td>
                <td align="center">Model 2</td>
                <td align="center">Model 3</td>
                <td align="center">Model 4</td>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td align="center">
                  <italic>α</italic>
                </td>
                <td align="center">-</td>
                <td align="center">-0.0878(-0.2519,0.0763)</td>
                <td align="center">-</td>
                <td align="center">-0.075 (-0.239,0.089)</td>
              </tr>
              <tr>
                <td align="center">
                  <italic>α</italic>
                  <sub>
                    <italic>o</italic>
                  </sub>
                </td>
                <td align="center">0.2520</td>
                <td align="center">0.2707 (0.2111,0.3303)</td>
                <td align="center">0.2163 (-0.3427,0.7753)</td>
                <td align="center">0.226 (-0.334,0.785)</td>
              </tr>
              <tr>
                <td align="center">
                  <italic>ϕ</italic>
                  <sub>1</sub>
                </td>
                <td align="center">-</td>
                <td align="center">-</td>
                <td align="center">-0.0034 (-0.0103,0.0035)</td>
                <td align="center">-0.003 (-0.010,0.004)</td>
              </tr>
              <tr>
                <td align="center">
                  <italic>ϕ</italic>
                  <sub>2</sub>
                </td>
                <td align="center">-</td>
                <td align="center">-</td>
                <td align="center">-0.0008 (-0.0099,0.0083)</td>
                <td align="center">-0.0005 (-0.0096,0.0086)</td>
              </tr>
              <tr>
                <td align="center">
                  <italic>ϕ</italic>
                  <sub>3</sub>
                </td>
                <td align="center">-</td>
                <td align="center">-</td>
                <td align="center">0.0115 (-0.0074,0.0305)</td>
                <td align="center">0.011 (-0.008,0.030)</td>
              </tr>
              <tr>
                <td align="center">
                  <italic>ϕ</italic>
                  <sub>4</sub>
                </td>
                <td align="center">-</td>
                <td align="center">-</td>
                <td align="center">0.0007 (-0.0128,0.0142)</td>
                <td align="center">0.0006 (-0.0129,0.0141)</td>
              </tr>
              <tr>
                <td align="center">
                  <italic>ϕ</italic>
                  <sub>5</sub>
                </td>
                <td align="center">-</td>
                <td align="center">-</td>
                <td align="center">-0.0011 (-0.0079,0.0057)</td>
                <td align="center">-0.0010 (-0.0078,0.0058)</td>
              </tr>
              <tr>
                <td align="center">
                  <italic>η</italic>
                </td>
                <td align="center">1.287</td>
                <td align="center">1.311(1.235,1.391)</td>
                <td align="center">1.241(0.710,2.171)</td>
                <td align="center">1.254(0.716,2.192)</td>
              </tr>
              <tr>
                <td align="center">Deviance</td>
                <td align="center">132</td>
                <td align="center">130.56</td>
                <td align="center">122.9983</td>
                <td align="center">122.18</td>
              </tr>
              <tr>
                <td align="center">Df</td>
                <td align="center">143</td>
                <td align="center">142</td>
                <td align="center">138</td>
                <td align="center">137</td>
              </tr>
              <tr>
                <td align="center">
                  <italic>κ</italic>
                </td>
                <td align="center">0.99</td>
                <td align="center">0.9942</td>
                <td align="center">0.9887</td>
                <td align="center">0.9906</td>
              </tr>
            </tbody>
          </table>
        </table-wrap>
        <p>The 95% confidence intervals for <italic>ϕ</italic><sub><italic>i </italic></sub>(<italic>i </italic>= 1,..., 5) in Models 3 and 4 also contain zero which shows that the covariates are not significant factors in risk of preterm birth. This result shows that none of the variables make significant contributions to the explanation of the variation in risk. Recall that <italic>η </italic>= exp(<italic>α</italic><sub><italic>o</italic></sub>) is a measure of the overall mean of the relative risk in the region under study. For each of the models, Table <xref ref-type="table" rid="T3">3</xref> gives the estimates of the overall risk together with its 95% confidence intervals. The overall mean of the relative risk is greater than 1 for each model which indicates that there is elevated risk of preterm birth across the whole of the Cape Breton municipality.</p>
      </sec>
      <sec>
        <title>Weighted regression results</title>
        <p>The result of the fit is given in Table <xref ref-type="table" rid="T4">4</xref>. None of the variables is significant in explaining the increased risk of preterm birth. The residual standard error for Model 4 was estimated to be 0.02347 on 137 degrees of freedom. Multiple <italic>R</italic>-square is 0.09795 which shows that the variables in the model account for about 10% of the total variation in the risk. The <italic>F</italic>-statistic for the regression relationship was estimated to be 2.479 on 6 and 137 degrees of freedom and the associated <italic>p</italic>-value is 0.0262. This shows that at least one of the parameters (<italic>α</italic>, and <italic>ϕ</italic><sub><italic>i</italic></sub>) does not equal zero. Hence, there is evidence of a regression relationship between the dependent variable (<italic>Y</italic><sub><italic>i</italic></sub>) and the area-specific variables (<italic>z</italic><sub><italic>i</italic></sub>).</p>
        <table-wrap position="float" id="T4">
          <label>Table 4</label>
          <caption>
            <p>Weighted regression result with parameter estimates, 95% CI, R-square, Residual standard error (RSE) and F-statistic (p-value)</p>
          </caption>
          <table frame="hsides" rules="groups">
            <thead>
              <tr>
                <td align="center">Parameter</td>
                <td align="center">Model 2</td>
                <td align="center">Model 3</td>
                <td align="center">Model 4</td>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td align="center">
                  <italic>α</italic>
                </td>
                <td align="center">-0.0996(-0.2513,0.0521)</td>
                <td align="center">-</td>
                <td align="center">-0.0878(-0.2364,0.0608)</td>
              </tr>
              <tr>
                <td align="center">
                  <italic>α</italic>
                  <sub>
                    <italic>o</italic>
                  </sub>
                </td>
                <td align="center">0.2325(0.1749,0.2901)</td>
                <td align="center">0.2092(-0.3219,0.7403)</td>
                <td align="center">0.2180(-0.3128,0.7488)</td>
              </tr>
              <tr>
                <td align="center">
                  <italic>ϕ</italic>
                  <sub>1</sub>
                </td>
                <td align="center">-</td>
                <td align="center">-0.0046(-0.0111,0.0019)</td>
                <td align="center">-0.0045(-0.0110,0.0020)</td>
              </tr>
              <tr>
                <td align="center">
                  <italic>ϕ</italic>
                  <sub>2</sub>
                </td>
                <td align="center">-</td>
                <td align="center">-0.0005(-0.0091,0.0081)</td>
                <td align="center">-0.0001(-0.0087,0.0085)</td>
              </tr>
              <tr>
                <td align="center">
                  <italic>ϕ</italic>
                  <sub>3</sub>
                </td>
                <td align="center">-</td>
                <td align="center">0.0111(-0.0073,0.0295)</td>
                <td align="center">0.0106(-0.0078,0.0290)</td>
              </tr>
              <tr>
                <td align="center">
                  <italic>ϕ</italic>
                  <sub>4</sub>
                </td>
                <td align="center">-</td>
                <td align="center">0.0026(-0.0107,0.0159)</td>
                <td align="center">0.0025(-0.0106,0.0156)</td>
              </tr>
              <tr>
                <td align="center">
                  <italic>ϕ</italic>
                  <sub>5</sub>
                </td>
                <td align="center">-</td>
                <td align="center">-0.0012(-0.0079,0.0055)</td>
                <td align="center">-0.0011(-0.0078,0.0056)</td>
              </tr>
              <tr>
                <td align="center">
                  <italic>R</italic>
                  <sup>2</sup>
                </td>
                <td align="center">0.0115</td>
                <td align="center">0.0891</td>
                <td align="center">0.0980</td>
              </tr>
              <tr>
                <td align="center">
                  <italic>RSE</italic>
                </td>
                <td align="center">0.0241</td>
                <td align="center">0.0235</td>
                <td align="center">0.0235</td>
              </tr>
              <tr>
                <td align="center"><italic>F</italic>(<italic>p – value</italic>)</td>
                <td align="center">1.657(0.2002)</td>
                <td align="center">2.700(0.0232)</td>
                <td align="center">2.479(0.0262)</td>
              </tr>
            </tbody>
          </table>
        </table-wrap>
        <sec>
          <title>Test for autocorrelation</title>
          <p>Next, Moran's I test was also carried out to examine whether there is spatial autocorrelation in the residuals. The result gave a correlation of -0.01628, variance of 0.002541 and standard error of 0.05041. In addition, the normal test statistic was -0.1843 with associated 2-sided <italic>p</italic>-value equal to 0.8538. These results are sufficient to conclude that there is no spatial autocorrelation in the residuals. Hence, there was no need to use spatial regression modelling.</p>
        </sec>
      </sec>
    </sec>
    <sec>
      <title>Discussion and conclusion</title>
      <p>In practice, a typical spatial regression modelling will start with the examination of the dependent variable for spatial dependency. This can be done with Moran's I statistic or Geary C statistic. If there is no spatial pattern, then ordinary least squares or weighted least squares is sufficient to model the data. On the other hand if the dependent variable shows a spatial patterns, the first order spatial pattern can be incorporated at the beginning of the modelling using an adjacency matrix. However, great care has to be taken when using spatial modelling. First, some of the available parametric tests for measuring spatial autocorrelation, including Moran's I [<xref ref-type="bibr" rid="B37">37</xref>] and Geary's C [<xref ref-type="bibr" rid="B38">38</xref>] methods, are not robust when the data is sparse. The non-parametric rank-based method [<xref ref-type="bibr" rid="B39">39</xref>] is not available in most standard statistical software. Second, the structure of the adjacency matrix may affect the result. Hence, it must be chosen carefully. This research is part of a project done to assess the effect of maternal proximity to the hazardous waste from the Sydney Tar Pond, Nova Scotia. Two question have been addressed in this project: first, is maternal proximity to hazardous waste and pollution from the Sydney Tar Pond sites associated with increased risk of preterm birth? Second, how much of the variation in risk of preterm birth can be explained by socioeconomic inequalities across the study region?</p>
      <p>In addressing these questions frequentist and Bayesian methods were employed. In the frequentist approach, Poisson regression for aggregated data and weighted least squares were fitted using distance from the Tar Pond and the following area specific-covariates: the proportion of persons who have no high school diploma; the rate of unemployment to population; the proportion of persons who are separated, divorced or widowed; the proportion of single parent families; and the proportion of people living alone. The same models were fitted using a Bayesian hierarchical model incorporating both structured and unstructured random effects to account for model overdispersion.</p>
      <p>Our intention was to combine all of the area covariates to form the deprivation index, but income data were not available in 14 of the 144 enumeration districts included in the study. So the effect of each variable was assessed independently. The overall estimate of relative risk of preterm birth was found to be greater than 1 for almost all the enumeration districts. Also, none of the area covariates in the model is significant in explaining the risk of preterm births.</p>
      <p>There was no evidence of any decrease in risk as we move away from the Tar Pond site. The results of both the weighted least squares and the quasi-likelihood Poisson regression agree with the result from the Bayesian hierarchical modelling which incorporates the spatial effects. The result of the Bayesian modelling shows that there is no significant spatial association of risk in the area studied. There was no obvious clustering of outcomes around the Tar Pond significant enough to find an association between maternal proximity to the Sydney Tar Ponds and risk of preterm birth. Although the three methods lead to similar results, we think the three-stage Bayesian hierarchical modelling is one of the best approaches for handling this problem. First, it allows the modelling of both sources of overdispersion, heterogeneity and spatial dependence or clustering in one model, and second, it allows the estimation of SIR with adjustment of sparse data. The least suggested method is the weighted least square method because it does not lend itself to some of the assumptions of Poisson models.</p>
      <p>The following are some of the limitations of this research. First, data were not available for 14 of the Enumeration districts. Hence, they were omitted from our analysis but the effects of this on spatial dependency or our conclusion are not known. Second, we have based our analysis on the 1996 data but we do not have any evidence of whether the exposure from the Tar Pond has decreased since 1996. Third, the use of aggregated data may increase the potential for ecological bias which can occur due to the differences between individual and group-level estimates of disease risk. In particular, factors that affect length of gestation such as parity have not been directly adjusted for in the modelling.</p>
      <p>Our experience with this project shows that more work is still needed in this area. None of the models was able to predict more that 10% of what we would like to know. The future plans include aggregating the data for up to ten years and modelling using other forms of <italic>g</italic>(<italic>d</italic>; <italic>θ</italic>). We will also consider using individual level data and incorporating other covariates. The study shows that there is an elevated risk of preterm births, which appears to be uniform across the whole of the Cape Breton regional municipality as shown by all the methods used. This shows that the pollution may be occurring on a wider scale and over time may have affected the ability to differentiate the EDs in terms of amount of exposure. A direct comparison of the Cape Breton regional municipality with other nearby municipalities may help answer some of the remaining questions.</p>
    </sec>
    <sec>
      <title>Competing interests</title>
      <p>The author(s) declare that they have no competing interests.</p>
    </sec>
    <sec>
      <title>Authors' contributions</title>
      <p>ASI and AC developed the project. All authors participated in preparing this manuscript.</p>
    </sec>
    <sec>
      <title>Pre-publication history</title>
      <p>The pre-publication history for this paper can be accessed here:</p>
      <p>
        <ext-link ext-link-type="uri" xlink:href="http://www.biomedcentral.com/1471-2288/7/39/prepub"/>
      </p>
    </sec>
    <sec sec-type="supplementary-material">
      <title>Supplementary Material</title>
      <supplementary-material content-type="local-data" id="S1">
        <caption>
          <title>Additional file 1</title>
          <p><bold>Bayesian diagnostic plots</bold>. Gelman Rubin plots from five parallel chains, kernel density plots of sampled values for parameters of model 4 based on five pooled chains and autocorrelation plot for each chain.</p>
        </caption>
        <media xlink:href="1471-2288-7-39-S1.pdf" mimetype="application" mime-subtype="pdf">
          <caption>
            <p>Click here for file</p>
          </caption>
        </media>
      </supplementary-material>
    </sec>
  </body>
  <back>
    <ack>
      <sec>
        <title>Acknowledgements</title>
        <p>This work was funded through an NSERC Discovery Grant to one of the authors (AC). We thank Prof. Pavlos Kanaroglou of the School of Geography and Earth Sciences for giving us the data used in this project and allowing the use of the Center for Spatial Analysis at McMaster University. Our appreciation also goes to Patrick Deluca, a member of the Center for Spatial Analysis at McMaster University, for his assistance. We thank the reviewers and associate editors for their invaluable suggestions that substantially improved the manuscript.</p>
      </sec>
    </ack>
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  <front>
    <journal-meta>
      <journal-id journal-id-type="nlm-ta">BMC Public Health</journal-id>
      <journal-title>BMC Public Health</journal-title>
      <issn pub-type="epub">1471-2458</issn>
      <publisher>
        <publisher-name>BioMed Central</publisher-name>
      </publisher>
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    <article-meta>
      <article-id pub-id-type="pmc">2080635</article-id>
      <article-id pub-id-type="publisher-id">1471-2458-7-228</article-id>
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      <article-id pub-id-type="doi">10.1186/1471-2458-7-228</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Measuring participant rurality in Web-based interventions</article-title>
      </title-group>
      <contrib-group>
        <contrib id="A1" corresp="yes" contrib-type="author">
          <name>
            <surname>Danaher</surname>
            <given-names>Brian G</given-names>
          </name>
          <xref ref-type="aff" rid="I1">1</xref>
          <email>briand@ori.org</email>
        </contrib>
        <contrib id="A2" contrib-type="author">
          <name>
            <surname>Hart</surname>
            <given-names>L Gary</given-names>
          </name>
          <xref ref-type="aff" rid="I2">2</xref>
          <email>garyhart@u.washington.edu</email>
        </contrib>
        <contrib id="A3" contrib-type="author">
          <name>
            <surname>McKay</surname>
            <given-names>H Garth</given-names>
          </name>
          <xref ref-type="aff" rid="I1">1</xref>
          <email>garthm@ori.org</email>
        </contrib>
        <contrib id="A4" contrib-type="author">
          <name>
            <surname>Severson</surname>
            <given-names>Herbert H</given-names>
          </name>
          <xref ref-type="aff" rid="I1">1</xref>
          <email>herb@ori.org</email>
        </contrib>
      </contrib-group>
      <aff id="I1"><label>1</label>Oregon Research Institute, 1715 Franklin Boulevard, Eugene, OR 97403 USA</aff>
      <aff id="I2"><label>2</label>WWAMI Rural Health Research Center, University of Washington, Seattle, WA USA</aff>
      <pub-date pub-type="collection">
        <year>2007</year>
      </pub-date>
      <pub-date pub-type="epub">
        <day>31</day>
        <month>8</month>
        <year>2007</year>
      </pub-date>
      <volume>7</volume>
      <fpage>228</fpage>
      <lpage>228</lpage>
      <ext-link ext-link-type="uri" xlink:href="http://www.biomedcentral.com/1471-2458/7/228"/>
      <history>
        <date date-type="received">
          <day>21</day>
          <month>12</month>
          <year>2006</year>
        </date>
        <date date-type="accepted">
          <day>31</day>
          <month>8</month>
          <year>2007</year>
        </date>
      </history>
      <permissions>
        <copyright-statement>Copyright © 2007 Danaher et al; licensee BioMed Central Ltd.</copyright-statement>
        <copyright-year>2007</copyright-year>
        <copyright-holder>Danaher et al; licensee BioMed Central Ltd.</copyright-holder>
        <license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/2.0">
          <p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/2.0"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>
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               Danaher
               G
               Brian
               
               briand@ori.org
            </dc:author><dc:title>
            Measuring participant rurality in Web-based interventions
         </dc:title><dc:date>2007</dc:date><dcterms:bibliographicCitation>BMC Public Health 7(1): 228-. (2007)</dcterms:bibliographicCitation><dc:identifier type="sici">1471-2458(2007)7:1&#x0003c;228&#x0003e;</dc:identifier><dcterms:isPartOf>urn:ISSN:1471-2458</dcterms:isPartOf><License rdf:about="http://creativecommons.org/licenses/by/2.0"><permits rdf:resource="http://web.resource.org/cc/Reproduction" xmlns=""/><permits rdf:resource="http://web.resource.org/cc/Distribution" xmlns=""/><requires rdf:resource="http://web.resource.org/cc/Notice" xmlns=""/><requires rdf:resource="http://web.resource.org/cc/Attribution" xmlns=""/><permits rdf:resource="http://web.resource.org/cc/DerivativeWorks" xmlns=""/></License></Work></rdf>-->
        </license>
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      <abstract>
        <sec>
          <title>Background</title>
          <p>Web-based health behavior change programs can reach large groups of disparate participants and thus they provide promise of becoming important public health tools. Data on participant rurality can complement other demographic measures to deepen our understanding of the success of these programs. Specifically, analysis of participant rurality can inform recruitment and social marketing efforts, and facilitate the targeting and tailoring of program content. Rurality analysis can also help evaluate the effectiveness of interventions across population groupings.</p>
        </sec>
        <sec sec-type="methods">
          <title>Methods</title>
          <p>We describe how the RUCAs (Rural-Urban Commuting Area Codes) methodology can be used to examine results from two Randomized Controlled Trials of Web-based tobacco cessation programs: the ChewFree.com project for smokeless tobacco cessation and the Smokers' Health Improvement Program (SHIP) project for smoking cessation.</p>
        </sec>
        <sec>
          <title>Results</title>
          <p>Using RUCAs methodology helped to highlight the extent to which both Web-based interventions reached a substantial percentage of rural participants. The ChewFree program was found to have more rural participation which is consistent with the greater prevalence of smokeless tobacco use in rural settings as well as ChewFree's multifaceted recruitment program that specifically targeted rural settings.</p>
        </sec>
        <sec>
          <title>Conclusion</title>
          <p>Researchers of Web-based health behavior change programs targeted to the US should routinely include RUCAs as a part of analyzing participant demographics. Researchers in other countries should examine rurality indices germane to their country.</p>
        </sec>
      </abstract>
    </article-meta>
  </front>
  <body>
    <sec>
      <title>Background</title>
      <p>One of the strengths characterizing Web-based health behavior change programs is the ability to reach participants based in disparate geographic locations. This is particularly important when a set of conditions obtains: (a) when individuals in rural settings are found to have serious modifiable health behaviors; (b) when rural individuals have more limited personal income to pay for personal care and/or transportation to care; and (c) when there are fewer per capita clinic-based health professionals [<xref ref-type="bibr" rid="B1">1</xref>]. Although the rural use of the Internet still lags behind usage levels observed for urban areas, Internet usage nonetheless is increasing rapidly [<xref ref-type="bibr" rid="B2">2</xref>,<xref ref-type="bibr" rid="B3">3</xref>]. In fact, recent data indicates that the adoption rate of broadband Internet services in rural settings is now on parity with urban areas [<xref ref-type="bibr" rid="B3">3</xref>]. These trends are encouraging and support using Web-based delivered interventions as one viable approach to reach underserved rural Americans [<xref ref-type="bibr" rid="B4">4</xref>]. When describing these interventions, it would be helpful to routinely describe participant rurality in addition to other demographic characteristics. This data can inform recruitment and social marketing efforts, and facilitate the targeting and tailoring of program content.</p>
      <p>Fortunately, there is a convenient, empirically-based methodology called RUCAs (Rural-Urban Commuting Area Codes) that can help US researchers accomplish this goal. In this report, we examine the use of RUCAs in two exemplar randomized controlled trials of Web-based tobacco cessation programs: one for smokeless tobacco cessation and the other for smoking cessation to better understand the nature of the population of users for these two intervention trials. We also provide examples of how RUCAs can be used to better understand the reach of behavior change programs delivered via the Internet.</p>
    </sec>
    <sec sec-type="methods">
      <title>Methods</title>
      <sec>
        <title>Measuring rurality using RUCAs</title>
        <p>There is no one universally agreed upon definition of rurality [<xref ref-type="bibr" rid="B5">5</xref>,<xref ref-type="bibr" rid="B6">6</xref>]. In their presentation of a handful of different taxonomies for rurality, Hart et al. [<xref ref-type="bibr" rid="B7">7</xref>] have recommended use of a flexible, non-monolithic approach to the measurement of rurality that seeks to capture those facets of the urban:rural continuum most relevant to the topic being considered. These researchers describe the development work supported by the University of Washington and the Economic Research Service (with additional funding through the federal Office of Rural Health Policy, Health Resources and Services Administration) that resulted in the development of the 33-category RUCA taxonomy that takes into account both the size of settlement (census-tract data) and the functional relationships between places (tract-level work-commuting data) [<xref ref-type="bibr" rid="B8">8</xref>,<xref ref-type="bibr" rid="B9">9</xref>]. In an effort to be more usable and comprehensive, RUCA developers subsequently mapped census tract RUCAs onto the US Postal Service ZIP code areas. [<xref ref-type="bibr" rid="B10">10</xref>,<xref ref-type="bibr" rid="B11">11</xref>] (see Table <xref ref-type="table" rid="T1">1</xref>).</p>
        <table-wrap position="float" id="T1">
          <label>Table 1</label>
          <caption>
            <p>Detailed list of rural urban commuting areas codes</p>
          </caption>
          <table frame="hsides" rules="groups">
            <tbody>
              <tr>
                <td align="left">
                  <bold>1 Metropolitan area core: primary flow within an Urbanized Area (UA)</bold>
                </td>
              </tr>
              <tr>
                <td align="left"> 1.0 No additional code</td>
              </tr>
              <tr>
                <td align="left"> 1.1 Secondary flow 30% through 49% to a larger UA</td>
              </tr>
              <tr>
                <td align="left">
                  <bold>2 Metropolitan area high commuting: primary flow 30% or more to a UA</bold>
                </td>
              </tr>
              <tr>
                <td align="left"> 2.0 No additional code</td>
              </tr>
              <tr>
                <td align="left"> 2.1 Secondary flow 30% through 49% to a larger UA</td>
              </tr>
              <tr>
                <td align="left">
                  <bold>3 Metropolitan area low commuting: primary flow 10% through 29% to a UA</bold>
                </td>
              </tr>
              <tr>
                <td align="left"> 3.0 No additional code</td>
              </tr>
              <tr>
                <td align="left">
                  <bold>4 Large rural area core: primary flow within an Urban Cluster (UC) of 10,000 through 49,999 (large UC)</bold>
                </td>
              </tr>
              <tr>
                <td align="left"> 4.0 No additional code</td>
              </tr>
              <tr>
                <td align="left"> 4.1 Secondary flow 30% through 49% to a UA</td>
              </tr>
              <tr>
                <td align="left"> 4.2 Secondary flow 10% through 29% to a UA</td>
              </tr>
              <tr>
                <td align="left">
                  <bold>5 Large rural high commuting: primary flow 30% or more to a large UC</bold>
                </td>
              </tr>
              <tr>
                <td align="left"> 5.0 No additional code</td>
              </tr>
              <tr>
                <td align="left"> 5.1 Secondary flow 30% through 49% to a UA</td>
              </tr>
              <tr>
                <td align="left"> 5.2 Secondary flow 10% through 29% to a UA</td>
              </tr>
              <tr>
                <td align="left">
                  <bold>6 Large rural low commuting: primary flow 10% through 29% to a large UC</bold>
                </td>
              </tr>
              <tr>
                <td align="left"> 6.0 No additional code</td>
              </tr>
              <tr>
                <td align="left"> 6.1 Secondary flow 10% through 29% to a UA</td>
              </tr>
              <tr>
                <td align="left">
                  <bold>7 Small rural town core: primary flow within an Urban Cluster (UC) of 2,500 through 9,999 (small UC)</bold>
                </td>
              </tr>
              <tr>
                <td align="left"> 7.0 No additional code</td>
              </tr>
              <tr>
                <td align="left"> 7.1 Secondary flow 30% through 49% to a UA</td>
              </tr>
              <tr>
                <td align="left"> 7.2 Secondary flow 30% through 49% to a large UC</td>
              </tr>
              <tr>
                <td align="left"> 7.3 Secondary flow 10% through 29% to a UA</td>
              </tr>
              <tr>
                <td align="left"> 7.4 Secondary flow 10% through 29% to a large UC</td>
              </tr>
              <tr>
                <td align="left">
                  <bold>8 Small rural town high commuting: primary flow 30% or more to a small UC</bold>
                </td>
              </tr>
              <tr>
                <td align="left"> 8.0 No additional code</td>
              </tr>
              <tr>
                <td align="left"> 8.1 Secondary flow 30% through 49% to a UA</td>
              </tr>
              <tr>
                <td align="left"> 8.2 Secondary flow 30% through 49% to a large UC</td>
              </tr>
              <tr>
                <td align="left"> 8.3 Secondary flow 10% through 29% to a UA</td>
              </tr>
              <tr>
                <td align="left"> 8.4 Secondary flow 10% through 29% to a large UC</td>
              </tr>
              <tr>
                <td align="left">
                  <bold>9 Small rural town low commuting: primary flow 10% through 29% to a small UC</bold>
                </td>
              </tr>
              <tr>
                <td align="left"> 9.0 No additional code</td>
              </tr>
              <tr>
                <td align="left"> 9.1 Secondary flow 10% through 29% to a UA</td>
              </tr>
              <tr>
                <td align="left"> 9.2 Secondary flow 10% through 29% to a large UC</td>
              </tr>
              <tr>
                <td align="left">
                  <bold>10 Isolated small rural areas: primary flow to a tract outside a UA or UC (including self)</bold>
                </td>
              </tr>
              <tr>
                <td align="left"> 10.0 No additional code</td>
              </tr>
              <tr>
                <td align="left"> 10.1 Secondary flow 30% through 49% to a UA</td>
              </tr>
              <tr>
                <td align="left"> 10.2 Secondary flow 30% through 49% to a large UC</td>
              </tr>
              <tr>
                <td align="left"> 10.3 Secondary flow 30% through 49% to a small UC</td>
              </tr>
              <tr>
                <td align="left"> 10.4 Secondary flow 10% through 29% to a UA</td>
              </tr>
              <tr>
                <td align="left"> 10.5 Secondary flow 10% through 29% to a large UC</td>
              </tr>
              <tr>
                <td align="left"> 10.6 Secondary flow 10% through 29% to a small UC</td>
              </tr>
            </tbody>
          </table>
        </table-wrap>
        <p>Because ZIP codes offer a finer-grained unit of analysis than counties, the ZIP code version of RUCAs is able to differentiate between rural portions of metropolitan counties and urban portions of non-metropolitan counties. RUCAs are now widely used for policy and research purposes [<xref ref-type="bibr" rid="B12">12</xref>-<xref ref-type="bibr" rid="B15">15</xref>]. Interested researchers can obtain freely-available downloadable copies of the ZIP code version of RUCAs from the University of Washington Rural Health Research Center [<xref ref-type="bibr" rid="B10">10</xref>] along with information about ways that RUCAs categories can be aggregated to best facilitate different rurality analyses [<xref ref-type="bibr" rid="B10">10</xref>]. One online document on the website highlights the fact that because census-tract data and tract-level work-commuting data change over time – sometimes substantially – it is critical to use the RUCA version that relates to the time when participant ZIP code data was collected and program participation occurred [<xref ref-type="bibr" rid="B10">10</xref>]. For example, RUCA version 1.11 is based on commuting patterns for 1990 and the 1998 ZIP code year whereas RUCA version 2.0 is based on commuting patterns for 2000 and the 2004 ZIP code year. The 2006 version of RUCA ZIP code data have recently been released for downloading on the University of Washington website [<xref ref-type="bibr" rid="B10">10</xref>].</p>
      </sec>
      <sec>
        <title>RUCA aggregation</title>
        <p>We used a common aggregation of RUCA codes that describes locations as one of four types: urban, large rural/town, small rural/town, and isolated small rural/town (see Table <xref ref-type="table" rid="T2">2</xref>). Using these groupings, the 2004 US population estimates show that the population is distributed as follows: 81.0% urban, 9.6% large rural, 5.2% small rural, and 4.2% isolated small rural [<xref ref-type="bibr" rid="B10">10</xref>]. The three rural groupings can be combined into an aggregate rural group to yield the useful dichotomous description of locations as being either urban or rural. Alternative aggregations of RUCAs could also be considered to more narrowly define groups. For instance, only the 10.0 RUCAs codes could be used to define what might be called "very isolated and small" or the RUCAs could be used in combination with information on paved road travel time to the nearest city [<xref ref-type="bibr" rid="B10">10</xref>] to define what might be termed "isolated and remote small" (RUCAs codes 10.0 and 10.2–10.6 which describe 60 minutes or greater from a city).</p>
        <table-wrap position="float" id="T2">
          <label>Table 2</label>
          <caption>
            <p>RUCAs aggregation</p>
          </caption>
          <table frame="hsides" rules="groups">
            <thead>
              <tr>
                <td align="center">Groups</td>
                <td align="left">RUCA codes</td>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td align="right">Urban</td>
                <td align="left">1.0, 1.1, 2.0, 2.1, 3.0, 4.1, 5.1, 7.1, 8.1, 10.1</td>
              </tr>
              <tr>
                <td align="right">Large rural/town</td>
                <td align="left">4.0, 4.2, 5.0, 5.2, 6.0, 6.1</td>
              </tr>
              <tr>
                <td align="right">Small rural/town</td>
                <td align="left">7.0, 7.2, 7.3, 7.4, 8.0, 8.2, 8.3, 8.4, 9.0, 9.1, 9.2</td>
              </tr>
              <tr>
                <td align="right">Isolated small rural/town</td>
                <td align="left">10.0, 10.2, 10.3, 10.4, 10.5, 10.6</td>
              </tr>
            </tbody>
          </table>
        </table-wrap>
      </sec>
      <sec>
        <title>Example 1: Using RUCAs in the ChewFree.com trial</title>
        <p>The prevalence of chewing tobacco use is markedly higher in rural counties compared to metropolitan areas [<xref ref-type="bibr" rid="B16">16</xref>,<xref ref-type="bibr" rid="B17">17</xref>]. Rural chewers wanting assistance to quit have relatively few local resources to help then quit using chewing tobacco [<xref ref-type="bibr" rid="B18">18</xref>,<xref ref-type="bibr" rid="B19">19</xref>]. The ChewFree.com project, a randomized controlled trial of two Web-based smokeless tobacco cessation websites (an Enhanced condition and a Basic control condition), recruited 2325 participants from across the US during the years 2004–2005. Ethics approval for the research was obtained through the Committee for the Protection of Human Subjects/Institutional Review Board of Oregon Research Institute. All participants provided their informed consent online.</p>
        <p>The recruitment methodology, participant exposure to program content, and outcome results are described elsewhere [<xref ref-type="bibr" rid="B20">20</xref>-<xref ref-type="bibr" rid="B22">22</xref>]. ChewFree participants (2507 of 2523) with valid ZIP codes included in the analysis were drawn from 49 states as well as one individual from the District of Columbia and another from the Armed Forces Pacific.</p>
        <p>In addition to the advantages of being available 24×7, Web-based interventions can deliver video content as a way to model the use of behavioral strategies and to provide stories or testimonials that can help build participant motivation to effect a behavior change. In addition, selective use of video when combined with other forms of interactivity may well encourage longer and more frequent visits (building participant engagement and exposure to helpful program content) [<xref ref-type="bibr" rid="B20">20</xref>].</p>
        <p>Participants who were randomized to the Enhanced Condition (N = 1260) of the ChewFree.com program had the option of reviewing online videos. The default setting for showing video or not was initially determined by an unobtrusive measure of the speed of each participant's Internet connection. In addition, each participant could subsequently override these default settings and change his/her program preferences about viewing the videos. Because successful delivery of video in Web-based programs requires broadband (high-speed) Internet access [<xref ref-type="bibr" rid="B23">23</xref>] and the prevalence of broadband use is less in rural settings, we examined the relationship between ChewFree.com participant rurality and their type of Internet access (broadband vs. dial-up). This analysis is limited to participants in the Enhanced condition for whom RUCA categories could be calculated and for whom data on the speed of Internet access was measured at baseline. For purposes of this analysis, we followed the recommendation of Danaher et al. [<xref ref-type="bibr" rid="B23">23</xref>] and operationally defined broadband as throughput speeds of at least 384 Kbps.</p>
      </sec>
      <sec>
        <title>Example 2: Using RUCAs in the Smokers' Health Improvement Program (SHIP) trial</title>
        <p>In their recent report describing smoking trend data based on the Behavioral Risk Factor Surveillance System (BRFSS), Doescher et al. [<xref ref-type="bibr" rid="B24">24</xref>] observed that "...rural residence itself is a risk factor for smoking and that many well-known risk factors for smoking, such as male gender and low socioeconomic status, are especially important among persons residing in rural locations" (p. 115). A growing number of Web-based interventions have focused on helping participants quit smoking [<xref ref-type="bibr" rid="B25">25</xref>-<xref ref-type="bibr" rid="B29">29</xref>]. The Smokers' Health Improvement Program (SHIP) project used online recruiting methods (Google and Yahoo ad campaigns) to enroll a total of 2318 smokers from the US and Canada to participate in the SHIP randomized controlled trial. Ethics approval for the research was obtained through the Committee for the Protection of Human Subjects/Institutional Review Board of Oregon Research Institute. All participants provided their informed consent online.</p>
        <p>For purposes of this analysis, we excluded individuals from Canada and those individuals for whom ZIP code data were invalid or incomplete which yielded the final sample of 2263 smokers drawn from all 50 states and the District of Columbia. Participants were assigned to one of two Web-based programs: (a) the QSN treatment condition which offered a tailored, video-enriched program for preparing to quit, quitting, and maintaining nonsmoking that was derived from a previously-described pilot study [<xref ref-type="bibr" rid="B30">30</xref>]; and (b) the Active Lives control condition that provided a personalized physical activity program to help participants become more fit which, in turn, would help them quit smoking.</p>
      </sec>
    </sec>
    <sec>
      <title>Results</title>
      <p>Illustrative example data on participant rurality in the Web-based smokeless tobacco cessation trial (ChewFree.com) and the Web-based smoking cessation trial (SHIP) are displayed in Table <xref ref-type="table" rid="T3">3</xref>. Owing in large part to large sample sizes and successful randomization, there were no observed differences in rurality between conditions within the ChewFree.com trial (χ<sup>2</sup>(3, <italic>N </italic>= 2507) = 0.55, <italic>p </italic>= .91) and the SHIP trial (χ<sup>2</sup>(3, <italic>N </italic>= 2263) = 0.12, <italic>p </italic>= .99). When we collapsed data across conditions and aggregated RUCA categories to permit an examination of the rural:urban dichotomy, results in both trials indicated that participation differed significantly by rurality: the ChewFree.com trial (χ<sup>2</sup>(1, <italic>N </italic>= 2507) = 192.67, <italic>p </italic>&lt; .001) and the SHIP trial (χ<sup>2</sup>(1, <italic>N </italic>= 2263) = 830.60, <italic>p </italic>&lt; .001).</p>
      <table-wrap position="float" id="T3">
        <label>Table 3</label>
        <caption>
          <p>Participant rurality in two Web-based tobacco cessation trials</p>
        </caption>
        <table frame="hsides" rules="groups">
          <tbody>
            <tr>
              <td/>
              <td align="center" colspan="2">ChewFree smokeless tobacco cessation trial (N = 2507)</td>
              <td align="center" colspan="2">SHIP smoking cessation trial (N = 2263)</td>
            </tr>
            <tr>
              <td/>
              <td colspan="2">
                <hr/>
              </td>
              <td colspan="2">
                <hr/>
              </td>
            </tr>
            <tr>
              <td align="right">RUCA groups</td>
              <td align="center">Enhanced Condition</td>
              <td align="center">Basic Condition</td>
              <td align="center">QSN</td>
              <td align="center">Active Lives Control</td>
            </tr>
            <tr>
              <td colspan="1">
                <hr/>
              </td>
              <td colspan="1">
                <hr/>
              </td>
              <td colspan="1">
                <hr/>
              </td>
              <td colspan="1">
                <hr/>
              </td>
              <td colspan="1">
                <hr/>
              </td>
            </tr>
            <tr>
              <td align="right">Urban</td>
              <td align="center">806<break/>64.3%</td>
              <td align="center">795<break/>63.4%</td>
              <td align="center">907<break/>80.1%</td>
              <td align="center">910<break/>80.5%</td>
            </tr>
            <tr>
              <td align="right">Large rural/town</td>
              <td align="center">203<break/>16.2%</td>
              <td align="center">200<break/>15.9%</td>
              <td align="center">119<break/>10.5%</td>
              <td align="center">116<break/>10.3%</td>
            </tr>
            <tr>
              <td align="right">Small rural/town</td>
              <td align="center">146<break/>11.7%</td>
              <td align="center">154<break/>12.3%</td>
              <td align="center">61<break/>5.4%</td>
              <td align="center">58<break/>5.1%</td>
            </tr>
            <tr>
              <td align="right">Isolated small rural/town</td>
              <td align="center">98<break/>7.8%</td>
              <td align="center">105<break/>8.4%</td>
              <td align="center">46<break/>4.1%</td>
              <td align="center">46<break/>4.1%</td>
            </tr>
          </tbody>
        </table>
      </table-wrap>
      <p>In Table <xref ref-type="table" rid="T4">4</xref> we consider participant rurality in each of the two trials using the broader context of the percentage of US population in the same RUCAs groupings [<xref ref-type="bibr" rid="B10">10</xref>]. While the rurality of smokers in the SHIP trial closely mirrored the national population distribution, the rurality of smokeless tobacco users in the ChewFree.com trial differed significantly from the population distribution – both when examining all four RUCAs groups presented in Table <xref ref-type="table" rid="T4">4</xref> (χ<sup>2</sup>(3, <italic>N </italic>= 2507) = 511.80, <italic>p </italic>&lt; .001) and also when the data were collapsed into a rural:urban dichotomy (χ<sup>2</sup>(1, <italic>N </italic>= 2507) = 478.50, <italic>p </italic>&lt; .001) with almost twice as many rural participants than would be expected from the distribution of rurality in the US population (36.2% vs. 19.0%, respectively). These Chewfree.com results reflect both smokeless tobacco usage patterns and ChewFree.com's targeted marketing effort.</p>
      <table-wrap position="float" id="T4">
        <label>Table 4</label>
        <caption>
          <p>Distribution of rural participants in two Web-based tobacco cessation trials and the US population</p>
        </caption>
        <table frame="hsides" rules="groups">
          <tbody>
            <tr>
              <td align="center">RUCA groups</td>
              <td align="center">ChewFree smokeless tobacco cessation trial</td>
              <td align="center">SHIP smoking cessation trial</td>
              <td align="center">US population</td>
            </tr>
            <tr>
              <td/>
              <td align="center"> (N = 2507)</td>
              <td align="center">(N = 2263)</td>
              <td/>
            </tr>
            <tr>
              <td colspan="1">
                <hr/>
              </td>
              <td colspan="1">
                <hr/>
              </td>
              <td colspan="1">
                <hr/>
              </td>
              <td colspan="1">
                <hr/>
              </td>
            </tr>
            <tr>
              <td align="right">Urban</td>
              <td align="center">63.9%</td>
              <td align="center">80.3%</td>
              <td align="center">81.0%</td>
            </tr>
            <tr>
              <td align="right">Large rural/town</td>
              <td align="center">16.1%</td>
              <td align="center">10.4%</td>
              <td align="center">9.6%</td>
            </tr>
            <tr>
              <td align="right">Small rural/town</td>
              <td align="center">12.0%</td>
              <td align="center">5.3%</td>
              <td align="center">5.2%</td>
            </tr>
            <tr>
              <td align="right">Isolated small rural/town</td>
              <td align="center">8.1%</td>
              <td align="center">4.1%</td>
              <td align="center">4.2%</td>
            </tr>
          </tbody>
        </table>
      </table-wrap>
      <p>We also examined type of Internet access and rurality among participants in Enhanced condition in ChewFree.com program. Results (see Table <xref ref-type="table" rid="T5">5</xref>) showed roughly equivalent dial-up vs. broadband access among urban participants. In contrast, among rural participants, there was a clear gradient such that dial-up access increased its relative percentage share as the home location became more rural, a result that underscores the importance of taking into consideration the bandwidth constraints of many rural Internet users.</p>
      <table-wrap position="float" id="T5">
        <label>Table 5</label>
        <caption>
          <p>Rurality by type of Internet access for the Enhanced Condition in the ChewFree.com smokeless tobacco cessation trial</p>
        </caption>
        <table frame="hsides" rules="groups">
          <tbody>
            <tr>
              <td align="center">RUCA groups</td>
              <td align="center">Dial-Up (N = 722)</td>
              <td align="center">Broadband (N = 510)</td>
            </tr>
            <tr>
              <td colspan="1">
                <hr/>
              </td>
              <td colspan="1">
                <hr/>
              </td>
              <td colspan="1">
                <hr/>
              </td>
            </tr>
            <tr>
              <td align="right">Urban</td>
              <td align="center">428<break/>53.8%</td>
              <td align="center">367<break/>46.2%</td>
            </tr>
            <tr>
              <td align="right">Large rural/town</td>
              <td align="center">117<break/>59.1%</td>
              <td align="center">81<break/>40.9%</td>
            </tr>
            <tr>
              <td align="right">Small rural/town</td>
              <td align="center">98<break/>69.0%</td>
              <td align="center">44<break/>31.0%</td>
            </tr>
            <tr>
              <td align="right">Isolated small rural/town</td>
              <td align="center">79<break/>81.4%</td>
              <td align="center">18<break/>18.6%</td>
            </tr>
          </tbody>
        </table>
      </table-wrap>
    </sec>
    <sec>
      <title>Discussion</title>
      <p>Web-based health behavior change programs are well-suited to reach persons in many settings, including rural locations. Their potential public health impact is particularly important for rural locations wherein access to behavior change services (e.g., tobacco cessation services) is limited by relatively low income, lower rates of health insurance, and the poor availability of health care [<xref ref-type="bibr" rid="B24">24</xref>,<xref ref-type="bibr" rid="B31">31</xref>]. If the target population is known to be segmented according to rural:urban settings, then describing the study sample according to its RUCA characteristics can facilitate our understanding of the extent to which interventions reached their intended audience [<xref ref-type="bibr" rid="B32">32</xref>,<xref ref-type="bibr" rid="B33">33</xref>]. RUCAs can also provide valuable feedback to help refine marketing campaigns for Web-based interventions [<xref ref-type="bibr" rid="B33">33</xref>]. For example, we found that recruitment to the ChewFree.com research project benefited from using a mixture of both Internet-based marketing and "earned-media" promotions through more traditional media channels (e.g., newspapers and radio) many of which were based in rural settings [<xref ref-type="bibr" rid="B21">21</xref>]. In addition, RUCAs can be used to target as well as tailor program content and health messages [<xref ref-type="bibr" rid="B34">34</xref>].</p>
      <p>Considering tobacco cessation, it is important to note that although Doescher et al. [<xref ref-type="bibr" rid="B24">24</xref>] recently reported the rural vs. urban distribution of smoking behavior by counties, to date we do not have finer-grained data that describes the number of smokers or smokeless tobacco users by ZIP codes. Thus, for tobacco cessation and very likely for many other important health behaviors, RUCAs do not yet provide us with the denominator to describe the percentage of eligible participants reached by Web-based tobacco cessation interventions [<xref ref-type="bibr" rid="B35">35</xref>]. Nonetheless, ZIP code-based RUCAs datasets for age, race, sex, population, and income (planned), and travel distance time to cities with a population of 50,000 or more can also be used to fine-tune the research. Likewise, additional analyses could combine RUCAs with other geocoded datasets such as the ZIP code-based Consumer Health Profiles available through the Office of Cancer Communications of the National Cancer Institute [<xref ref-type="bibr" rid="B36">36</xref>,<xref ref-type="bibr" rid="B37">37</xref>], proprietary market segmentation datasets from Claritas, Inc[<xref ref-type="bibr" rid="B38">38</xref>,<xref ref-type="bibr" rid="B39">39</xref>], and US Census Bureau data on defined region, division, and state [<xref ref-type="bibr" rid="B40">40</xref>]. Finally, it is helpful to consider ways that RUCAs can mesh with other geography-based tools such as spatial analysis [<xref ref-type="bibr" rid="B41">41</xref>].</p>
      <p>One noteworthy limitation of the current report is that it uses a taxonomy that applies only to US locations. Not only do US-based Web interventions attract participation from other countries [e.g., [<xref ref-type="bibr" rid="B27">27</xref>]], but Web-based interventions obviously can be hosted in and marketed to participants in countries other than the US. In this regard, other countries have their own measures for categorizing rurality that could potentially be usefully employed to describe participation in their Web-based programs. Examples include the use of Rural and Small Town (RST) designations as a part of the Metropolitan Area and Census Agglomeration influenced Zones (MIZ) in Canada [<xref ref-type="bibr" rid="B42">42</xref>,<xref ref-type="bibr" rid="B43">43</xref>], the Accessibility/Remoteness Index (ARIA+) in Australia [<xref ref-type="bibr" rid="B44">44</xref>], and the Carstairs area deprivation measures in the UK [<xref ref-type="bibr" rid="B45">45</xref>,<xref ref-type="bibr" rid="B46">46</xref>].</p>
    </sec>
    <sec>
      <title>Conclusion</title>
      <p>Because RUCAs linked to ZIP code data can be downloaded at no cost, there appear to be few barriers to obtaining the considerable benefits associated with routinely reporting RUCA-measured rurality along with other key indices of participant demographics in reporting results of Web-based health behavior change programs targeted to US participants. Using data drawn from two Web-based RCTs we highlighted examples showing ways that RUCAs can be used as an integral evaluation component.</p>
    </sec>
    <sec>
      <title>Competing interests</title>
      <p>The author(s) declare that they have no competing interests.</p>
    </sec>
    <sec>
      <title>Authors' contributions</title>
      <p>BGD conceived of the study, conceptualized ideas, supervised its conduct, and designed and coordinated the data collection phase. LGH, HGM, and HHS all helped to interpret findings and contributed to the text. All authors reviewed drafts of the manuscript and approved the version to be published.</p>
    </sec>
    <sec>
      <title>Pre-publication history</title>
      <p>The pre-publication history for this paper can be accessed here:</p>
      <p>
        <ext-link ext-link-type="uri" xlink:href="http://www.biomedcentral.com/1471-2458/7/228/prepub"/>
      </p>
    </sec>
  </body>
  <back>
    <ack>
      <sec>
        <title>Acknowledgements</title>
        <p>The authors thank Edward Lichtenstein for his review of an earlier draft of this report. This project was supported by National Cancer Institute grants R01-CA84225 (ChewFree.com; Herbert H. Severson, PI) and R01-CA79946 (Smokers' Health Improvement Program; H. Garth McKay, PI).</p>
      </sec>
    </ack>
    <ref-list>
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</metadata></record><record><header><identifier>oai:pubmedcentral.nih.gov:2080636</identifier><datestamp>2007-11-17</datestamp><setSpec>bmcph</setSpec><setSpec>pmc-open</setSpec></header><metadata><article xmlns="http://dtd.nlm.nih.gov/2.0/xsd/archivearticle" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://dtd.nlm.nih.gov/archiving/2.3/xsd/archivearticle.xsd" article-type="research-article">
  <front>
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      <journal-id journal-id-type="nlm-ta">BMC Public Health</journal-id>
      <journal-title>BMC Public Health</journal-title>
      <issn pub-type="epub">1471-2458</issn>
      <publisher>
        <publisher-name>BioMed Central</publisher-name>
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    <article-meta>
      <article-id pub-id-type="pmc">2080636</article-id>
      <article-id pub-id-type="publisher-id">1471-2458-7-238</article-id>
      <article-id pub-id-type="pmid">17850670</article-id>
      <article-id pub-id-type="doi">10.1186/1471-2458-7-238</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Comparison of patient comprehension of rapid HIV pre-test fundamentals by information delivery format in an emergency department setting</article-title>
      </title-group>
      <contrib-group>
        <contrib id="A1" corresp="yes" contrib-type="author">
          <name>
            <surname>Merchant</surname>
            <given-names>Roland C</given-names>
          </name>
          <xref ref-type="aff" rid="I1">1</xref>
          <xref ref-type="aff" rid="I2">2</xref>
          <xref ref-type="aff" rid="I3">3</xref>
          <email>rmerchant@lifespan.org</email>
        </contrib>
        <contrib id="A2" contrib-type="author">
          <name>
            <surname>Gee</surname>
            <given-names>Erin M</given-names>
          </name>
          <xref ref-type="aff" rid="I1">1</xref>
          <email>erin.gee@gmail.com</email>
        </contrib>
        <contrib id="A3" contrib-type="author">
          <name>
            <surname>Clark</surname>
            <given-names>Melissa A</given-names>
          </name>
          <xref ref-type="aff" rid="I2">2</xref>
          <email>Melissa_Clark@brown.edu</email>
        </contrib>
        <contrib id="A4" contrib-type="author">
          <name>
            <surname>Mayer</surname>
            <given-names>Kenneth H</given-names>
          </name>
          <xref ref-type="aff" rid="I2">2</xref>
          <xref ref-type="aff" rid="I4">4</xref>
          <email>Kenneth_Mayer@brown.edu</email>
        </contrib>
        <contrib id="A5" contrib-type="author">
          <name>
            <surname>Seage</surname>
            <given-names>George R</given-names>
            <suffix>III</suffix>
          </name>
          <xref ref-type="aff" rid="I3">3</xref>
          <email>gseage@hsph.harvard.edu</email>
        </contrib>
        <contrib id="A6" contrib-type="author">
          <name>
            <surname>DeGruttola</surname>
            <given-names>Victor G</given-names>
          </name>
          <xref ref-type="aff" rid="I5">5</xref>
          <email>victor@sdac.harvard.edu</email>
        </contrib>
      </contrib-group>
      <aff id="I1"><label>1</label>Department of Emergency Medicine, Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA</aff>
      <aff id="I2"><label>2</label>Department of Community Health, Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA</aff>
      <aff id="I3"><label>3</label>Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA</aff>
      <aff id="I4"><label>4</label>Department of Medicine, Division of Infectious Diseases, Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA</aff>
      <aff id="I5"><label>5</label>Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, USA</aff>
      <pub-date pub-type="collection">
        <year>2007</year>
      </pub-date>
      <pub-date pub-type="epub">
        <day>12</day>
        <month>9</month>
        <year>2007</year>
      </pub-date>
      <volume>7</volume>
      <fpage>238</fpage>
      <lpage>238</lpage>
      <ext-link ext-link-type="uri" xlink:href="http://www.biomedcentral.com/1471-2458/7/238"/>
      <history>
        <date date-type="received">
          <day>8</day>
          <month>8</month>
          <year>2007</year>
        </date>
        <date date-type="accepted">
          <day>12</day>
          <month>9</month>
          <year>2007</year>
        </date>
      </history>
      <permissions>
        <copyright-statement>Copyright © 2007 Merchant et al; licensee BioMed Central Ltd.</copyright-statement>
        <copyright-year>2007</copyright-year>
        <copyright-holder>Merchant et al; licensee BioMed Central Ltd.</copyright-holder>
        <license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/2.0">
          <p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/2.0"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>
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               Merchant
               C
               Roland
               
               
               
               rmerchant@lifespan.org
            </dc:author><dc:title>
            Comparison of patient comprehension of rapid HIV pre-test fundamentals by information delivery format in an emergency department setting
         </dc:title><dc:date>2007</dc:date><dcterms:bibliographicCitation>BMC Public Health 7(1): 238-. (2007)</dcterms:bibliographicCitation><dc:identifier type="sici">1471-2458(2007)7:1&#x0003c;238&#x0003e;</dc:identifier><dcterms:isPartOf>urn:ISSN:1471-2458</dcterms:isPartOf><License rdf:about="http://creativecommons.org/licenses/by/2.0"><permits rdf:resource="http://web.resource.org/cc/Reproduction" xmlns=""/><permits rdf:resource="http://web.resource.org/cc/Distribution" xmlns=""/><requires rdf:resource="http://web.resource.org/cc/Notice" xmlns=""/><requires rdf:resource="http://web.resource.org/cc/Attribution" xmlns=""/><permits rdf:resource="http://web.resource.org/cc/DerivativeWorks" xmlns=""/></License></Work></rdf>-->
        </license>
      </permissions>
      <abstract>
        <sec>
          <title>Background</title>
          <p>Two trials were conducted to compare emergency department patient comprehension of rapid HIV pre-test information using different methods to deliver this information.</p>
        </sec>
        <sec sec-type="methods">
          <title>Methods</title>
          <p>Patients were enrolled for these two trials at a US emergency department between February 2005 and January 2006. In Trial One, patients were randomized to a no pre-test information or an in-person discussion arm. In Trial Two, a separate group of patients were randomized to an in-person discussion arm or a Tablet PC-based video arm. The video, "Do you know about rapid HIV testing?", and the in-person discussion contained identical Centers for Disease Control and Prevention-suggested pre-test information components as well as information on rapid HIV testing with OraQuick<sup>®</sup>. Participants were compared by information arm on their comprehension of the pre-test information by their score on a 26-item questionnaire using the Wilcoxon rank-sum test.</p>
        </sec>
        <sec>
          <title>Results</title>
          <p>In Trial One, 38 patients completed the no-information arm and 31 completed the in-person discussion arm. Of these 69 patients, 63.8% had twelve years or fewer of formal education and 66.7% had previously been tested for HIV. The mean score on the questionnaire for the in-person discussion arm was higher than for the no information arm (18.7 vs. 13.3, p ≤ 0.0001). In Trial Two, 59 patients completed the in-person discussion and 55 completed the video arms. Of these 114 patients, 50.9% had twelve years or fewer of formal education and 68.4% had previously been tested for HIV. The mean score on the questionnaire for the video arm was similar to the in-person discussion arm (20.0 vs. 19.2; p ≤ 0.33).</p>
        </sec>
        <sec>
          <title>Conclusion</title>
          <p>The video "Do you know about rapid HIV testing?" appears to be an acceptable substitute for an in-person pre-test discussion on rapid HIV testing with OraQuick<sup>®</sup>. In terms of adequately informing ED patients about rapid HIV testing, either form of pre-test information is preferable than for patients to receive no pre-test information.</p>
        </sec>
      </abstract>
    </article-meta>
  </front>
  <body>
    <sec>
      <title>Background</title>
      <p>According to CDC estimates, there were 1,039,000–1,185,000 persons living with an HIV infection in the United States as of 2003 [<xref ref-type="bibr" rid="B1">1</xref>]. Of these, at least 25% are infected with HIV and are unaware of their infection. To help those infected with HIV learn their HIV status, the Centers for Disease Control and Prevention (CDC) advocate expanding HIV testing in non-traditional test settings, such as emergency departments (EDs) [<xref ref-type="bibr" rid="B2">2</xref>,<xref ref-type="bibr" rid="B3">3</xref>]. Rapid HIV testing might further reduce the number of persons unaware of their HIV status by streamlining the HIV testing process and by making HIV testing more readily available in a variety of locations. In September 2006, the CDC released new guidelines on HIV testing for healthcare settings [<xref ref-type="bibr" rid="B3">3</xref>]. To help facilitate HIV testing, the CDC recommended that traditional pre-test counseling be simplified by separating the routine requirement for pre-test information from the as needed provision of prevention counseling.</p>
      <p>One limitation of HIV testing in non-traditional settings is the difficulty of effectively providing pre-test information to those undergoing testing. In a busy ED, it can be challenging for staff to adequately give patients CDC-recommended components of HIV pre-test information. The open-space environment of EDs, the numerous distractions and noises, the sometimes critical nature of patient visits, and staff time limitations make it difficult to educate patients about HIV and HIV testing. In addition, staff knowledge about HIV testing varies, so information presented to patients might not be uniform and sometimes might not be accurate. Although written information is a potential alternative to an in-person discussion, this might not be adequate for all patients, given wide variations in patient reading abilities.</p>
      <p>One approach to address limitations of staff availability and to ensure standardization of HIV pre-test information is through the use of a patient educational video in lieu of an in-person discussion. Videos have been recommended or used as an adjunct to pre-test information or as substitutes for in-person discussion for standard (as opposed to rapid) HIV testing [<xref ref-type="bibr" rid="B4">4</xref>-<xref ref-type="bibr" rid="B8">8</xref>]. However, there have been few studies evaluating their effectiveness in providing this information, particularly as compared to an in-person discussion. Calderon, et al. created a video for standard HIV testing at the Jacobi ED in New York in response to a lack of HIV counselors after normal business hours [<xref ref-type="bibr" rid="B9">9</xref>]. Using a questionnaire developed by the authors, they observed that patients watching the video demonstrated greater knowledge (a 7% higher mean score) about standard HIV testing than those receiving information from an HIV test counselor. To our knowledge, there have been no studies in any setting evaluating the utility of a rapid HIV educational video as a substitute for in-person discussions about rapid HIV testing.</p>
      <p>Prior to the release of the new CDC HIV testing guidelines, we conducted two randomized controlled trials comparing different methods of delivering rapid HIV pre-test information to adult ED patients. We assessed patient comprehension of rapid HIV pre-test information using a questionnaire. In Trial One, we compared patient comprehension using this questionnaire among patients randomized to receive no pre-test information to those randomized to receive an in-person discussion about rapid HIV testing from an HIV test counselor. In Trial Two, we compared a separate group of patients who were randomized to an in-person discussion to those randomized to receive HIV pre-test information from the educational video, "Do you know about rapid HIV testing?"[<xref ref-type="bibr" rid="B10">10</xref>] The video and the in-person discussion contained the same CDC-recommended elements on pre-test HIV information as well as the same information specific to rapid HIV testing with OraQuick<sup>®</sup>. The goal of this pilot study was to evaluate these methods of pre-test information delivery prior to the conduct of a larger randomized controlled trial that included performing rapid HIV testing.</p>
    </sec>
    <sec sec-type="methods">
      <title>Methods</title>
      <sec>
        <title>Study design</title>
        <p>Two randomized controlled trials were conducted that examined different methods of rapid HIV testing information delivery. The trials were conducted sequentially. For both trials, participant understanding of rapid HIV testing fundamentals was evaluated using a questionnaire. The first trial compared participants who received no information to those who underwent an in-person discussion. The second trial compared participants who underwent an in-person discussion to those who watched an educational video. The Rhode Island Hospital institutional review board (IRB) approved the study. This study was a pilot to a larger trial comparing the video to the in-person discussion information delivery methods among patients undergoing rapid HIV testing with OraQuick<sup>®</sup>.</p>
      </sec>
      <sec>
        <title>Study population and eligibility</title>
        <p>The two trials were performed at the Rhode Island Hospital ED, which is a large, urban, academic ED in the northeastern US. Patients eligible for the trials were ED patients 18-55-years-old who were not pregnant; not incarcerated or in home confinement; not known to be HIV infected; able to speak, read, and write in English; were not deaf; and were not critically ill, intoxicated, or presenting to the ED for a psychiatric problem. Participants could only be members of one trial.</p>
      </sec>
      <sec>
        <title>Study conduct</title>
        <p>Trial One was conducted February-April 2005 and Trial Two between April 2005-January 2006. A research assistant (RA) conducted the trials weekdays during arbitrarily selected eight-hour shifts. The shifts began between 7 a.m. and 3 p.m. and ended between 3 p.m. and 11 p.m. For each trial, a research assistant (RA) randomly screened for study eligibility 50% of the medical records of patients who were present in the ED during the RA's shift. Before each shift, the RA used a random number generator to choose either the number 1 or 2 [<xref ref-type="bibr" rid="B11">11</xref>]. These numbers represented "odd" and "even" terminal medical record digits, respectively. The RAs screened only the "odd" or the "even" medical records for that shift as determined by this random selection scheme. The random selection was conducted to reduce the possibility that the RA might selectively choose patients to include in the study that could affect the outcome of the study, i.e., reduce selection bias.</p>
        <p>The RAs screened the ED medical records in the ambulatory care and urgent care areas of the ED looking for patients who potentially met the study eligibility criteria. Patients in the critical care, substance abuse, and psychiatric evaluation areas of the ED were not screened for study inclusion. The demographic profile (age, gender, race/ethnicity, marital status, and insurance type) for every patient screened was recorded into the study database. The RAs also recorded the reasons for exclusion from the study and did not approach those who were ineligible by ED medical record review.</p>
        <p>Patients who appeared to meet eligibility criteria by medical record review were approached by the RA. The RA briefly outlined the study purpose to the patient and asked for their verbal consent to confirm their demographic profile, study eligibility, and to ask additional questions about their HIV testing history and HIV status. Patients who declined to answer these questions or who were found to meet exclusion criteria during this brief interview (e.g., told the RA that they were HIV-infected) were excluded from the study. The RA recorded the reasons for their exclusion. Patients who met study eligibility were apprised of the study and invited to participate. Verbal agreement to participate was obtained.</p>
        <p>In Trial One, patients were randomized to an in-person discussion on rapid HIV testing information arm or a no-information arm. The no-information arm received no rapid HIV pre-test information of any type. In Trial Two, patients were randomized to an in-person discussion arm or a video arm. The RA randomized patients for each trial using their penultimate medical record number. Odd-numbered patients were assigned to the in-person discussion while even-numbered patients were assigned the other arm, respective to the trial. Following the delivery of rapid HIV test information (or no information), the RA orally administered an identical questionnaire to all participants to assess their comprehension on the material presented. At the completion of the questionnaire, respondents were given an opportunity to discuss any questions or concerns about the material or topics presented or the study itself. At the completion of the study, participants were provided a copy of the written consent summary and a brochure on HIV and HIV testing that also gave a list of locations in the local area where they could be tested for HIV.</p>
      </sec>
      <sec>
        <title>Rapid HIV pre-test information delivery</title>
        <p>For both trials, the in-person discussion was a semi-scripted conversation between the participant and RA on five topics: HIV and AIDS, HIV transmission, HIV prevention, HIV testing, and rapid HIV testing. An outline of the points covered in the in-person discussion is provided in Figure <xref ref-type="fig" rid="F1">1</xref>. The outline was created by the study authors and is based upon CDC recommendations for pre-test information [<xref ref-type="bibr" rid="B8">8</xref>] as well as manufacturer details on rapid HIV testing with OraQuick<sup>® </sup>[<xref ref-type="bibr" rid="B12">12</xref>]. RAs conducting the study memorized the outline and were trained to deliver it through mock-interviews. The principal investigator observed the RAs during the trials, critiqued their performance, and corrected deviations from the outline. The RAs also underwent training by the state department of health to be certified as HIV test counselors.</p>
        <fig position="float" id="F1">
          <label>Figure 1</label>
          <caption>
            <p>In-person discussion rapid HIV pre-test information outline.</p>
          </caption>
          <graphic xlink:href="1471-2458-7-238-1"/>
        </fig>
        <p>The in-person discussion resembled a didactic presentation yet was conducted in a conversational style. Participants were asked an opening question for each of the five topics. The RA would endorse or correct the participant's response then state the points relevant to that topic---whether or not the participant answered the opening question correctly. To ensure uniformity of the presented information, the RA limited the discussion to the outline. The RAs had an abbreviated version of the outline in Figure <xref ref-type="fig" rid="F1">1</xref> to use as a reference during the in-person discussion, but were not permitted read the outline verbatim to patients.</p>
        <p>In Trial Two, the video information arm patients watched the 9.5 minute animated and live-action educational video "Do you know about rapid HIV testing?"[<xref ref-type="bibr" rid="B10">10</xref>] that contained the same rapid HIV pre-test information elements presented to the in-person discussion arm. The video and its development are described in the accompanying manuscript: Development of the rapid HIV testing video, "Do you know about rapid HIV testing?" [see Additional file <xref ref-type="supplementary-material" rid="S1">1</xref>]. Participants randomized to the video arm watched the video on a hand-held Tablet PC while awaiting medical care in the ED. They listened to the video using headphones provided by the RA.</p>
      </sec>
      <sec>
        <title>Assessment of participant comprehension of rapid HIV testing fundamentals</title>
        <p>Participants in both trials were asked to complete the "HIV pre-test information comprehension" questionnaire to assess their comprehension of rapid HIV testing fundamentals. The development of the 26-item, "true", "false", "I don't know" questionnaire is described in the accompanying manuscript: Development of the "HIV pre-test information comprehension" questionnaire [see Additional file <xref ref-type="supplementary-material" rid="S2">2</xref>]. Participants in both trials received the identical version of the questionnaire. The RAs administered the questionnaire verbally to participants and recorded the responses onto a Tablet PC database. RAs provided all participants with a standardized, brief introduction to the nature of the questions, the reason for the questionnaire ("to determine how well we were able to give you this information about HIV and rapid HIV testing"), and the form of the responses needed ("true", "false", or "I don't know"). The RAs also informed participants that they would not be able to assist in answering the questions during the administration of the questionnaire, but could repeat questions as needed. Participants were asked to choose the response they thought was best, but to feel free to answer any question as "I don't know" when unsure of an answer. The RAs discussed the questions and answers with the participants after they completed the questionnaire.</p>
      </sec>
      <sec>
        <title>Data collection and analysis</title>
        <p>The RAs recorded all study data (demographic and HIV test history, eligibility determinations, responses to the questionnaire, etc.) onto a Tablet PC study database using the QDS<sup>® </sup>(NOVA Research, Bethesda, MD) data entry and management software. To ensure accuracy of the data entry, the data were entered in duplicate with immediate data verification. The data were analyzed using Stata 9.2 (Stata Corporation, College Station, TX). The analysis included tabulating the results of the medical record screening and eligibility determinations; participant demographic profiles, educational level, and HIV testing histories; and responses to the "HIV pre-test information comprehension" questionnaire. Patients were compared by their demographic profiles according to their eligibility, participation, and study arm assignment using Pearson's χ<sup>2 </sup>test for categorical values; Fisher's exact test for categorical values with small samples; two-sample tests of binomial proportions for dichotomous values; and Wilcoxon rank-sum test for continuous values. Participant educational level and HIV testing history were compared by study arm assignment using Pearson's χ<sup>2 </sup>test and Fisher's exact test.</p>
        <p>The mean score and standard deviation, median, and range for each of the five topics areas of the questionnaire and the entire questionnaire were calculated by arm assignment for both trials. We originally estimated requiring a sample size of 55 for each arm of Trial Two to demonstrate a 12% absolute increase in mean scores. We assumed the same standard deviation for each arm, a normal distribution of scores, α = 0.05, β = 0.10, and use of Student's t-test. However, using plots of the scores for each trial and the Wilk-Shapiro test, we observed that the scores were not normally distributed, therefore, the scores for the arms were instead compared using the Wilcoxon rank-sum test. Differences were considered significant at the α = 0.05 level. In an exploratory analysis, the proportions of participants answering each question correctly were compared by arm assignment using two-sample tests of binomial proportions. This exploratory analysis was used to help identify sub-topics that might not have been well addressed in the pre-test information stage or highlight questions that might not have been well understood by participants.</p>
      </sec>
    </sec>
    <sec>
      <title>Results</title>
      <sec>
        <title>Study participant demography and HIV testing history</title>
        <sec>
          <title>Trial One</title>
          <p>Figure <xref ref-type="fig" rid="F2">2</xref> depicts the results of the screening and enrollment for Trial One. Of the 349 ED patients whose medical records were randomly screened for Trial One, 88 were eligible for participation. The primary reason for ineligibility was age &lt; 18 or age &gt; 55 years (50.6%). Twenty patients declined or did not complete the screening process. Of the 88 patients who completed the screening process with the RA and were eligible for the study, 73 originally agreed to be in the study. Of these, 34 patients were randomized to the in-person discussion and 39 to the no-information arm. Three people randomized to the in-person discussion arm and one in the no-information arm dropped out of the study.</p>
          <fig position="float" id="F2">
            <label>Figure 2</label>
            <caption>
              <p>Trial one screening and enrollment diagram.</p>
            </caption>
            <graphic xlink:href="1471-2458-7-238-2"/>
          </fig>
          <p>Table <xref ref-type="table" rid="T1">1</xref> provides a comparison of the demography and HIV testing history of the patients by whether or not they participated in the study and by study arm. The participant and non-participant groups and the in-person discussion and no-information arms had similar demographic and HIV testing history profiles. Most of the participants were male, white, single/never married, had governmental insurance (Medicaid, Medicare, or both), had twelve or fewer years of formal education, and had previously been tested for HIV. Of those who had ever been tested for HIV, 40.4% had been tested within the prior year. The participants in the two arms were similar in their profiles except for partner status and time elapsed since their last HIV test. There were relatively more single/never married and separated participants in the no-information arm and relatively more married and divorced participants in the in-person discussion arm. There were relatively more participants who had been tested within the past six months in the no-information arm.</p>
          <table-wrap position="float" id="T1">
            <label>Table 1</label>
            <caption>
              <p>Demographic and HIV testing history profiles: Trial One</p>
            </caption>
            <table frame="hsides" rules="groups">
              <thead>
                <tr>
                  <td/>
                  <td align="center">
                    <bold>Non-participants</bold>
                  </td>
                  <td align="center">
                    <bold>Participants</bold>
                  </td>
                  <td align="center">
                    <bold>p-value</bold>
                  </td>
                  <td align="center">
                    <bold>In-person discussion arm</bold>
                  </td>
                  <td align="center">
                    <bold>No information arm</bold>
                  </td>
                  <td align="center">
                    <bold>p-value</bold>
                  </td>
                </tr>
                <tr>
                  <td/>
                  <td align="center">
                    <italic>n = 15</italic>
                  </td>
                  <td align="center">
                    <italic>n = 73</italic>
                  </td>
                  <td align="center"><italic>p</italic>≤</td>
                  <td align="center">
                    <italic>n = 34*</italic>
                  </td>
                  <td align="center">
                    <italic>n = 39*</italic>
                  </td>
                  <td align="center"><italic>p</italic>≤</td>
                </tr>
              </thead>
              <tbody>
                <tr>
                  <td align="center">
                    <bold>Median age (Range)</bold>
                  </td>
                  <td align="center">40 (19–54)</td>
                  <td align="center">35 (19–55)</td>
                  <td align="center">0.27</td>
                  <td align="center">38 (19–55)</td>
                  <td align="center">34 (19–55)</td>
                  <td align="center">0.14</td>
                </tr>
                <tr>
                  <td/>
                  <td align="center">
                    <italic>%</italic>
                  </td>
                  <td align="center">
                    <italic>%</italic>
                  </td>
                  <td/>
                  <td align="center">
                    <italic>%</italic>
                  </td>
                  <td align="center">
                    <italic>%</italic>
                  </td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">
                    <bold>Gender</bold>
                  </td>
                  <td/>
                  <td/>
                  <td align="center">0.45</td>
                  <td/>
                  <td/>
                  <td align="center">0.60</td>
                </tr>
                <tr>
                  <td align="center">Female</td>
                  <td align="center">33.3</td>
                  <td align="center">43.8</td>
                  <td/>
                  <td align="center">52.9</td>
                  <td align="center">59.0</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">Male</td>
                  <td align="center">66.7</td>
                  <td align="center">56.2</td>
                  <td/>
                  <td align="center">47.1</td>
                  <td align="center">41.0</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">
                    <bold>Ethnicity/Race</bold>
                  </td>
                  <td/>
                  <td/>
                  <td align="center">0.75</td>
                  <td/>
                  <td/>
                  <td align="center">0.96</td>
                </tr>
                <tr>
                  <td align="center">Black</td>
                  <td align="center">20.0</td>
                  <td align="center">30.1</td>
                  <td/>
                  <td align="center">32.4</td>
                  <td align="center">28.2</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">Hispanic</td>
                  <td align="center">6.7</td>
                  <td align="center">5.5</td>
                  <td/>
                  <td align="center">5.9</td>
                  <td align="center">5.1</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">White</td>
                  <td align="center">73.3</td>
                  <td align="center">61.6</td>
                  <td/>
                  <td align="center">58.8</td>
                  <td align="center">64.1</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">Other</td>
                  <td align="center">0.0</td>
                  <td align="center">2.8</td>
                  <td/>
                  <td align="center">2.9</td>
                  <td align="center">2.6</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">
                    <bold>Partner status</bold>
                  </td>
                  <td/>
                  <td/>
                  <td align="center">0.19</td>
                  <td/>
                  <td/>
                  <td align="center">0.04</td>
                </tr>
                <tr>
                  <td align="center">Single/never married</td>
                  <td align="center">26.7</td>
                  <td align="center">52.1</td>
                  <td/>
                  <td align="center">41.2</td>
                  <td align="center">61.5</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">Married</td>
                  <td align="center">46.7</td>
                  <td align="center">27.4</td>
                  <td/>
                  <td align="center">38.2</td>
                  <td align="center">17.9</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">Divorced</td>
                  <td align="center">26.6</td>
                  <td align="center">12.3</td>
                  <td/>
                  <td align="center">17.7</td>
                  <td align="center">7.7</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">Separated</td>
                  <td align="center">0.0</td>
                  <td align="center">5.5</td>
                  <td/>
                  <td align="center">0.0</td>
                  <td align="center">10.3</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">Unmarried couple</td>
                  <td align="center">0.0</td>
                  <td align="center">2.7</td>
                  <td/>
                  <td align="center">2.9</td>
                  <td align="center">2.6</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">
                    <bold>Insurance status</bold>
                  </td>
                  <td/>
                  <td/>
                  <td align="center">0.46</td>
                  <td/>
                  <td/>
                  <td align="center">0.09</td>
                </tr>
                <tr>
                  <td align="center">Private</td>
                  <td align="center">20.0</td>
                  <td align="center">34.2</td>
                  <td/>
                  <td align="center">35.3</td>
                  <td align="center">33.3</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">Governmental</td>
                  <td align="center">46.7</td>
                  <td align="center">43.8</td>
                  <td/>
                  <td align="center">53.0</td>
                  <td align="center">35.9</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">Private/Governmental</td>
                  <td align="center">6.6</td>
                  <td align="center">1.4</td>
                  <td/>
                  <td align="center">2.9</td>
                  <td align="center">0.0</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">None</td>
                  <td align="center">26.7</td>
                  <td align="center">19.2</td>
                  <td/>
                  <td align="center">8.8</td>
                  <td align="center">28.2</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">Don't know</td>
                  <td align="center">0.0</td>
                  <td align="center">1.4</td>
                  <td/>
                  <td align="center">0.0</td>
                  <td align="center">2.6</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">
                    <bold>Years of formal education</bold>
                  </td>
                  <td/>
                  <td/>
                  <td align="center">0.16</td>
                  <td/>
                  <td/>
                  <td align="center">0.43</td>
                </tr>
                <tr>
                  <td align="center">Grades 1–8</td>
                  <td align="center">6.6</td>
                  <td align="center">1.4</td>
                  <td/>
                  <td align="center">0.0</td>
                  <td align="center">2.6</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">Grades 9–11</td>
                  <td align="center">6.7</td>
                  <td align="center">21.9</td>
                  <td/>
                  <td align="center">17.7</td>
                  <td align="center">25.6</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">Grade 12 or equivalent</td>
                  <td align="center">60.0</td>
                  <td align="center">41.1</td>
                  <td/>
                  <td align="center">38.2</td>
                  <td align="center">43.6</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">College 1–3 years</td>
                  <td align="center">26.7</td>
                  <td align="center">21.9</td>
                  <td/>
                  <td align="center">23.5</td>
                  <td align="center">20.5</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">College 4 years</td>
                  <td align="center">0.0</td>
                  <td align="center">13.7</td>
                  <td/>
                  <td align="center">20.6</td>
                  <td align="center">7.7</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">
                    <bold>Prior HIV test</bold>
                  </td>
                  <td/>
                  <td/>
                  <td align="center">0.19</td>
                  <td/>
                  <td/>
                  <td align="center">0.99</td>
                </tr>
                <tr>
                  <td align="center">Yes</td>
                  <td align="center">53.3</td>
                  <td align="center">64.4</td>
                  <td/>
                  <td align="center">64.7</td>
                  <td align="center">64.1</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">No</td>
                  <td align="center">40.0</td>
                  <td align="center">35.6</td>
                  <td/>
                  <td align="center">35.3</td>
                  <td align="center">35.9</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">Don't know</td>
                  <td align="center">6.7</td>
                  <td align="center">0.0</td>
                  <td/>
                  <td align="center">0.0</td>
                  <td align="center">0.0</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">
                    <bold>Time elapsed since last HIV test</bold>
                  </td>
                  <td align="center">
                    <italic>n = 8</italic>
                  </td>
                  <td align="center">
                    <italic>n = 47</italic>
                  </td>
                  <td align="center">0.21</td>
                  <td align="center">
                    <italic>n = 22</italic>
                  </td>
                  <td align="center">
                    <italic>n = 25</italic>
                  </td>
                  <td align="center">0.03</td>
                </tr>
                <tr>
                  <td align="center">&gt; 5 years</td>
                  <td align="center">0.0</td>
                  <td align="center">17.0</td>
                  <td/>
                  <td align="center">18.2</td>
                  <td align="center">16.0</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">&gt; 2 years ≤ 5 years</td>
                  <td align="center">37.5</td>
                  <td align="center">21.3</td>
                  <td/>
                  <td align="center">31.8</td>
                  <td align="center">12.0</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">&gt; 1 year ≤ 2 years</td>
                  <td align="center">25.0</td>
                  <td align="center">21.3</td>
                  <td/>
                  <td align="center">27.3</td>
                  <td align="center">16.0</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">&gt; 6 months ≤ 1 year</td>
                  <td align="center">0.0</td>
                  <td align="center">14.9</td>
                  <td/>
                  <td align="center">18.2</td>
                  <td align="center">12.0</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">≤6 months</td>
                  <td align="center">25.0</td>
                  <td align="center">25.5</td>
                  <td/>
                  <td align="center">4.6</td>
                  <td align="center">44.0</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">Don't recall</td>
                  <td align="center">12.5</td>
                  <td align="center">0.0</td>
                  <td/>
                  <td align="center">0.0</td>
                  <td align="center">0.0</td>
                  <td/>
                </tr>
              </tbody>
            </table>
            <table-wrap-foot>
              <p>*Three patients in the in-person discussion and one in the no information arm dropped out from the study after randomization</p>
            </table-wrap-foot>
          </table-wrap>
        </sec>
        <sec>
          <title>Trial Two</title>
          <p>Figure <xref ref-type="fig" rid="F3">3</xref> depicts the results of the screening and enrollment for Trial Two. Of the 1,062 ED patients whose medical records were randomly screened for Trial Two, 216 were eligible for participation. The primary reason for ineligibility was age &lt; 18 or age &gt; 55 years (47.9%). Forty-four patients declined or did not complete the screening process. Of the 216 patients who completed the screening process and were eligible for the study, 120 originally agreed to be in the study. Of these, 62 were randomized to the in-person discussion and 58 to the video arm. Three people randomized to the in-person arm and three to the video arm dropped out of the study.</p>
          <fig position="float" id="F3">
            <label>Figure 3</label>
            <caption>
              <p>Trial two screening and enrollment diagram.</p>
            </caption>
            <graphic xlink:href="1471-2458-7-238-3"/>
          </fig>
          <p>As shown in Table <xref ref-type="table" rid="T2">2</xref>, Trial Two participants and non-participants had similar demographic profiles. There were more non-participants who had not been previously tested for HIV. Most of the participants were male, white, single/never married, had private healthcare insurance, had twelve or fewer years of formal education, and had previously been tested for HIV. Of those tested for HIV, 43.2% had been tested within the past year. The two randomized arms were similar in their demographic and HIV history profiles.</p>
          <table-wrap position="float" id="T2">
            <label>Table 2</label>
            <caption>
              <p>Demographic and HIV testing history profiles: Trial Two</p>
            </caption>
            <table frame="hsides" rules="groups">
              <thead>
                <tr>
                  <td/>
                  <td align="center">
                    <bold>Non-participants</bold>
                  </td>
                  <td align="center">
                    <bold>Participants</bold>
                  </td>
                  <td align="center">
                    <bold>p-value</bold>
                  </td>
                  <td align="center">
                    <bold>Video arm</bold>
                  </td>
                  <td align="center">
                    <bold>No information arm</bold>
                  </td>
                  <td align="center">
                    <bold>p-value</bold>
                  </td>
                </tr>
                <tr>
                  <td/>
                  <td align="center">
                    <italic>n = 96</italic>
                  </td>
                  <td align="center">
                    <italic>n = 120</italic>
                  </td>
                  <td align="center"><italic>p</italic>≤</td>
                  <td align="center">
                    <italic>n = 58*</italic>
                  </td>
                  <td align="center">
                    <italic>n = 62*</italic>
                  </td>
                  <td align="center"><italic>p</italic>≤</td>
                </tr>
              </thead>
              <tbody>
                <tr>
                  <td align="center">
                    <bold>Median age (Range)</bold>
                  </td>
                  <td align="center">38 (18–55)</td>
                  <td align="center">35 (18–55)</td>
                  <td align="center">0.21</td>
                  <td align="center">34 (19–55)</td>
                  <td align="center">37 (19–55)</td>
                  <td align="center">0.45</td>
                </tr>
                <tr>
                  <td/>
                  <td align="center">
                    <italic>%</italic>
                  </td>
                  <td align="center">
                    <italic>%</italic>
                  </td>
                  <td/>
                  <td align="center">
                    <italic>%</italic>
                  </td>
                  <td align="center">
                    <italic>%</italic>
                  </td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">
                    <bold>Gender</bold>
                  </td>
                  <td/>
                  <td/>
                  <td align="center">0.62</td>
                  <td/>
                  <td/>
                  <td align="center">0.48</td>
                </tr>
                <tr>
                  <td align="center">Female</td>
                  <td align="center">50.0</td>
                  <td align="center">46.7</td>
                  <td/>
                  <td align="center">50.0</td>
                  <td align="center">43.6</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">Male</td>
                  <td align="center">50.0</td>
                  <td align="center">53.3</td>
                  <td/>
                  <td align="center">50.0</td>
                  <td align="center">56.4</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">
                    <bold>Ethnicity/Race</bold>
                  </td>
                  <td/>
                  <td/>
                  <td align="center">0.69</td>
                  <td/>
                  <td/>
                  <td align="center">0.09</td>
                </tr>
                <tr>
                  <td align="center">Black</td>
                  <td align="center">19.4</td>
                  <td align="center">14.2</td>
                  <td/>
                  <td align="center">8.6</td>
                  <td align="center">19.4</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">Hispanic</td>
                  <td align="center">11.2</td>
                  <td align="center">11.7</td>
                  <td/>
                  <td align="center">8.6</td>
                  <td align="center">14.5</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">White</td>
                  <td align="center">66.3</td>
                  <td align="center">69.1</td>
                  <td/>
                  <td align="center">74.2</td>
                  <td align="center">64.5</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">Other</td>
                  <td align="center">3.1</td>
                  <td align="center">5.0</td>
                  <td/>
                  <td align="center">8.6</td>
                  <td align="center">1.6</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">
                    <bold>Partner status</bold>
                  </td>
                  <td/>
                  <td/>
                  <td align="center">0.35</td>
                  <td/>
                  <td/>
                  <td align="center">0.50</td>
                </tr>
                <tr>
                  <td align="center">Single/never married</td>
                  <td align="center">41.9</td>
                  <td align="center">33.3</td>
                  <td/>
                  <td align="center">32.8</td>
                  <td align="center">33.9</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">Married</td>
                  <td align="center">31.6</td>
                  <td align="center">30.0</td>
                  <td/>
                  <td align="center">31.0</td>
                  <td align="center">29.0</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">Divorced</td>
                  <td align="center">10.2</td>
                  <td align="center">17.5</td>
                  <td/>
                  <td align="center">22.4</td>
                  <td align="center">12.9</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">Separated</td>
                  <td align="center">5.1</td>
                  <td align="center">4.2</td>
                  <td/>
                  <td align="center">3.5</td>
                  <td align="center">4.8</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">Widowed</td>
                  <td align="center">1.0</td>
                  <td align="center">0.0</td>
                  <td/>
                  <td align="center">0.0</td>
                  <td align="center">0.0</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">Unmarried couple</td>
                  <td align="center">10.2</td>
                  <td align="center">15.0</td>
                  <td/>
                  <td align="center">10.3</td>
                  <td align="center">19.4</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">
                    <bold>Insurance status</bold>
                  </td>
                  <td/>
                  <td/>
                  <td align="center">0.99</td>
                  <td/>
                  <td/>
                  <td align="center">0.48</td>
                </tr>
                <tr>
                  <td align="center">Private</td>
                  <td align="center">44.9</td>
                  <td align="center">44.2</td>
                  <td/>
                  <td align="center">43.1</td>
                  <td align="center">45.2</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">Governmental</td>
                  <td align="center">34.7</td>
                  <td align="center">35.8</td>
                  <td/>
                  <td align="center">34.5</td>
                  <td align="center">37.1</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">Private/Governmental</td>
                  <td align="center">1.0</td>
                  <td align="center">1.7</td>
                  <td/>
                  <td align="center">0.0</td>
                  <td align="center">3.2</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">None</td>
                  <td align="center">19.4</td>
                  <td align="center">18.3</td>
                  <td/>
                  <td align="center">22.4</td>
                  <td align="center">14.5</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">
                    <bold>Years of formal education</bold>
                  </td>
                  <td/>
                  <td/>
                  <td align="center">0.17</td>
                  <td/>
                  <td/>
                  <td align="center">0.63</td>
                </tr>
                <tr>
                  <td align="center">Grades 1–8</td>
                  <td align="center">5.1</td>
                  <td align="center">2.5</td>
                  <td/>
                  <td align="center">3.5</td>
                  <td align="center">1.6</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">Grades 9–11</td>
                  <td align="center">30.6</td>
                  <td align="center">18.3</td>
                  <td/>
                  <td align="center">17.2</td>
                  <td align="center">19.4</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">Grade 12 or equivalent</td>
                  <td align="center">27.6</td>
                  <td align="center">30.8</td>
                  <td/>
                  <td align="center">36.2</td>
                  <td align="center">25.8</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">College 1–3 years</td>
                  <td align="center">24.5</td>
                  <td align="center">34.2</td>
                  <td/>
                  <td align="center">32.8</td>
                  <td align="center">35.5</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">College 4 years</td>
                  <td align="center">12.2</td>
                  <td align="center">14.2</td>
                  <td/>
                  <td align="center">10.3</td>
                  <td align="center">17.7</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">
                    <bold>Prior HIV test</bold>
                  </td>
                  <td/>
                  <td/>
                  <td align="center">0.02</td>
                  <td/>
                  <td/>
                  <td align="center">0.23</td>
                </tr>
                <tr>
                  <td align="center">Yes</td>
                  <td align="center">55.1</td>
                  <td align="center">68.3</td>
                  <td/>
                  <td align="center">65.5</td>
                  <td align="center">71.0</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">No</td>
                  <td align="center">44.9</td>
                  <td align="center">29.2</td>
                  <td/>
                  <td align="center">29.3</td>
                  <td align="center">29.0</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">Don't know</td>
                  <td align="center">0.0</td>
                  <td align="center">2.5</td>
                  <td/>
                  <td align="center">5.2</td>
                  <td align="center">0.0</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">
                    <bold>Time elapsed since last HIV test</bold>
                  </td>
                  <td align="center">
                    <italic>n = 54</italic>
                  </td>
                  <td align="center">
                    <italic>n = 81</italic>
                  </td>
                  <td align="center">0.95</td>
                  <td align="center">
                    <italic>n = 22</italic>
                  </td>
                  <td align="center">
                    <italic>n = 25</italic>
                  </td>
                  <td align="center">0.34</td>
                </tr>
                <tr>
                  <td align="center">&gt; 5 years</td>
                  <td align="center">24.1</td>
                  <td align="center">23.5</td>
                  <td/>
                  <td align="center">24.3</td>
                  <td align="center">22.7</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">&gt; 2 years ≤ 5 years</td>
                  <td align="center">22.2</td>
                  <td align="center">17.3</td>
                  <td/>
                  <td align="center">16.2</td>
                  <td align="center">18.2</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">&gt; 1 year ≤ 2 years</td>
                  <td align="center">13.0</td>
                  <td align="center">16.0</td>
                  <td/>
                  <td align="center">21.6</td>
                  <td align="center">11.4</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">&gt; 6 months ≤ 1 year</td>
                  <td align="center">16.7</td>
                  <td align="center">19.7</td>
                  <td/>
                  <td align="center">10.8</td>
                  <td align="center">27.3</td>
                  <td/>
                </tr>
                <tr>
                  <td align="center">≤6 months</td>
                  <td align="center">24.0</td>
                  <td align="center">23.5</td>
                  <td/>
                  <td align="center">27.1</td>
                  <td align="center">20.4</td>
                  <td/>
                </tr>
              </tbody>
            </table>
            <table-wrap-foot>
              <p>*Three patients in each arm dropped out of the study after randomization</p>
            </table-wrap-foot>
          </table-wrap>
        </sec>
      </sec>
      <sec>
        <title>Rapid HIV testing comprehension</title>
        <p>Table <xref ref-type="table" rid="T3">3</xref> shows by arm assignment the percentages of participants correctly answering the "HIV pre-test information comprehension" questions. The results of the two-sample tests of binomial proportions are provided in an exploratory analysis to identify potential sub-topics or questions that might not have been well understood by participants. Across both trials, there were twelve questions correctly answered by more than 50% of the patients in all arms and five correctly answered by more than 75% of patients in all arms. Fewer than 50% of participants in all arms were able to correctly answer the questions regarding the role of HIV antibodies (question 15) and phlebotomy for the rapid HIV test (question 25).</p>
        <table-wrap position="float" id="T3">
          <label>Table 3</label>
          <caption>
            <p>Correct responses on the "HIV pre-test information comprehension" questionnaire</p>
          </caption>
          <table frame="hsides" rules="groups">
            <thead>
              <tr>
                <td/>
                <td/>
                <td align="center" colspan="3">
                  <bold>Trial One</bold>
                </td>
                <td align="center" colspan="3">
                  <bold>Trial Two</bold>
                </td>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td/>
                <td/>
                <td align="center">
                  <bold>No information</bold>
                </td>
                <td align="center">
                  <bold>In-person discussion</bold>
                </td>
                <td align="center">
                  <bold>p-value</bold>
                </td>
                <td align="center">
                  <bold>In person discussion</bold>
                </td>
                <td align="center">
                  <bold>Video</bold>
                </td>
                <td align="center">
                  <bold>p-value</bold>
                </td>
              </tr>
              <tr>
                <td/>
                <td/>
                <td align="center">
                  <italic>n = 31</italic>
                </td>
                <td align="center">
                  <italic>n = 38</italic>
                </td>
                <td/>
                <td align="center">
                  <italic>n = 59</italic>
                </td>
                <td align="center">
                  <italic>n = 55</italic>
                </td>
                <td/>
              </tr>
              <tr>
                <td align="center">
                  <bold>Question</bold>
                </td>
                <td align="center">
                  <bold>HIV/AIDS Definition</bold>
                </td>
                <td align="center">
                  <italic>%</italic>
                </td>
                <td align="center">
                  <italic>%</italic>
                </td>
                <td align="center">p≤</td>
                <td align="center">
                  <italic>%</italic>
                </td>
                <td align="center">
                  <italic>%</italic>
                </td>
                <td align="center">p≤</td>
              </tr>
              <tr>
                <td colspan="8">
                  <hr/>
                </td>
              </tr>
              <tr>
                <td align="center">1</td>
                <td align="left">If you were HIV infected, current drug treatments would let you live longer. (T)</td>
                <td align="center">86.8</td>
                <td align="center">90.3</td>
                <td align="center">0.65</td>
                <td align="center">83.1</td>
                <td align="center">89.1</td>
                <td align="center">0.36</td>
              </tr>
              <tr>
                <td align="center">2</td>
                <td align="left">People can get AIDS without getting HIV. (F)</td>
                <td align="center">36.8</td>
                <td align="center">71.0</td>
                <td align="center">0.00</td>
                <td align="center">86.4</td>
                <td align="center">76.4</td>
                <td align="center">0.17</td>
              </tr>
              <tr>
                <td align="center">3</td>
                <td align="left">Being infected with HIV does not mean you have AIDS. (T)</td>
                <td align="center">65.8</td>
                <td align="center">90.3</td>
                <td align="center">0.01</td>
                <td align="center">89.8</td>
                <td align="center">74.6</td>
                <td align="center">0.03</td>
              </tr>
              <tr>
                <td align="center">4</td>
                <td align="left">A person can be infected with HIV for 5 years or more without getting AIDS. (T)</td>
                <td align="center">76.3</td>
                <td align="center">96.8</td>
                <td align="center">0.01</td>
                <td align="center">91.5</td>
                <td align="center">92.7</td>
                <td align="center">0.81</td>
              </tr>
              <tr>
                <td/>
                <td align="center">
                  <bold>HIV Transmission</bold>
                </td>
                <td/>
                <td/>
                <td/>
                <td/>
                <td/>
                <td/>
              </tr>
              <tr>
                <td align="center">5</td>
                <td align="left">A person cannot get HIV by donating blood. (T)</td>
                <td align="center">39.5</td>
                <td align="center">54.8</td>
                <td align="center">0.21</td>
                <td align="center">57.6</td>
                <td align="center">65.5</td>
                <td align="center">0.39</td>
              </tr>
              <tr>
                <td align="center">6</td>
                <td align="left">A woman with HIV can give HIV to her baby during breastfeeding. (T)</td>
                <td align="center">68.4</td>
                <td align="center">100.0</td>
                <td align="center">0.00</td>
                <td align="center">98.3</td>
                <td align="center">94.6</td>
                <td align="center">0.28</td>
              </tr>
              <tr>
                <td align="center">7</td>
                <td align="left">If someone gets HIV through needle sharing, that person can only spread HIV by sharing needles with other people. (F)</td>
                <td align="center">63.2</td>
                <td align="center">80.7</td>
                <td align="center">0.10</td>
                <td align="center">79.7</td>
                <td align="center">89.1</td>
                <td align="center">0.17</td>
              </tr>
              <tr>
                <td align="center">8</td>
                <td align="left">Coins, such as quarters or nickels, can carry HIV. (F)</td>
                <td align="center">68.4</td>
                <td align="center">93.6</td>
                <td align="center">0.01</td>
                <td align="center">98.3</td>
                <td align="center">90.9</td>
                <td align="center">0.08</td>
              </tr>
              <tr>
                <td align="center">9</td>
                <td align="left">A person cannot get HIV by putting their tongue in the mouth of someone who has HIV. (T)</td>
                <td align="center">42.1</td>
                <td align="center">61.3</td>
                <td align="center">0.11</td>
                <td align="center">67.8</td>
                <td align="center">81.8</td>
                <td align="center">0.08</td>
              </tr>
              <tr>
                <td/>
                <td align="center">
                  <bold>HIV Prevention</bold>
                </td>
                <td/>
                <td/>
                <td/>
                <td/>
                <td/>
                <td/>
              </tr>
              <tr>
                <td align="center">10</td>
                <td align="left">HIV is destroyed by bleach. (T)</td>
                <td align="center">13.2</td>
                <td align="center">58.1</td>
                <td align="center">0.00</td>
                <td align="center">55.9</td>
                <td align="center">52.7</td>
                <td align="center">0.73</td>
              </tr>
              <tr>
                <td align="center">11</td>
                <td align="left">If you use injection drugs, the only way to prevent getting HIV is to quit using them. (F)</td>
                <td align="center">50.0</td>
                <td align="center">64.5</td>
                <td align="center">0.22</td>
                <td align="center">61.0</td>
                <td align="center">65.5</td>
                <td align="center">0.62</td>
              </tr>
              <tr>
                <td align="center">12</td>
                <td align="left">Wearing insect repellant to keep away mosquitoes will help prevent you from getting HIV. (F)</td>
                <td align="center">81.6</td>
                <td align="center">61.3</td>
                <td align="center">0.06</td>
                <td align="center">86.4</td>
                <td align="center">89.1</td>
                <td align="center">0.66</td>
              </tr>
              <tr>
                <td align="center">13</td>
                <td align="left">Not having sex is the only way to reduce your risk of getting HIV. (F)</td>
                <td align="center">71.1</td>
                <td align="center">74.2</td>
                <td align="center">0.77</td>
                <td align="center">71.2</td>
                <td align="center">74.6</td>
                <td align="center">0.68</td>
              </tr>
              <tr>
                <td align="center">14</td>
                <td align="left">You can prevent getting HIV after sex by washing your genitals or private parts. (F)</td>
                <td align="center">84.2</td>
                <td align="center">83.8</td>
                <td align="center">0.96</td>
                <td align="center">93.1</td>
                <td align="center">96.4</td>
                <td align="center">0.43</td>
              </tr>
              <tr>
                <td/>
                <td align="center">
                  <bold>HIV Testing</bold>
                </td>
                <td/>
                <td/>
                <td/>
                <td/>
                <td/>
                <td/>
              </tr>
              <tr>
                <td align="center">15</td>
                <td align="left">HIV makes antibodies which harm a person's body. (F)</td>
                <td align="center">10.5</td>
                <td align="center">19.4</td>
                <td align="center">0.31</td>
                <td align="center">30.5</td>
                <td align="center">23.6</td>
                <td align="center">0.41</td>
              </tr>
              <tr>
                <td align="center">16</td>
                <td align="left">Having blood drawn for an HIV test will make you anemic. (F)</td>
                <td align="center">81.6</td>
                <td align="center">93.6</td>
                <td align="center">0.12</td>
                <td align="center">91.5</td>
                <td align="center">89.1</td>
                <td align="center">0.66</td>
              </tr>
              <tr>
                <td align="center">17</td>
                <td align="left">The HIV antibody test will help strengthen your antibodies to keep you from getting infected with HIV. (F)</td>
                <td align="center">76.3</td>
                <td align="center">83.9</td>
                <td align="center">0.43</td>
                <td align="center">83.1</td>
                <td align="center">85.5</td>
                <td align="center">0.73</td>
              </tr>
              <tr>
                <td align="center">18</td>
                <td align="left">If you were infected with HIV one week ago, your HIV test will be negative. (T)</td>
                <td align="center">42.1</td>
                <td align="center">61.3</td>
                <td align="center">0.11</td>
                <td align="center">57.6</td>
                <td align="center">80.0</td>
                <td align="center">0.10</td>
              </tr>
              <tr>
                <td align="center">19</td>
                <td align="left">The HIV antibody test will not tell you if you have AIDS. (T)</td>
                <td align="center">42.1</td>
                <td align="center">42.2</td>
                <td align="center">0.99</td>
                <td align="center">55.9</td>
                <td align="center">69.1</td>
                <td align="center">0.15</td>
              </tr>
              <tr>
                <td align="center">20</td>
                <td align="left">If your HIV test is negative, it must be repeated within a week to confirm the results. (F)</td>
                <td align="center">31.6</td>
                <td align="center">61.3</td>
                <td align="center">0.01</td>
                <td align="center">54.2</td>
                <td align="center">70.9</td>
                <td align="center">0.07</td>
              </tr>
              <tr>
                <td/>
                <td align="center">
                  <bold>Rapid HIV Testing</bold>
                </td>
                <td/>
                <td/>
                <td/>
                <td/>
                <td/>
                <td/>
              </tr>
              <tr>
                <td align="center">21</td>
                <td align="left">It takes one to two days to perform a rapid HIV test. (F)</td>
                <td align="center">18.4</td>
                <td align="center">77.4</td>
                <td align="center">0.00</td>
                <td align="center">81.4</td>
                <td align="center">74.6</td>
                <td align="center">0.38</td>
              </tr>
              <tr>
                <td align="center">22</td>
                <td align="left">An invalid rapid HIV test result means you've been infected with HIV for fewer than 3 months. (F)</td>
                <td align="center">34.2</td>
                <td align="center">61.3</td>
                <td align="center">0.03</td>
                <td align="center">72.9</td>
                <td align="center">78.2</td>
                <td align="center">0.51</td>
              </tr>
              <tr>
                <td align="center">23</td>
                <td align="left">If your rapid HIV test is positive, then you will need a test to confirm this. (T)</td>
                <td align="center">71.1</td>
                <td align="center">87.1</td>
                <td align="center">0.09</td>
                <td align="center">81.4</td>
                <td align="center">89.1</td>
                <td align="center">0.25</td>
              </tr>
              <tr>
                <td align="center">24</td>
                <td align="left">The rapid HIV test with OraQuick uses a sample of your urine. (F)</td>
                <td align="center">34.2</td>
                <td align="center">90.3</td>
                <td align="center">0.00</td>
                <td align="center">81.4</td>
                <td align="center">87.3</td>
                <td align="center">0.39</td>
              </tr>
              <tr>
                <td align="center">25</td>
                <td align="left">A needle can be used to take blood from your arm for the OraQuick rapid HIV test. (T)</td>
                <td align="center">42.1</td>
                <td align="center">45.2</td>
                <td align="center">0.80</td>
                <td align="center">37.3</td>
                <td align="center">38.9</td>
                <td align="center">0.86</td>
              </tr>
              <tr>
                <td align="center">26</td>
                <td align="left">Even if your rapid HIV test is positive, you may not have HIV. (T)</td>
                <td align="center">39.5</td>
                <td align="center">61.3</td>
                <td align="center">0.07</td>
                <td align="center">54.2</td>
                <td align="center">63.6</td>
                <td align="center">0.31</td>
              </tr>
            </tbody>
          </table>
        </table-wrap>
        <p>Compared to the no-information arm in Trial One, the percentage of participants in the in-person discussion arm with correct answers to the questionnaire was significantly greater statistically for ten of the questions, but was greater in absolute value for twenty-three of the questions. Compared to the in-person discussion arm, the percentage of patients in the no-information arm was greater in absolute value for two questions and was the same as the in-person discussion arm for one question. There were two questions for which the percentage of correct responses was ≤50% in the in-person discussion arm as opposed to fourteen in the no-information arm.</p>
        <p>Compared to the in-person discussion arm in Trial Two, the percentage of participants in the video arm with correct answers to the questionnaire was not significantly greater statistically for any of the questions, but was greater in absolute value for eighteen of the questions. The percentage of participants in the in-person discussion arm was significantly greater statistically than for participants in the video arm for one question (question 3), but was greater in absolute value for seven other questions. For both arms of the trial, there were two questions (questions fifteen and twenty-five) for which the percentage of correct responses was ≤50%.</p>
        <p>Table <xref ref-type="table" rid="T4">4</xref> depicts the mean, median, and range of scores by arm assignment and subject area for the "HIV pre-test information comprehension" questionnaire. As shown for Trial One, participants in the in-person discussion arm had greater scores overall and had greater scores for each of the five subject areas than those in the no-information arm. The standard deviations for those in the no-information arm were also larger, which indicated a wide variation in ability to answer the questions among those in this arm. The difference in scores was largest for the rapid HIV testing section of the questionnaire. For Trial Two, there was a trend of higher scores in the video than the in-person discussion arm for three of the subject areas. Although the overall mean score appeared to be 4% larger for the video than the in-person discussion arm, there was no difference in these scores at our specified level of statistical significance and sample size using the Wilcoxon rank-sum test.</p>
        <table-wrap position="float" id="T4">
          <label>Table 4</label>
          <caption>
            <p>Mean and median scores on the "HIV pre-test information comprehension" questionnaire</p>
          </caption>
          <table frame="hsides" rules="groups">
            <thead>
              <tr>
                <td/>
                <td align="center" colspan="5">
                  <bold>Trial One</bold>
                </td>
                <td align="center" colspan="5">
                  <bold>Trial Two</bold>
                </td>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td/>
                <td align="center" colspan="2">
                  <bold>No information</bold>
                </td>
                <td align="center" colspan="2">
                  <bold>In-person discussion</bold>
                </td>
                <td align="center">
                  <bold>p-value</bold>
                </td>
                <td align="center" colspan="2">
                  <bold>In-person discussion</bold>
                </td>
                <td align="center" colspan="2">
                  <bold>Video</bold>
                </td>
                <td align="center">
                  <bold>p-value</bold>
                </td>
              </tr>
              <tr>
                <td/>
                <td align="center" colspan="2">
                  <italic>n = 38</italic>
                </td>
                <td align="center" colspan="2">
                  <italic>n = 31</italic>
                </td>
                <td/>
                <td align="center" colspan="2">
                  <italic>n = 59</italic>
                </td>
                <td align="center" colspan="2">
                  <italic>n = 55</italic>
                </td>
                <td/>
              </tr>
              <tr>
                <td colspan="11">
                  <hr/>
                </td>
              </tr>
              <tr>
                <td align="center">
                  <bold>Subject Area</bold>
                </td>
                <td align="center">
                  <italic>μ (σ)</italic>
                </td>
                <td align="center">
                  <italic>Median (range)</italic>
                </td>
                <td align="center">
                  <italic>μ (σ)</italic>
                </td>
                <td align="center">
                  <italic>Median (range)</italic>
                </td>
                <td align="center"><italic>p</italic>≤</td>
                <td align="center">
                  <italic>μ (σ)</italic>
                </td>
                <td align="center">
                  <italic>Median (range)</italic>
                </td>
                <td align="center">
                  <italic>μ (σ)</italic>
                </td>
                <td align="center">
                  <italic>Median (range)</italic>
                </td>
                <td align="center"><italic>p</italic>≤</td>
              </tr>
              <tr>
                <td colspan="11">
                  <hr/>
                </td>
              </tr>
              <tr>
                <td align="center">HIV/AIDS Definition</td>
                <td align="center">2.66 (1.15)</td>
                <td align="center">3 (0–4)</td>
                <td align="center">3.48 (0.68)</td>
                <td align="center">4 (1–4)</td>
                <td align="center">0.00</td>
                <td align="center">3.51 (0.68)</td>
                <td align="center">4 (1–4)</td>
                <td align="center">3.33 (0.86)</td>
                <td align="center">4 (1–4)</td>
                <td align="center">0.35</td>
              </tr>
              <tr>
                <td align="center">HIV Transmission</td>
                <td align="center">2.82 (1.18)</td>
                <td align="center">3 (1–5)</td>
                <td align="center">3.90 (0.94)</td>
                <td align="center">4 (2–5)</td>
                <td align="center">0.00</td>
                <td align="center">4.02 (0.96)</td>
                <td align="center">4 (2–5)</td>
                <td align="center">4.22 (0.79)</td>
                <td align="center">4 (2–5)</td>
                <td align="center">0.34</td>
              </tr>
              <tr>
                <td align="center">HIV Prevention</td>
                <td align="center">2.84 (1.37)</td>
                <td align="center">3 (0–5)</td>
                <td align="center">3.52 (1.03)</td>
                <td align="center">4 (2–5)</td>
                <td align="center">0.04</td>
                <td align="center">3.73 (1.19)</td>
                <td align="center">4 (1–5)</td>
                <td align="center">3.73 (1.10)</td>
                <td align="center">4 (1–5)</td>
                <td align="center">0.85</td>
              </tr>
              <tr>
                <td align="center">HIV Testing</td>
                <td align="center">2.84 (1.42)</td>
                <td align="center">3 (0–6)</td>
                <td align="center">3.65 (1.20)</td>
                <td align="center">4 (1–5)</td>
                <td align="center">0.01</td>
                <td align="center">3.73 (1.27)</td>
                <td align="center">4 (0–6)</td>
                <td align="center">4.18 (1.06)</td>
                <td align="center">4 (2–6)</td>
                <td align="center">0.05</td>
              </tr>
              <tr>
                <td align="center">Rapid HIV Testing</td>
                <td align="center">2.03 (1.38)</td>
                <td align="center">2 (0–5)</td>
                <td align="center">4.26 (1.12)</td>
                <td align="center">4 (2–6)</td>
                <td align="center">0.00</td>
                <td align="center">4.29 (1.25)</td>
                <td align="center">4 (2–6)</td>
                <td align="center">4.45 (1.14)</td>
                <td align="center">5 (1–6)</td>
                <td align="center">0.39</td>
              </tr>
              <tr>
                <td align="center">
                  <bold>All Subject Areas</bold>
                </td>
                <td align="center">13.34 (4.45)</td>
                <td align="center">13 (6–24)</td>
                <td align="center">18.71 (3.50)</td>
                <td align="center">20 (10–24)</td>
                <td align="center">0.00</td>
                <td align="center">19.2 (3.63)</td>
                <td align="center">20 (11–25)</td>
                <td align="center">20.0 (2.98)</td>
                <td align="center">21 (11–25)</td>
                <td align="center">0.33</td>
              </tr>
            </tbody>
          </table>
        </table-wrap>
      </sec>
    </sec>
    <sec>
      <title>Discussion</title>
      <p>The CDC recently recommended routine, universal HIV screening in US primary care settings and EDs [<xref ref-type="bibr" rid="B3">3</xref>]. The new guidelines for the healthcare setting advocate for the use of written or oral HIV pre-test information to streamline the testing process. Given the many limitations of giving HIV pre-test information in oral or written form to patients, we examined if a video could be a good substitute for an in-person discussion.</p>
      <p>We found that ED patients randomly assigned to the educational video, "Do you know about rapid HIV testing?" demonstrated as good or better comprehension of rapid HIV testing fundamentals than ED patients randomly assigned to an in-person discussion. The video we developed and evaluated is freely available via the internet [<xref ref-type="bibr" rid="B10">10</xref>]. We believe that it can be used as a substitute for an in-person discussion for persons undergoing rapid HIV testing, whether in the ED or other settings. This substitution is particularly important for resource poor, busy, rapid HIV testing settings with limited numbers of or access to HIV counselors.</p>
      <p>We also observed that patient knowledge about rapid HIV testing can clearly be improved in the short term through an in-person discussion. Our findings also show that patients who do not receive any type of rapid HIV pre-test information have much less knowledge about HIV, HIV transmission, HIV prevention, and HIV testing than those who undergo an in-person discussion with an HIV test counselor. It is even more concerning that this knowledge was low even though the majority of patients had previously been tested for HIV and presumably received HIV pre-test information as part of that test. Since rapid HIV testing involves a few nuances compared to standard HIV testing, particularly the three possible test results, our results suggest that some type of information should be provided to patients prior to their undergoing testing. Our study results indicate that either an in-person discussion or a video presentation would satisfy this need. Of course, the long-term retention of this knowledge was not directly assessed through this study. Future studies could evaluate whether or not the knowledge was retained, which might impact how the information is used to prevent HIV transmission.</p>
      <p>This study has a number of limitations. First, the study was conducted at a single ED in the US and had several exclusion criteria that reduced the scope of the study population. As a result, the results might not be generalized to other populations and settings. However, given the diversity of the participants in our study, the random selection of participants, and the random assignment of participants to information arms, we believe that our results are reasonably applicable to most other English-speaking patient groups. Second, the questionnaire we developed and employed in this study is not a perfect indicator of patient comprehension of these topics. There might have been other areas of difference or even similarity between arms not measured in our questionnaire. However, the administration of an identical questionnaire in a standardized fashion to randomly selected groups helped ensure that it was a consistent evaluator. Further, the extensive questionnaire development process helped produce a reasonably valid estimator of patient knowledge on the presented topics. Third, the study was not conducted on patients undergoing rapid HIV testing. It is possible that patients who know they will be tested would have a greater stake in listening to the information presented to them. As a result, differences between the in-person discussion and video arms might be reduced for these patients. To address this possibility, we are conducting a larger study comparing in-person discussion to video presentation among patients being tested for HIV OraQuick<sup>®</sup>. Fourth, the study did not show that members of the video arm had greater mean scores than those in the in-person discussion arm. A much larger sample size might have demonstrated a difference. Further, there is some loss of power to using a Wilcoxon rank-sum test, which might account for a failure to detect a difference between the video and in-person discussion arms. Also, because we originally assumed a normal distribution of scores and planned our sample size for trial 2 accordingly, we might have underpowered our study. A non-inferiority study design might have been a preferable method for evaluating this trial. For the subsequent larger trial, we changed the trial design to accommodate a non-inferiority design. Fifth, the randomization process did not produce equal size groups and was not concealed to the RA. Although no significant loss of power is expected, given the sample size, there is a possibility that the RA could have encouraged some patients to be in the trial based upon the type of assignment (video, in-person discussion, or no information) they were intended to receive. We expect that this influence is probably small and that more than likely the imbalance is due to less than optimal allocation of patients into groups.</p>
    </sec>
    <sec>
      <title>Conclusion</title>
      <p>We found that the video "Do you know about rapid HIV testing?" appears to be an acceptable substitute for an in-person discussion on rapid HIV testing with OraQuick<sup>® </sup>in the ED setting. We also observed that either form of pre-test information was preferable than providing no information. We believe that this freely available video can be used for patients undergoing rapid HIV testing with OraQuick<sup>® </sup>to help inform them about HIV and rapid HIV testing particularly in resource poor or busy HIV testing settings, such as the ED.</p>
    </sec>
    <sec>
      <title>Abbreviations</title>
      <p>HIV: human immunodeficiency virus</p>
      <p>Tablet PC: personal computer</p>
      <p>CDC: Centers for Disease Control and Prevention</p>
      <p>ED: emergency department</p>
      <p>US: United States</p>
      <p>AIDS: acquired immunodeficiency syndrome</p>
      <p>IRB: institutional review board</p>
      <p>RA: research assistant</p>
    </sec>
    <sec>
      <title>Competing interests</title>
      <p>The author(s) declare that they have no competing interests.</p>
    </sec>
    <sec>
      <title>Authors' contributions</title>
      <p>RCM conceived of, designed, and executed the study, performed the analysis, and was the primary author of this manuscript. EMG assisted with the design, execution, and analysis of the study. MAC, KHM, GRS, and VGD were mentors to RCM on this project and helped oversee the design and analysis of the study and the preparation of the manuscript. All authors read and approved the final manuscript.</p>
    </sec>
    <sec>
      <title>Pre-publication history</title>
      <p>The pre-publication history for this paper can be accessed here:</p>
      <p>
        <ext-link ext-link-type="uri" xlink:href="http://www.biomedcentral.com/1471-2458/7/238/prepub"/>
      </p>
    </sec>
    <sec sec-type="supplementary-material">
      <title>Supplementary Material</title>
      <supplementary-material content-type="local-data" id="S1">
        <caption>
          <title>Additional file 1</title>
          <p>Development of the rapid HIV testing video, "Do you know about rapid HIV testing?". This manuscript provides a detailed summary of the development of the rapid HIV testing video, "Do you know about rapid HIV testing?"</p>
        </caption>
        <media xlink:href="1471-2458-7-238-S1.pdf" mimetype="application" mime-subtype="pdf">
          <caption>
            <p>Click here for file</p>
          </caption>
        </media>
      </supplementary-material>
      <supplementary-material content-type="local-data" id="S2">
        <caption>
          <title>Additional file 2</title>
          <p>Development of the "HIV pre-test information" questionnaire. This manuscript provides a detailed summary of the development of the "HIV pre-test information" questionnaire used for this trial.</p>
        </caption>
        <media xlink:href="1471-2458-7-238-S2.pdf" mimetype="application" mime-subtype="pdf">
          <caption>
            <p>Click here for file</p>
          </caption>
        </media>
      </supplementary-material>
    </sec>
  </body>
  <back>
    <ack>
      <sec>
        <title>Acknowledgements</title>
        <p>The results of this study were presented at the 2006 American Public Health Association annual meeting in Boston, MA, on November 6, 2006. We would like to thank the study participants for being involved in the study and the research assistants for ably conducting the study. We also thank Sheryl Lyss of the CDC for her advice in the design of the study, Stacey Christie of the Creative Network of Abbott Laboratories, Inc., for collaborating with the production of the video, Carol Browning of the Rhode Island Department of Health for training the research assistants in HIV counseling and testing techniques, and Donna Casellas of OraSure Technologies, Inc., for providing rapid HIV testing training to the research assistants. RCM was supported by a National Institute for Allergy and Infectious Diseases career development grant, K23 AI060363.</p>
      </sec>
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</metadata></record><record><header><identifier>oai:pubmedcentral.nih.gov:2080637</identifier><datestamp>2007-11-17</datestamp><setSpec>bmcdb</setSpec><setSpec>pmc-open</setSpec></header><metadata><article xmlns="http://dtd.nlm.nih.gov/2.0/xsd/archivearticle" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://dtd.nlm.nih.gov/archiving/2.3/xsd/archivearticle.xsd" article-type="research-article">
  <front>
    <journal-meta>
      <journal-id journal-id-type="nlm-ta">BMC Dev Biol</journal-id>
      <journal-title>BMC Developmental Biology</journal-title>
      <issn pub-type="epub">1471-213X</issn>
      <publisher>
        <publisher-name>BioMed Central</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="pmc">2080637</article-id>
      <article-id pub-id-type="publisher-id">1471-213X-7-102</article-id>
      <article-id pub-id-type="pmid">17850654</article-id>
      <article-id pub-id-type="doi">10.1186/1471-213X-7-102</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Alpha6beta1 integrin expressed by sperm is determinant in mouse fertilization</article-title>
      </title-group>
      <contrib-group>
        <contrib id="A1" contrib-type="author">
          <name>
            <surname>Barraud-Lange</surname>
            <given-names>Virginie</given-names>
          </name>
          <xref ref-type="aff" rid="I1">1</xref>
          <email>barraud@smbh.univ-paris13.fr</email>
        </contrib>
        <contrib id="A2" contrib-type="author">
          <name>
            <surname>Naud-Barriant</surname>
            <given-names>Nathalie</given-names>
          </name>
          <xref ref-type="aff" rid="I1">1</xref>
          <email>nathalie.naud@wanadoo.fr</email>
        </contrib>
        <contrib id="A3" contrib-type="author">
          <name>
            <surname>Saffar</surname>
            <given-names>Line</given-names>
          </name>
          <xref ref-type="aff" rid="I2">2</xref>
          <email>lsaffar@smbh.univ-paris13.fr</email>
        </contrib>
        <contrib id="A4" contrib-type="author">
          <name>
            <surname>Gattegno</surname>
            <given-names>Liliane</given-names>
          </name>
          <xref ref-type="aff" rid="I2">2</xref>
          <email>liliane.gattegno@jvr.ap-hop-paris.fr</email>
        </contrib>
        <contrib id="A5" contrib-type="author">
          <name>
            <surname>Ducot</surname>
            <given-names>Beatrice</given-names>
          </name>
          <xref ref-type="aff" rid="I3">3</xref>
          <email>ducot@vjf.inserm.fr</email>
        </contrib>
        <contrib id="A6" contrib-type="author">
          <name>
            <surname>Drillet</surname>
            <given-names>Anne-Sophie</given-names>
          </name>
          <xref ref-type="aff" rid="I4">4</xref>
          <email>drillet@cochin.inserm.fr</email>
        </contrib>
        <contrib id="A7" contrib-type="author">
          <name>
            <surname>Bomsel</surname>
            <given-names>Morgane</given-names>
          </name>
          <xref ref-type="aff" rid="I4">4</xref>
          <email>bomsel@cochin.inserm.fr</email>
        </contrib>
        <contrib id="A8" corresp="yes" contrib-type="author">
          <name>
            <surname>Wolf</surname>
            <given-names>Jean-Philippe</given-names>
          </name>
          <xref ref-type="aff" rid="I1">1</xref>
          <email>jean-philippe.wolf@cch.aphp.fr  </email>
        </contrib>
        <contrib id="A9" contrib-type="author">
          <name>
            <surname>Ziyyat</surname>
            <given-names>Ahmed</given-names>
          </name>
          <xref ref-type="aff" rid="I1">1</xref>
          <email>aziyyat@smbh.univ-paris13.fr</email>
        </contrib>
      </contrib-group>
      <aff id="I1"><label>1</label>Biologie de la Reproduction, UFR SMBH, Université Paris 13, Bobigny, France. Service d'Histologie-Embryologie-Cytogénétique, Hôpital Jean Verdier (AP-HP), Bondy, France</aff>
      <aff id="I2"><label>2</label>EA 3410 UFR SMBH, Université Paris 13, Bobigny, France</aff>
      <aff id="I3"><label>3</label>INSERM-INED Epidémiologie-Démographie-Sciences sociales, CHU Bicêtre, Le Kremlin-Bicêtre, France</aff>
      <aff id="I4"><label>4</label>Entrée Muqueuse du VIH et Immunité Muqueuse, Département de Biologie Cellulaire, Institut Cochin, Université Paris Descartes, CNRS (UMR 8104), Inserm U56, Paris, France</aff>
      <pub-date pub-type="collection">
        <year>2007</year>
      </pub-date>
      <pub-date pub-type="epub">
        <day>12</day>
        <month>9</month>
        <year>2007</year>
      </pub-date>
      <volume>7</volume>
      <fpage>102</fpage>
      <lpage>102</lpage>
      <ext-link ext-link-type="uri" xlink:href="http://www.biomedcentral.com/1471-213X/7/102"/>
      <history>
        <date date-type="received">
          <day>18</day>
          <month>12</month>
          <year>2006</year>
        </date>
        <date date-type="accepted">
          <day>12</day>
          <month>9</month>
          <year>2007</year>
        </date>
      </history>
      <permissions>
        <copyright-statement>Copyright © 2007 Barraud-Lange et al; licensee BioMed Central Ltd.</copyright-statement>
        <copyright-year>2007</copyright-year>
        <copyright-holder>Barraud-Lange et al; licensee BioMed Central Ltd.</copyright-holder>
        <license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/2.0">
          <p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/2.0"/>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>
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               Barraud-Lange
               Virginie
               
               barraud@smbh.univ-paris13.fr
            </dc:author><dc:title>
            Alpha6beta1 integrin expressed by sperm is determinant in mouse fertilization
         </dc:title><dc:date>2007</dc:date><dcterms:bibliographicCitation>BMC Developmental Biology 7(1): 102-. (2007)</dcterms:bibliographicCitation><dc:identifier type="sici">1471-213X(2007)7:1&#x0003c;102&#x0003e;</dc:identifier><dcterms:isPartOf>urn:ISSN:1471-213X</dcterms:isPartOf><License rdf:about="http://creativecommons.org/licenses/by/2.0"><permits rdf:resource="http://web.resource.org/cc/Reproduction" xmlns=""/><permits rdf:resource="http://web.resource.org/cc/Distribution" xmlns=""/><requires rdf:resource="http://web.resource.org/cc/Notice" xmlns=""/><requires rdf:resource="http://web.resource.org/cc/Attribution" xmlns=""/><permits rdf:resource="http://web.resource.org/cc/DerivativeWorks" xmlns=""/></License></Work></rdf>-->
        </license>
      </permissions>
      <abstract>
        <sec>
          <title>Background</title>
          <p>Based on inhibition tests, the alpha6beta1 integrin was suggested to be a sperm receptor, but further experiments using gene deletion techniques have shown that neither oocyte alpha6, nor beta1 integrin subunits were essential for mouse fertilization.</p>
        </sec>
        <sec>
          <title>Results</title>
          <p>Using Western blot analysis and immunofluorescence, we showed that the mouse sperm expresses the alpha6beta1 integrin. As for oocyte, binding of GoH3 anti-alpha6 antibody to sperm induces a specific inhibition of sperm fertilizing ability. Comparing zona-intact and zona-free eggs in fusion tests, we showed that the removal of the zona pellucida by acid treatment bypasses fertilizing oocyte alpha6beta1 integrin's function in the adhesion/fusion process.</p>
        </sec>
        <sec>
          <title>Conclusion</title>
          <p>These findings show that alpha6beta1 integrin is expressed by both gametes and is functional in their membranes interaction. These results and previous reports, about fertilization of alpha6 or beta1 integrin subunits deleted oocytes by wild type sperm, suggest that the presence of alpha6beta1 integrin on one of the two gamete membranes can rescue the fertilization process. This hypothesis is further supported by the exchange of membrane fragments occurring between gametes prior to fusion that we recently reported.</p>
        </sec>
      </abstract>
    </article-meta>
  </front>
  <body>
    <sec>
      <title>Background</title>
      <p>Sperm-egg interaction is a complex molecular process leading to gamete fusion mediated by a series of molecular interactions. Evidences have been put forward suggesting the involvement of members of the ADAMs, tetraspanins and integrins families in this mechanism. Recently, Izumo, a sperm protein belonging to the immunoglobulin superfamily, was found to be essential for the fusion [<xref ref-type="bibr" rid="B1">1</xref>]. Three groups reported that <italic>Cd9</italic>-deficient female mice present a dramatic reduction of their fertility due to a lack of fusion ability of their oocytes [<xref ref-type="bibr" rid="B2">2</xref>-<xref ref-type="bibr" rid="B4">4</xref>]. We recently showed that double knock-out <italic>Cd9</italic><sup>-/-</sup>/<italic>Cd81</italic><sup>-/- </sup>female mice are completely infertile [<xref ref-type="bibr" rid="B5">5</xref>] and that, upon fertilization, CD9 tetraspanin controls α6β1 integrin relocation in patches on the egg membrane [<xref ref-type="bibr" rid="B6">6</xref>].</p>
      <p>Integrins have also been implicated in sperm-oocyte interaction. Based on several experiments, mouse egg α6β1 integrin was described to function as a receptor of the sperm fertilin β. During further experiments, the function-blocking mAb directed against the α6 integrin subunit, GoH3, turned out to inhibit sperm-oocyte binding, and peptides derived from the sperm fertilin β disintegrin domain sequence bind to α6β1 integrin [<xref ref-type="bibr" rid="B7">7</xref>-<xref ref-type="bibr" rid="B9">9</xref>]. However, mouse gamete binding and fusion tests using GoH3 mAb gave disparate results, partly according to the technique used for ZP removal [<xref ref-type="bibr" rid="B7">7</xref>,<xref ref-type="bibr" rid="B10">10</xref>,<xref ref-type="bibr" rid="B11">11</xref>]. The binding of sperm to mouse oocytes was not inhibited when ZP had been removed using an acidic treatment [<xref ref-type="bibr" rid="B12">12</xref>] and the fertilization rate (FR) of cumulus-intact mouse oocytes was not reduced [<xref ref-type="bibr" rid="B11">11</xref>]. Recently, we have shown that GoH3 strongly inhibited human sperm-egg fusion when the ZP had been removed by microdissection [<xref ref-type="bibr" rid="B6">6</xref>]. Moreover, oocytes from α6 integrin-deficient mice show normal binding and fusion with sperm, suggesting that the α6 integrin is not essential for gamete binding and fusion [<xref ref-type="bibr" rid="B11">11</xref>]. These results suggested that the α6 integrin function could be redundant, possibly with another member of the integrin family also expressed on oocyte membrane. However, according to experiments performed by He <italic>et al</italic>., none of the integrins known to be present on the oocyte are essential for gamete fusion [<xref ref-type="bibr" rid="B13">13</xref>].</p>
      <p>Major questions about integrins' roles in sperm-oocyte fusion remain unsolved. The possible effect of anti-α6β1 antibodies on mouse sperm functions has never been addressed, whereas expression of α6β1 integrin on human spermatozoa has already been reported. The integrin subunits α4, α5 and α6 have also been detected on normal human sperm using flow cytometry, their expressions being reduced in cases of terato- or oligoasthenoteratozoospermia [<xref ref-type="bibr" rid="B14">14</xref>]. The β1 integrin subunit has been detected by histochemistry on basement membrane of the tubuli seminiferi, spermatocytes, spermatids and spermatozoa in human [<xref ref-type="bibr" rid="B15">15</xref>]. Furthermore, a positive correlation between the expression of β1 integrin on human spermatozoa and their fertilizing ability has been demonstrated suggesting that sperm integrins may be determinant in egg-sperm recognition and interaction [<xref ref-type="bibr" rid="B16">16</xref>,<xref ref-type="bibr" rid="B17">17</xref>]. Hence, Reddy <italic>et al</italic>. proposed α6β1 integrin as a clinical marker to evaluate sperm quality [<xref ref-type="bibr" rid="B16">16</xref>]. Several other studies performed on human sperm demonstrated correlations between their level of integrin expression and their fertilization ability [<xref ref-type="bibr" rid="B18">18</xref>-<xref ref-type="bibr" rid="B20">20</xref>]. The presence of sperm integrin in human raises the question of its possible expression by mouse sperm. In spite of numerous experiments involving the anti-α6 mAb GoH3 in mouse gamete interaction, this point has never been investigated and discussed, whereas it can account for some of the reported data discrepancies.</p>
      <p>Another point deals with the model of ZP-free oocyte that was most frequently used to study gamete interaction [<xref ref-type="bibr" rid="B7">7</xref>,<xref ref-type="bibr" rid="B9">9</xref>,<xref ref-type="bibr" rid="B21">21</xref>]. To focus the studies on events that occur at the plasma membrane level, the ZP was removed by chemical, enzymatic or mechanical methods. Indeed, this model prevents any interference between both gamete membranes and is considered to be more convenient for studying their interaction. However, ZP removal dramatically modifies the local conditions of gamete interaction and may also explain some contradictory results that have been previously reported. We recently showed that upon ZP removal, several integrin subunits, including α6, and tetraspanins are relocated and clustered into patches [<xref ref-type="bibr" rid="B6">6</xref>]. Simultaneously, several oocyte functions related to fusion are modified. Hence, in human oocyte, the mAb anti-CD9 is effective in inhibiting gamete fusion only if it is introduced in the medium before zona removal and not after [<xref ref-type="bibr" rid="B6">6</xref>], suggesting that CD9 tetraspanin function is bypassed by this membrane remodeling. In this study, we now demonstrate the expression of α6 and β1 integrin subunits by mouse sperm. We performed IVF assay after preincubation of sperm and/or oocyte with antibodies. Experiments were performed using both acid Tyrode (AT) ZP-free and cumulus-intact oocytes. Thus, we demonstrated that mouse sperm express α6β1 integrin and that this integrin is involved in the sperm-oocyte interaction process.</p>
    </sec>
    <sec>
      <title>Results</title>
      <sec>
        <title>Alpha6 and beta1 integrin subunits are expressed on mouse sperm membrane</title>
        <sec>
          <title>Western blot analysis</title>
          <p>Expression of α6 integrin subunit on cauda epididymal sperm was evaluated by immunoblot analysis. As shown on figure <xref ref-type="fig" rid="F1">1A</xref>, a specific band at 120 kDa, the expected molecular weight of α6 integrin subunit under reducing conditions, was detected on sperm (lane 2: 1 million and lane 3: 2 millions of sperm) and on F9 Whole Cell Lysate (lane 1: 50 μg proteins), serving as positive control. The control using a non-specific rabbit polyclonal antibody was negative. The specificity of this result has been confirmed using another antibody raised against α6 integrin subunit and its specific blocking peptide. As illustrated in figure <xref ref-type="fig" rid="F1">1B</xref>, the specific band present at 120 kDa with the anti-α6 integrin antibody (lane 1) has disappeared when the anti-α6 integrin antibody was preincubated with its specific blocking peptide (lane 2). These results demonstrated the expression of α6 integrin subunit on sperm.</p>
          <fig position="float" id="F1">
            <label>Figure 1</label>
            <caption>
              <p><bold>Expression of alpha6beta1 integrin on mouse sperm</bold>. Alpha 6 integrin subunit expression was investigated by Western blot analysis. Proteins from epididymal sperm were extracted with 1% NP40, subjected to SDS-PAGE under reducing conditions and blotted with two different anti-α6 integrin antibodies to reinforce the specificity of the detection. <bold>A: </bold>120 kDa specific band was detected on sperm extracts after rabbit polyclonal antibody incubation (H-87 at 0,2 μg/ml), (lanes 2 and 3: 1 and 2 millions of sperm, respectively). This band corresponds to α6 integrin subunit as confirmed by the use of the F9 Whole Cell Lysate as positive control (lane 1: 50 μg of proteins). No specific band appeared when a non specific rabbit IgG was used (lane 4). <bold>B</bold>: Using the N-19, goat polyclonal antibody rose against a peptide mapping at N-terminus of α6 integrin subunit, a similar band was detected (lane 1). This band disappeared when the blocking peptide was added (lane 2).</p>
            </caption>
            <graphic xlink:href="1471-213X-7-102-1"/>
          </fig>
        </sec>
        <sec>
          <title>Immunofluorescence analysis</title>
          <p>Immunofluorescence analysis of mouse sperm was carried out with anti-α6 and anti-β1 integrin antibodies (GoH3 and MB1.2, respectively). In parallel, acrosomal status was assessed by <italic>Pisum sativum agglutinin </italic>(PSA) staining protocol. Data revealed different distribution patterns of the integrin subunits on the sperm membrane as shown in figure <xref ref-type="fig" rid="F2">2</xref>. Freshly recovered non capacitated sperm did not show any distinct fluorescence (Fig. <xref ref-type="fig" rid="F2">2c</xref>). After 90 minutes under capacitating conditions, more than 70% of sperm presented integrin molecules on their membranes organized in various patterns: dense fluorescent dots of the equatorial region of non acrosome reacted (AR) capacitated sperm (40%; Fig. <xref ref-type="fig" rid="F2">2f</xref>) or AR sperm (50%; Fig. <xref ref-type="fig" rid="F2">2i</xref>) and an exclusive distribution in the post acrosomal region of AR sperm (10%; Fig. <xref ref-type="fig" rid="F2">2l</xref>). Control isotype or secondary antibody alone gave no signal (data not shown). Similar distribution, staining and relative proportions were found for β1 integrin subunit (Fig. <xref ref-type="fig" rid="F2">2e'h'k'</xref>).</p>
          <fig position="float" id="F2">
            <label>Figure 2</label>
            <caption>
              <p><bold>Expression and distribution of alpha6beta1 integrin on mouse sperm</bold>. Distribution of α6β1 integrin was studied by immunofluorescence microscopy. Spermatozoa were exposed to FITC-PSA (a, d, g, j) after anti-α6 integrin GoH3 antibody (b, e, h, k) or anti-β1 integrin MB1.2 antibody (e', h', k') followed by Alexa Fluor<sup>® </sup>594 (red) goat anti-rat IgG secondary antibody. The following fluorescent patterns were recorded: negative non capacitated sperm (b), equatorial localization on capacitated sperm (e, e', h, h') and post-acrosomal localization (k, k') only on capacitated AR sperm. c, f, i and l represent composite images generated by superimposition of the green and red signals. Arrows indicate the position of intact (white) or reacted (yellow) acrosome. In order to distinguish the different spermatic regions, they were delimited on the image (a); 1: acrosome, 2: equatorial region and 3: post-acrosomal region. Bar = 5 μm.</p>
            </caption>
            <graphic xlink:href="1471-213X-7-102-2"/>
          </fig>
        </sec>
        <sec>
          <title>Flow cytometry analysis</title>
          <p>Presence of α6 and β1 integrin subunits on capacitated mouse sperm was confirmed afterwards by flow cytometry after indirect immunofluorescence staining. Capacitated spermatozoa labeled with anti-α6 (Fig. <xref ref-type="fig" rid="F3">3A</xref>) and anti-β1 antibodies (Fig. <xref ref-type="fig" rid="F3">3B</xref>) were distributed in single peaks with a mean fluorescence intensity of 21 and 34 versus 5 and 8 for control isotype, respectively. Freshly recovered non capacitated sperm was not stained (data not shown).</p>
          <fig position="float" id="F3">
            <label>Figure 3</label>
            <caption>
              <p><bold>Flow cytometric analysis of alpha6beta1 integrin expression on mouse sperm</bold>. Expression of α6 and β1 integrin subunits on capacitated mouse sperm was evaluated by flow cytometry. Sperm cells were incubated with the mAb anti-α6 (GoH3) (<bold>A</bold>) or anti-β1 (MB1.2) (<bold>B</bold>) or Rat IgG2a isotype negative control (<bold>A</bold>, <bold>B</bold>), stained with Alexa Fluor<sup>® </sup>594 (red) goat anti-rat IgG, then analyzed by flow cytometry on the basis of FSC/FL1 (cell size/relative fluorescence) parameters.</p>
            </caption>
            <graphic xlink:href="1471-213X-7-102-3"/>
          </fig>
        </sec>
      </sec>
      <sec>
        <title>Effects of antibodies against alpha6 and beta1 integrin subunits on mouse sperm-egg fusion</title>
        <p>Since the presence of α6 and β1 integrin subunits on mouse sperm was demonstrated, we next investigated their involvement during fertilization. We evaluated, in the presence or in the absence of antibodies, the percentage of fertilized eggs (FR) in both cumulus-intact and acid Tyrode (AT) zona-free egg assays and the average number of sperm fused per egg (fertilization index: FI) in AT zona-free egg assays. As these integrin subunits are also expressed by the oocytes [<xref ref-type="bibr" rid="B7">7</xref>], we determined to what extent each gamete is involved in the inhibition process. Different groups were studied. The group 1 was the control IVF. In groups 2 and 3, only one of the two gametes (oocytes or sperm, respectively) was preincubated with function-blocking antibodies, washed and inseminated without antibodies. In group 4, both gametes were separately preincubated with the function-blocking antibodies, washed and then inseminated without any antibody as in previous groups. In group 5, oocytes were inseminated in presence of antibodies without any preincubation. In groups 6, 7 and 8, anti-β1 antibody was present during the insemination while oocytes, sperm or both had been preincubated with it. Results differed according to the presence or the absence of ZP. When experiments were performed with isotype (rat IgG2a) or with medium containing sodium azide at 0,02% final concentration as controls, no inhibition was detected (data not shown). It is important to note that none of the function blocking antibody used altered the sperm motility.</p>
        <sec>
          <title>Effect of GoH3 on cumulus-intact egg insemination (Table <xref ref-type="table" rid="T1">1</xref>)</title>
          <table-wrap position="float" id="T1">
            <label>Table 1</label>
            <caption>
              <p>Effects of alpha6 and beta1 integrin subunits antibodies on sperm-egg fusion</p>
            </caption>
            <table frame="hsides" rules="groups">
              <thead>
                <tr>
                  <td align="center">Groups</td>
                  <td align="center" colspan="2">Antibodies preincubation</td>
                  <td align="center">Antibodies during IVF</td>
                  <td align="center">FR (%) cumulus-intact (<italic>n</italic>. oocytes)</td>
                  <td align="center">FI* AT zona-free (<italic>n</italic>. oocytes)</td>
                </tr>
                <tr>
                  <td/>
                  <td align="center">Sperm</td>
                  <td align="center">Oocytes</td>
                  <td/>
                  <td/>
                  <td/>
                </tr>
              </thead>
              <tbody>
                <tr>
                  <td align="center" colspan="6"><bold>Anti-α6 (GoH3) </bold>at 200 μg/ml</td>
                </tr>
                <tr>
                  <td colspan="6">
                    <hr/>
                  </td>
                </tr>
                <tr>
                  <td align="center">1</td>
                  <td align="center">-</td>
                  <td align="center">-</td>
                  <td align="center">-</td>
                  <td align="center">91 ± 3 (85)</td>
                  <td align="center">4,6 ± 0,3 (51)<sup>e</sup></td>
                </tr>
                <tr>
                  <td align="center">2</td>
                  <td align="center">-</td>
                  <td align="center">+</td>
                  <td align="center">-</td>
                  <td align="center">68 ± 6 (64)<sup>a</sup></td>
                  <td align="center">4,8 ± 0,3 (49)<sup>e</sup></td>
                </tr>
                <tr>
                  <td align="center">3</td>
                  <td align="center">+</td>
                  <td align="center">-</td>
                  <td align="center">-</td>
                  <td align="center">50 ± 6 (81)<sup>b,<italic>c</italic></sup></td>
                  <td align="center">2,5 ± 0,2 (44)<sup>b,<italic>e</italic></sup></td>
                </tr>
                <tr>
                  <td align="center">4</td>
                  <td align="center">+</td>
                  <td align="center">+</td>
                  <td align="center">-</td>
                  <td align="center">31 ± 7 (44)<sup>b</sup></td>
                  <td align="center">2,6 ± 0,2 (34)<sup>b,<italic>e</italic></sup></td>
                </tr>
                <tr>
                  <td align="center">5</td>
                  <td align="center">-</td>
                  <td align="center">-</td>
                  <td align="center">+</td>
                  <td align="center">10 ± 3 (77)<sup>b,d</sup></td>
                  <td align="center">4 ± 0,3 (38)<sup>e</sup></td>
                </tr>
                <tr>
                  <td colspan="6">
                    <hr/>
                  </td>
                </tr>
                <tr>
                  <td align="center" colspan="6"><bold>Anti-β1 (L16) </bold>at 50 μg/ml</td>
                </tr>
                <tr>
                  <td colspan="6">
                    <hr/>
                  </td>
                </tr>
                <tr>
                  <td align="center">1</td>
                  <td align="center">-</td>
                  <td align="center">-</td>
                  <td align="center">-</td>
                  <td align="center">72 ± 5 (82)</td>
                  <td align="center">4,5 ± 0,2 (56)<sup>e</sup></td>
                </tr>
                <tr>
                  <td align="center">5-6-7-8<sup>§</sup></td>
                  <td align="center">±</td>
                  <td align="center">±</td>
                  <td align="center">+</td>
                  <td align="center">20 ± 5 (269)<sup>b</sup></td>
                  <td align="center">2,6 ± 0,2 (108)<sup>e</sup></td>
                </tr>
              </tbody>
            </table>
            <table-wrap-foot>
              <p>FR, fertilization rate; FI, fertilization index; Ab, antibody; AT, acid Tyrode; *, Number of spermatozoa per oocyte;<sup>§</sup>, In groups 2 to 4 of the anti-β1 tests, the antibody was absent during insemination and FR and FI were comparable to the control (group 1) (data not shown), FR and FI in groups 5 to 8 were no significantly different between them and values given here are means; a, significantly different from control, P &lt; 0.0002; b, significantly different from control, P &lt; 0.0001; c, significantly different from group 2, P &lt; 0.03; d, significantly different from group 4, P &lt; 0.003; e, FR on AT zona-free assay was 100%; Results represent the mean ± s. e. m from three different experiments.</p>
            </table-wrap-foot>
          </table-wrap>
          <p>Control FR was 91% ± 3. Our protocols of selective preincubation of each gamete allowed us to discriminate between GoH3 effects on oocytes and sperm respectively. When oocytes (group 2) and sperm (group 3) were preincubated with GoH3, the FR was reduced by 26% (68% versus 91%; P &lt; 0.0002) or 45% (50% versus 91%; P &lt; 0.0001), respectively. GoH3 was even more potent in inhibiting sperm than oocyte functions (P &lt; 0.03). When both gametes were preincubated (group 4), the FR inhibition was 65% (31% versus 91%; P &lt; 0.0001) corresponding to the additive effect of GoH3 on each gamete. The three hours of cumulus-intact oocytes insemination with GoH3 and without any preincubation (group 5) gave nearly a 90% inhibition of the FR, compared to the control (10% versus 91%; P &lt; 0.0001). This inhibition was stronger (P &lt; 0.003) than that recorded after preincubation of both gametes with the antibody. This could be explained by the inhibition of lately recruited GoH3 binding sites during the incubation.</p>
        </sec>
        <sec>
          <title>Effect of G0H3 on acid Tyrode zona-free egg insemination (Table <xref ref-type="table" rid="T1">1</xref>)</title>
          <p>In all groups of AT zona-free egg assay, membrane gamete interaction is immediate. Because of this extremely rapid process, all eggs were fertilized (FR = 100%). GoH3 mAb had no effect on AT zona-free oocytes since the FI of group 2 was not modified when compared to the control group, showing that ZP removal by AT renders oocytes insensitive to GoH3 effects. Only sperm preincubation (group 3) with GoH3 significantly reduced the FI. Interestingly, if both gametes were inseminated in presence of GoH3, without preincubation (group 5), the FI was not reduced. In contrast, if the same experiment was performed with cumulus-intact eggs, an almost complete inhibition was observed. Therefore: 1) the AT zona removal induced a disappearance of the GoH3 effects on the oocytes, 2) sperm GoH3 effect is not immediate and requires a delay to be effective. This explains that sperm preincubation inhibits ZP-intact but not AT-ZP-free oocytes fertilization and suggests that the time to get through the ZP could be a necessary delay for sperm inhibition to appear.</p>
        </sec>
        <sec>
          <title>Cumulus-intact and acid Tyrode zona-free egg assays with anti-beta1 integrin subunit antibody (Table <xref ref-type="table" rid="T1">1</xref>)</title>
          <p>Gamete preincubation with anti-β1 mAb (L16), both in cumulus-intact and AT ZP-free assays, had no effect (groups 2 to 4, data not shown) while the presence of the antibody during insemination impaired gamete interaction (groups 5–8) and was not modified by any preincubation. In cumulus-intact eggs assay, in presence of anti-integrin subunit β1 mAb, the FR was significantly decreased by approximately 70% (P &lt; 0.0001), compared to the control group. In AT zona-free egg assays, all inseminated oocytes were fertilized (FR = 100%), but a significant reduction in the FI (approximately 50%, P &lt; 0.0001) was obtained in all groups.</p>
        </sec>
      </sec>
      <sec>
        <title>Zona pellucida removal modifies alpha6 and beta1 integrin subunits distribution</title>
        <p>In an attempt to explain the lack of anti-α6 antibody effect on AT zona-free oocytes, we studied the localization of α6β1 integrin on zona-intact and AT zona-free eggs by immunofluorescence and confocal microscopy analysis. About 90 optical sections, representing nearly half of the eggs, were collected and superimposed using the maximum projection function as shown on figure <xref ref-type="fig" rid="F4">4</xref>. Whereas the α6 and β1 integrin subunits were distributed homogeneously with fine punctuations around the egg surface of zona-intact oocytes (Fig. <xref ref-type="fig" rid="F4">4e</xref> and <xref ref-type="fig" rid="F4">4g</xref>), ZP removal resulted in a modification of the alpha6 and beta1 integrin subunits distribution. Indeed, both formed patches on the AT zona-free oocyte membrane (Fig. <xref ref-type="fig" rid="F4">4f</xref> and <xref ref-type="fig" rid="F4">4h</xref>). This integrin redistribution induced upon AT ZP removal seems to put the oocyte at a stage in which integrins are no longer required for adhesion/fusion, explaining in turn the absence of anti-α6 antibody effect on AT zona-free oocytes during fertilization.</p>
        <fig position="float" id="F4">
          <label>Figure 4</label>
          <caption>
            <p><bold>Acid Tyrode's zona removal modifies distribution of alpha6 and beta1 integrin subunits on mouse oocytes</bold>. Zona-intact or acid Tyrode ZP-free mouse oocytes were incubated with anti-α6 integrin GoH3 (e, f) or anti-β1 integrin MB1.2 antibodies (g, h), then with Alexa Fluor<sup>® </sup>488 (green) or 594 (red) goat anti-rat IgG respectively and analyzed by confocal microscopy as described in Material and methods. These molecules were distributed homogeneously with fine punctuations around the surface of the zona-intact oocytes (e, g), but both formed patches on the acid Tyrode zona-free oocyte surface (f, h). About 90 sections, representing nearly half of the eggs were collected. The maximum projection function was then used to superimpose the different sections. Transmission images corresponding to each oocyte are shown (a, b, c, and d). Bar = 20 μm.</p>
          </caption>
          <graphic xlink:href="1471-213X-7-102-4"/>
        </fig>
      </sec>
    </sec>
    <sec>
      <title>Discussion</title>
      <p>Here, we show that the α6β1 integrin is expressed on mouse sperm and is functionally involved in the sperm-oocyte interaction process. These data reinforce the role of α6β1 integrin in the process of gamete interaction [<xref ref-type="bibr" rid="B6">6</xref>,<xref ref-type="bibr" rid="B7">7</xref>]. We also confirm that AT-ZP removal bypasses the α6β1 integrin function in mouse oocyte at the time of gamete interaction.</p>
      <p>We show that mouse sperm express α6β1 integrin by western blot analysis, flow cytometry and immunofluorescence confocal microscopy. This last technique enables to localize the α6β1 integrin on the surface of capacitated and capacitated and AR spermatozoa. Alpha6beta1 integrin clusterisation at the surface of the spermatozoon head in a dotty pattern suggests its activation. As the fertilizing spermatozoon normally present in the perivitelline space is AR, is more likely to present this staining pattern. As the fusion starts at the equatorial and post acrosomal region [<xref ref-type="bibr" rid="B22">22</xref>], this localization of the α6β1 sperm integrin reinforces its probable implication in the adhesion/fusion process.</p>
      <p>Our results are different from those of other groups [<xref ref-type="bibr" rid="B7">7</xref>,<xref ref-type="bibr" rid="B23">23</xref>]. In our study, when zona pellucida was totally removed by acid Tyrode, oocytes were insensitive to GoH3 effect. Consequently, we observed gamete interaction inhibition only when sperm was preincubated with GoH3, while Almeida <italic>et al</italic>. reported a total inhibition by GoH3 (after oocyte preincubation) of oocyte-sperm binding and therefore of fusion [<xref ref-type="bibr" rid="B7">7</xref>]. This inhibition could have been due to GoH3 effect on both oocyte and sperm. Indeed, in these experiments, very brief chymotrypsin treatment was used and may not have completely removed the zona pellucida [<xref ref-type="bibr" rid="B24">24</xref>]. Hence, oocytes were probably not totally insensitive to GoH3 effect. Furthermore, in their experiment, GoH3 have not been washed out from oocyte preincubation medium before sperm addition, contrary to what we did. Therefore, the delay necessary for the spermatozoon to get through the zona pellucida may have stood for the time of GoH3 sperm preincubation. Actually, these experimental conditions were closer to our cumulus-intact IVF ones, accounting for similar results in apparently different IVF conditions. In our previous study, we probably also misinterpreted the GoH3 effect on the human IVF by allotting it exclusively to the oocyte integrin [<xref ref-type="bibr" rid="B6">6</xref>]. This effect may have mainly been mediated by the spermatic one.</p>
      <p>Two previous studies, using zona-intact or cumulus-intact eggs assays, reported GoH3 lack of inhibition on gamete fusion [<xref ref-type="bibr" rid="B11">11</xref>,<xref ref-type="bibr" rid="B23">23</xref>]. In the first one, the IVF test was run in small volumes (10 μl). As stated in the report itself, it is known that IVF is inefficient in these conditions (Control FR = 30%). This might have hidden the GoH3 inhibition effect. In the second experiment, contrary to the 3 hours incubation commonly used and as used in our study, insemination lasted 24 hours. Therefore, the evaluation of the FR was not performed according to the presence of decondensed sperm head within the ooplasm, but to the two cell stage criteria. This is not the usual criterion to evaluate fertilization per se, but that of egg activation which can also be achieved by parthenogenetic process.</p>
      <p>The most frequent argument to rule out the possible role of α6β1 integrin in gamete interaction is the fertility of α6 or β1 integrin subunits deleted mice oocytes [<xref ref-type="bibr" rid="B11">11</xref>,<xref ref-type="bibr" rid="B13">13</xref>]. However, all the experiments performed with deleted oocytes, including mating, used wild-type spermatozoa. According to our present results which show the presence of the α6β1 integrin on sperm, these spermatozoa carried the α6 and β1 integrin subunits that had been deleted on the oocyte. This means that, prior to fusion, at the gamete membrane merge, these molecules were present. We therefore have to hypothesize that the presence of this integrin on one of the two fusing membranes is sufficient for fusion. Such hypothesis is supported by the sperm oocyte membrane exchange occurring prior to fusion we reported recently [<xref ref-type="bibr" rid="B25">25</xref>]. In this work, we have shown that CD9 tetraspanin is transferred with the exchanged membrane fragment from oocyte to sperm. One can hypothesize that sperm α6β1 integrin could transfer too and, therefore, may have rescued adhesion and fusion in deleted oocytes. The way to definitively answer the question of the implication of α6β1 integrin in gamete interaction during fertilization is the deletion of α6 and/or β1 integrin gene in both gametes. This part of study is under current evaluation.</p>
      <p>In our study, AT zona-free eggs were all fertilized whatever the anti-α6 or anti-β1 integrin subunits antibodies used. This could be explained by the direct free access for sperm to oocyte membrane, preventing the effect of the antibody on the sperm. But, importantly, the FI was not affected even when oocytes were preincubated with GoH3 showing that they had become insensitive to its effects. Thus, the oocyte α6β1 integrin is in such a situation that it is no longer needed. As fusion still occurs, we have to conclude that it had been bypassed by the AT ZP removal. This is another reason for the FR being poorly affected by GoH3 on AT ZP-free eggs. Similar bypasses have already been described in human eggs upon mechanical ZP removal [<xref ref-type="bibr" rid="B6">6</xref>]. When mouse intact <italic>Cd9</italic><sup>-/- </sup>eggs are inseminated, spermatozoa swim into the perivitelline space without binding to the oolemma. On the contrary, large amounts of spermatozoa tightly bind to the oolemma of AT zona-free <italic>Cd9</italic><sup>-/- </sup>mouse eggs [<xref ref-type="bibr" rid="B4">4</xref>].</p>
      <p>To investigate this hypothesis, we studied α6 and β1 integrin subunits distribution on ZP-intact and AT ZP-free oocytes. α6 and β1 integrin subunits were evenly distributed on the surface of zona-intact mouse eggs (Fig. <xref ref-type="fig" rid="F4">4e,g</xref>). On the oocyte surface of AT ZP-free eggs, these integrins were detected as well, but in larger regularly arranged patches (Fig. <xref ref-type="fig" rid="F4">4f,h</xref>). The same relocation had been observed in human egg upon ZP removal [<xref ref-type="bibr" rid="B6">6</xref>]. We also have reported a relocation of the α6 integrin subunit upon fertilization of mouse zona-intact eggs [<xref ref-type="bibr" rid="B6">6</xref>] suggesting that the two phenomena are linked. We can then hypothesize that fertilization and α6β1 integrin redistribution are physiologically linked. Once this relocation has happened, α6β1 integrin has less or no function in the process of gamete binding and fusion. This means that anti-α6 antibodies have few or no effect on AT ZP-free mouse oocytes. For all these reasons and also because is closer to what the physiology should be, experiments using zona-intact eggs have to be preferred to the zona-free oocytes ones.</p>
      <p>Takahashi reported an α6β1 integrin clustering at the point of gamete contact on ZP-free oocyte [<xref ref-type="bibr" rid="B9">9</xref>]. The presence of α6β1 integrin on the capacitated and AR sperm suggests another non exclusive interpretation. The cluster of α6β1 integrin at the point of gamete contact could also be due to the superimposition of oocyte and sperm α6β1 integrin detection. The fact that α6β1 is not detectable on the surface of fresh sperm may explain why clusterisation was not reported when using non capacitated sperm [<xref ref-type="bibr" rid="B9">9</xref>]. In our study, the fertilizing index of AT ZP-free oocytes was reduced only when sperm had been preincubated with GoH3, supporting the existence of a direct effect of this antibody on sperm functions.</p>
    </sec>
    <sec>
      <title>Conclusion</title>
      <p>The presence of functional α6β1 integrin on mouse sperm raises the question about the role of this integrin in gamete interaction. It appears as one piece of a multimolecular binding and fusion complex which should be present on both oocyte and sperm membranes. As it can be bypassed by the oocyte membrane reorganization upon ZP removal, we can hypothesize that binding of its ligand to oolemma α6β1 integrin is one of the first steps of gamete membrane interaction process. The only essential molecules that had been recognized so far for sperm-egg binding and fusion are the CD9 tetraspanin on the oocyte [<xref ref-type="bibr" rid="B2">2</xref>-<xref ref-type="bibr" rid="B4">4</xref>] and on the sperm membrane, the Izumo immunoglobulin [<xref ref-type="bibr" rid="B1">1</xref>], which are up to date the unique unilaterally distributed molecules. It could be interesting to study its relation to the sperm α6β1 integrin. A similar interest should be granted to the integrin potential ligands on the sperm.</p>
    </sec>
    <sec sec-type="methods">
      <title>Methods</title>
      <sec>
        <title>Antibodies</title>
        <p>The function blocking rat mAbs against the integrin α6 (GoH3) or polyclonal goat anti-β1 integrin (L16) subunits were purchased from R&amp;D Systems (France) and Santa Cruz Biotechnology (USA) respectively. For immunofluorescence studies, the rat mAb anti-mouse β1 integrin (clone MB1.2) came from Chemicon International (USA). Secondary antibodies used in immunocytochemistry and flow cytometry experiments were Alexa Fluor<sup>® </sup>488 (green) or 594 (red) goat anti-rat IgG from Molecular Probes (Invitrogen, France). Rat IgG2a isotype (Serotec, France) was used as negative control. Vectashield mounting medium supplemented with DAPI and FITC-PSA were purchased from Vector Laboratories (USA). For Western blot analysis, the rabbit polyclonal antibody raised against the C-terminus of mouse integrin α6 (H-87), the goat polyclonal antibody rose against a peptide mapping at N-terminus of integrin α6 (N-19) and the specific blocking peptide of N-19 antibody were from Santa Cruz Biotechnology. The non-specific rabbit polyclonal antibody and the biotinylated goat anti-rabbit IgG were from Vector Laboratories; the polyclonal rabbit anti-goat HRP-conjugated was from DakoCytomation (Denmark); the streptavidin HRP-conjugated was from Immunotech (France).</p>
      </sec>
      <sec>
        <title>Gamete preparation and in vitro fertilization</title>
        <sec>
          <title>Cumulus-intact or acid Tyrode zona-free oocyte preparation</title>
          <p>B6CBA F1 female mice (5–8 weeks old) purchased from Charles River Laboratories (France) were superovulated with 5 IU PMSG and 5 IU hCG (Intervet, France) 48 hours apart. Twelve to 14 hours after hCG injection, the animals were sacrificed by cervical dislocation. Cumulus oophorus were collected by tearing the ampulla wall of the oviduct and placed in Whittingham's medium [<xref ref-type="bibr" rid="B26">26</xref>] with 3% BSA (Sigma) at 37°C under 5% CO<sub>2 </sub>in air under mineral oil (Sigma). When needed cumulus cells were removed by a brief exposure to hyaluronidase (Sigma) (0.01%). The ZP was then dissolved with acidic Tyrode's (AT) solution (pH 2.5) (Sigma) under visual monitoring. The AT zona-free eggs were rapidly washed five times and directly fixed, or kept at 37°C under 5% CO<sub>2 </sub>in air for 3 hours to recover their fertilization ability.</p>
        </sec>
        <sec>
          <title>Sperm preparation</title>
          <p>Mouse spermatozoa were obtained from the caudae epididymis of B6CBA F1 mice (8 to 13-week-old) and capacitated at 37°C for 90 minutes in a 500 μl drop of Whittingham's medium supplemented with 30 mg/ml BSA, under mineral oil.</p>
        </sec>
        <sec>
          <title>In vitro fertilization</title>
          <p>Cumulus-intact or AT zona-free eggs were inseminated with capacitated spermatozoa for 3 hours in a 100 μl drop of medium. Then, they were washed and directly mounted in Vectashield/DAPI for observation under UV light (Zeiss Axioskop 20 microscope). Were considered fertilized, the oocyte showing fluorescent decondensed sperm head within their cytoplasm. To assess the FI, the number of decondensed sperm head was recorded.</p>
          <p>To test the effect of antibodies on the FR and FI, one or both gametes were separately preincubated for 30 minutes in medium supplemented with GoH3 at 200 μg/ml or L16 at 50 μg/ml prior to IVF. Oocytes were then washed and sperm were diluted 1:100 into the final droplet containing the oocytes. To test fusion, oocytes were inseminated at a final sperm concentration of 10<sup>5</sup>/ml for AT zona-free egg assay and 10<sup>6</sup>/ml for cumulus-intact egg assay in a new drop of Whittingham's medium + 3% BSA with or without the antibody.</p>
        </sec>
      </sec>
      <sec>
        <title>Sperm Immunolabeling and Fluorescence Microscopy</title>
        <p>Freshly recovered or capacitated spermatozoa were washed in PBS containing 1% BSA, centrifuged at 600 g for 5 minutes and immediately fixed in 4% PFA in PBS-1% BSA at 4°C for 1 hour. After washing, the fixed spermatozoa were incubated in PBS with 20 μg/ml of rat anti-α6 or anti-β1 integrin subunits antibodies (GoH3 and MB1.2, respectively) for 1 hour and then with 10 μg/ml of Alexa Fluor<sup>® </sup>594 (red) goat anti-rat IgG for 1 hour. Control immunofluorescent studies were performed using isotype (IgG<sub>2a</sub>) as primary antibody or Alexa Fluor<sup>® </sup>594 goat anti-rat IgG alone.</p>
        <p>Alexa Fluor<sup>® </sup>594 labeled cells were submitted to the PSA-staining protocol for the sequential detection of integrin distribution and acrosomal status. Spermatozoa were treated for 30 minutes in 95% ethanol at 4°C, washed by centrifugation through PBS and stained with FITC-conjugated lectin PSA (25 μg/ml in PBS) for 10 minutes. After repeated washing with double distilled water, a drop of sperm suspension was smeared on slide, air-dried, mounted with Vectashield/DAPI and covered with a coverslip for analysis. Detection was performed using a Zeiss Axiophot epifluorescence microscope and images were digitally acquired with a camera (Coolpix 4500, Nikon).</p>
      </sec>
      <sec>
        <title>Flow cytometry analysis of alpha6 and beta1 integrin subunits on mouse spermatozoa</title>
        <p>Freshly recovered and capacitated sperm surface expression of α6 and β1 integrin subunits were evaluated using a FACScan flow cytometer (Becton Dickinson, San Jose, CA, USA) equipped with argon laser (power: 15 mW, wavelength: 488 nm). Flow cytometer was driven with the Cellquest software (Becton Dickinson). The staining procedure was the same as that used for immunofluorescence. Finally, sperm was kept in 1% PFA in PBS at 10<sup>6 </sup>sperm/ml. For each sample, 5,000 cells were analyzed at a flow rate of 200–300 cells per second using FSC/FL1 (cell size/relative fluorescence) parameters. The fluorescence data were collected using the logarithmic amplifier. Autofluorescence of the sample was measured using sperm that were never exposed to antibodies and negative controls were performed with the isotype and second antibody or second antibody alone.</p>
      </sec>
      <sec>
        <title>Confocal analysis of indirect immunofluorescence oocyte staining</title>
        <p>Immunodetection of the integrin subunits was carried out on ZP-intact and AT zona-free eggs. Oocytes were fixed in 2% PFA diluted in PBS-1% BSA for 20 minutes. For detection of the α6 or β1 integrin subunits, oocytes were incubated with the primary antibody GoH3 or MB1.2 (20 μg/ml each one) for 1 hour at room temperature (RT) and then with the suitable secondary antibodies for 1 hour at RT. Controls were prepared by replacing primary antibody by rat IgG2a isotype.</p>
        <p>Oocytes were mounted in PBS 1× in Lab-Tek<sup>® </sup>chambers (Nalge Nunc International, Naperville, USA) and images were captured using a Leica TCS SP2 AOBS confocal microscope. Ninety oocytes sections were collected. The maximum projection function was then used to superimpose the different sections. Image analysis was performed using ImageJ free-software [<xref ref-type="bibr" rid="B27">27</xref>].</p>
      </sec>
      <sec>
        <title>Western Blot analysis</title>
        <p>Capacitated sperm were washed twice in PBS, the pellet snap-frozen in liquid N2 and stored at -80°C for further use. Sperm aliquots were lysed in 50 mM Tris (pH 8), 150 mM Nacl, 1 mM EDTA, 0,25% sodium desoxycholate and 1% NP40, supplemented with Protease Inhibitor Cocktail (Sigma) for 1 hour on ice, boiled for 5 minutes with an equal volume of 2× NuPAGE<sup>® </sup>LDS sample buffer (Invitrogen, France) supplemented with 5% β-mercaptoethanol. Semen lysate was gently sonicated. F9 Whole Cell Lysate (Abcam, France) was used as a positive control for the α6 integrin subunit detection. Sample proteins were separated by 4 to 20% SDS-Polyacrilamide gel electrophoresis (Euromedex, France) and electro-transferred to Immobilon-P membranes (Millipore, France). Membranes were blocked overnight with Western Blocking Reagent (Roche, France) prior incubation with appropriate primary antibodies (Rabbit anti-α6 integrin: 0,2 μg/ml, non-specific rabbit IgG: 0,2 μg/ml) for 90 minutes at 37°C followed by biotinylated appropriate secondary antibodies (biotinylated anti-rabbit: 0,2 μg/ml) and HRP-Streptavidin (0,02 μg/ml), each for 1 hour at 37°C. For competition study between anti-α6 integrin antibody (N-19) and its specific blocking peptide, a mixing of equal volume of each of them was prepared and incubated at 4°C overnight. The day after, membranes were incubated with either this mixing or with the anti-α6 integrin antibody (N-19) alone at the dilution 1/200 (1 μg/ml), overnight at 4°C; the membranes were then kept 1 hour at 37°C before an incubation with the secondary rabbit anti-goat antibody HRP-conjugated (1/2000) for 1 hour at RT. HRP activity was revealed by ECL detection kit (Amersham Biosciences, UK) and autoradiography (BioMax Light Film, Kodac). Film exposure was less than 5 minutes.</p>
      </sec>
      <sec>
        <title>Statistical analysis</title>
        <p>Statistical analysis was performed using Statview<sup>® </sup>package. Means were compared by non-paired t test. Differences were considered significant at <italic>P </italic>&lt; 0.05.</p>
      </sec>
    </sec>
    <sec>
      <title>Abbreviations</title>
      <p>AR- Acrosome reacted.</p>
      <p>AT- Acid Tyrode.</p>
      <p>FI- Fertilization index.</p>
      <p>FR- Fertilization rate.</p>
      <p>IVF- In vitro fertilization.</p>
      <p>PSA- <italic>Pisum sativum agglutinin.</italic></p>
      <p>RT- Room temperature.</p>
      <p>ZP- Zona pellucida.</p>
    </sec>
    <sec>
      <title>Authors' contributions</title>
      <p>VB-L participated in the design of the study, Western blot analysis, confocal analysis and helped to draft the manuscript. NN-B carried out the sperm immunolabeling and fluorescence microscopy and participated to oocytes confocal analysis. LS and LG carried out the flow cytometry analysis. BD performed the statistical analysis. ASD participated in the Western blot analysis. MB participated in the design of the study, the Western blot analysis and redaction of the manuscript. JPW participated in the design of the study and redaction of the manuscript. AZ conceived and coordinated the study, drafted the manuscript, carried out the gamete preparation and in vitro fertilization assays. All authors read and approved the final manuscript.</p>
    </sec>
  </body>
  <back>
    <ack>
      <sec>
        <title>Acknowledgements</title>
        <p>We thank S. Chambris (Université Paris 13) for his technical assistance, P. Bourdoncle for confocal analysis, A. Benkhelifa, L. Dandolo and D. Montjean for editorial assistance and the authors of the plugins of ImageJ freeware. This work was supported by grants from Organon (subvention FARO), Association Jacques Salat-Baroux and the Société d'Andrologie de Langue Française (SALF).</p>
      </sec>
    </ack>
    <ref-list>
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        <citation citation-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Inoue</surname>
              <given-names>N</given-names>
            </name>
            <name>
              <surname>Ikawa</surname>
              <given-names>M</given-names>
            </name>
            <name>
              <surname>Isotani</surname>
              <given-names>A</given-names>
            </name>
            <name>
              <surname>Okabe</surname>
              <given-names>M</given-names>
            </name>
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          <article-title>The immunoglobulin superfamily protein Izumo is required for sperm to fuse with eggs</article-title>
          <source>Nature</source>
          <year>2005</year>
          <volume>434</volume>
          <fpage>234</fpage>
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