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  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">IJPDS</journal-id>
      <journal-title-group>
        <journal-title>International Journal of Population Data Science</journal-title>
        <abbrev-journal-title>IJPDS</abbrev-journal-title>
      </journal-title-group>
      <issn pub-type="epub">2399-4908</issn>
      <publisher>
        <publisher-name>Swansea University</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.23889/ijpds.v7i3.2082</article-id>
      <article-id pub-id-type="publisher-id">7:03:306</article-id>
      <title-group>
        <article-title>The UK Longitudinal Linkage Collaboration legal &amp; governance framework: managing ‘delegated and distributed’ data processing working with cross-sectorial data owners.</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Oakley</surname>
            <given-names initials="J">Jacqui</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Flaig</surname>
            <given-names initials="R">Robin</given-names>
          </name>
          <xref ref-type="aff" rid="affil-2">2</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Turner</surname>
            <given-names initials="E">Emma</given-names>
          </name>
          <xref ref-type="aff" rid="affil-3">3</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Campbell</surname>
            <given-names initials="K">Kirsteen</given-names>
          </name>
          <xref ref-type="aff" rid="affil-4">4</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Evans</surname>
            <given-names initials="J">Katharine</given-names>
          </name>
          <xref ref-type="aff" rid="affil-5">5</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>McLachlan</surname>
            <given-names initials="S">Stela</given-names>
          </name>
          <xref ref-type="aff" rid="affil-6">6</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Thomas</surname>
            <given-names initials="R">Richard</given-names>
          </name>
          <xref ref-type="aff" rid="affil-7">7</xref>
        </contrib>
      </contrib-group>
      <aff id="affil-1"><label>1</label>
        <institution>Department of Geography, McGill University, Montréal, Quebec</institution>
      </aff>
      <aff id="affil-2"><label>2</label>
        <institution>Health Analysis Division, Statistics Canada, Ottawa, Ontario</institution>
      </aff>
      <aff id="affil-3"><label>3</label>
        <institution>Department of Epidemiology; Department of Medicine; Centre for Outcomes Research and Evaluation, McGill, Montréal</institution>
      </aff>
      <aff id="affil-4"><label>4</label>
        <institution>School of Planning, University of Waterloo, Waterloo, Ontario</institution>
      </aff>
      <aff id="affil-5"><label>5</label>
        <institution>Department of Geography; Institute for Health and Social Policy, Faculty of Medicine, McGill, Montreal, Quebec</institution>
      </aff>
      <aff id="affil-6"><label>6</label>
        <institution>Department of Geography and Planning, University of Toronto, Toronto, Ontario</institution>
      </aff>
      <aff id="affil-7"><label>7</label>
        <institution>Queen’s University, Kingston, Ontario</institution>
      </aff>
      <pub-date date-type="pub" publication-format="electronic"><day></day><month>09</month><year>2022</year></pub-date>
      <pub-date date-type="collection" publication-format="electronic"><year>2022</year></pub-date>
      <volume>7</volume>
      <issue>3</issue>
      <elocation-id>2082</elocation-id>
      <permissions>
        <license license-type="open-access" xlink:href="https://creativecommons.org/licences/by/4.0/">
          <license-p>This work is licenced under a Creative Commons Attribution 4.0 International License.</license-p>
        </license>
      </permissions>
      <self-uri xlink:href="https://ijpds.org/article/view/2082">This article is available from the IJPDS website at: https://ijpds.org/article/view/2082</self-uri>
    </article-meta>
  </front>
  <body>
    <sec>
      <title>Objectives</title>
      <p>Hypertension is a leading cause of cardiovascular disease and premature death. Neighbourhoods characterized by a high proportion of fast-food outlets may contribute to hypertension in residents; however, limited research has explored these associations. The objectives of this study were to assess associations between neighbourhood fast-food environments, measured and self-reported hypertension.</p>
    </sec>
    <sec>
      <title>Approach</title>
      <p>We used data from 10,700 adults who participated in six cycles of the Canadian Health Measures Survey (CHMS). Measured hypertension was defined as having an average systolic blood pressure (BP) of ≥140, a diastolic BP  ≥90 mm Hg or being on BP lowering medication. Participants were also asked if they had been diagnosed with high BP or if they take BP lowering medication (i.e., self-reported hypertension). We characterized the fast-food environment of each participant’s neighbourhood using the Canadian Food Environment Dataset (Can-FED). We considered the proportion of fast-food outlets relative to fast-food outlets and full-service restaurants as a continuous variable.</p>
    </sec>
    <sec>
      <title>Results</title>
      <p>The mean proportion of fast-food outlets was 23.3% (SD 26.8%). A one standard deviation (SD) increase in the proportion to fast-food outlets was associated with higher odds of measured hypertension in the full sample (OR=1.17, 95% CI 1.05 to 1.31) and in sex-specific models (women: OR=1.14, 95% CI 1.01 to 1.29; and men: OR=1.21, 95% CI 1.03 to 1.43). A one standard deviation (SD) increase in the proportion to fast-food outlets was associated with higher odds of self-reported hypertension in the full sample (OR=1.13, 95% CI 1.02 to 1.24); however, associations were inconclusive in sex-specific models (women: OR=1.11, 95% CI 0.99 to 1.26; and men: OR=1.14, 95% CI 0.99 to 1.33).</p>
    </sec>
    <sec>
      <title>Conclusion</title>
      <p>By linking neighbourhood food environment measures that were created from an administrative data source (the Statistics Canada Business Register) to individual-level data from the CHMS, we were able to demonstrate that reducing the proportion of fast-food outlets in neighbourhoods may reduce rates of hypertension and support individually targeted interventions.</p>
    </sec>
  </body>
</article>