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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.v9i5.2897</article-id>
      <article-id pub-id-type="publisher-id">9:5:404</article-id>
      <title-group>
        <article-title>Association between neighbourhood poverty and type 2 diabetes risk. Does moving from a high to lower poverty neighbourhood reduce diabetes risk?</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Majumder</surname>
            <given-names initials="S">Sharmin</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Booth</surname>
            <given-names initials="G">Gillian</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
          <xref ref-type="aff" rid="affil-2">2</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Moineddin</surname>
            <given-names initials="R">Rahim</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Pinto</surname>
            <given-names initials="A">Andrew</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
          <xref ref-type="aff" rid="affil-3">3</xref>
        </contrib>
      </contrib-group>
      <aff id="affil-1"><label>1</label><institution>University of Toronto</institution></aff>
      <aff id="affil-2"><label>2</label><institution>ICES (formerly known as the Institute for Clinical Evaluative Sciences)</institution></aff>
      <aff id="affil-3"><label>3</label><institution>Upstream Lab, MAP/Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, Unity Health Toronto</institution></aff>
      <pub-date date-type="pub" publication-format="electronic">
        <day>18</day>
        <month>09</month>
        <year>2024</year>
      </pub-date>
      <pub-date date-type="collection" publication-format="electronic">
        <year>2024</year>
      </pub-date>
      <volume>9</volume>
      <issue>5</issue>
      <elocation-id>2897</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/2897">This article is available from the IJPDS website at: https://ijpds.org/article/view/2897</self-uri>
    </article-meta>
  </front>
  <body>
    <sec>
      <title>Objectives</title>
      <p>Diabetes, a pressing global public health crisis, Diabetes, a global health crisis, is significantly impacted by social determinants, including neighborhood characteristics. This study aims to to assess whether relocation from a high poverty to lower poverty neighbourhood is associated with a reduction in T2D incidence.</p>
    </sec>
    <sec>
      <title>Methods and Results</title>
      <p>This population-based, propensity-matched cohort study will use linked administrative health to examine the association between neighborhood relocation and T2D incidence. The study population will include adults (age ≥20 years) residing in high poverty urban neighborhoods between April 1st, 2002, to March 31st, 2021, as defined by an area Low-Income Measure - After Tax value of 38,730 dollars for a household size 4 based on the Canadian Census. Individuals will be followed for a new diagnosis of T2D using a validated algorithm based on hospitalization and physicians’ claims data. Propensity score matching will used to match individuals who moved from high-to-lower poverty neighbourhoods to one of two comparison groups: those moving from high-to-high poverty areas and those who remain in their original neighbourhood. Time-to-event analysis utilizing Cox proportional hazards regression with a robust variance estimator will be used to compare T2D incidence between matched groups. As a sensitivity analysis, non-propensity score modeling will be conducted using neighbourhood of residence as a time-varying covariate. The results of the aforementioned analyses will be presented during the conference.</p>
    </sec>
    <sec>
      <title>Implications</title>
      <p>By clarifying the link between neighborhood poverty and T2D incidence, the results will guide focused interventions to alleviate health inequalities in socioeconomically disadvantaged areas.</p>
    </sec>
  </body>
</article>