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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.v10i3.3233</article-id>
      <article-id pub-id-type="publisher-id">10:3:199</article-id>
      <title-group>
        <article-title>Long COVID, post-viral fatigue syndrome, and fatigue consultation records in
          children in England using administrative primary care data</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Chiovoloni</surname>
            <given-names initials="R">Roberta</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Stannard</surname>
            <given-names initials="S">Sebastian</given-names>
          </name>
          <xref ref-type="aff" rid="affil-2">2</xref>
          <xref ref-type="aff" rid="affil-3">3</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Ziauddeen</surname>
            <given-names initials="N">Nida</given-names>
          </name>
          <xref ref-type="aff" rid="affil-2">2</xref>
          <xref ref-type="aff" rid="affil-3">3</xref>
          <xref ref-type="aff" rid="affil-4">4</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Fraser</surname>
            <given-names initials="S">Simon</given-names>
          </name>
          <xref ref-type="aff" rid="affil-2">2</xref>
          <xref ref-type="aff" rid="affil-3">3</xref>
          <xref ref-type="aff" rid="affil-4">4</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Alwan</surname>
            <given-names initials="N">Nisreen A</given-names>
          </name>
          <xref ref-type="aff" rid="affil-2">2</xref>
          <xref ref-type="aff" rid="affil-3">3</xref>
          <xref ref-type="aff" rid="affil-4">4</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Owen</surname>
            <given-names initials="R">Rhiannon K</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
      </contrib-group>
      <aff id="affil-1"><label>1</label><institution>Population Data Science, Faculty of Medicine,
        Swansea University Medical School, Swansea, United Kingdom</institution></aff>
      <aff id="affil-2"><label>2</label><institution>School of Primary Care, Population Sciences and
        Medical Education, Faculty of Medicine, University of Southampton, Southampton, United
        Kingdom</institution></aff>
      <aff id="affil-3"><label>3</label><institution>NIHR Applied Research Collaboration Wessex,
        Southampton, United Kingdom</institution></aff>
      <aff id="affil-4"><label>4</label><institution>University Hospital Southampton NHS Foundation
        Trust, Southampton, United Kingdom</institution></aff>
      <pub-date>
        <day>01</day>
        <month>06</month>
        <year>2025</year>
      </pub-date>
      <pub-date date-type="collection" publication-format="electronic">
        <year>2025</year>
      </pub-date>
      <volume>8</volume>
      <issue>4</issue>
      <elocation-id>3233</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/3233">This article is available from the
        IJPDS website at: https://ijpds.org/article/view/3233</self-uri>
    </article-meta>
  </front>
  <body>
    <sec>
      <title>Objectives</title>
      <p>Using multistate models, we evaluated how the sequence of developing coexisting diseases,
        specifically obesity and hypertension, influences the trajectories to patient burden
        (defined as two hospital admissions within a five year period) and mortality. Our findings
        aim to provide insights into disease trajectories, identifying potential delays in diagnosis
        and prolonged high-burden states.</p>
    </sec>
    <sec>
      <title>Methods</title>
      <p>We used administrative and electronic health record data from Welsh residents aged 18 and
        older on the 1st January 2005. Obesity and hypertension records were identified using
        primary and secondary care data sources.</p>
      <p>We applied a multistate model to examine condition accrual and its association with
        hospital admissions and mortality in an 18-year window, accounting for competing risks.
        Individuals transitioned between healthy, obesity, hypertension, combined obesity and
        hypertension, burden, and death (absorbing state). Cox regression models estimated
        transition hazards, adjusting for age, sex, and Welsh Index of Multiple Deprivation.
        Analyses were conducted in the SAIL Databank using R.</p>
    </sec>
    <sec>
      <title>Results</title>
      <p>The study included 2,432,723 individuals (48.8% female) with a median age of 37.9
        (24.1-51.7) years. 950,001 individuals remained event-free, 822,728 developed obesity and
        185,056 hypertension as first condition, and 157,066 developed both.</p>
      <p>Overall, 805,076 (33.1%) reached the burden state.</p>
      <p>Middle-aged individuals (40 years old) in the hypertension state had a higher risk of
        burden (0.80) by the end of the 18-year window than those in the combined obesity and
        hypertension states (0.62 and 0.55). Risk was lower for females than males (aHR 0.96, 95%
        0.95-0.98).</p>
      <p>Mortality risk within the first five years post-diagnosis was highest for individuals who
        developed hypertension followed by obesity, compared to those with hypertension alone or
        obesity preceding hypertension (0.01 vs 0.0075 and 0.008).</p>
      <p>Men had higher mortality risks than women across all transitions.</p>
    </sec>
    <sec>
      <title>Conclusion</title>
      <p>Our study highlights the differential risk of multiple hospital admissions in people with
        earlier healthcare coding of obesity and/or hypertension. These findings can highlight
        optimal times to identify risk factors to prevent adverse health outcomes.</p>
    </sec>
  </body>
</article>