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<a href="./analytic15.html" class="sidebar-item-text sidebar-link"><span class="chapter-number">32</span> <span class="chapter-title">Recoding cycle 9</span></a>
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<a href="./analytic17.html" class="sidebar-item-text sidebar-link"><span class="chapter-number">33</span> <span class="chapter-title">Recoding cycle 10</span></a>
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<a href="./merge13to17.html" class="sidebar-item-text sidebar-link"><span class="chapter-number">34</span> <span class="chapter-title">Merge three cycles</span></a>
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<li><a href="#choose-a-u.s.-data-source" id="toc-choose-a-u.s.-data-source" class="nav-link active" data-scroll-target="#choose-a-u.s.-data-source"><span class="toc-section-number">1.1</span> Choose a U.S. data source</a></li>
<li><a href="#confounder-identification" id="toc-confounder-identification" class="nav-link" data-scroll-target="#confounder-identification"><span class="toc-section-number">1.2</span> Confounder identification</a></li>
<li><a href="#structure-of-the-data" id="toc-structure-of-the-data" class="nav-link" data-scroll-target="#structure-of-the-data"><span class="toc-section-number">1.3</span> Structure of the data</a></li>
<li><a href="#identify-measured-and-unmeasured-variables-in-the-data" id="toc-identify-measured-and-unmeasured-variables-in-the-data" class="nav-link" data-scroll-target="#identify-measured-and-unmeasured-variables-in-the-data"><span class="toc-section-number">1.4</span> Identify measured and unmeasured variables in the data</a></li>
<li><a href="#fitting-crude-model-to-obtain-or" id="toc-fitting-crude-model-to-obtain-or" class="nav-link" data-scroll-target="#fitting-crude-model-to-obtain-or"><span class="toc-section-number">1.5</span> Fitting crude model to obtain OR</a></li>
</ul>
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<h1 class="title d-none d-lg-block"><span class="chapter-number">1</span> <span class="chapter-title">Data to Analyze</span></h1>
</div>
<div class="quarto-title-meta">
</div>
</header>
<p>To answer the research question “Does obesity increase the risk of developing diabetes?” in the <mark>U.S. context</mark>, we do the following:</p>
<section id="choose-a-u.s.-data-source" class="level2 page-columns page-full" data-number="1.1">
<h2 data-number="1.1" class="anchored" data-anchor-id="choose-a-u.s.-data-source"><span class="header-section-number">1.1</span> Choose a U.S. data source</h2>
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<ul>
<li><strong>Data source</strong>: National Health and Nutrition Examination Survey (<a href="https://wwwn.cdc.gov/nchs/nhanes/">NHANES</a>) <span class="citation" data-cites="nhanes">(<a href="references.html#ref-nhanes" role="doc-biblioref">Disease Control and Prevention 2021</a>)</span>
<ul>
<li><a href="https://wwwn.cdc.gov/nchs/nhanes/continuousnhanes/default.aspx?BeginYear=2013">2013-2014</a>,</li>
<li><a href="https://wwwn.cdc.gov/nchs/nhanes/continuousnhanes/default.aspx?BeginYear=2015">2015-2016</a>,</li>
<li><a href="https://wwwn.cdc.gov/nchs/nhanes/continuousnhanes/default.aspx?BeginYear=2017">2017-2018</a></li>
</ul></li>
<li><strong>Availability</strong>: NHANES is a <mark>publicly available</mark> dataset that can be downloaded for free from the CDC website.</li>
<li><strong>Design</strong>: Observational cross-sectional data. Hence, inferring causality is not a possibility or our objective here.</li>
</ul>
</div></div></section>
<section id="confounder-identification" class="level2 page-columns page-full" data-number="1.2">
<h2 data-number="1.2" class="anchored" data-anchor-id="confounder-identification"><span class="header-section-number">1.2</span> Confounder identification</h2>
<p><strong>Directed acyclic graph (DAG)</strong></p>
<div class="no-row-height column-margin column-container"><div class="">
<p><span class="citation" data-cites="greenland1999causal">(<a href="references.html#ref-greenland1999causal" role="doc-biblioref">Greenland, Pearl, and Robins 1999</a>)</span></p>
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<p>
</p><pre class="mermaid mermaid-js" data-tooltip-selector="#mermaid-tooltip-1">flowchart TB
A[Obesity A] --> Y(Diabetes Y)
L[Confounders C] --> Y
L --> A
</pre>
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<p><img src="images/DAGbdcomplete0.png" style="width:100.0%" class="figure-img"></p>
<p></p><figcaption class="figure-caption">Hypothesized Directed acyclic graph drawn based on analyst’s best understanding of the literature</figcaption><p></p>
</figure>
</div>
</div>
</div>
<div class="no-row-height column-margin column-container"><div class="">
<p><strong>Exposure</strong>: Being obese</p>
</div><div class="">
<p><strong>Outcome</strong>: Developing diabetes</p>
</div><div class="">
<p><strong>Confounders</strong>: Demographic and lab variables</p>
</div></div>
</section>
<section id="structure-of-the-data" class="level2 page-columns page-full" data-number="1.3">
<h2 data-number="1.3" class="anchored" data-anchor-id="structure-of-the-data"><span class="header-section-number">1.3</span> Structure of the data</h2>
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<p>
</p><pre class="mermaid mermaid-js" data-tooltip-selector="#mermaid-tooltip-2">flowchart LR
D[NHANES 2013-14] --> demo[Demographic Variables and Sample Weights]
demo --> Age
demo --> Sex
demo --> Education
demo --> r[Race or ethnicity]
demo --> m[Marital status]
demo --> Income
demo --> b[Birth place]
demo --> sf[Survey features: sampling weights, strata, cluster]
D --> bmi[Body Measures]
bmi --> Obesity
D --> diq[Diabetes]
diq --> Diabetes
diq --> f[Family history of diabetes]
D --> smq[Smoking - Cigarette Use]
smq --> Smoking
D --> dbq[Diet Behavior & Nutrition]
dbq --> Diet
D --> paq[Physical Activity]
paq --> p[Physical activities]
D --> huq[Hospital Utilization & Access to Care]
huq --> mm[Medical access]
D --> bpx[Blood Pressure]
bpx --> sbp[Systolic Blood Pressure]
bpx --> dbp[Diastolic Blood Pressure]
D --> bpq[Blood Pressure & Cholesterol]
bpq --> hc[High cholesterol]
D --> slq[Sleep Disorders]
slq --> Sleep
D --> biopro[Standard Biochemistry Profile]
biopro --> u[Uric acid]
biopro --> Protein
biopro --> Bilirubin
biopro --> Phosphorus
biopro --> Sodium
biopro --> Potassium
biopro --> Globulin
biopro --> Calcium
D --> rxq[Prescription Medications - ICD-10-CM codes]
style D fill:#FFA500;
style rxq fill:#00FF00;
style biopro fill:#00FF00;
style slq fill:#00FF00;
style bpq fill:#00FF00;
style bpx fill:#00FF00;
style huq fill:#00FF00;
style paq fill:#00FF00;
style dbq fill:#00FF00;
style smq fill:#00FF00;
style diq fill:#00FF00;
style bmi fill:#00FF00;
style demo fill:#00FF00;
</pre>
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<p>We do the same for the following cycles:</p>
<ul>
<li>NHANES 2015-16</li>
<li>NHANES 2017-18</li>
</ul>
</div></div></section>
<section id="identify-measured-and-unmeasured-variables-in-the-data" class="level2 page-columns page-full" data-number="1.4">
<h2 data-number="1.4" class="anchored" data-anchor-id="identify-measured-and-unmeasured-variables-in-the-data"><span class="header-section-number">1.4</span> Identify measured and unmeasured variables in the data</h2>
<p>Find variables capturing the following concepts in the data based on a hypothesized DAG.</p>
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tr:nth-child(even) td:nth-child(1),
tr:nth-child(even) td:nth-child(2) {
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th {
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<table class="table">
<thead>
<tr class="header">
<th>Role</th>
<th>Data Component</th>
<th>Variables considered based on DAG</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td>Outcome</td>
<td><a href="https://wwwn.cdc.gov/Nchs/Data/Nhanes/Public/2017/DataFiles/DIQ_J.htm">DIQ</a></td>
<td><em>Have diabetes</em><a href="#fn1" class="footnote-ref" id="fnref1" role="doc-noteref"><sup>1</sup></a></td>
</tr>
<tr class="even">
<td>Exposure</td>
<td><a href="https://wwwn.cdc.gov/Nchs/Data/Nhanes/Public/2017/DataFiles/BMX_J.htm">BMX</a></td>
<td><em>Obese</em>; <a href="https://www.cdc.gov/obesity/adult-obesity-facts/index.html">BMI >= 30</a></td>
</tr>
<tr class="odd">
<td>Confounder</td>
<td>(<em>demographic</em>) <a href="https://wwwn.cdc.gov/Nchs/Data/Nhanes/Public/2017/DataFiles/DEMO_J.htm">DEMO</a></td>
<td>Age, Sex, Education, Race/ethnicity, Marital status, Annual household income, County of birth, Survey cycle year</td>
</tr>
<tr class="even">
<td></td>
<td>(<em>behaviour</em>) <a href="https://wwwn.cdc.gov/Nchs/Data/Nhanes/Public/2017/DataFiles/SMQ_J.htm">SMQ</a>, <a href="https://wwwn.cdc.gov/Nchs/Data/Nhanes/Public/2017/DataFiles/PAQ_J.htm">PAQ</a>, <a href="https://wwwn.cdc.gov/Nchs/Data/Nhanes/Public/2017/DataFiles/SLQ_J.htm">SLQ</a>, <a href="https://wwwn.cdc.gov/Nchs/Data/Nhanes/Public/2017/DataFiles/DBQ_J.htm">DBQ</a></td>
<td>Smoking<a href="#fn2" class="footnote-ref" id="fnref2" role="doc-noteref"><sup>2</sup></a>, Vigorous work activity, Sleep<a href="#fn3" class="footnote-ref" id="fnref3" role="doc-noteref"><sup>3</sup></a>, Diet<a href="#fn4" class="footnote-ref" id="fnref4" role="doc-noteref"><sup>4</sup></a></td>
</tr>
<tr class="odd">
<td></td>
<td>(<em>health history / access</em>) <a href="https://wwwn.cdc.gov/Nchs/Data/Nhanes/Public/2017/DataFiles/DIQ_J.htm">DIQ</a>, <a href="https://wwwn.cdc.gov/Nchs/Data/Nhanes/Public/2017/DataFiles/HUQ_J.htm">HUQ</a></td>
<td>Diabetes family history, Access to care<a href="#fn5" class="footnote-ref" id="fnref5" role="doc-noteref"><sup>5</sup></a></td>
</tr>
<tr class="even">
<td></td>
<td>(<em>lab</em>) <a href="https://wwwn.cdc.gov/Nchs/Data/Nhanes/Public/2017/DataFiles/BPX_J.htm">BPX</a>, <a href="https://wwwn.cdc.gov/Nchs/Data/Nhanes/Public/2017/DataFiles/BPQ_J.htm">BPQ</a>, <a href="https://wwwn.cdc.gov/Nchs/Data/Nhanes/Public/2017/DataFiles/BIOPRO_J.htm">BIOPRO</a></td>
<td>Blood pressure (systolic, diastolic<a href="#fn6" class="footnote-ref" id="fnref6" role="doc-noteref"><sup>6</sup></a>), Cholesterol, Uric acid, Total Protein, Total Bilirubin, Phosphorus, Sodium, Potassium, Globulin, Total Calcium</td>
</tr>
</tbody>
</table>
<div class="no-row-height column-margin column-container"><div class="">
<ul>
<li>14 demographic, behavioral, health history related variables
<ul>
<li>Mostly <strong>categorical</strong></li>
</ul></li>
<li>11 lab variables
<ul>
<li>Mostly <strong>continuous</strong></li>
</ul></li>
</ul>
</div></div></section>
<section id="fitting-crude-model-to-obtain-or" class="level2" data-number="1.5">
<h2 data-number="1.5" class="anchored" data-anchor-id="fitting-crude-model-to-obtain-or"><span class="header-section-number">1.5</span> Fitting crude model to obtain OR</h2>
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Crude association
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<p>Here we estimate the crude association between the exposure and the outcome.</p>
</div>
</div>
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<div class="sourceCode cell-code" id="cb1"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a>out.formula <span class="ot"><-</span> <span class="fu">as.formula</span>(<span class="st">"outcome ~ exposure"</span>)</span>
<span id="cb1-2"><a href="#cb1-2" aria-hidden="true" tabindex="-1"></a>fit <span class="ot"><-</span> <span class="fu">glm</span>(out.formula,</span>
<span id="cb1-3"><a href="#cb1-3" aria-hidden="true" tabindex="-1"></a> <span class="at">data =</span> hdps.data,</span>
<span id="cb1-4"><a href="#cb1-4" aria-hidden="true" tabindex="-1"></a> <span class="at">family=</span> <span class="fu">binomial</span>(<span class="at">link =</span> <span class="st">"logit"</span>))</span>
<span id="cb1-5"><a href="#cb1-5" aria-hidden="true" tabindex="-1"></a>fit.summary <span class="ot"><-</span> <span class="fu">summary</span>(fit)<span class="sc">$</span>coef[<span class="st">"exposure"</span>,</span>
<span id="cb1-6"><a href="#cb1-6" aria-hidden="true" tabindex="-1"></a> <span class="fu">c</span>(<span class="st">"Estimate"</span>, </span>
<span id="cb1-7"><a href="#cb1-7" aria-hidden="true" tabindex="-1"></a> <span class="st">"Std. Error"</span>, </span>
<span id="cb1-8"><a href="#cb1-8" aria-hidden="true" tabindex="-1"></a> <span class="st">"Pr(>|z|)"</span>)]</span>
<span id="cb1-9"><a href="#cb1-9" aria-hidden="true" tabindex="-1"></a>fit.ci <span class="ot"><-</span> <span class="fu">confint</span>(fit, <span class="at">level =</span> <span class="fl">0.95</span>)[<span class="st">"exposure"</span>, ]</span>
<span id="cb1-10"><a href="#cb1-10" aria-hidden="true" tabindex="-1"></a>fit.summary_with_ci.crude <span class="ot"><-</span> <span class="fu">c</span>(fit.summary, fit.ci)</span>
<span id="cb1-11"><a href="#cb1-11" aria-hidden="true" tabindex="-1"></a>knitr<span class="sc">::</span><span class="fu">kable</span>(<span class="fu">t</span>(<span class="fu">round</span>(fit.summary_with_ci.crude, <span class="dv">2</span>)))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output-display">
<table class="table table-sm table-striped">
<thead>
<tr class="header">
<th style="text-align: right;">Estimate</th>
<th style="text-align: right;">Std. Error</th>
<th style="text-align: right;">Pr(>|z|)</th>
<th style="text-align: right;">2.5 %</th>
<th style="text-align: right;">97.5 %</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td style="text-align: right;">0.66</td>
<td style="text-align: right;">0.08</td>
<td style="text-align: right;">0</td>
<td style="text-align: right;">0.51</td>
<td style="text-align: right;">0.81</td>
</tr>
</tbody>
</table>
</div>
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</div>
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<div id="refs" class="references csl-bib-body hanging-indent" role="doc-bibliography" style="display: none">
<div id="ref-nhanes" class="csl-entry" role="doc-biblioentry">
Disease Control, Centers for, and Prevention. 2021. <span>“National Health and Nutrition Examination Survey (NHANES).”</span> <em>National Center for Health Statistics</em>.
</div>
<div id="ref-greenland1999causal" class="csl-entry" role="doc-biblioentry">
Greenland, Sander, Judea Pearl, and James M Robins. 1999. <span>“Causal Diagrams for Epidemiologic Research.”</span> <em>Epidemiology</em>, 37–48.
</div>
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<section id="footnotes" class="footnotes footnotes-end-of-document" role="doc-endnotes">
<hr>
<ol>
<li id="fn1"><p>combination of (a) Doctor told you have diabetes, (b) Taking insulin now, (c) Take diabetic pills to lower blood sugar.<a href="#fnref1" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
<li id="fn2"><p>cigarette use (at least 100 cigarettes in life)<a href="#fnref2" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
<li id="fn3"><p>Sleep hours/workdays<a href="#fnref3" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
<li id="fn4"><p>How healthy is the diet<a href="#fnref4" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
<li id="fn5"><p>Routine place to go for healthcare<a href="#fnref5" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
<li id="fn6"><p>average of 4 measurements<a href="#fnref6" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
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