SPC365

Association of Anthropometric Indices with Coronary Artery Disease: A Comparative Analysis of Central and General Adiposity Measures

Session: Sessão de Comunicações Orais 05 – Para além do LDL: determinantes metabólicos do risco cardiovascular
Speaker: Gonçalo Bettencourt Abreu

Congress: CPC 2026
Topic: J. Preventive Cardiology
Theme: 28. Risk Factors and Prevention
Subtheme: 28.3 Secondary Prevention
Session Type: Comunicações Orais
FP Number: ---
Authors: Gonçalo Bettencourt Abreu; Maria Isabel Mendonça; Francisco Sousa; Matilde Ferreira; Francisca Escórcio Silva; Eva Henriques; Sónia Freitas; Mariana Rodrigues; Sofia Borges; António Drumond; Ana Célia Sousa; Roberto Palma Dos Reis

<p style="text-align:justify"><span style="font-size:12pt"><span style="font-family:Aptos,sans-serif"><strong><span style="font-size:11.0pt"><span style="font-family:&quot;Calibri&quot;,sans-serif">Introduction:</span></span></strong><span style="font-size:11.0pt"><span style="font-family:&quot;Calibri&quot;,sans-serif"> Obesity is a well-established risk factor for coronary artery disease (CAD). Increasing evidence, however, indicates that obesity should not be regarded solely as a risk factor but as a chronic, multifactorial disease with complex metabolic and inflammatory consequences. A recent <em>Lancet Diabetes &amp; Endocrinology</em> Commission (2025) proposed redefining obesity beyond the exclusive use of body mass index (BMI), recommending the integration of BMI with additional anthropometric indices that better capture adipose tissue distribution and cardiometabolic risk. These developments reinforce the need to identify which anthropometric markers more accurately reflect obesity-related cardiovascular risk.</span></span></span></span></p>

<p style="text-align:justify"><span style="font-size:12pt"><span style="font-family:Aptos,sans-serif"><strong><span style="font-size:11.0pt"><span style="font-family:&quot;Calibri&quot;,sans-serif">Objective:</span></span></strong><span style="font-size:11.0pt"><span style="font-family:&quot;Calibri&quot;,sans-serif"> To compare three anthropometric indices&mdash;waist-to-height ratio (WHtR), BMI, and waist-to-hip ratio (WHR)&mdash;in their association with CAD and determine which index performs best in our population.</span></span></span></span></p>

<p style="text-align:justify"><span style="font-size:12pt"><span style="font-family:Aptos,sans-serif"><strong><span style="font-size:11.0pt"><span style="font-family:&quot;Calibri&quot;,sans-serif">Methods:</span></span></strong><span style="font-size:11.0pt"><span style="font-family:&quot;Calibri&quot;,sans-serif"> We conducted a prospective study including 3,157 individuals classified into CAD and non-CAD groups. Student&rsquo;s t-tests assessed differences between groups. ROC curves and pairwise AUC comparisons were performed using DeLong&rsquo;s test. Multivariable logistic regression models were constructed for each index, adjusted for sex, age, diabetes, dyslipidaemia, hypertension, smoking, sedentary lifestyle, and alcohol intake (&gt;300 g/week).</span></span></span></span></p>

<p style="text-align:justify"><span style="font-size:12pt"><span style="font-family:Aptos,sans-serif"><strong><span style="font-size:11.0pt"><span style="font-family:&quot;Calibri&quot;,sans-serif">Results:</span></span></strong><span style="font-size:11.0pt"><span style="font-family:&quot;Calibri&quot;,sans-serif"> All anthropometric indices were significantly higher in CAD patients: WHtR (p&lt;0.0001), BMI (p=0.001), and WHR (p&lt;0.0001). WHtR showed an AUC of 0.599 (95% CI: 0.582&ndash;0.617), BMI an AUC of 0.545 (95% CI: 0.527&ndash;0.562), and WHR an AUC of 0.604 (95% CI: 0.587&ndash;0.621). Pairwise comparisons showed significant differences between WHtR and BMI (</span></span><span style="font-size:11.0pt"><span style="font-family:&quot;Calibri&quot;,sans-serif">&Delta;</span></span><span style="font-size:11.0pt"><span style="font-family:&quot;Calibri&quot;,sans-serif">AUC = 0.055; p&lt;0.0001) and between BMI and WHR (</span></span><span style="font-size:11.0pt"><span style="font-family:&quot;Calibri&quot;,sans-serif">&Delta;</span></span><span style="font-size:11.0pt"><span style="font-family:&quot;Calibri&quot;,sans-serif">AUC=0.060; p&lt;0.0001), with no significant difference between WHtR and WHR (</span></span><span style="font-size:11.0pt"><span style="font-family:&quot;Calibri&quot;,sans-serif">&Delta;</span></span><span style="font-size:11.0pt"><span style="font-family:&quot;Calibri&quot;,sans-serif">AUC=0.005; p=0.605). In adjusted regression, WHtR was associated with CAD (OR=4.05; p=0.036), WHR showed a strong association (OR=16.71; p&lt;0.0001), and BMI demonstrated an inverse association (OR=0.98; p=0.020).</span></span></span></span></p>

<p><strong><span style="font-size:11.0pt"><span style="font-family:&quot;Calibri&quot;,sans-serif">Conclusion:</span></span></strong><span style="font-size:11.0pt"><span style="font-family:&quot;Calibri&quot;,sans-serif"> Anthropometric indices were associated with CAD, with central-adiposity measures showing the strongest associations. These indices are simple to calculate and apply in routine practice and may help identify individuals at higher risk of CAD, allowing preventive measures to be implemented in a timely manner.</span></span></p>