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Conicity index: an underrated anthropometric marker of cardiovascular risk
Session:
Sessão de Posters 32 - Comportamento, mente e metabolismo
Speaker:
Ivo Santos Palmeiro
Congress:
CPC 2026
Topic:
J. Preventive Cardiology
Theme:
28. Risk Factors and Prevention
Subtheme:
28.2 Risk Factors and Prevention – Cardiovascular Risk Assessment
Session Type:
Posters Eletrónicos
FP Number:
---
Authors:
Ivo Santos Palmeiro; Joana Silva Ferreira; Patrícia Bernardes; Marco Tomaz; David Campos; Catarina Lagoas Pohle; Jéni Quintal; Quitéria Rato; Filipe Seixo
Abstract
<p style="text-align:justify"><span style="font-size:12pt"><span style="font-family:"Times New Roman",serif"><strong>Background</strong>: Obesity is a recognized cardiovascular risk factor (CVRF), but current cardiovascular (CV) risk calculators SCORE2/OP don’t take it directly into account. Specific tools are needed to better assess obesity and predict CV risk among this population.</span></span></p> <p><span style="font-size:12pt"><span style="font-family:"Times New Roman",serif"><strong>Purpose</strong>: We sought to find the anthropometric indicator of adiposity that best correlates to cardiovascular risk.</span></span></p> <p style="text-align:justify"><span style="font-size:12pt"><span style="font-family:"Times New Roman",serif"><strong>Methods:</strong> We conducted an observational study including all participants in a local CV screening event that took place in May 2025. Demographic, anthropometric, clinical and laboratory data were collected on-site. 10-year risk of CV events was calculated using SCORE2/OP. Physical activity was assessed using the International Physical Activity Questionnaire (IPAQ). We compared different anthropometric parameters and explored their association with cardiovascular risk. The conicity index (CI) was calculated as: waist circumference / [0.109 x </span></span><em>√</em> <span style="font-size:12pt"><span style="font-family:"Times New Roman",serif">(body weight/height)].</span></span></p> <p style="text-align:justify"><span style="font-size:12pt"><span style="font-family:"Times New Roman",serif"><strong>Results</strong>: A total of 436 individuals screened were included in our analysis (median age 68 years; 69% female). We identified 24 (7.9%) individuals with low CV risk, 146 (48.0%) with moderate CV risk, 62 (20.4%) with high CV risk and 72 (23.7%) with very high CV risk. In our cohort, mean CI was 1.30 ± 0.10, mean BMI was 26.5 ± 4.5 Kg/m<sup>2</sup>, mean waist circumference was 93.2 ± 11.6 cm and mean cervical circumference was 36.3 ± 3.5 cm. Over half of the cohort (52%) had low physical activity (IPAQ 1), 48% had arterial hypertension, 14% had diabetes mellitus and 11% had obstructive sleep apnoea.</span></span></p> <p style="text-align:justify"><span style="font-size:12pt"><span style="font-family:"Times New Roman",serif">Spearman correlation showed that CI (</span></span>ρ<span style="font-size:12pt"><span style="font-family:"Times New Roman",serif"> 0.42, p<0.01), cervical circumference (</span></span>ρ<span style="font-size:12pt"><span style="font-family:"Times New Roman",serif"> 0.31, p<0.01) and waist circumference (</span></span>ρ<span style="font-size:12pt"><span style="font-family:"Times New Roman",serif"> 0.29, p<0.01) were all significantly associated with a higher SCORE2/OP, with CI having the strongest correlation. BMI failed to show correlation (</span></span>ρ<span style="font-size:12pt"><span style="font-family:"Times New Roman",serif"> 0.08, p=0.17).</span></span></p> <p style="text-align:justify"><span style="font-size:12pt"><span style="font-family:"Times New Roman",serif">On ROC analysis, CI outperformed BMI, cervical and waist circumference as a marker of high/very-high CV risk (AUC 0.719, p<0.01 – fig.1), with an optimal cutoff </span></span>≥<span style="font-size:12pt"><span style="font-family:"Times New Roman",serif"> 1.36 (54% sensitivity, 83% specificity).</span></span></p> <p><span style="font-size:12pt"><span style="font-family:"Times New Roman",serif"><strong>Conclusion: </strong></span></span><span style="font-size:12pt"><span style="font-family:"Times New Roman",serif">Our results suggest that the conicity index may be the most useful anthropometric measure, showing the strongest correlation with cardiovascular risk, and should therefore be considered when assessing overweight population. Further large-scale studies are required to confirm its added value as a predictor of atherosclerotic events.</span></span></p>
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