Predictive performance of seven clinical surrogates of visceral adipose tissue for cardiovascular mortality: A sub-analysis of 102,385 adults from the Mexico City Prospective Study
Résumé fourni par la source
BACKGROUND: Visceral adipose tissue (VAT) has been associated with cardiovascular disease (CVD) mortality. However, the comparative performance of VAT-related clinical surrogates remains poorly characterized. OBJECTIVES: To evaluate the performance of seven VAT-related clinical surrogates for predicting CVD and cause-specific CVD mortality. METHODS: We analyzed data from the Mexico City Prospective Cohort, a population-based prospective cohort study, with baseline recruitmetn between 1998 - 2004 and ongoing mortality follow-up. CVD mortality included deaths from cardiac, stroke-related, and other vascular causes. Seven VAT-related surrogates (METS-VF, CVAI, EVA, DAAT, LAAP, VAI, and DAI) were estimated using clinical, biochemical, and anthropometric data at baseline. Associations with outcomes were evaluated using Cox regression models to estimate adjusted hazard ratios (aHRs). Discrimination was assessed with Harrell's C-statistic (Cs) and fixed-point at 10-years receiver operating characteristic (ROC) curves, and calibration with slope plots. RESULTS: In a subsample of 102,385 participants (median age: 47 years; 67% female), 4,068 (3.97%) died from any CVD causes. METS-VF (Cs: 0.722; aHR: 1.17, 95% CI: 1.12-1.23), EVA (Cs: 0.72; 1.14, 1.12-1.23), CVAI (Cs: 0.70; 1.13, 1.09-1.18), and DAAT (Cs: 0.626; 1.13, 1.09-1.18) were positively associated with CVD mortality and showed the highest predictive capacity among the surrogates. Adding METS-VF to a CVD risk score among individuals classified as intermediate risk improved discrimination for CVD mortality. CONCLUSIONS: In this large cohort of Mexican adults, four VAT-related clinical surrogates, particularly METS-VF, demonstrated good discriminatory performance for long-term CVD mortality. These indices could help to identify individuals with high VAT accumulation and high CVD risk in resource-limited settings.