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Background: Metabolic Score for Visceral Fat (METS-VF) is a novel indicator for estimating intra-abdominal fat, yet its connection with coronary artery calcification (CAC) remains uncharted. Our research aims to explore the novel METS-VF indicator’s link to CAC while comparing its performance against relevant anthropometric indices. Methods: This study enrolled participants who underwent health checkups and computed tomography scans for categorizing severity of CAC using the coronary artery calcium score. The METS-VF was calculated and compared with anthropometric indices in estimating the presence of CAC and different CAC severity using receiver operating characteristic curves. Results: Overall, 1217 participants (mean age 50.7 ± 9.9, 53.8% male) were included. METS-VF (odds ratio [OR], 1.506; 95% confidence interval [CI], 1.181–1.921; p = 0.001) was positively associated with the presence of CAC, even after accounting for cardiometabolic factors. Notably, METS-VF was positively associated with mild (OR, 1.450; 95% CI, 1.115–1.886; p = 0.006), moderate (OR, 1.865; 95% CI, 1.137–3.062; p = 0.014), and severe (OR, 2.316; 95% CI, 1.090–4.923; p = 0.029) CAC. Moreover, METS-VF yielded the highest area under curve (AUC) value in the estimation of the CAC presence (AUC = 0.710), mild (AUC = 0.682), moderate (AUC = 0.757), and severe (AUC = 0.807) CAC when compared with body mass index, waist circumference, visceral adiposity index, triglyceride–glucose index, and metabolic score for insulin resistance. The optimal METS-VF cut-off value was 6.4 for predicting CAC. Conclusions: METS-VF emerged as a strong independent marker for detecting CAC presence across mild, moderate, and severe CAC categories, outperforming major anthropometric indices in accurately estimating the presence of CAC and different severity of CAC.

This study aimed to investigate the performance of innovative and traditional cardiometabolic indices, including body mass index (BMI), waist circumference (WC), Chinese visceral adiposity index (CVAI), visceral adiposity index, lipid accumulation product, a body shape index (ABSI), body roundness index, conicity index (CI), triglyceride-glucose (TyG) index, TyG-BMI, and TyG-WC, in estimating atherosclerotic cardiovascular disease (ASCVD) risk in 3143 Taiwanese adults aged 20–79 years. Elevated 10-year ASCVD risk was defined as ≥7.5% using the Pooled Cohort Equations. The performance of different indices in estimating elevated ASCVD risk was assessed by receiver operating characteristic (ROC) curves. In multivariate-adjusted logistic regression analyses, all cardiometabolic indices (p-value < 0.001) were significantly associated with elevated ASCVD risk in both genders, except for ABSI and CI in women. In particular, CVAI had the largest area under the curve (AUC) in men (0.721) and women (0.883) in the ROC analyses. BMI had the lowest AUC in men (0.617), while ABSI had the lowest AUC in women (0.613). The optimal cut-off value for CVAI was 83.7 in men and 70.8 in women. CVAI performed best among various cardiometabolic indices in estimating elevated ASCVD risk. CVAI may be a reliable index for identifying people at increased risk of ASCVD.

This study aimed to evaluate the performance of 11 obesity-related indices, including body mass index (BMI), waist circumference, waist-to-height ratio, waist–hip ratio, a body shape index, abdominal volume index, body adiposity index, body roundness index, conicity index, visceral adiposity index (VAI), and triglyceride glucose (TyG) index, in identifying metabolic syndrome (MetS) in adults. The information of 5000 participants was obtained from the Taiwan Biobank. Logistic regression analyses were performed to determine the associations between MetS and obesity-related indices with odds ratio (ORs). The predictive performance of the indices to identify MetS was compared using receiver operating characteristic (ROC) curves and areas under curves (AUCs). Multivariate-adjusted logistic regression showed that the ORs for MetS increased across the quartiles of each index. ROC curves analysis demonstrated that TyG index had the greatest AUC in men (AUC = 0.850) and women (AUC = 0.890). Furthermore, VAI had the greatest AUC in men (AUC = 0.867) and women (AUC = 0.925) aged 30−50 years, while TyG index had the greatest AUC in men (AUC = 0.849) and women (AUC = 0.854) aged 51−70 years. Among the studied obesity-related indices, TyG index and VAI exhibited the best performance for identifying MetS in adults. TyG index and VAI may be the relevant indices to assess MetS in clinical practice.