Evaluation of Novel and Traditional Anthropometric Indices for Predicting Metabolic Syndrome and Its Components: A Cross-Sectional Study of the Nepali Adult Population

Background Various anthropometric indices have been proposed to assess central obesity and predict metabolic syndrome (MetS). However, their predictive capabilities for MetS have not been evaluated in the Nepali adult population. This study aimed to compare the predictive potential of 12 anthropometric indices for MetS and its components among Nepali adults. Methods Baseline data were collected from 1116 adult residents (424 females, 792 males) of Gandaki Province, Nepal aged between 30–86 years. Twelve anthropometric indices viz. Body Mass Index (BMI), Waist-Hip Ratio (WHR), Waist-Height Ratio (WHtR), Weight-Adjusted-Waist Index (WWI) A Body Shape Index (ABSI), Abdominal Volume Index (AVI), Body Adiposity Index (BAI), Body Roundness Index (BRI), Clinica Universidad de Navarra-Body Adiposity Estimator (CUN-BAE), Conicity Index (CI), Lipid Accumulation Product (LAP), Visceral Adiposity Index (VAI) were calculated. MetS was defined using modified National Cholesterol Education Program (NCEP) Adult Treatment Panel III (NCEP-ATP III) criteria. Receiver operating characteristic curve analysis was carried out to determine the predictive ability (AUCs, optimal cut-offs, Youden indices, sensitivities, and specificities) of these indices for MetS and its components. AUC differences between various index pairs were also calculated. Results VAI demonstrated the best performance in predicting MetS (AUC: 0.866 for females, 0.882 for males), followed by LAP (AUC: 0.839 for females, 0.869 for males). WHR showed good performance (AUC: 0.749 for females, 0.722 for males). WHtR and BRI performed similarly (AUCs: 0.687–0.697). Optimal cutoffs were as follows: VAI > 1.97 (females), > 2.16 (males); LAP > 53.4 (both sexes); WHR > 0.98 (both sexes); WHtR > 0.638 (females), > 0.56 (males); BRI > 5.76 (females), > 4.75 (males). ABSI and BAI exhibited the poorest diagnostic performance for MetS prediction in both sexes (AUC < 0.530). Conclusion Among Nepali adults, VAI and LAP outperformed traditional measures such as BMI, WHR and WHtR in predicting MetS and its components. These findings contribute to developing population-specific screening strategies for MetS in Nepal, potentially enhancing early detection and prevention of cardiometabolic disorders.