Comparison of Anthropometric Indices for Predicting the Risk of Metabolic Diseases: Result from Ravansar NonCommunicable Disease (RaNCD) Cohort Study

Abstract Background The effectiveness of anthropometric indices in predicting metabolic diseases is still of debate. This study aimed to compare anthropometric indices for predicting the risk of metabolic diseases. Methods We used the data of 10,047 Iranian adults aged 35 to 65 years participating in the first phase of Ravansar Non-Communicable Disease (RaNCD) cohort study. The investigated metabolic diseases included cardiovascular diseases (CVDs), hypertension, dyslipidemia, and diabetes. Anthropometric indices included body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR), waist-to-hip ratio (WHR), visceral fat area (VFA), body fat mass (BFM), percent body fat (PBF), fat mass index (FMI), a body shape index (ABSI), and body roundness index (BRI). The predictive power of anthropometric indices was evaluated using Receiver Operating Characteristic (ROC) curve analysis. Results The BRI (AUC: 0.76; 95%CI: 0.74–0.78), WHtR (AUC: 0.63; 95%CI: 0.61–0.66), and PBF (AUC: 0.62; 95%CI: 0.59–0.64) indices showed the highest power for predicting CVDs, while WHtR (AUC: 0.65; 95%CI: 0.62–0.68) and BRI (AUC: 0.64; 95%CI: 0.61–0.67) indices were most effective for predicting diabetes. In men, BRI (AUC: 0.64, 95%CI: 0.61–0.66) and WHtR (AUC: 0.63, 95%CI: 0.61–0.65) indices had the highest power for predicting hypertension, while in women, BMI, WHtR, and VFA (AUC ≥ 0.60) indices were most effective for predicting hypertension. Additionally, BMI, BFM, FMI, VFA, and WHR indices had the highest power for predicting dyslipidemia (AUC ≥ 0.63). Conclusion Increasing anthropometric indices, especially BRI, WHtR, VFA, and BFM, can be used as independent predictors for metabolic diseases.