Prediction of Metabolic Syndrome Related Disease by Anthropo-metric Obesity Indices: Analysis of the 2023 KNHANES

Purpose: This study aimed to Purpose: This study aimed to systematically compare and analyze the predictive power of traditional anthropometric obesity indices BMI (body mass index) and WC (waist circumference) and adjusted indices ABSI (a body shape index and BRI (body roundness index) for metabolic syndrome-related diseases, including hypertension, dia-betes, hypercholesterolemia, and hypertriglyceridemia, in Korean adults. Methods: Data were obtained from the 2023 Korea National Health and Nutrition Examination Survey (KNHANES), and a total of 5,906 adults aged 19 years or older (2,573 men and 3,333 women) were included in the final analysis. All analyses were conducted using Python 3.11. Descriptive sta-tistics, receiver operating characteristic (ROC) curve analysis, decision curve analysis (DCA), and net reclassification im-provement (NRI) were applied to evaluate predictive performance. Results: ROC analysis demonstrated that BMI and WC consistently showed stable and high predictive power, while BRI exhibited a similar level of performance. In contrast, ABSI presented limited predictive ability across all diseases. Furthermore, DCA and NRI analyses indicated that, under certain con-ditions, BRI and ABSI provided superior predictive performance compared to traditional indices. Conclusions: This study reaffirms the clinical utility of traditional obesity indices such as BMI and WC while highlighting the complementary potential of BRI and ABSI. These findings suggest the necessity of incorporating multiple obesity indices, alongside lifestyle and meta-bolic factors, to achieve more precise risk prediction and early detection of metabolic syndrome.