A Multi-Dimensional Empirical Study on the Relationship Between Obesity and Metabolic Syndrome in Asian Populations

Abstract

The epidemiological characteristics of metabolic syndrome (MetS) in the Asian population are unique, especially the significant association between lean obesity and visceral fat accumulation. However, existing studies have insufficient quantitative analysis of key predictive indicators and lack simplified screening models for the Asian population. This study was based on the data of 295 Asian adults and used a binary logistic regression model to analyze the association between indicators such as Body Mass Index (BMI), waist circumference, blood lipid, and blood glucose and MetS. The significance of each variable and the predictive performance of the model were evaluated through two model constructions (full variables and optimized variables). The preliminary model shows that BMI, Albuminuria, Blood Glucose, and Triglycerides have significant positive effects on MetS (OR values are 1.227, 3.811, 1.015, and 1.008, respectively, p<0.05). High-Density Lipoprotein (HDL) had a negative effect (OR=0.913, p<0.01). After eliminating non-significant variables in the optimized model, the goodness of fit was significantly improved (Nagelkerke R²=0.629), and the prediction accuracy reached 88.14%. BMI, albuminuria, blood glucose, and triglycerides are the core predictive indicators of MetS in the Asian population, and HDL has a protective effect. The optimized model provides an efficient tool for clinical screening. It is recommended to pay attention to high-risk groups with a normal BMI but excessive visceral fat.