Novel anthropometric indices for predicting diabetes mellitus: A population-based study.

Abstract

There is still no complete agreement on the best anthropometric index for identifying type 2 diabetes. This study aims to evaluate the predictive power of the novel indices compared with traditional and to better understand how gender influences this association. Baseline data of the Kharameh cohort study, which includes Iranian adults between 40 and 70 years, were used in this cross-sectional study. Anthropometric indices such as BMI, WHR, WHtR, ABSI, BRI, and BAI were evaluated for identifying type 2 diabetes. Statistical analysis was performed using independent t-tests and logistic regression to examine the association of these indices with diabetes in men and women. ROC curves were calculated to determine the sensitivity and specificity of each index. Fifteen percent of our 10,663 participants had diabetes. Anthropometric indices were significantly higher in the diabetic group than in the non-diabetic group and were significantly associated with an increased risk of type 2 diabetes. WHR performed as the best in predicting diabetes, with an optimal cutoff point of WHR > 0.95 for both sexes. BMI and BAI were the least accurate, with AUCs of less than 60 % for both sexes. The findings underscore the crucial role of body fat distribution, particularly central or abdominal obesity, in predicting diabetes risk. The use of anthropometric indices like WHR could be valuable in identifying individuals at high risk for type 2 diabetes, thereby aiding the development of effective screening and prevention programs.