Diabetes is a chronic and concerning health condition that poses a significant public health challenge. Given that preventing, detecting early, and treating T2DM can enhance public health outcomes, the objective of this study was to identify the most effective obesity indices and determine their optimal cut-off points for predicting the risk of T2DM in an Iranian population.
This study was conducted on 8,019 male and female participants aged between 35 and 70 years in the context of Shahedieh cohort study. The ROC curve analysis was utilized to determine the optimal cut-off point of each anthropometric index to predict diabetes in age-sex categories.
The overall diabetes incidence in the study population was 2.5%, with 2.5% in men and 2.4% in women. In men, significant differences in most of the anthropometric indices were observed between diabetic individuals and healthy counterparts. This study found that for women 45–65, BMI and weight, and for men under 65 years, weight, WHR, BMI, WC, WHTR, AVI, and BRI are efficient T2DM predictors. The AUC of these indices varied from 0.593 (95% CI: 0.510–0.676) to 0.668 (95% CI: 0.586–0.750) in men, and from 0.587 (95% CI: 0.510–0.664) to 0.644 (95% CI: 0.535–0.754) in women.
Anthropometric indices and body roundness are simple, inexpensive, and noninvasive means markers to predict the risk of diabetes. Our findings show that most of the studied indices had acceptable prediction power for men except for elderly. For women over 45 years old, weight and BMI are appropriate predictors. It seems that the approach of reducing diabetes incidence through early detection and primary prevention is achievable.