Novel anthropometric indices for predicting type 2 diabetes mellitus

Area of Science:

• Endocrinology and Metabolism
• Public Health
• Biostatistics

Background:

• Type 2 diabetes mellitus (T2DM) poses a significant global health challenge.
• First-degree relatives (FDRs) of diabetic patients have an elevated risk of developing T2DM.
• Identifying reliable anthropometric indices for early T2DM prediction in high-risk populations is crucial.

Purpose of the Study:

• To evaluate and compare the efficacy of various anthropometric indices in predicting T2DM.
• To identify optimal cutoff points for these indices in predicting T2DM among Iranian FDRs of diabetic patients.
• To determine which anthropometric measures are most accurate for T2DM risk stratification in this population.

Main Methods:

• Retrospective analysis of data from 2082 FDRs of diabetic patients.
• Logistic regression modeling to assess the association between anthropometric indices and T2DM.
• Receiver operating characteristic (ROC) curve analysis to determine optimal cutoff points and compare index performance using Area Under the Curve (AUC).

Main Results:

• The overall prevalence of T2DM among the studied FDRs was 15.3%.
• Waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), and body roundness index (BRI) demonstrated fair and comparable predictive performance (AUC values) for T2DM in both sexes.
• Body mass index (BMI) and body adiposity index (BAI) showed the lowest predictive accuracy among all assessed indices for both men and women.

Conclusions:

• WHtR, BRI, VAI, and WHR are superior anthropometric indices for predicting T2DM in FDRs of diabetic patients compared to BMI and BAI.
• These indices offer a valuable, non-invasive tool for T2DM risk assessment in clinical settings.
• Further validation studies in diverse populations are recommended to support the widespread clinical adoption of these predictive indices.