Association of Anthropometric Indices with Type 2 Diabetes Prevalence: Evidence from the Rural Fasa Cohort

Mohammad Reza  Astaneh; Susan  Darroudi; Mohammad Ebrahim  Astaneh; Narges  Fereydouni

doi:10.18502/ijdl.v25i6.20883

Mohammad Reza Astaneh Student Research Committee, Fasa University of Medical Sciences, Fasa, Iran
Susan Darroudi Department of Medical and Surgical Sciences for Children and Adults. University of Modena and Reggio Emilia, Via del Pozzo 71, 41124 Modena, Modena, Italia
Mohammad Ebrahim Astaneh Department of Anatomical Sciences, School of Medicine, Fasa University of Medical Sciences, Fasa, Iran
Narges Fereydouni Noncommunicable Diseases Research Center, Fasa University of Medical Sciences, Fasa, Iran

DOI: https://doi.org/10.18502/ijdl.v25i6.20883

Keywords: Type 2 Diabetes, Anthropometric Indices, Central Obesity, Visceral Adiposity, Predictive Performance, ROC Curve Analysis

Abstract

Background: Type 2 diabetes is rapidly increasing, particularly in the Middle East where central obesity is a major contributor to disease burden. Identifying high-risk individuals requires indices that assess visceral adiposity more effectively than body mass index (BMI). This study compared nine anthropometric indices in relation to diabetes and determined their predictive capacity and optimal cut-off values.

Methods: This cross-sectional analysis included 10,103 adults aged 35–70 years from the FASA cohort. Diabetes was defined as fasting glucose ≥126 mg/dL or antidiabetic medication use. Measurements included BMI, waist circumference (WC), hip circumference (HC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), body roundness index (BRI), body adiposity index (BAI), a body shape index (ABSI), abdominal volume index (AVI), and weight- adjusted waist index (WWI). Associations were examined using logistic regression (crude and adjusted models). Discriminatory accuracy was assessed using receiver operating characteristic (ROC) curves, area under the curve (AUC), and Youden's index.

Results: Individuals with diabetes exhibited higher values across anthropometric indices (p< 0.05). In adjusted models, WC, WHR, WHtR, AVI, and WWI remained significant predictors (p< 0.05). WHR demonstrated the highest AUC (0.651, p< 0.001). Optimal cut-off values with high sensitivity and specificity included WHR= 0.91, WHtR= 0.53, and BRI= 4.1.

Conclusion: Central obesity indices—particularly WHR, WHtR, and BRI—demonstrated superior discriminatory capacity for diabetes and support the use of simple waist-based indices for early screening