Abstract
OBJECTIVE: This study evaluates the association between various anthropometric indices and prediabetes prevalence among adults in the United States. METHODS: We conducted a cross-sectional analysis on participants aged ≥20 years using data from the National Health and Nutrition Examination Survey (NHANES) cycles 2021-2023. Weight, height, waist circumference, and hip circumference were used to calculate indices such as BMI, waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), conicity index, abdominal volume index (AVI), body roundness index (BRI), body adiposity index (BAI), and a body shape index (ABSI). Multivariable logistic regression assessed associations between indices and prediabetes risk. Receiver Operating Characteristic (ROC) curve analysis evaluated the discriminatory power of each index. RESULTS: Among 2515 participants, 49.6 % had prediabetes. Higher quartiles of BMI, Waist circumference, WHR, WHtR, CI, AVI, BRI, BAI, and ABSI were significantly associated with increased prediabetes risk (P < 0.05). WHR demonstrated the highest discriminatory power (AUC: 0.695; 95 % CI; 0.674, 0.716), followed by conicity index (AUC; 0.693; 95 % CI; 0.672, 0.714). CONCLUSIONS: Central adiposity measures, particularly WHR and CI, are more effective than BMI in identifying individuals at risk for prediabetes. However, due to the cross-sectional nature of our study, causal relationships between anthropometric indices and prediabetes risk cannot be established.