2254-P: Comparing Seven Adiposity Indexes in Their Ability to Predict Type 2 Diabetes Risk across Five U.S. Cohorts

Introduction and Objective: Understanding an individual’s risk of developing Type 2 Diabetes (T2D) may facilitate timely interventions to prevent or delay its onset. We compared the predictive performance of 7 adiposity indexes for T2D risk across 5 US cohorts with well-characterized T2D incidence. Methods: Data came from 5 cohorts: Southwest US American Indians (n=2627), Blacks (n=2156) and Whites (n=2109) from CARDIA, and Blacks (n=2602) and Whites (n=9512) from ARIC. We calculated adiposity indexes from anthropometric measures. Predictive performance was assessed by the hazard ratio (HR) per SD, by change in area under the receiver operating characteristic curve (ΔAUC), and by net reclassification information (NRI) obtained from Cox models adjusted for age, sex, and BMI. Results: There were 3942 T2D cases in 301K years of follow-up. Figure 1 shows HRs for T2D risk, ΔAUCs and NRIs for all indexes. Across cohorts, the Relative Fat Mass (RFM) had the highest HR, waist-to-hip ratio had the highest increase in AUC while the waist-to-height ratio and the roundness index had the highest NRI. We observed heterogeneity between studies for all predictive performance measures for all indexes. Conclusion: The predictive utility of adiposity indexes for T2D varies significantly across cohorts. Integrating simple adiposity indexes with BMI enhances the predictive accuracy of T2D risk by capturing both central adiposity and body fat distribution across 5 US cohorts.