Anthropometric Predictors of Type 2 Diabetes Among White and Black Adults Dale S. Hardy, PhD, RD, Devita T. Stallings, PhD, RN, Jane T. Garvin, PhD, RN, Francine C. Gachupin, PhD, Hongyan Xu, PhD, Susan B. Racette, PhDDale S. Hardy, PhD, RD, CDE, Devita T. Stallings, PhD, RN, Jane T. Garvin, PhD, RN, Francine C. Gachupin, PhD, Hongyan Xu, PhD, Susan B. Racette, PhD OBJECTIVES To determine the best anthropometric measures for discrimination of type 2 diabetes (T2DM) among White and Black males and females: (1) a body shape index (ABSI) (2) body adiposity index (BAI) (3) body mass index (BMI) (4) waist circumference (WC) (5) waist to height ratio (WHtR) (6) waist to hip ratio (WHR) To identify Youden index cut-points for each anthropometric measure. BACKGROUND Blacks are 1.7 times as likely to develop diabetes as Whites. 1 Because T2DM is an obesity-related disease, anthropometric measures are recommended for assessing increase risk of T2DM. BMI provides an estimate of general obesity but does not distinguish between fat and muscle mass. 2 Research indicates that WC, WHR, and WHtR are better discriminators of T2DM risk than BMI. 3,4 WC, a measure of central obesity shown to increase the risk of T2DM in various populations, has varied cut-off values depending on race and gender. 2,3 BAI has been used primarily with Mexicans and African Americans. 5 ABSI and BAI discrimination for T2DM is unknown in Whites and Blacks and further research is needed. 5,6 METHODS Data Sources: Atherosclerosis Risk in Communities study data from dbGaP from Study Population: 11,256 Whites and 3,986 Blacks aged years Outcome Variable: T2DM Predictor Variables: (1) ABSI: WC (m)/((BMI kg/m 2 ) 0.66 /height (m) 0.5 ) (2) BAI: Hip circumference (cm)/((height (m) 1.5 )-18) (3) BMI: body weight (kg)/height (m 2 ) (4) WC (cm) (5) WHtR: WC (cm)/height (cm) (6) WHR: WC (cm)/hip circumference (cm) Covariates: Age, physical activity, family history of T2DM Youden Index: To identify the critical threshold for anthropometric measures to distinguish between individuals with and without T2DM in our sample Best Fit Model: Lowest Akaike Information Criteria (AIC) and highest Receiver Operator Characteristic Concordance-Statistic (ROC C-Statistic) Data Analysis: Logistic regression using Stata, Version 13 (StataCorp, College Station, TX) BMI, WC, WHtR, and WHR were comparable discriminators of T2DM among White and Black males. WC, WHtR, and WHR were comparable discriminators of T2DM among White females. WHR was the best discriminator of T2DM among Black females. ABSI was the poorest discriminator of T2DM of all anthropometric measures across race- gender groups except for Black females. In general, Blacks had lower Youden index cut-points for anthropometric measures than their White counterparts. DISCUSSION/CONCLUSIONS No one anthropometric measure was best for all race-gender groups. We did not take into consideration if individuals were pre-diabetic having blood glucose values above normal and below diabetic levels. T2DM is a metabolic condition that develops over time and is associated with higher anthropometric values. The cut-points identified in this sample are not meant to identify the earliest onset of T2DM but to distinguished between individuals with and without diabetes in our sample. Future research should aim to identify race-gender specific cut-points for each anthropometric measure for T2DM risk. REFERENCES 1.Centers for Disease Control and Prevention (CDC). Numbers (in millions) of civilian, noninstitutionalized persons with diagnosed diabetes, United States, Lee CM, Huxley RR, Wildman RP, Woodward M. Indices of abdominal obesity are better discriminators of cardiovascular risk factors than BMI: A meta-analysis. J Clin Epidemiol. 2008;61(7): Huxley R, James WP, Barzi F, et al. Ethnic comparisons of the cross-sectional relationships between measures of body size with diabetes and hypertension. Obes Rev. 2008;9 Suppl 1: Ashwell M, Gunn P, Gibson S. Waist-to-height ratio is a better screening tool than waist circumference and BMI for adult cardiometabolic risk factors: Systematic review and meta- analysis. Obes Rev. 2012;13(3): Bergman RN. A better index of body adiposity. Obesity (Silver Spring). 2012;20(6): Krakauer NY, Krakauer JC: A new body shape index predicts mortality hazard independently of body mass index. PLoS One. 7:e39504, RESULTS Contact information: Dale Hardy, PhD,