A composite of BMI and waist circumference may be a better obesity metric in Indians with high risk for type 2 diabetes: An analysis of NMB-2017, a nationwide cross-sectional study

Abstract

Aims: Obesity measurement is a vital component of most type 2 diabetes screening tests; while studies had shown that waist circumference (WC) is a better predictor in South Asians, there is evidence that BMI is also effective. Our objective was to evaluate the efficacy of BMI_WC, a composite measure, against BMI and WC.

Methods: Using data from a nationwide randomized cluster sample survey (NMB-2017), we analyzed 7496 adults at high risk for type 2 diabetes. WC, BMI, and BMI_WC were evaluated using Odds Ratio (OR), and Classification scores (Sensitivity, Specificity, and Accuracy). These were validated using Indian Diabetes Risk Score (IDRS) by replacing WC with BMI and BMI_WC, and calculating Sensitivity, Specificity, and Accuracy.

Results: BMI_WC had higher OR (2·300) compared to WC (1·87) and BMI (2·26). WC, BMI, and BMI_WC were all highly Sensitive (0·75, 0·81, 0·70 resp.). But BMI_WC had significantly higher Specificity (0.36) when compared to WC and BMI (0.27 each). IDRS_WC, IDRS_BMI, and IDRS_BMIWC were all highly Sensitive (0·87, 0·88, 0·82 resp.). But IDRS_BMIWC had significantly higher Specificity (0·39) compared to IDRS_WC and IDRS_BMI (0·30, 0·31 resp.).

Conclusions: Both WC and BMI are good predictors of risk for T2DM, but BMI_WC is a better predictor, with higher Specificity; this may indicate that Indians with high values of both central (high WC) and general (BMI > 23) obesity carry higher risk for type 2 diabetes than either one in isolation. Using BMI_WC in IDRS improves its performance on Accuracy and Specificity.

Keywords: Anthropometric; BMI; Central fat; Obesity; Type 2 diabetes.