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.

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 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 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, and calculating Sensitivity, Specificity, and Accuracy.

RESULTS

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

CONCLUSIONS

Both WC and BMI are good predictors of risk for T2DM, but BMI 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 in IDRS improves its performance on Accuracy and Specificity.