BMI does not accurately predict overweight in Asian Indians in northern India

Abstract

Asian Indians are at high risk for the development of atherosclerosis and related complications, possibly initiated by higher body fat (BF). The present study attempted to establish appropriate cut-off levels of the BMI for defining overweight, considering percentage BF in healthy Asian Indians in northern India as the standard. A total of 123 healthy volunteers (eighty-six males aged 18--75 years and thirty-seven females aged 20--69 years) participated in the study. Clinical examination and anthropometric measurements were performed, and percentage BF was calculated. BMI for males was 21.4 (sd 3.7) kg/m(2) and for females was 23.3 (sd 5.5) kg/m(2). Percentage BF was 21.3 (sd 7.6) in males and 35.4 (sd 5.0) in females. A comparison of BF data among Caucasians, Blacks, Polynesians and Asian ethnic groups (e.g. immigrant Chinese) revealed conspicuous differences. Receiver operating characteristic (ROC) curve analysis showed a low sensitivity and negative predictive value of the conventional cut-off value of the BMI (25 kg/m(2)) in identifying subjects with overweight as compared to the cut-off value based on percentage BF (males >25, females >30). This observation is particularly obvious in females, resulting in substantial misclassification. Based on the ROC curve, a lower cut-off value of the BMI (21.5 kg/m(2) for males and 19.0 kg/m(2) for females) displayed the optimal sensitivity and specificity, and less misclassification in identification of subjects with high percentage BF. Furthermore, a novel obesity variable, BF:BMI, was tested and should prove useful for interethnic comparison of body composition. In the northern Indian population, the conventional cut-off level of the BMI underestimates overweight and obesity when percentage BF is used as the standard to define overweight. These preliminary findings, if confirmed in a larger number of subjects and with the use of instruments having a higher accuracy of BF assessment, would be crucial for planning and the prevention and treatment of various obesity-related metabolic diseases in the Asian Indian population.