Waist Measurements Could Provide Better Diabetes Risk Detection Than BMI

Summary:
A Diabetes Care study involving 598,883 adults across 82 low- and middle-income countries found that waist circumference (WC) and relative fat mass (RFM) were more effective than BMI in identifying diabetes risk among people with intermediate BMI. Diabetes prevalence was 9.1%, with higher risk observed among those in the highest WC and RFM groups. The findings suggest that adding WC or RFM to diabetes screening could improve early risk detection, particularly among individuals whose BMI alone may not indicate elevated metabolic risk. 

Waist circumference (WC) and relative fat mass (RFM) showed greater accuracy than BMI in identifying diabetes risk among adults with intermediate BMI across 82 low- and middle-income countries.

A study published in Diabetes Care reported that waist-related measurements may strengthen diabetes risk evaluation beyond BMI, particularly for adults whose BMI falls within the intermediate range. The researchers examined nationally representative data from 598,883 adults aged 25 years and older across 82 low- and middle-income countries (LMICs), including individuals with BMI values between 18.5 and 29.9 kg/m².

The overall prevalence of diabetes was 9.1%. Participants in the highest quintiles for both WC and RFM had the greatest diabetes risk. Both measures also provided better discrimination of diabetes compared with BMI. Among men, the area under the curve (AUC) was 0.69 for both WC and RFM, compared with 0.64 for BMI. Among women, the respective AUC values were 0.69 for WC, 0.69 for RFM and 0.63 for BMI.

Across different regions and between sexes, RFM generally performed at least as well as WC and, in some cases, showed better performance.

The findings indicate that using BMI as the sole measure may fail to identify some individuals who have elevated metabolic risk despite having BMI values within or close to the conventional range. Adding WC or RFM to diabetes screening approaches could support earlier identification of at-risk individuals and enable more effective allocation of limited healthcare resources in LMICs.