A body mass index (BMI) of 30 kg/m2 may not be the best way to define obesity in postmenopausal women, new research shows.

“Using that cutoff point could result in misclassification,” Hailey Banack of the University at Buffalo, The State University of New York, told Reuters Health in a telephone interview. “You are going to be missing out on women who are truly obese because you are misclassifying them as not obese.”

Given the changes in body composition that occur with aging in women, several investigators have questioned whether a BMI cutoff of 30 kg/m2 is the best way to determine older people’s obesity status, Dr Banak and her team note.

She and her colleagues compared BMI-defined obesity in relation to adiposity in 1,329 postmenopausal women participating in the Buffalo OsteoPerio Study, all of whom had dual-energy x-ray absorptiometry (DXA). Their findings were published online November 15 in Menopause.

According to BMI cutoffs, 35% were overweight and 21% were obese. Mean adiposity was 22.7% for underweight women, 32.6% for normal-weight women, and 38.5% and 43.4%, respectively, for overweight and obese women.

Using BMI >30 kg/m2 to define obesity, 35% body fat had 32.4% sensitivity and 99.3% specificity for obesity; 38% body fat had 44.6% sensitivity and 97.1% specificity; and 40% body fat had 55.2% sensitivity and 94.6% specificity.

The optimal BMI cutoff using 35% body fat to define obesity was 24.85 kg/m2, while it was 26.49 kg/m2 using 38% body fat and 27.05 kg/m2 for 40% body fat.

“This research shows we should potentially be looking at lowering the BMI cutpoint to define obesity in postmenopausal women,” Dr. Banack said. In the meantime, she added, physicians should be cautious when using the 30 kg/m2 cutoff in clinical decision making or to assess risk in postmenopausal women.

Next steps include investigating whether the findings apply to older men as well, Dr Banack said. “We need to do a better job of understanding the relationship between BMI and body fat and how these relate ultimately to disease risk.”