HealthDay News — Using BMI to diagnose obesity substantially underestimates the burden of disease when compared with dual-energy X-ray absorptiometry (DXA) scan, a direct simultaneous measure of body fat, muscle mass and bone density, study data indicate.
Among a sample of 1,393 adults with both BMI and DXA derived percent body fat data available for comparison, 39% were misclassified as non-obese based on BMI, despite meeting percent body fat obesity criteria.
“Our results demonstrate the prevalence of false-negative BMIs, increased misclassifications in women of advancing age and the reliability of gender-specific revised BMI cut-offs,” Nirav R. Shah, MD, of New York University School of Medicine and Eric. R. Braverman, MD, of Weill-Cornell Medical College, both in New York City, reported in PLoS One.
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They performed a retrospective chart review of 9,088 patients who had outpatient visits at a multispecialty private practice from 1998 to 2009, and analyzed data for the 1,393 patients with data available for BMI, DXA, and fasting leptin and insulin levels. Patients had an average BMI of 27.3% kg/m2 (SD=5.9) and an average percent body fat of 31.3% (SD=9.3). Mean patient age was 51.4 years; 63% were women and 75% were white.
BMI characterized 26% of the subjects as obese, while DXA indicated that 64% of them were obese, the researchers found. BMI misclassified more women as nonobese (49%), whereas men were more frequently misclassified as obese (25%), when percent body fat indicated otherwise.
An analysis of the 539 patients who were misclassified using BMI revealed that advancing age was clearly correlated with misclassification among women, with 49% of those aged 50 to 59 years and 59% of those aged 70 years and older misclassified. There was no association between advancing age and obesity misclassification in men.
These differences may be explained by the fact that women lose more muscle mass with age, and BMI may not accurately measure muscle mass in men.
Clinicians should consider revising BMI obesity cut-points to increase diagnostic sensitivity and maximize the prevention of obesity-related co-morbidities, the researchers urged.
For women, adjusting the BMI cut-point for obesity to 24 instead of 30 would increase the test’s sensivity from 35% to 79%, while decreasing specificity only 13%, the researchers determined. Similarly, setting the BMI cut-point at 28 for men instead of 30 would increase sensitivity from 51% to 72% with only a 12% loss of specificity.
“The current systematic underestimation of adiposity in large scale studies, and subsequent use of such studies for public health policy-making, can readily be corrected, resulting in a more appropriate sense of urgency and more cogent weighing of public health priorities,” the researchers wrote.
A strong relationship was also identified between increased leptin levels and increased body fat. Further study is need to determine the potential for leptin as a marker for managing obesity in the future.
The researchers acknowledged several study limitations, including it’s cross sectional design, lack of racial and ethnic diversity and inability to compare other anthropometric indices, such as waist-to-hip ratio with corresponding DXA measurements, due to lack of hip circumference data.
The study was funded by the PATH Foundation, which has received financial support from the Life Extension Foundation. The researchers disclosed financial ties to the pharmaceutical and medical industries.
Shah NR, Braverman ER. PLoS ONE. 2012;7(4): e33308.doi:10.1371/journal.pone.0033308.
