Comparison of Methods to Assess Body Composition Changes during a Period of Weight Loss


  • The costs of publication of this article were defrayed, in part, by the payment of page charges. This article must, therefore, be hereby marked “advertisement” in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

6400 Perkins Road, Baton Rouge, LA 70810. E-mail:


Objective: To assess the accuracy of body composition measurements by air displacement plethysmography and bioelectrical impedance analysis (BIA) compared with DXA during weight loss.

Research Methods and Procedures: Fifty-six healthy but overweight participants, 34 women and 22 men (age, 52 ± 8.6 years; weight, 92.2 ± 11.6 kg; BMI, 33.3 ± 2.9 kg/m2) were studied in an outpatient setting before and after 6 months of weight loss (weight loss, 5.6 ± 5.5 kg). Subjects were excluded if they had initiated a new drug therapy within 30 days of randomization, were in a weight loss program, or took a weight loss drug within 90 days of randomization. Subjects were randomly assigned either to a self-help program, consisting of two 20-minute sessions with a nutritionist and provision of printed materials and other self-help resources, or to attendance at meetings of a commercial program (Weight Watchers). Body composition was examined by each of the methods before and after weight loss.

Results: BIA (42.4 ± 5.8%) underestimated percentage fat, whereas the BodPod (Siri = 51.7 ± 6.9%; Brozek = 48.5 ± 6.5%) overestimated percentage fat compared with DXA (46.1 ± 7.9%) before weight loss. Correlation coefficients for detecting changes in body composition between DXA and the other methods were relatively high, with Brozek Δfat mass (FM; r2 = 0.63), Siri FM (r2 = 0.65), tetrapolar BIA percentage fat (r2 = 0.57), and Tanita FM (r2 = 0.61) being the highest.

Discussion: In conclusion, all of the methods were relatively accurate for assessing body composition compared with DXA, although there were biases. Furthermore, each of the methods was sensitive enough to detect changes with weight loss.