Measurements of body composition by dual-energy X-ray absorptiometry improve prediction of energy expenditure.

Abstract

The prediction of energy expenditure by dual-energy X-ray absorptiometry (DXA) and bioimpedance analysis (BIA) was assessed in 35 healthy individuals of both sexes, with a mean body mass index (BMI) of 23.8 kg/m2 (range 18-33.8), and mean age of 30 years (22-40). Energy expenditure (EE) was measured under standard conditions in a respiration chamber, the total and regional body composition by DXA, and total body composition by BIA. When body composition was measured by BIA, 88.5% of the variation in 24-h EE was explained by lean body mass (LBM); this figure was increased by DXA, where total lean tissue mass (LTM) and total fat tissue mass (FTM) could account for 91.5% of the variation. Also, the prediction of resting energy expenditure (REE) was improved by DXA, from 88.1% to 89.8% (LBM vs. LTM, FTM). Measurements of regional body composition showed that trunk LTM was significantly superior as a predictor, especially of REE and sleeping EE (EE sleep), compared to the peripheral LTM; thus, the predictions of REE were 83% vs. 87% (peripheral vs. trunk), respectively; and the predictions of EE sleep were 83% vs. 89% (peripheral vs. trunk), respectively. Therefore, body composition measurements by DXA improved the prediction of EE. Trunk LTM was a superior predictor, especially of REE and EE sleep, compared to peripheral LTM. In conclusion, the present results suggest that measuring total and regional body composition by DXA can somewhat improve the prediction of EE.