The failure of some obese subjects to lose weight while eating a diet they report as low in calories is due to an energy intake substantially higher than reported and an overestimation of physical activity, not to an abnormality in thermogenesis.

Dual-photon absorptiometry (DPA) allows separation of body mass into bone mineral, fat, and fat-free soft tissue. This report evaluates the potential of DPA to isolate appendages of human subjects and to quantify extremity skeletal muscle mass (limb fat-free soft tissue). The method was evaluated in 34 healthy adults who underwent DPA study, anthropometry of the limbs, and estimation of whole-body skeletal muscle by models based on total body potassium (TBK) and nitrogen (TBN) and on fat-free body mass (FFM). DPA appendicular skeletal muscle (22.0 +/- 3.1 kg, mean +/- SD) represented 38.7% of FFM, with similar proportions in males and females. There were strong correlations (all p less than 0.001) between limb muscle mass estimated by DPA and anthropometric limb muscle areas (r = 0.82-0.92), TBK (r = 0.94), and total-body muscle mass based on TBK-FFM (r = 0.82) and TBK-TBN (r = 0.82) models. Appendicular skeletal muscle mass estimated by DPA is thus a potentially practical and accurate method of quantifying human skeletal muscle mass in vivo.

The purposes of this study were to determine whether there are significant differences between two- and four-compartment model estimates of body composition, whether these differences are associated with aqueous and mineral fractions of the fat-free mass (FFM); and whether the differences are retained in equations for predicting body composition from anthropometry and bioelectric resistance. Body composition was estimated in 98 men and women aged 65-94 y by using a four-compartment model based on hydrodensitometry, 3H2O dilution, and dual-photon absorptiometry. These estimates were significantly different from those obtained by using Siri's two-compartment model. The differences were associated significantly (P less than 0.0001) with variation in the aqueous fraction of FFM. Equations for predicting body composition from anthropometry and resistance, when calibrated against two-compartment model estimates, retained these systematic errors. Equations predicting body composition in elderly people should be calibrated against estimates from multicompartment models that consider variability in FFM composition.