Background: Using soft-tissue composition in conventional regional dual-energy X-ray absorptiometry (DXA) scans of the spine and hip to predict whole body composition (whole-body fat mass, whole-body lean mass and trunk-fat mass) instead of a whole body DXA scan.
Methods: We identified 143 adult patients who underwent DXA evaluation of the whole body. Anthropometric indices were also measured. Datasets were split randomly into two parts; the derivation set including a sample of 100 subjects, and the validation set including a sample of 43 subjects. Multiple regression analysis with the backward stepwise elimination procedure was used for the derivation set and the estimates were then compared with the actual measurements from the whole-body scans for the validation set. The Ra2 (adjusted coefficient of multiple determination) and SSE (error sum of squares) criteria were applied to compare regression models.
Results: Using multiple linear regression analyses, the best equation for predicting whole-body fat mass (Ra2= 0. 945) included gender, height, weight, waist circumference (WC), spine fat fraction and hip fat fraction; the best equation for predicting whole-body lean mass (Ra2 = 0. 970) included gender, weight, WC, spine fat fraction and hip fat fraction; and the best equation for predicting trunk-fat mass (Ra2 = 0. 944) included gender, weight, spine fat fraction and hip fat fraction.
Conclusion: The results of this study show that regional DXA scans of the spine and hip can be used to accurately predict body composition.