Total and regional dual X-ray absorptiometry derived four-compartment model

Background & aims: Dual X-ray absorptiometry (DXA) software allows for total and regional (i.e., arms and legs) assessment of body composition, with recent advancements allowing for DXA derived volume. The use of DXA derived volume allows for the development of a convenient four-compartment model to accurately measure body composition. The purpose of the current study is to evaluate the validity of a regional DXA derived four-compartment model. Methods: A total of 30 males and females underwent one whole body DXA scan, underwater weighing, total and regional bioelectrical impedance spectroscopy, and regional measures of water displacement. Manually created region of interest boxes assessed regional DXA body composition. Linear regression models with fat mass from the DXA as the dependent variable and body volume from water displacement, total body water from bioelectrical impedance spectroscopy, and DXA bone mineral and body mass as independent variables created regional four-compartment models. Measures of fat-free mass and percent fat were calculated using the four-compartment derived fat mass. T-tests assessed DXA derived four-compartment model to the traditional four-compartment model with volume assessed by water displacement. Regression models were cross-validated using the Repeated k-fold Cross Validation method. Results: Arm and leg regional DXA derived four-compartment model for fat mass (p = 0.999, both arm and leg), fat-free mass (p = 0.999, both arm and leg), and percent fat (arm: p = 0.766; leg: p = 0.938) were not significantly different from the regional four-compartment model with regional volume measured via water displacement. Cross-validation of each model produced R² values of 0.669 for the arm and 0.783 for the leg. Conclusions: The DXA can be used to create four-compartment model for estimating total and regional fat mass, fat-free mass, and percent fat. Therefore, these results allow for a convenient regional four-compartment model with DXA derived regional volume.