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Updated: May 21, 2025
Author Spotlight: Advancements in 3D Optical Imaging for Comprehensive Body Composition Assessment in Modern Research
Published on: June 7, 2024
Novel comparative analysis and equation development for body volume estimation using dual-energy x-ray absorptiometry
Tiago R Silva1,2, Filipe Jesus2, Rui Poínhos1
1Faculty of Nutrition and Food Sciences, University of Porto, Rua do Campo Alegre, no 823, 4150-180, Porto, Portugal.
Background/Objectives:
Dual-energy x-ray absorptiometry (DXA) has been suggested as an alternative method for estimating body volume (BV), a component of the reference four-compartment body composition model. This study reports the development and validation of DXA-BVSilva, a novel DXA-derived BV equation. An additional aim was to develop an estimate of lean soft tissue density (DLST), a key variable in the theory-based approach, by estimating total body protein with a six-compartment model.
Methods:
A sample of 332 athletes (36.7% females) from several sports were randomly assigned to either the development (n = 232) or cross-validation group (n = 100). DXA-BVSilva was developed via linear regression of DXA-measured fat, lean soft tissue, and bone mineral mass against BV measured with air displacement plethysmography (ADP). A DLST estimate of 1.064 kg/L (SD = 0.006) was obtained from a subset of the development sample comprising 201 athletes (36.3% females) with available measurements of total-body water by deuterium dilution, bone mineral by DXA and BV by ADP, enabling total-body protein determination from a six-compartment model.
Results:
DXA-BVSilva provided the closest BV estimation (mean difference = 0.05 L, SD = 0.46 L; ES [95% CI] = 0.11 [-0.08; 0.31]) and the 95% limits of agreement (-0.86 to 0.96 L) were narrower than existing empirical equations.
Conclusion:
We conducted the first comparative analysis of both empirical and theoretical BV estimation methods using DXA, demonstrating the validity of DXA-BVSilva for BV estimation in athletes, presenting a robust alternative to ADP, with potential applications in multicomponent body composition models.
