Comparison of segmental body composition estimated by bioelectrical impedance analysis and dual-energy X-ray absorptiometry. (December 2018) - Wingo, Brooks C.; Barry, Valene Garr; Ellis, Amy C.; Gower, Barbara A.
Summary: Background & aims: Segmental body composition may be an important indicator of health and nutritional status in conditions where variations in fat and lean mass are frequently isolated to a particular body segment (e.g. paralysis, sarcopenia). Until recently, segment-specific body composition could only be assessed using invasive and expensive methods such as dual-energy x-ray absorptiometry (DXA), magnetic resonance imaging (MRI), or computed tomography (CT). Bioelectrical impedance analysis (BIA) may be a rapid, inexpensive alternative for assessing segmental composition, but it has not been fully validated for this purpose. The purpose of this study was to compare segmental estimates of lean and fat mass using BIA versus a criterion standard of DXA. Methods: A cross-sectional pilot study was conducted in n = 30 healthy adults. Outcome measures included total mass, fat mass and lean mass of arm, leg and trunk. Pearson correlation coefficients ( r ) and paired-samples t-tests ( t ) were used to assess relationships between each outcome as measured by BIA and DXA. Results: Although the methods were strongly correlated for all measures, (r > .87 for all segments) BIA routinely overestimated lean mass for arm and trunk (mean difference arm: 0.97 kg, p = .008; trunk: 5.58 kg, p < .0001); and underestimated fat mass for arm and leg (mean difference arm: 0.42 kg, p < .0001; leg: 1.94 kg p < .0001). BIA overestimated total body lean mass in 93% of participants and underestimated total body fat mass in 90% of participants. Conclusions: Significant discrepancies were noted between DXA and BIA in all body segments. Further research is needed to refine BIA methods for segmental composition estimates in heterogeneous samples and disease-specific populations before this methods can be used reliably in a clinical setting.