Determining body composition using different bioimpedance technologies: Is an agreement possible?
Year: 2025
Type: article
Study design: Observational Study
Abstract: BACKGROUND AND AIMS: Disagreement between bioelectrical impedance analysis (BIA) technologies in measuring resistance (R), reactance (Xc), and phase angle (PhA) is well documented and mainly due to device-specific features. Whether such a variability translates into differences in body composition estimates remains uncertain. This study evaluated agreement in fat-free mass (FFM) estimates from different BIA technologies against dual-energy X-ray absorptiometry (DXA), while accounting for the role of predictive equations. Additionally, agreement of BIA-based fat mass (FM), indirectly calculated from FFM, was assessed. METHODS: ) participated in this study. Whole-body foot-to-hand and direct segmental BIA at 50 kHz measured R, Xc, and PhA. DXA served as the reference. Predictive equations for FFM were developed by stepwise regression in two-thirds of the sample and validated in the remaining third. Agreement was evaluated between BIA technologies and against DXA using Bland-Altman and Lin's concordance correlation coefficient. RESULTS: Foot-to-hand BIA yielded lower R (p < 0.001) but higher Xc and PhA (p < 0.001) than direct segmental BIA. Despite these differences, no significant bias (p > 0.05) was observed in FFM estimation across devices. Concordance analyses indicated high agreement without systematic deviations. FM derived from FFM agreed with DXA at a group level but showed systematic trends at the individual level. CONCLUSIONS: Although raw bioelectrical parameters differ between technologies, FFM estimates can be comparable when equations are derived within the same population and reference method. However, FM indirectly obtained from FFM lacks accuracy at the individual level.
Source: Clinical Nutrition
Authors: Francesco Campa, A. Sampieri, G. Cerullo, L. Zoffoli, G. Coratella, Antonio Paoli
Institutions: University of Padua, University of Milan
Language: English
Subfield: Physiology
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $3,320
OpenAlex ID: W4415829186