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Comparison of generalized and athletic bioimpedance-based predictive equations for estimating fat-free mass in resistance-trained exercisers.
- Source :
-
Nutrition (Burbank, Los Angeles County, Calif.) [Nutrition] 2022 Oct; Vol. 102, pp. 111694. Date of Electronic Publication: 2022 Apr 22. - Publication Year :
- 2022
-
Abstract
- Objectives: This study aimed to test whether athlete-specific, bioelectrical, impedance-based equations to estimate fat-free mass (FFM) could be more accurate than generalized equations when testing resistance-trained exercisers.<br />Methods: A total of 50 resistance-trained men (age 30.9 ± 7.4 y; body mass index: 25.3 ± 2.2 kg/m <superscript>2</superscript> ) and 20 men from the general population (age 29.9 ± 9.1 y; body mass index: 22.8 ± 2.4 kg/m <superscript>2</superscript> ) underwent bioelectrical impedance and dual-energy x-ray absorptiometry (DXA) evaluations. FFM was derived by one bioelectrical impedance-based equation specific for athletes and three generalized equations, all developed with foot-to-hand bioimpedance technologies at a 50 kHz frequency. DXA was the reference method for the FFM assessment.<br />Results: Compared with DXA, when assessing the resistance-trained participants, the athletic-specific equation had neither mean (-0.89 kg; P = 0.789) or proportional bias (r = -0.104; P = 0.474) with a coefficient of determination equal to R <superscript>2</superscript>  = 0.91. In contrast, the three generalized predictive equations overestimated FFM (range, 4.11-5.37 kg; P < 0.05) with R <superscript>2</superscript> ranging from 0.84 to 0.90. The athletic-specific equation underestimated FFM in the general population participants (-2.93 kg; P < 0.05).<br />Conclusions: When assessing body composition in resistance-trained exercisers, specific equations for athletes should be preferred to generalized ones to avoid an overestimation in FFM. Furthermore, athlete-specific and generalized formulas cannot be used interchangeably, even when assessing body composition in the general population.<br /> (Copyright © 2022 Elsevier Inc. All rights reserved.)
Details
- Language :
- English
- ISSN :
- 1873-1244
- Volume :
- 102
- Database :
- MEDLINE
- Journal :
- Nutrition (Burbank, Los Angeles County, Calif.)
- Publication Type :
- Academic Journal
- Accession number :
- 35810579
- Full Text :
- https://doi.org/10.1016/j.nut.2022.111694