Abstract
Background: Bioelectrical Impedance Analysis (BIA) is a fast, practical, non-invasive, and frequently used method for fat-free mass (FFM) estimation. The aims of this study were to validate predictive equations of BIA to FFM estimation in Army cadets and to develop and validate a specific BIA equation for this population. Methods: A total of 396 males, Brazilian Army cadets, aged 17–24 years were included. The study used eight published predictive BIA equations, a specific equation in FFM estimation, and dual-energy X-ray absorptiometry (DXA) as a reference method. Student’s t-test (for paired sample), linear regression analysis, and Bland–Altman method were used to test the validity of the BIA equations. Results: Predictive BIA equations showed significant differences in FFM compared to DXA (p < 0.05) and large limits of agreement by Bland–Altman. Predictive BIA equations explained 68% to 88% of FFM variance. Specific BIA equations showed no significant differences in FFM, compared to DXA values. Conclusion: Published BIA predictive equations showed poor accuracy in this sample. The specific BIA equations, developed in this study, demonstrated validity for this sample, although should be used with caution in samples with a large range of FFM.
Highlights
Adequate assessment of body composition is very important for the identification of possible health risks related to the excess or lack of different body components
No significant differences were found between development and cross-validation groups
Several authors reported strong correlation between fat-free mass (FFM) estimated by Bioelectrical Impedance Analysis (BIA) and dual-energy X-ray absorptiometry (DXA) [19,31,32], and as observed in our study (Figure 1), they found great individual variability confirmed by large limits of agreement [32]
Summary
Adequate assessment of body composition is very important for the identification of possible health risks related to the excess or lack of different body components It helps in monitoring the processes of growth and aging and of some diseases, providing important evaluation data of nutritional interventions and physical exercise programs [1,2]. FFM is comprised mostly by muscle mass and is related to the prevention of the fall risk in the elderly, as well as having significant influence on physical performance [5] The evaluation of this body component can contribute to the development, monitoring, and improvement of physical training programs [6], as well as in the reduction of body fat [7]. Results: Predictive BIA equations showed significant differences in FFM compared to DXA (p < 0.05) and large limits of agreement by Bland–Altman
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