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Bioelectrical impedance analysis (BIA) and anthropometry are considered alternatives to well-established reference techniques for assessing body composition. In team sports, the percentage of fat mass (FM%) is one of the most informative parameters, and a wide range of predictive equations allow for its estimation through both BIA and anthropometry. Although it is not clear which of these two techniques is more accurate for estimating FM%, the choice of the predictive equation could be a determining factor. The present study aimed to examine the validity of BIA and anthropometry in estimating FM% with different predictive equations, using dual X-ray absorptiometry (DXA) as a reference, in a group of futsal players. A total of 67 high-level male futsal players (age 23.7 ± 5.4 years) underwent BIA, anthropometric measurements, and DXA scanning. Four generalized, four athletic, and two sport-specific predictive equations were used for estimating FM% from raw bioelectric and anthropometric parameters. DXA-derived FM% was used as a reference. BIA-based generalized equations overestimated FM% (ranging from 1.13 to 2.69%, p < 0.05), whereas anthropometry-based generalized equations underestimated FM% in the futsal players (ranging from −1.72 to −2.04%, p < 0.05). Compared to DXA, no mean bias (p > 0.05) was observed using the athletic and sport-specific equations. Sport-specific equations allowed for more accurate and precise FM% estimations than did athletic predictive equations, with no trend (ranging from r = −0.217 to 0.235, p > 0.05). Regardless of the instrument, the choice of the equation determines the validity in FM% prediction. In conclusion, BIA and anthropometry can be used interchangeably, allowing for valid FM% estimations, provided that athletic and sport-specific equations are applied.

This study aimed to (i) characterise the body composition of professional and semi-professional male futsal players, (ii) assess the validity of commonly used equations to estimate FM%, (iii) develop and cross-validate a futsal-specific FM% prediction equation. In a cross-sectional design, 78 adult male futsal players were assessed for body mass, stature, skinfolds, and girths as per the International Society for the Advancement of Kinanthropometry protocol and completed a dual-energy X-ray absorptiometry (DXA) scan for reference body composition data. Using paired-sample t-tests, the FM% from the DXA and nine published equations were compared. New sport-specific models were developed by stepwise multiple regression. Existing equations were cross-validated using the least squares regression, concordance correlation coefficient, and the Bland−Altman analyses. New equations were further cross-validated using the PRESS approach. None of the existing equations accurately predicted the DXA-derived FM% (p < 0.001; R2 ≤ 0.76, SEE ≥ 1.59; CCC ≤ 0.83; bias = −8.2% to −1.3%, limited agreement, and varying trends). The novel Bettery® equation: −0.620 + (0.159 ∗ Σ4SKF [triceps, abdominal, iliac crest, and front thigh (mm)]) + (0.120 ∗ waist girth (cm)), demonstrated a high accuracy (R2 = 0.85, SEE = 1.32%), a moderate strength of agreement (CCC = 0.92), no bias (0.2%), good agreement (±2.5%), and no trend (r = −0.157; p = 0.170) against the DXA. The Bettery® equation is the first to allow for a valid and sport-specific assessment of FM% in male futsal players.

β-hydroxy-β-methylbutyrate (HMB) is a leucine metabolite that is purported to increase fat-free mass (FFM) gain and performance in response to resistance exercise training (RET). The aim of this systematic review and meta-analysis was to determine the efficacy of HMB supplementation in augmenting FFM and strength gains during RET in young adults. Outcomes investigated were: total body mass (TBM), FFM, fat mass (FM), total single repetition maximum (1RM), bench press (BP) 1RM, and lower body (LwB) 1RM. Databases consulted were: Medical Literature Analysis and Retrieval System Online (Medline), Excerpta Medica database (Embase), The Cumulative Index to Nursing and Allied Health Literature (CINAHL), and SportDiscus. Fourteen studies fit the inclusion criteria; however, 11 were analyzed after data extraction and funnel plot analysis exclusion. A total of 302 participants (18-45 y) were included in body mass and composition analysis, and 248 were included in the strength analysis. A significant effect was found on TBM. However, there were no significant effects for FFM, FM, or strength outcomes. We conclude that HMB produces a small effect on TBM gain, but this effect does not translate into significantly greater increases in FFM, strength or decreases in FM during periods of RET. Our findings do not support the use of HMB aiming at improvement of body composition or strength with RET.