Methods over Materials: The Need for Sport-Specific Equations to Accurately Predict Fat Mass Using Bioimpedance Analysis or Anthropometry

Abstract

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.

Keywords: BIA; body composition; body fat; futsal; predictive equations; skinfolds.

Figure 1

Mean and individual values for the percentage of fat mass (FM%) obtained from Dual X-ray Absorptiometry (DXA) and the selected equations; the upper and lower limits represent the standard deviation of the data. BIA = bioelectrical impedance analysis; Eq. 1 = Lukaski and Bolonchuk [21]; Eq. 2 = Sun et al. [22]; Eq. 3 = Durnin and Womersley [23]; Eq. 4 = Lean et al. [24]; Eq. 5 = Matias et al. [25]; Eq. 6 = Stewart et al. [26]; Eq. 7 = Evans et al. [27]; Eq. 8 = Witers et al. [28]; Eq. 9 = Matias et al. [29]; Eq. 10 = Giro et al. [30]. The dotted line identifies the mean value obtained with DXA; * = significant difference from DXA.

Figure 2

Results from regression, concordance, and agreement analyses between the percentage of fat mass (FM%) estimated from the selected BIA-based predictive equations and the reference method (DXA) in the futsal players. In the upper panel, the scatterplots show the relationship between the estimated and the reference FM% and the Lin’s concordance correlation coefficient (CCC), including precision (ρ) and accuracy (C_b) indexes. In the lower panel, the results of Bland–Altman analyses are shown. Eq. 1 = Lukaski and Bolonchuk [21]; Eq. 2 = Sun et al. [22]; Eq. 3 = Matias et al. [25]; Eq. 4 = Stewart et al. [26]; Eq. 5 = Matias et al. [29].

Figure 3

Results from regression, concordance, and agreement analyses between the percentage of fat mass (FM%) estimated from the selected anthropometry-based predictive equations and the reference method (DXA) in the futsal players. In the upper panel, the scatterplots show the relationship between the estimated and the reference FM% and the Lin’s concordance correlation coefficient (CCC), including precision (ρ) and accuracy (C_b) indexes. In the lower panel, the results of the Bland–Altman analyses are shown. Eq. 1 = Durnin and Womersley [23]; Eq. 2 = Lean et al. [24]; Eq. 3 = Evans et al. [27]; Eq. 4; Witers et al. [28]; Eq. 5 = Giro et al. [30].