Bias varies for bioimpedance analysis and skinfold technique when stratifying collegiate male athletes' fat-free mass hydration levels

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

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.

Assessment Methods of Body Fat in Recreational Marathon Runners: Bioelectrical Impedance Analysis versus Skinfold Thickness

The aim of the present study was to examine (a) the relationship of body fat (BF) assessed by bioimpedance analysis (BIA) and skinfold thickness (SKF) and (b) the variation of BF by age depending on the assessment method. Participants were 32 women and 134 men recreational marathon runners, who were tested for BF using both assessment methods (BIA and SKF). Rc between BIA and SKF assessment methods was 0.803 (95% CI; 0.640, 0.897) in women and 0.568 (95% CI; 0.481, 0.644) in men. A large main effect of the assessment method on BF was observed (p < 0.001, η² = 0.156) with SKF presenting higher BF than BIA by 2.9%. The difference between SKF and BIA was 3.9 ± 2.7% (95% confidence intervals, CI; 3.4; 4.3, p < 0.001) in men, whereas no difference was found in women (−0.9 ± 2.9%; 95% CI; -1.9; -0.2, p = 0.101). BF correlated with age with small magnitude (BIA, r = 0.18, p = 0.036; SKF, r = 0.23, p = 0.007) in men, i.e., the older the age, the higher the BF. A similar trend of moderate magnitude was observed in women for BIA (r = 0.45, p = 0.011), but not for SKF (r = 0.33, p = 0.067). In conclusion, practitioners involved in the training of recreational runners would be advised to consider that BIA elicits a lower BF value than the SKF method in men.

Ultrasound Measurements of Subcutaneous Fat Thickness Are Robust Against Hydration Changes

Ultrasound is an appealing tool to assess body composition, combining the portability of a field method with the accuracy of a laboratory method. However, unlike other body composition methods, the effect of hydration status on validity is unknown. This study evaluated the impact of acute hydration changes on ultrasound measurements of subcutaneous fat thickness and estimates of body fat percentage. In a crossover design, 11 adults (27.1 ± 10.5 years) completed dehydration and hyperhydration trials to alter body mass by approximately ±2%. Dehydration was achieved via humid heat (40 °C, 60% relative humidity) with exercise, whereas hyperhydration was via ingestion of lightly salted water. Ultrasound measurements were taken at 11 body sites before and after each treatment. Participants lost 1.56 ± 0.58 kg (-2.0 ± 0.6%) during the dehydration trial and gained 0.90 ± 0.21 kg (1.2 ± 0.2%) during the hyperhydration trial even after urination. The sum of fat thicknesses as measured by ultrasound differed by <0.90 mm across trials (p = .588), and ultrasound estimates of body fat percentage differed by <0.5% body fat. Ultrasound measures of subcutaneous adipose tissue were unaffected by acute changes in hydration status by extents beyond which are rare and overtly self-correcting, suggesting that this method provides reliable and robust body composition results even when subjects are not euhydrated.

Evaluation of fat-free mass hydration in athletes and non-athletes

PURPOSE

To evaluate the hydration of fat-free mass (FFM) in athletes and non-athletes.

METHODS

We analyzed the data of 128 healthy young adults (athletes: 61 men, 36 women; non-athletes: 19 men, 12 women) using the two-component (2C), 3C and 4C models. Under-water weighing or air-displacement plethysmography and deuterium dilution methods were used for estimating body density and total body water, respectively. The bone mineral content (BMC) was determined using whole-body scans by dual-energy X-ray absorptiometry.

RESULTS

There was no significant difference in FFM hydration between the athletes (men, 72.3 ± 1.3%; women, 71.8 ± 1.3%) and non-athletes (men, 72.1 ± 1.2%; women, 72.2% ± 1.0%) in the 3C model. The total mean FFM hydration (72.1% ± 1.3%) was similar to the corresponding value in the literature (~ 73%). The estimation error of the percentage fat by the 2C vs the 4C model was significantly and highly correlated with hydration (r = 0.96), BMC (r = - 0.70), and total body protein (r = - 0.86) in the 4C model FFM.

CONCLUSION

Although FFM hydration was similar in athletes and non-athletes, it would be underestimated or overestimated when the 2C model is used for evaluation, and the biological FFM hydration value deviates from the 73% value inter-individually. Despite that this inter-individual variation in FFM hydration is low in terms of between-individual standard deviation (1.3%), the BMC and total body protein differ greatly in athletes, and when it affects FFM hydration, it may also affect the percentage fat measurement in the 2C model. Thus, FFM hydration would not be affected by FFM, percent body fat, or the athletic status.