Estimation Of Skeletal Muscle Tissue In Athletes Using Dual X Ray Absorptiometry, Anthropometry, And Bioelectrical Impedance

Abstract

Anthropometry and Bioelectrical Impedance Analysis (BIA) are the most used procedures to assess musculoskeletal tissue (MST) and body composition in athletes; however, the evidence exhibits significant diferences when compared against reference methods or even in intra-analytical analyses. PURPOSE: To analyze the correlations and differences found in the MST determined by Dual X-Ray Absorptiometry (DXA), Anthropometry, and BIA in a sample of Mexican triathletes. METHODS: Amateur triathletes (n = 30; 20 males, 10 females), aged 18-40, were included. Estimations were performed by using DXA Hologic QDR, BIA BodyStat 1500, and the anthropometric evaluation as defined by the International Society for the Advancement of Kinanthropometry (ISAK) by an ISAK level 3 anthropometrist. The equation used as a reference to derive MST from appendicular lean soft tissue (ALST) measured with DXA, was compared with the results obtained from the Janssen formula for BIA, and the Heymsfield and Kerr formulas accepted for anthropometric data. RESULTS: The bivariate correlation showed significant associations between the variables expressed in kg and percentage (DXA vs Janssen: r = .967, r = .838; DXA vs Heymsfield: r = .973, r = .867; DXA vs Kerr: r = .967, r = .824, respectively). Significant differences (p < 0.001) were found when compared the mean between DXA vs Kerr in terms of kg and percentage (25.41 kg ± 5.89 vs 33.00 kg ± 6.82; and 36.66% ± 4.04 vs 47.75% ± 3.57, respectively). In a post-hoc analysis, heterogeneous results of means were identified with all the formulas used. CONCLUSIONS: The Heymsfield and Janssen equations can be used in people with similar features to the study population, showing reliable results when compared with the reference method. Kerr's formula overestimated the MST values. Whether an estimation using any of the proposed equations, it is always recommended to use the same in subsequent evaluations. Studies with larger samples are necessary to prove if the results can be replicated.