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      Anthropometric prediction of DXA-measured body composition in female team handball players

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          Abstract

          Background

          The relevance of body composition (BC) to performance in sport has long been appreciated with special concern on the total and regional proportion of fat and muscle. Dual-energy X-ray absorptiometry (DXA) is able to accurately measure BC, but it may not be easily available in practice; anthropometry has long been used as a simple and inexpensive field method to objectively assess BC. The aim of this study was twofold: first, to develop and validate a sport-specific anthropometric predictive equation for total body fat mass (FM) and lean mass components in female handball players to be used in the sport setting; second, to cross-validate in female team handball players several independently developed, predictive equations for BC in female athletes.

          Methods

          A total of 85 female team handball players (30 wings, 31 backs, 14 pivots, 10 goalkeepers) of different competitive levels underwent anthropometry and a whole-body DXA scan. Multiple linear regression analysis was used to develop predictive equations in a derivation sample ( n = 60) of randomly selected players using demographic and anthropometric variables. The developed equations were used to predict DXA outcomes in an independent validation sample ( n = 25).

          Results

          Statistically significant ( P < 0.001) models were developed for total body FM (adjusted R 2 = 0.943, standard error of the estimate, SEE = 1,379 g), percentage FM (adjusted R 2 = 0.877, SEE = 2.00%), fat-free soft tissue mass (FFSTM) (adjusted R 2 = 0.834, SEE = 2,412 g), fat-free mass (FFSTM + bone mineral content; adjusted R 2 = 0.829, SEE = 2,579 g). All models were robust to collinearity. Each developed equation was successfully validated in the remaining 25 players using correlation analysis, mean signed difference, t-test, and Bland–Altman plot. The whole dataset of team handball players ( n = 85) was used to cross-validate several predictive equations independently developed by others in female athletes. Equations significantly ( P < 0.001 for all; t-test) over- or underestimated the corresponding DXA measurements.

          Discussion

          It is concluded that in team female handball players the anthropometric equations presented herein are able to estimate body fat and FFSTM with accuracy. Several BC predictive anthropometric equations developed in different female athletic populations revealed inaccurate when tested in team handball players. These results should be of use for coaches, physical trainers, and nutritionists when evaluating the physical status of female team handball players.

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          Most cited references37

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          Current status of body composition assessment in sport: review and position statement on behalf of the ad hoc research working group on body composition health and performance, under the auspices of the I.O.C. Medical Commission.

          Quantifying human body composition has played an important role in monitoring all athlete performance and training regimens, but especially so in gravitational, weight class and aesthetic sports wherein the tissue composition of the body profoundly affects performance or adjudication. Over the past century, a myriad of techniques and equations have been proposed, but all have some inherent problems, whether in measurement methodology or in the assumptions they make. To date, there is no universally applicable criterion or 'gold standard' methodology for body composition assessment. Having considered issues of accuracy, repeatability and utility, the multi-component model might be employed as a performance or selection criterion, provided the selected model accounts for variability in the density of fat-free mass in its computation. However, when profiling change in interventions, single methods whose raw data are surrogates for body composition (with the notable exception of the body mass index) remain useful.
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            Reference Values for Body Composition and Anthropometric Measurements in Athletes

            Background Despite the importance of body composition in athletes, reference sex- and sport-specific body composition data are lacking. We aim to develop reference values for body composition and anthropometric measurements in athletes. Methods Body weight and height were measured in 898 athletes (264 female, 634 male), anthropometric variables were assessed in 798 athletes (240 female and 558 male), and in 481 athletes (142 female and 339 male) with dual-energy X-ray absorptiometry (DXA). A total of 21 different sports were represented. Reference percentiles (5th, 25th, 50th, 75th, and 95th) were calculated for each measured value, stratified by sex and sport. Because sample sizes within a sport were often very low for some outcomes, the percentiles were estimated using a parametric, empirical Bayesian framework that allowed sharing information across sports. Results We derived sex- and sport-specific reference percentiles for the following DXA outcomes: total (whole body scan) and regional (subtotal, trunk, and appendicular) bone mineral content, bone mineral density, absolute and percentage fat mass, fat-free mass, and lean soft tissue. Additionally, we derived reference percentiles for height-normalized indexes by dividing fat mass, fat-free mass, and appendicular lean soft tissue by height squared. We also derived sex- and sport-specific reference percentiles for the following anthropometry outcomes: weight, height, body mass index, sum of skinfold thicknesses (7 skinfolds, appendicular skinfolds, trunk skinfolds, arm skinfolds, and leg skinfolds), circumferences (hip, arm, midthigh, calf, and abdominal circumferences), and muscle circumferences (arm, thigh, and calf muscle circumferences). Conclusions These reference percentiles will be a helpful tool for sports professionals, in both clinical and field settings, for body composition assessment in athletes.
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              A note on studentizing a test for heteroscedasticity

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                Author and article information

                Contributors
                Journal
                PeerJ
                PeerJ
                PeerJ
                PeerJ
                PeerJ
                PeerJ Inc. (San Diego, USA )
                2167-8359
                27 November 2018
                2018
                : 6
                : e5913
                Affiliations
                Laboratory of Anthropometry and Body Composition, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona , Verona, Italy
                Author information
                http://orcid.org/0000-0003-1117-296X
                http://orcid.org/0000-0002-8011-4379
                Article
                5913
                10.7717/peerj.5913
                6266933
                30515356
                ada23d30-4e86-4e20-86e1-1d996604d70e
                © 2018 Cavedon et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.

                History
                : 1 June 2018
                : 10 October 2018
                Funding
                The authors received no funding for this work.
                Categories
                Global Health
                Kinesiology
                Public Health

                handball players,anthropometry,fat mass,skeletal muscle,skinfolds,predictive equation

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