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Body Composition of Elite Female Players in Five Different Sports Games
The goal of this study was to identify and compare body composition (BC) variables in elite female athletes (age ± years): volleyball (27.4 ± 4.1), softball (23.6 ± 4.9), basketball (25.9 ± 4.2), soccer (23.2 ± 4.2) and handball (24.0 ± 3.5) players. Fat-free mass (FFM), fat mass, percentage of fat...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Akademia Wychowania Fizycznego w Katowicach
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4415834/ https://www.ncbi.nlm.nih.gov/pubmed/25964823 http://dx.doi.org/10.1515/hukin-2015-0021 |
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author | Mala, Lucia Maly, Tomas Zahalka, František Bunc, Vaclav Kaplan, Ales Jebavy, Radim Tuma, Martin |
author_facet | Mala, Lucia Maly, Tomas Zahalka, František Bunc, Vaclav Kaplan, Ales Jebavy, Radim Tuma, Martin |
author_sort | Mala, Lucia |
collection | PubMed |
description | The goal of this study was to identify and compare body composition (BC) variables in elite female athletes (age ± years): volleyball (27.4 ± 4.1), softball (23.6 ± 4.9), basketball (25.9 ± 4.2), soccer (23.2 ± 4.2) and handball (24.0 ± 3.5) players. Fat-free mass (FFM), fat mass, percentage of fat mass (FMP), body cell mass (BCM), extracellular mass (ECM), their ratio, the percentage of BCM in FFM, the phase angle (α), and total body water, with a distinction between extracellular (ECW) and intracellular water, were measured using bioimpedance analysis. MANOVA showed significant differences in BC variables for athletes in different sports (F60.256 = 2.93, p < 0.01, η2 = 0.407). The results did not indicate any significant differences in FMP or α among the tested groups (p > 0.05). Significant changes in other BC variables were found in analyses when sport was used as an independent variable. Soccer players exhibited the most distinct BC, differing from players of other sports in 8 out of 10 variables. In contrast, the athletes with the most similar BC were volleyball and basketball players, who did not differ in any of the compared variables. Discriminant analysis revealed two significant functions (p < 0.01). The first discriminant function primarily represented differences based on the FFM proportion (volleyball, basketball vs. softball, soccer). The second discriminant function represented differences based on the ECW proportion (softball vs. soccer). Although all of the members of the studied groups competed at elite professional levels, significant differences in the selected BC variables were found. The results of the present study may serve as normative values for comparison or target values for training purposes. |
format | Online Article Text |
id | pubmed-4415834 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Akademia Wychowania Fizycznego w Katowicach |
record_format | MEDLINE/PubMed |
spelling | pubmed-44158342015-05-11 Body Composition of Elite Female Players in Five Different Sports Games Mala, Lucia Maly, Tomas Zahalka, František Bunc, Vaclav Kaplan, Ales Jebavy, Radim Tuma, Martin J Hum Kinet Research Article The goal of this study was to identify and compare body composition (BC) variables in elite female athletes (age ± years): volleyball (27.4 ± 4.1), softball (23.6 ± 4.9), basketball (25.9 ± 4.2), soccer (23.2 ± 4.2) and handball (24.0 ± 3.5) players. Fat-free mass (FFM), fat mass, percentage of fat mass (FMP), body cell mass (BCM), extracellular mass (ECM), their ratio, the percentage of BCM in FFM, the phase angle (α), and total body water, with a distinction between extracellular (ECW) and intracellular water, were measured using bioimpedance analysis. MANOVA showed significant differences in BC variables for athletes in different sports (F60.256 = 2.93, p < 0.01, η2 = 0.407). The results did not indicate any significant differences in FMP or α among the tested groups (p > 0.05). Significant changes in other BC variables were found in analyses when sport was used as an independent variable. Soccer players exhibited the most distinct BC, differing from players of other sports in 8 out of 10 variables. In contrast, the athletes with the most similar BC were volleyball and basketball players, who did not differ in any of the compared variables. Discriminant analysis revealed two significant functions (p < 0.01). The first discriminant function primarily represented differences based on the FFM proportion (volleyball, basketball vs. softball, soccer). The second discriminant function represented differences based on the ECW proportion (softball vs. soccer). Although all of the members of the studied groups competed at elite professional levels, significant differences in the selected BC variables were found. The results of the present study may serve as normative values for comparison or target values for training purposes. Akademia Wychowania Fizycznego w Katowicach 2015-04-07 /pmc/articles/PMC4415834/ /pubmed/25964823 http://dx.doi.org/10.1515/hukin-2015-0021 Text en © Editorial Committee of Journal of Human Kinetics This article is an open-access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/). |
spellingShingle | Research Article Mala, Lucia Maly, Tomas Zahalka, František Bunc, Vaclav Kaplan, Ales Jebavy, Radim Tuma, Martin Body Composition of Elite Female Players in Five Different Sports Games |
title | Body Composition of Elite Female Players in Five Different Sports Games |
title_full | Body Composition of Elite Female Players in Five Different Sports Games |
title_fullStr | Body Composition of Elite Female Players in Five Different Sports Games |
title_full_unstemmed | Body Composition of Elite Female Players in Five Different Sports Games |
title_short | Body Composition of Elite Female Players in Five Different Sports Games |
title_sort | body composition of elite female players in five different sports games |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4415834/ https://www.ncbi.nlm.nih.gov/pubmed/25964823 http://dx.doi.org/10.1515/hukin-2015-0021 |
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