{"title":"[Bioimpedance analysis of body composition and rest energy expenditure in highly trained cross-country skiers].","authors":"E A Bushmanova, A Yu Lyudinina","doi":"10.33029/0042-8833-2024-93-3-23-30","DOIUrl":null,"url":null,"abstract":"<p><p>The body composition monitoring using bioimpedance analysis (BIA) is important in assessing the functional state of athletes in sports. Based on changes of body composition, it is possible to optimize the actual dietary intake, as well as successfully organize the training process. <b>The purpose</b> of this research was to conduct a comparative assessment of BIA parameters and rest energy expenditure (REE) in highly trained cross-country skiers and young non-athletes. <b>Material and methods</b>. The members of the national cross-country skiing team from the Komi Republic and Russian Federation (n=30; age - 22.3±2.7 years) were examined. Practically healthy medical students served as a control group for the present study (n=40; age - 20.2±2.4 years). The participants successively passed the following study steps: assessment of the body composition by BIA (ACCUNIQ BC380), REE determination by indirect non-fasting calorimetry and calculation technique. <b>Results</b>. The parameters of total body water, fat-free mass, lean tissue and body cell mass were higher in contrast to the fat mass percentage in the athletes (р<0.001). The calculated REE was lower than measured REE among all the participants. At the same time, the REE calculated by the Ketch-McArdle formula significantly differed between the groups, while no differences were found between the REE calculated by the Harris-Benedict prediction equation. The measured REE were significantly higher by 16% (p<0.001) i n athletes compared to those in the control group. <b>Conclusion</b>. The body composition of athletes was distinguished by a significantly higher amounts of total body water, fat-free mass, skeletal muscle, active cell mass, and lower percentage of fat mass compared to healthy untrained individuals. The results obtained among athletes coincided with the idea that the magnitude of REE is determined by the mass of metabolically active tissues and to a lesser extent depends on the fat mass. BIA results can be used to monitor athletes' body composition during the training process.</p>","PeriodicalId":23652,"journal":{"name":"Voprosy pitaniia","volume":"93 3","pages":"23-30"},"PeriodicalIF":0.0000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Voprosy pitaniia","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.33029/0042-8833-2024-93-3-23-30","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/4/22 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0
Abstract
The body composition monitoring using bioimpedance analysis (BIA) is important in assessing the functional state of athletes in sports. Based on changes of body composition, it is possible to optimize the actual dietary intake, as well as successfully organize the training process. The purpose of this research was to conduct a comparative assessment of BIA parameters and rest energy expenditure (REE) in highly trained cross-country skiers and young non-athletes. Material and methods. The members of the national cross-country skiing team from the Komi Republic and Russian Federation (n=30; age - 22.3±2.7 years) were examined. Practically healthy medical students served as a control group for the present study (n=40; age - 20.2±2.4 years). The participants successively passed the following study steps: assessment of the body composition by BIA (ACCUNIQ BC380), REE determination by indirect non-fasting calorimetry and calculation technique. Results. The parameters of total body water, fat-free mass, lean tissue and body cell mass were higher in contrast to the fat mass percentage in the athletes (р<0.001). The calculated REE was lower than measured REE among all the participants. At the same time, the REE calculated by the Ketch-McArdle formula significantly differed between the groups, while no differences were found between the REE calculated by the Harris-Benedict prediction equation. The measured REE were significantly higher by 16% (p<0.001) i n athletes compared to those in the control group. Conclusion. The body composition of athletes was distinguished by a significantly higher amounts of total body water, fat-free mass, skeletal muscle, active cell mass, and lower percentage of fat mass compared to healthy untrained individuals. The results obtained among athletes coincided with the idea that the magnitude of REE is determined by the mass of metabolically active tissues and to a lesser extent depends on the fat mass. BIA results can be used to monitor athletes' body composition during the training process.