Diego A Bonilla1,2,3,4, Lidia G De León5, Pedro Alexander-Cortez6, Adrián Odriozola-Martínez4, Carlos A Herrera-Amante7, Salvador Vargas-Molina8, Jorge L Petro1,3. 1. Research Division, DBSS International, Colombia. 2. Research Group in Biochemistry and Molecular Biology, Universidad Distrital Francisco José de Caldas, Colombia. 3. Research Group in Physical Activity, Sports and Health Sciences (GICAFS), Universidad de Córdoba, Colombia. 4. kDNA Genomics®, 200145University of the Basque Country UPV/EHU, Spain. 5. Facultad de Ciencias de la Cultura Física, 27763Universidad Autónoma de Chihuahua, México. 6. 341925Universidad Nacional Experimental Politécnica, Venezuela. 7. Division of Health Sciences, 539174University of Guadalajara, México. 8. EADE-University of Wales Trinity Saint David, Spain.
Abstract
BACKGROUND: Kinanthropometry offers to exercise and health professionals a standardized procedure of acquiring surface anatomical measurements that might be used to track changes in body composition. AIM: To describe simple anthropometric indices to monitor body composition changes in amateur and elite athletes, and to provide reference values during the competition phase. METHODS: A search of articles indexed in PubMed/MEDLINE, ScienceDirect, Cochrane, and SciELO databases using the string body composition AND (anthropometric OR skinfolds OR circumferences OR girth OR estimation equation) AND "body fat". Inclusion criteria were: quantitative and/or qualitative research published between 2009 and 2020, written in English or Spanish, reporting simple anthropometric indices that included skinfolds, girths, or basic measures in amateur and elite athletes. RESULTS: A total of 51 studies (Price's index = 66.4%) met all the inclusion criteria and were included in this scoping review. Contrary to the frequent practice, the use of a regression equation might not be accurate to evaluate body composition. To avoid this, anthropometrists should base their analysis on the absolute values of the sum of skinfolds (∑S) and related variables, such as skinfold-corrected girths and lean mass index. While not definitive, because further research is required, the practical recommendations and updated reference values in competition phase provided by this review would contribute to the accurate identification of body composition changes. CONCLUSIONS: ∑S and lean mass index have been shown to be valid for monitoring changes in fat mass and fat-free mass, respectively. More research is needed to derive the lean mass index-specific coefficient for each sports population.
BACKGROUND: Kinanthropometry offers to exercise and health professionals a standardized procedure of acquiring surface anatomical measurements that might be used to track changes in body composition. AIM: To describe simple anthropometric indices to monitor body composition changes in amateur and elite athletes, and to provide reference values during the competition phase. METHODS: A search of articles indexed in PubMed/MEDLINE, ScienceDirect, Cochrane, and SciELO databases using the string body composition AND (anthropometric OR skinfolds OR circumferences OR girth OR estimation equation) AND "body fat". Inclusion criteria were: quantitative and/or qualitative research published between 2009 and 2020, written in English or Spanish, reporting simple anthropometric indices that included skinfolds, girths, or basic measures in amateur and elite athletes. RESULTS: A total of 51 studies (Price's index = 66.4%) met all the inclusion criteria and were included in this scoping review. Contrary to the frequent practice, the use of a regression equation might not be accurate to evaluate body composition. To avoid this, anthropometrists should base their analysis on the absolute values of the sum of skinfolds (∑S) and related variables, such as skinfold-corrected girths and lean mass index. While not definitive, because further research is required, the practical recommendations and updated reference values in competition phase provided by this review would contribute to the accurate identification of body composition changes. CONCLUSIONS: ∑S and lean mass index have been shown to be valid for monitoring changes in fat mass and fat-free mass, respectively. More research is needed to derive the lean mass index-specific coefficient for each sports population.
Authors: Diego A Bonilla; Luis A Cardozo; Jorge M Vélez-Gutiérrez; Adrián Arévalo-Rodríguez; Salvador Vargas-Molina; Jeffrey R Stout; Richard B Kreider; Jorge L Petro Journal: Int J Environ Res Public Health Date: 2022-10-05 Impact factor: 4.614
Authors: Diego A Bonilla; Leidy T Duque-Zuluaga; Laura P Muñoz-Urrego; Katherine Franco-Hoyos; Alejandra Agudelo-Martínez; Maximiliano Kammerer-López; Jorge L Petro; Richard B Kreider Journal: Nutrients Date: 2022-09-29 Impact factor: 6.706
Authors: Diego A Bonilla; Leidy T Duque-Zuluaga; Laura P Muñoz-Urrego; Yurany Moreno; Jorge M Vélez-Gutiérrez; Katherine Franco-Hoyos; Alejandra Agudelo-Martínez; Gustavo Humeres; Richard B Kreider; Jorge L Petro Journal: Int J Environ Res Public Health Date: 2022-08-27 Impact factor: 4.614