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THE JOURNAL OF SPORTS MEDICINE AND PHYSICAL FITNESS
A Journal on Applied Physiology, Biomechanics, Preventive Medicine,
Sports Medicine and Traumatology, Sports Psychology
Indexed/Abstracted in: Chemical Abstracts, CINAHL, Current Contents/Clinical Medicine, EMBASE, PubMed/MEDLINE, Science Citation Index Expanded (SciSearch), Scopus
Impact Factor 1,111
Original articles BODY COMPOSITION, SPORT NUTRITION AND SUPPLEMENTATION (ERGOGENICS)
The Journal of Sports Medicine and Physical Fitness 2009 September;49(3):278-84
Correlation between body mass index and body composition in elite athletes
Garrido-Chamorro R. P. 1,2, Sirvent-Belando J. E. 3,4, Gonzalez-Lorenzo M. 5, Martin-Carratala M. L. 3, Roche E. 6 ✉
1 Department of Clinical Medicine, University Miguel Hernández, Alicante, Spain
2 Emergency Unit, General Hospital of Alicante, Alicante, Spain
3 Department of Analytical Chemistry, Nutrition and Bromatology University of Alicante, Alicante, Spain
4 Service for Sportmen Support, Centro de Tecnificación,Alicante, Spain
5 Critical Care Unit, General Hospital of Alicante, Alicante, Spain
6 Department of Applied Biology-Nutrition, University Miguel Hernandez, Alicante, Spain
AIM: The body mass index (BMI) of an athlete is directly related to his/her weight, however, whether this parameter is actually related to specific anthropometric compartments is still in debate. The aim of this study was to determine the correlation between BMI and fat, muscle and bone percentages.
METHODS: To this end, body anthropometric parameters were determined in 3971 athletes according to International Society for Advancement of Kinanthropometry (ISAK) provided equations. Pearson’s correlation coefficient was calculated to analyze the relation between BMI and the different anthropometric values. Intraclass correlation coefficient was calculated to validate if BMI is an adequate parameter to measure body composition.
RESULTS: The average values found in the different anthropometric parameters, with the exception of bone mass percentage, increased in association with the BMI. However, this positive increase, or decrease in the case of bone mass, is only maintained up to a certain BMI value that differs depending on the parameter analyzed. Athletes that present normal BMI values (18.5-25 kg/m2 up until 27 kg/m2), as well as in several cases where the athletes presented higher values (30-33 kg/m2), displayed positive increases for fat percentage, but not for muscle and bone. Pearson’s coefficient indicates that BMI has a high correlation with fat content, but not muscle percentage, in athletes.
CONCLUSIONS: As seen in the training programs, the data showed that well-trained athletes tend to display optimal muscle contents, being the fat content the only parameter that could influence BMI. However, intraclass correlation coefficient shows that BMI cannot be used as a direct measurement of body fat content in athletes.