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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, NUTRITION
The Journal of Sports Medicine and Physical Fitness 2016 November;56(11):1331-8
Insights into body composition adaptation: should we reconsider the use of Body Mass Index in some sports?
Tijana DURMIĆ 1, 2, Marina DJELIĆ 2, 3, Jelena SUZIĆ LAZIĆ 4, Biljana LAZOVIĆ POPOVIĆ 5, Milica DEKLEVA 2, 6, Ivan SOLDATOVIC 7, Sanja MAZIĆ 2, 3 ✉
1 Institute of Forensic Medicine, Belgrade, Serbia; 2 School of Medicine, University of Belgrade, Belgrade, Serbia; 3 Institute of Medical Physiology, Belgrade, Serbia; 4 University Clinical Center “Dr Dragisa Misovic-Dedinje”, Belgrade, Serbia; 5 University Clinical Center “Zemun”, Belgrade, Serbia; 6 University Clinical Center “Zvezdara”, Belgrade, Serbia; 7 Institute of Medical Statistics, Belgrade, Serbia
BACKGROUND: The purposes of this study were to indentify the under/overweight/obese frequencies by Body Mass Index (BMI) and body fat percentage (BF%) in athletes within groups of sport and to investigate the accuracy of the BMI as a measure of BF%.
METHODS: Cross-sectional design study on elite male athletes (N.=2234, aged 22±4 years) from 51 sports disciplines who were classified according to two different sport classifications: predominant characteristic of training (four group model) and type and intensity of exercise (nine group model). All athletes underwent full anthropometric testing.
RESULTS: After stratification, the majority of athletes were in normal weight category. According to 4 group model, BMI is showed as statistically significant, reliable and independent predictor of BF% in all groups of sports. In nine groups model all correlated parameters were positive for athletes being statistically significant (P<0.001) with exception of group LSMD, MSMD and HSMD (P>0.05). The highest positive correlation between BMI and BF% was in group MSLD (r=0.53; P<0.001) and in power sports group (r=0.24; P<0.001).
CONCLUSIONS: BMI could be an accurate predictor of BF% in athletes but that depends on group of sport. Our results suggest the BMI could use only in power and MSLD groups of sport.