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BODY MASS INDEX AND BODY FAT CONTENT IN ELITE ATHLETES

Jelena Popadić Gaćeša ,
Jelena Popadić Gaćeša

Department of Physiology, Faculty of Medicine, University of Novi Sad , Novi Sad , Serbia

Otto Barak ,
Otto Barak

Department of Physiology, Faculty of Medicine, University of Novi Sad , Novi Sad , Serbia

Dae Karaba Jakovljevic ,
Dae Karaba Jakovljevic

Department of Physiology, Faculty of Medicine, University of Novi Sad , Novi Sad , Serbia

Aleksandar Klašnja ,
Aleksandar Klašnja

Department of Physiology, Faculty of Medicine, University of Novi Sad , Novi Sad , Serbia

Vladimir Galiċ ,
Vladimir Galiċ

Department of Physiology, Faculty of Medicine, University of Novi Sad , Novi Sad , Serbia

Miodrag Drapšin ,
Miodrag Drapšin

Department of Physiology, Faculty of Medicine, University of Novi Sad , Novi Sad , Serbia

Damir Lukač ,
Damir Lukač

Department of Physiology, Faculty of Medicine, University of Novi Sad , Novi Sad , Serbia

Nikola Grujić
Nikola Grujić

Department of Physiology, Faculty of Medicine, University of Novi Sad , Novi Sad , Serbia

Published: 02.12.2011.

Volume 3, Issue 2 (2011)

pp. 43-48;

https://doi.org/10.31382/EQOL201102065P

Abstract

The aim of this study was to evaluate body fat content (BF) of elite athletes obtained by two different field methods for body composition measurements and to compare it with body mass index (BMI) values. The research was conducted on 40 male athletes (20 runners and 20 handball players) and 30 non athletes. BF was calculated from the skinfold values (BFsft) and estimated using a hand-held impedance analyzer (BFbia%). Body mass index, waist to hip ratio (WHR) and waist to stature ratio (WSR) were calculated from adequate anthropometric values. Comparing the BF content between non athletes and two different sport groups, significant difference was found in all parameters between runners and non athletes (p < 0.05). Significant difference was found between BF values of runners and handball players (p < 0.05). Runners have had significantly lower BF, estimated by both methods. They also have had significantly lower WHR and WSR (p < 0.05). In the group of athletes and non athletes with BMI higher than 25 kg/m 2 , or lower than 20 kg/m 2 , comparing with others, no significant difference was found in BFsft and WHR. BMI is not a good predictor of BF, because it does not provide specific information about body fatness, but rather body heaviness. Bioimpedance and anthropometry methods could be used to monitor non obese subjects in clinical routine and population based studies. For BF estimation in athletes, we recommend anthropometry, rather than bioimpedance because of inter individual and inter sports variations in arms length and regional masculinity.

Keywords

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