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. 2018 Mar 14:2018:6843792.
doi: 10.1155/2018/6843792. eCollection 2018.

Accuracy of Anthropometric Equations for Estimating Body Fat in Professional Male Soccer Players Compared with DXA

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Accuracy of Anthropometric Equations for Estimating Body Fat in Professional Male Soccer Players Compared with DXA

Juan R López-Taylor et al. J Sports Med (Hindawi Publ Corp). .

Abstract

Background: There are several published anthropometric equations to estimate body fat percentage (BF%), and this may prompt uncertainty about their application.

Purpose: To analyze the accuracy of several anthropometric equations (developed in athletic [AT] and nonathletic [NAT] populations) that estimate BF% comparing them with DXA.

Methods: We evaluated 131 professional male soccer players (body mass: 73.2 ± 8.0 kg; height: 177.5 ± 5.8 cm; DXA BF% [median, 25th-75th percentile]: 14.0, 11.9-16.4%) aged 18 to 37 years. All subjects were evaluated with anthropometric measurements and a whole body DXA scan. BF% was estimated through 14 AT and 17 NAT anthropometric equations and compared with the measured DXA BF%. Mean differences and 95% limits of agreement were calculated for those anthropometric equations without significant differences with DXA.

Results: Five AT and seven NAT anthropometric equations did not differ significantly with DXA. From these, Oliver's and Civar's (AT) and Ball's and Wilmore's (NAT) equations showed the highest agreement with DXA. Their 95% limits of agreement ranged from -3.9 to 2.3%, -4.8 to 1.8%, -3.4 to 3.1%, and -3.9 to 3.0%, respectively.

Conclusion: Oliver's, Ball's, Civar's, and Wilmore's equations were the best to estimate BF% accurately compared with DXA in professional male soccer players.

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References

    1. Ackland T. R., Lohman T. G., Sundgot-Borgen J., et al. Current status of body composition assessment in sport: review and position statement on behalf of the Ad Hoc research working group on body composition health and performance, under the auspices of the I.O.C. medical commission. Sports Medicine. 2012;42(3):227–249. doi: 10.2165/11597140-000000000-00000. - DOI - PubMed
    1. Rico-Sanz J. Body composition and nutritional assessments in soccer. International Journal of Sport Nutrition and Exercise Metabolism. 1998;8(2):113–123. doi: 10.1123/ijsn.8.2.113. - DOI - PubMed
    1. Sporis G., Jukic I., Ostojic S. M., Milanovic D. Fitness profiling in soccer: Physical and physiologic characteristics of elite players. The Journal of Strength and Conditioning Research. 2009;23(7):1947–1953. doi: 10.1519/JSC.0b013e3181b3e141. - DOI - PubMed
    1. Nikolaidis P. T., Ruano M. A. G., de Oliveira N. C., et al. Who runs the fastest? Anthropometric and physiological correlates of 20 m sprint performance in male soccer players. Research in Sports Medicine. 2016;24(4):341–351. doi: 10.1080/15438627.2016.1222281. - DOI - PubMed
    1. Bunc V., Hráský P., Skalská M. Changes in body composition, during the season, in highly trained soccer players. The Open Sports Sciences Journal. 2015;8(1):18–24. doi: 10.2174/1875399X01508010018. - DOI

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