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Are increases in skeletal muscle mass accompanied by changes to resting metabolic rate in rugby athletes over a pre-season training period?
Journal article   Peer reviewed

Are increases in skeletal muscle mass accompanied by changes to resting metabolic rate in rugby athletes over a pre-season training period?

Kristen L MacKenzie-Shalders, Nuala M Byrne, Neil A King and Gary J Slater
European Journal of Sport Science, Vol.19(7), pp.885-892
2019
PMID: 30614386
url
https://doi.org/10.1080/17461391.2018.1561951View
Published Version

Abstract

metabolism nutrition measurement prediction team sport
Optimising dietary energy intake is essential for effective sports nutrition practice in rugby athletes. Effective dietary energy prescription requires careful consideration of athletes' daily energy expenditure with the accurate prediction of resting metabolic rate (RMR) important due to its influence on total energy expenditure and in turn, energy balance. This study aimed to (a) measure rugby athletes RMR and (b) report the change in RMR in developing elite rugby players over a rugby preseason subsequent to changes in body composition and (c) explore the accurate prediction of RMR in rugby athletes. Eighteen developing elite rugby union athletes (age 20.2±1.7 years, body mass 101.2±14.5 kg, stature 184.0±8.4 cm) had RMR (indirect calorimetry) and body composition (dual energy x-ray absorptiometry) measured at the start and end of a rugby preseason ∼14 weeks later. There was no statistically significant difference in RMR over the preseason period (baseline 2389±263 kcal.day-1 post 2373±270 kcal.day-1) despite a significant increase in lean mass of +2.0±1.6 kg (P < 0.01) and non-significant loss of fat mass. The change in RMR was non-significant and non-meaningful; thus, this study contradicts the commonly held anecdotal perception that an increase in skeletal muscle mass will result in a significant increase in metabolic rate and daily energy needs. Conventional prediction equations generally under-estimated rugby athletes' measured RMR, and may be problematic for identifying low energy availability, and thus updated population-specific prediction equations may be warranted to inform practice.

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