Literature DB >> 30758869

Resting metabolic rate prediction equations and the validity to assess energy deficiency in the athlete population.

K L Schofield1, H Thorpe1, S T Sims1.   

Abstract

NEW
FINDINGS: What is the topic of this review? We review the issues with using predicted resting metabolic rate equations in athletic populations. What advances does it highlight? The use of dated predicted resting metabolic rate equations is not appropriate for athletic populations until more studies have been conducted among these unique populations. ABSTRACT: Resting metabolic rate (RMR) is the amount of energy the body uses at rest. A suppressed RMR has been correlated with low energy availability and therefore used as an indicator of an individual's energy state. Furthermore, confounding identification of low energy availability within an athletic population are the physiological measures required, which can be time consuming and require professional expertise. To negate the demands of laboratory protocols in measuring RMR, predicted RMR (p RMR) equations were developed. Caution should be exercised when applying the p RMR equations for determining low energy availability in athletes owing to the population used to develop the equations and the higher metabolic cost of fat-free mass, thus elevated RMR, associated with athletes. Moreover, a low ratio of measured RMR to p RMR is often used as an alternative marker for energy deficiency. Predictive equations should implement fat-free mass within the algorithm when estimating RMR in athletic populations. The purpose of this paper is to describe p RMR equation development and the issues associated with use of p RMR equations for athletic populations. As professional sport increases, validation of p RMR equations in the modern athlete population is needed to monitor energy availability for athletic health and performance.
© 2019 The Authors. Experimental Physiology © 2019 The Physiological Society.

Entities:  

Keywords:  athlete; energy availability; methodology; predictive resting metabolic rate; resting metabolic rate; validity

Mesh:

Year:  2019        PMID: 30758869     DOI: 10.1113/EP087512

Source DB:  PubMed          Journal:  Exp Physiol        ISSN: 0958-0670            Impact factor:   2.969


  5 in total

1.  Predictive equations for resting metabolic rate are not appropriate to use in Brazilian male adolescent football athletes.

Authors:  Taillan M Oliveira; Paula A Penna-Franca; Christian H Dias-Silva; Victor Z Bittencourt; Fabio F L C Cahuê; Sidnei J Fonseca-Junior; Anna Paola T R Pierucci
Journal:  PLoS One       Date:  2021-01-14       Impact factor: 3.240

2.  Resting Energy Expenditure of Master Athletes: Accuracy of Predictive Equations and Primary Determinants.

Authors:  Petra Frings-Meuthen; Sara Henkel; Michael Boschmann; Philip D Chilibeck; José Ramón Alvero Cruz; Fabian Hoffmann; Stefan Möstl; Uwe Mittag; Edwin Mulder; Natia Rittweger; Wolfram Sies; Hirofumi Tanaka; Jörn Rittweger
Journal:  Front Physiol       Date:  2021-03-22       Impact factor: 4.566

3.  Association of energy availability with resting metabolic rates in competitive female teenage runners: a cross-sectional study.

Authors:  Norimitsu Kinoshita; Eriko Uchiyama; Kazuko Ishikawa-Takata; Yuka Yamada; Kenta Okuyama
Journal:  J Int Soc Sports Nutr       Date:  2021-11-16       Impact factor: 5.150

Review 4.  Low Energy Availability in Athletes 2020: An Updated Narrative Review of Prevalence, Risk, Within-Day Energy Balance, Knowledge, and Impact on Sports Performance.

Authors:  Danielle M Logue; Sharon M Madigan; Anna Melin; Eamonn Delahunt; Mirjam Heinen; Sarah-Jane Mc Donnell; Clare A Corish
Journal:  Nutrients       Date:  2020-03-20       Impact factor: 5.717

Review 5.  Energy Requirements and Nutritional Strategies for Male Soccer Players: A Review and Suggestions for Practice.

Authors:  Andrew T Hulton; James J Malone; Neil D Clarke; Don P M MacLaren
Journal:  Nutrients       Date:  2022-02-04       Impact factor: 5.717

  5 in total

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