Myths and Methodologies: Resting metabolic rate prediction equations and the validity to assess energy deficiency in the athlete population

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 (LEA) and therefore used as an indicator of an individual's energy state. Furthermore, confounding identification of LEA within an athletic population are the physiological measures required; which can be time consuming and needing professional expertise. To negate the demands of laboratory protocols in measuring RMR, predicted RMR ( _pRMR) equations were developed. Caution should be raised when applying the _pRMR equations for determining LEA in athletes due to 1) the population used to develop the equations and; 2) the higher metabolic cost of fat free mass (FFM), thus elevated RMR, associated with athletes. Moreover, a low ratio of measured RMR to _pRMR is often used as an alternative marker for energy deficiency. Predictive equations should implement FFM within the algorithm when estimating RMR in athletic populations. The purpose of this paper is to describe _pRMR equation development and the issues using _pRMR equations for athletic populations. As professional sport increases, validation of _pRMR equations in the modern athlete population is needed to monitor energy availability for athletic health and performance.

This article is protected by copyright. All rights reserved

http://bit.ly/2SMHVsK