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

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

doi:10.3389/fphys.2021.641455

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

Front Physiol. 2021 Mar 22:12:641455. doi: 10.3389/fphys.2021.641455. eCollection 2021.

Authors

Affiliations

¹ German Aerospace Center (DLR), Institute of Aerospace Medicine, Cologne, Germany.
² Experimental and Clinical Research Center - a joint co-operation between Charité Universitätsmedizin Berlin and Max Delbrück Center for Molecular Medicine, Berlin, Germany.
³ College of Kinesiology, University of Saskatchewan, Saskatoon, SK, Canada.
⁴ Facultad de Medicina, Instituto de Investigación Biomédica de Málaga, Universidad de Málaga, Málaga, Spain.
⁵ Department of Internal Medicine III, University Hospital Cologne, Cologne, Germany.
⁶ Department of Kinesiology and Health Education, The University of Texas at Austin, Austin, TX, United States.
⁷ Department of Pediatrics and Adolsecent Medicine, Hospital Cologne, Cologne, Germany.

Abstract

Resting energy expenditure (REE) is determined mainly by fat-free mass (FFM). FFM depends also on daily physical activity. REE normally decreases with increased age due to decreases in FFM and physical activity. Measuring REE is essential for estimating total energy expenditure. As such, there are a number of different equations in use to predict REE. In recent years, an increasing number of older adults continue to participate in competitive sports creating the surge of master athletes. It is currently unclear if these equations developed primarily for the general population are also valid for highly active, older master athletes. Therefore, we tested the validity of six commonly-used equations for predicting REE in master athletes. In conjunction with the World Masters Athletic Championship in Malaga, Spain, we measured REE in 113 master athletes by indirect calorimetry. The most commonly used equations to predict REE [Harris & Benedict (H&B), World Health Organization (WHO), Müller (MÜL), Müller-FFM (MÜL-FFM), Cunningham (CUN), and De Lorenzo (LOR)] were tested for their accuracies. The influences of age, sex, height, body weight, FFM, training hours per week, phase angle, ambient temperature, and athletic specialization on REE were determined. All estimated REEs for the general population differed significantly from the measured ones (H&B, WHO, MÜL, MÜL-FFM, CUN, all p < 0.005). The equation put forward by De Lorenzo provided the most accurate prediction of REE for master athletes, closely followed by FFM-based Cunningham's equation. The accuracy of the remaining commonly-used prediction equations to estimate REE in master athletes are less accurate. Body weight (p < 0.001), FFM (p < 0.001), FM (p = 0.007), sex (p = 0.045) and interestingly temperature (p = 0.004) are the significant predictors of REE. We conclude that REE in master athletes is primarily determined by body composition and ambient temperature. Our study provides a first estimate of energy requirements for master athletes in order to cover adequately athletes' energy and nutrient requirements to maintain their health status and physical performance.

Keywords: body composition; energy metabolism; master athletes; predictive equation; resting energy expenditure.