Abstract
OBJECTIVES: Using equations to predict resting metabolic rate (RMR) has yielded different degrees of validity, particularly when sex and different physical activity levels were considered. Therefore, the purpose of the present study was to determine the validity of several different predictive equations to estimate RMR in female and male adults with varying physical activity levels.
METHOD: We measured the RMR of 50 adults (26 females and 24 males) evenly distributed through activity levels varying from sedentary to ultra-endurance. Body composition was measured by dual X-ray absorptiometry and physical activity was monitored by accelerometry. Ten equations to predict RMR were applied (using Body Mass [BM]: Harris & Benedict, 1919; Mifflin et al., 1990 [Mifflin BM ]; Pontzer et al., 2021 [Pontzer BM ]; Schofield, 1985; FAO/WHO/UNU, 2004; and using Fat-Free Mass (FFM): Cunningham, 1991; Johnstone et al., 2006; Mifflin et al., 1990 [Mifflin FFM ]; Nelson et al. 1992; Pontzer et al., 2021 [Pontzer FFM ]). The accuracy of these equations was analyzed, and the effect of sex and physical activity was evaluated using different accuracy metrics.
RESULTS: Equations using BM were less accurate for females, and their accuracy was influenced by physical activity and body composition. FFM equations were slightly less accurate for males but there was no obvious effect of physical activity or other sample parameters. Pontzer FFM provides higher accuracy than other models independent of the magnitude of RMR, sex, activity levels, and sample characteristics.
CONCLUSION: Equations using FFM were more accurate than BM equations in our sample. Future studies are needed to test the accuracy of RMR prediction equations in diverse samples.
Original language | English |
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Article number | e24005 |
Journal | American Journal of Human Biology |
Early online date | 16 Oct 2023 |
DOIs | |
Publication status | Published - 16 Oct 2023 |
Bibliographical note
ACKNOWLEDGMENTSThe authors are sincerely grateful to all the volunteers involved in this experimental study. This research was performed in the Human Integrative Physiology Laboratory (Dept. of Human Nutrition, Foods, and Exercise, Virginia Tech, Blacksburg, VA, USA). OPN is funded by a Virginia Tech Presidential Postdoctoral Fellowship, KHR by a Virginia Tech Translational Obesity Research Interdisciplinary Graduate Education Predoctoral Fellow-ship, and GZR is funded by Next Generation EU funds Margarita Salas Postdoctoral Fellowship.
FUNDING INFORMATION
OPN is funded by a Virginia Tech Presidential Postdoctoral Fellowship, and KHR by a Virginia Tech Translational Obesity Research Interdisciplinary Graduate Education Predoctoral Fellowship