Validity of predictive equations for total energy expenditure against doubly labeled water.

Variations in physical activity energy expenditure can make accurate prediction of total energy expenditure (TEE) challenging. The purpose of the present study was to determine the accuracy of available equations to predict TEE in individuals varying in physical activity (PA) levels. TEE was measured by DLW in 56 adults varying in PA levels which were monitored by accelerometry. Ten different models were used to predict TEE and their accuracy and precision were evaluated, considering the effect of sex and PA. The models generally underestimated the TEE in this population. An equation published by Plucker was the most accurate in predicting the TEE in our entire sample. The Pontzer and Vinken models were the most accurate for those with lower PA levels. Despite the levels of accuracy of some equations, there were sizable errors (low precision) at an individual level. Future studies are needed to develop and validate these equations.

Validation of predictive equations to estimate resting metabolic rate of females and males across different activity levels.

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 [MifflinBM]; Pontzer et al., 2021 [PontzerBM]; Schofield, 1985; FAO/WHO/UNU, 2004; and using Fat-Free Mass (FFM): Cunningham, 1991; Johnstone et al., 2006; Mifflin et al., 1990 [MifflinFFM]; Nelson et al. 1992; Pontzer et al., 2021 [PontzerFFM]). 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. PontzerFFM 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.