New Predictive Resting Metabolic Rate Equations for High-Level Athletes: A Cross-Validation Study

Abstract

Purpose: The present study aims a) to assess the agreement between the measured resting metabolic rate (RMR) using indirect calorimetry and different predictive equations (predicted RMR), and b) to propose and cross-validate two new predictive equations for estimating the RMR in high-level athletes. Methods: The RMR of 102 athletes (44 women) was assessed using indirect calorimetry, whereas the body composition was assessed using skinfolds. Comparisons between measured and predicted RMR values were performed using one-way ANOVA. Mean difference, root mean square error (RMSE), simple linear regression, and Bland-Altman plots were used to evaluate the agreement between measured and predicted RMR. The accuracy of predictive equations was analyzed using narrower and wider accuracy limits (±5% and ±10%, respectively) of measured RMR. Multiple linear regression models were employed to develop the new predictive equations based on traditional predictors (equation 1) and the stepwise method (equation 2). Results: The new equations 1 and 2 presented good agreement based on the mean difference (3 and −15 kcal•d −1 ), RMSE (200 and 192 kcal•d −1 ), and R 2 (0.71 and 0.74), respectively, and accuracy (61% of subjects between the limit of ±10% of measured RMR). Cunningham's equation provided the best performance for males and females among the existing equations, whereas Jagim's equation showed the worst performance for males (mean difference = −335 kcal•d −1 ; RMSE = 386 kcal•d −1 ). Compared with measured RMR, most predictive equations showed heteroscedastic distribution (linear regression's intercept and slope significantly different from zero; P ≤ 0.05), mainly in males. Conclusions: The new proposed equations can estimate the RMR in high-level athletes accurately. Cunningham's equation is a good option from existing equations, and Jagim's equation should not be used in high-level male athletes.

Sex Differences in Resting Metabolic Rate among Athletes and Association with Body Composition Parameters: A Follow-Up Investigation

“…A secondary aim of the current study was to identify predictors of RMR. The results demonstrated that body mass was the strongest predictor of RMR for both male and female athletes, which is in agreement with our initial findings [ 5 ] and those previously reported in elite-level national athletes [ 15 ], yet contradictory to previous reports [ 1 , 16 , 17 , 18 , 19 ]. In our initial study, it was reported that body mass accounted for 53% and 77% of the variation in measured RMR for men and women, respectively.…”

Development and validation of novel equation for prediction of resting energy expenditure in active Saudi athletes

“…This study included both genders and many sports, including group and individual games. The development of equations for a mixture of athletes playing different types of sports was seen in De Lorenzo et al, [ 17 ] 10 Haaf and Weijs, [ 19 ] Freire et al, [ 21 ] Jagim et al, [ 22 ] Frings-Meuthen et al, [ 38 ] and Reale et al [ 39 ] On the other hand, some equations were developed in 1 sport type or only 1 gender, such as (Cocate et al, [ 30 ] Hannon et al, [ 31 ] Joseph et al, [ 32 ] MacKenzie-Shalders et al, [ 33 ] Midorikawa et al, [ 34 ] O’Neil et al [ 35 ] ) creating a narrow limit for application in practice. The average TEE may differ in different sports based on the amount and duration of physical activity spent during the matches and the body mass of the player.…”

“…Ten Haaf et al [19] 11.936 × Wt (kg) + 587.728 × Ht (m)-8.129 × Age (yrs.) + 191.027 × G + 29.279 Athletes in the Netherlands 90 2014 7 Marra et al [20] (17.2 × Wt)-( 5.95 × Age) + 748 Athletes in Italy 126 2021 8 Freire et al [21] 729. Kim et al [23] 730.4 + 15 × FFM Athletes in Korea 50 2015 FFM = fat-free mass, G = gender (1 for men and 0 for women), Ht = height, RMR = resting metabolic rate, Wt = body weight.…”

Comparison of Actual and Predicted Resting Energy Expenditure in Skilled Endurance Athletes

“…To compare the actual resting energy expenditure (REE act ) and the one calculated using the equations, three equations were chosen based on the analysis of the literature on the research topic, which are widely used in physiology to calculate REE in different population groups, including athletes, based on body weight and length, age and gender: Harris-Benedict [11], Mifflin [12], and World Health Organization (WHO) [13]. We also selected three formulas specifically designed for athletes based on the same equations: De Lorenzo [14], ten Haaf [15], Freire [16].…”