Predictive equations for resting metabolic rate are not appropriate to use in Brazilian male adolescent football athletes

Abstract

High accuracy in estimating energy expenditure is essential for enhancing sports performance. The resting metabolic rate (RMR), as a primary component of total energy expenditure (TEE), is commonly estimated using predictive equations. However, these references may not be applicable to adolescent athletes. The purpose of this cross-sectional study was to analyse the differences between predicted RMR in relation to energy expenditure measured by indirect calorimetry (IC) among 45 Brazilian male adolescent football athletes. Indirect calorimetry (IC) and anthropometric (bioimpedance) measurements were recorded at a single visit to the laboratory after fasting overnight. The mean age was 15.6 ± 1.14 years, body mass was 63.05 ± 7.8 kg, and height was 172 ± 7.5 cm. The RMR values predicted by equations proposed by the Food and Agriculture Organization (FAO) (United Nations), Henry and Rees (HR), Harris Benedict (HB), and Cunningham (CUN) were compared with IC RMR values, by correlation analysis. The FAO and HR predictive equations yielded different values from IC (IC: 1716.26 ± 202.58, HR: 1864.87 ± 147.78, FAO: 1854.28 ± 130.19, p = 0.001). A moderate correlation of 0.504 was found between the results of HB and IC. In the survival-agreement model, the CUN equation showed low disagreement with the IC RMR, with error values between 200 and 300 kcal/day. The results showed that HB and CUN yielded similar values as IC, with the CUN equation showing low disagreement with IC; hence, adolescent athletes should undergo evaluation with precise laboratory methods to ensure that accurate information about RMR is recorded.

The accuracy of ten common resting metabolic rate prediction equations in men and women collegiate athletes

“…Further research is warranted into the agreeability of the Freire equation in other athletic populations, primarily across high‐level collegiate athletes from a variety of sports (Freire et al, 2021). Other research in men athletes have reported the Harris Benedict equation to be the most accurate prediction equation (Balci et al, 2021; Jagim et al, 2018; Oliveira et al, 2021), which is interesting as it was developed in less active individuals and also does not account for FFM.…”

“…Similarly, the equation of Tinsley et al was developed in muscular men and women physique athletes, and is also largely based on FFM (Tinsley et al, 2018). Among the sample initially Other research in men athletes have reported the Harris Benedict equation to be the most accurate prediction equation (Balci et al, 2021;Jagim et al, 2018;Oliveira et al, 2021), which is interesting as it was developed in less active individuals and also does not account for FFM. For women, the De Lorenzo equation demonstrated the strongest agreeability with measured RMR values, which is in agreement with prior in athletic populations (Frings-Meuthen et al, 2021;Haaf & Weijs, 2014).…”

Effect of gas exchange data selection methods on resting metabolic rate estimation in young athletes

“…Despite the high cost and necessity of trained professionals, IC is the best method for evaluating RMR. Predictive equations would be an alternative for estimating RMR, but unfortunately, most perform poorly in adolescent non-athletes [ 30 , 31 ] and adolescent athletes [ 5 , 32 ]. IC assessments in athletes are relatively complex because of the duration of the current protocols (~60 min if the acclimation period prior to the RMR assessment is considered) and their training and competition schedules [ 27 , 33 ].…”