Comparison between Measured and Predicted Resting Metabolic Rate Equations in Cross-Training Practitioners

Ana Flávia Sordi, Bruno Ferrari Silva, Breno Gabriel da Silva, Déborah Cristina de Souza Marques, Isabela Mariano Ramos, Maria Luiza Amaro Camilo, Jorge Mota, Pablo Valdés-Badilla, Sidney Barnabé Peres and Braulio Henrique Magnani Branco ()
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Ana Flávia Sordi: Interdisciplinary Laboratory of Intervention in Health Promotion, Cesumar University, Maringá 87050-390, Paraná, Brazil
Bruno Ferrari Silva: Interdisciplinary Laboratory of Intervention in Health Promotion, Cesumar University, Maringá 87050-390, Paraná, Brazil
Breno Gabriel da Silva: Luiz de Queiroz College of Agriculture–ESALQ, USP Department of Exact Sciences, University of Sao Paulo, Sao Paulo 13418-900, Sao Paulo, Brazil
Déborah Cristina de Souza Marques: Interdisciplinary Laboratory of Intervention in Health Promotion, Cesumar University, Maringá 87050-390, Paraná, Brazil
Isabela Mariano Ramos: Interdisciplinary Laboratory of Intervention in Health Promotion, Cesumar University, Maringá 87050-390, Paraná, Brazil
Maria Luiza Amaro Camilo: Interdisciplinary Laboratory of Intervention in Health Promotion, Cesumar University, Maringá 87050-390, Paraná, Brazil
Jorge Mota: Research Center in Physical Activity, Health and Leisure (CIAFEL), Faculty of Sports, University of Porto (FADEUP), Porto 4200-450, Portugal
Pablo Valdés-Badilla: Department of Physical Activity Sciences, Faculty of Education Sciences, Universidad Católica del Maule, Talca 3530000, Chile
Sidney Barnabé Peres: Department of Physiological Sciences, State University of Maringá, Maringá 87020-900, Paraná, Brazil
Braulio Henrique Magnani Branco: Interdisciplinary Laboratory of Intervention in Health Promotion, Cesumar University, Maringá 87050-390, Paraná, Brazil

IJERPH, 2024, vol. 21, issue 7, 1-14

Abstract: This study aimed to investigate the resting metabolic rate (RMR) in cross-training practitioners (advanced and novice) using indirect calorimetry (IC) and compare it with predictive equations proposed in the scientific literature. Methods: A cross-sectional and comparative study analyzed 65 volunteers, both sexes, practicing cross-training (CT). Anthropometry and body composition were assessed, and RMR was measured by IC (FitMate PRO ® ), bioimpedance (BIA-InBody 570 ® ), and six predictive equations. Data normality was tested by the Kolgomorov–Smirnov test and expressed as mean ± standard deviation with 95% confidence intervals (CI), chi-square test was performed to verify ergogenic resources, and a Bland–Altman plot (B&A) was made to quantify the agreement between two quantitative measurements. One-way ANOVA was applied to body composition parameters, two-way ANOVA with Bonferroni post hoc was used to compare the RMR between groups, and two-way ANCOVA was used to analyze the adjusted RMR for body and skeletal muscle mass. The effect size was determined using Cohen’s d considering the values adjusted by ANCOVA. If a statistical difference was found, post hoc Bonferroni was applied. The significance level was p < 0.05 for all tests. Results: The main results indicated that men showed a higher RMR than women, and the most discrepant equations were Cunningham, Tinsley (b), and Johnstone compared to IC. Tinsley’s (a) equation indicated greater precision in measuring the RMR in CM overestimated it by only 1.9%, and BIA and the Harris–Benedict in CW overestimated RMR by only 0.1% and 3.4%, respectively. Conclusions: The BIA and Harris–Benedict equation could be used reliably to measure the RMR of females, while Tinsley (a) is the most reliable method to measure the RMR of males when measuring with IC is unavailable. By knowing which RMR equations are closest to the gold standard, these professionals can prescribe a more assertive diet, training, or ergogenic resources. An assertive prescription increases performance and can reduce possible deleterious effects, maximizing physical sports performance.

Keywords: athletic; energy expenditure; calorimetry; extreme functional fitness training (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2024
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