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Comparison between measured and predicted resting metabolic rate equations in cross-training practitioners

dc.contributor.authorSordi, Ana Flávia
dc.contributor.authorFerrari Silva, Bruno
dc.contributor.authorda Silva, Breno Gabrie
dc.contributor.authorde Souza Marques, Déborah Cristina
dc.contributor.authorMariano Ramos, Isabela
dc.contributor.authorAmaro Camilo, Maria Luiza
dc.contributor.authorMota, Jorge
dc.contributor.authorValdés-Badilla, Pablo
dc.contributor.authorPeres, Sidney Barnabé
dc.contributor.authorMagnani Branco, Braulio
dc.date.accessioned2024-08-26T15:34:52Z
dc.date.available2024-08-26T15:34:52Z
dc.date.issued2024
dc.identifier.urihttp://repositorio.ucm.cl/handle/ucm/5631
dc.description.abstractThis 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.es_CL
dc.language.isoenes_CL
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 Chile*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/cl/*
dc.sourceInternational Journal of Environmental Research and Public Health, 21(7), 891es_CL
dc.subjectAthletices_CL
dc.subjectEnergy expenditurees_CL
dc.subjectCalorimetryes_CL
dc.subjectExtreme functional fitness traininges_CL
dc.titleComparison between measured and predicted resting metabolic rate equations in cross-training practitionerses_CL
dc.typeArticlees_CL
dc.ucm.facultadFacultad de Ciencias de la Educaciónes_CL
dc.ucm.indexacionScopuses_CL
dc.ucm.urimdpi.com/1660-4601/21/7/891es_CL
dc.ucm.doidoi.org/10.3390/ijerph21070891es_CL


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Atribución-NoComercial-SinDerivadas 3.0 Chile
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