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

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.

Body composition and cardiorespiratory fitness of overweight COVID-19 survivors in different severity degrees: a cohort study.

COVID-19 sequelae are varied, and whether they are temporary or permanent is still unknown. Identifying these sequelae may guide therapeutic strategies to improve these individuals' recovery. This prospective cohort aimed to assess body composition, cardiopulmonary fitness, and long-term symptoms of overweight individuals affected by COVID-19. Participants (n = 90) were divided into three groups according to the severity of acute COVID-19: mild (no hospitalization), moderate (hospitalization, without oxygen support), and severe/critical cases (hospitalized in Intensive Care Unit). We assessed body composition with a tetrapolar multifrequency bioimpedance, hemodynamic variables (heart rate, blood pressure, and peripheral oxygen saturation-SpO2) at rest, and the Bruce test with direct gas exchange. Two assessments with a one-year interval were performed. The most prevalent long-term symptoms were memory deficit (66.7%), lack of concentration (51.7%), fatigue (65.6%), and dyspnea (40%). Bruce test presented a time effect with an increase in the distance walked after 1 year just for severe/critical group (p < 0.05). SpO2 was significantly lower in the severe/critical group up to 5 min after the Bruce test when compared to the mild group, and diastolic blood pressure at the end of the Bruce test was significantly higher in the severe/critical group when compared to mild group (p < 0.05; for all comparisons). A time effect was observed for body composition, with increased lean mass, skeletal muscle mass, fat-free mass, and lean mass just for the severe/critical group after 1 year (p < 0.05). Cardiopulmonary fitness parameters did not differ among the groups, except for respiratory quotient with higher values for the severe/critical group when compared to itself after 1 year. All COVID-19 patients might present long-term sequelae, regardless of the acute disease severity. Reassessing and identifying the most prevalent long-term sequelae are essential to perform more precise health promotion interventions.

Resting metabolic rate in bodybuilding: Differences between indirect calorimetry and predictive equations.

BACKGROUND & AIMS: Estimating resting metabolic rate (RMR) is one of the main determinants of an athlete's energy needs. This study aimed to investigate the RMR of bodybuilding athletes using indirect calorimetry (IC) and compare it with predictive formulas proposed in the scientific literature. METHODS: 71 volunteers divided into four experimental groups: active control group for women (CGW; n = 16); active control group for men (CGM; n = 17); bodybuilder women (BBW; n = 13); and bodybuilder men (BBM; n = 25) were evaluated. The body composition was performed using the bioelectrical impedance (BIA), and the RMR was measured using an IC. The data obtained from the BIA instrument were used to calculate the RMR of all volunteers using six equations. Data normality was tested, and the unpaired t-test compared anthropometric parameters, body composition, and RMR. The Bland-Altman (B&A) plot was used to analyze the agreement between IC, BIA, and predictive equations, and the difference between the methods was calculated. An analysis of covariance (ANCOVA) with Bonferroni post hoc was used for RMR analysis and adjusted for body weight and skeletal muscle mass. RESULTS: The main findings indicated that the Johnstone equation showed a large discrepancy underestimating the RMR of BBW and BBM when compared to IC, and the De Lorenzo and Tinsley equations (a) approached the more accurate analysis method of measuring RMR in BBW and BBM, respectively. CONCLUSION: Professionals who work with bodybuilding and performance will be able to use the present study to improve their nutrition support.

The effectiveness of high-intensity interval training on body composition of rodent models of obesity: A systematic review and meta-analysis.

The present systematic review was compiled to analyze the effectiveness of High-intensity interval training (HIIT) protocols on the body composition of rodents with obesity. Databases were searched until February 2021 for experimental trials in rodents with a minimum duration of four weeks of HIIT and endpoints associated with obesity. The data were analyzed by meta-analysis performed for comparisons of body composition. Sensitivity analysis was performed to investigate the consistency of individual researches. Of all of the 524 studies found, only 14 were included. The analysis showed a significant reduction in body weight ([CI 95%: -8.35; -1.98] P ≤ 0.01), adiposity index ([IC 95%: -1.04; -0.80] P ≤ 0.01), and fat pads ([IC 95%: -0.59; -0.06] P ≤ 0.01). HIIT performed on treadmill or water was effective to reduce body weight (P < 0.05). In conclusion, HIIT attenuated both body weight and adiposity induced either by HFD (high-fat diet) or by GOM (genetic obese model), thereby inducing positive changes in body composition.

Are rating of perceived exertion and heart rate methods useful to monitor the internal training load in functional training?

Abstract Aim: The study aimed to quantify and characterize the Training Load (TL) in a Functional Training (FT) model using Heart Rate (HR) and Session Rating of Perceived Exertion (sRPE) methods, and to verify whether these methods could be valid to monitor the TL during a FT program. Methods: The study design consisted of two phases: phase 1 - composed of a single training session of FT (FTSESSION), in which HR, sRPE, and pre- and post-exercise lactate [La] levels were assessed; phase 2 - composed of a FT program (FTPROGRAM) with eight weeks of duration and two sessions per week. The HR and SRPE were utilized to monitor all training sessions, and the results between sessions 1 vs. 8, 8 vs. 9, and 9 vs. 16 were compared. Results: On phase 1, HR distribution demonstrated that the participants spent about 75% of the total training time above 80% HRmax. Post-exercise [La] values were significantly higher (p < 0.05) than pre-exercise. The mean sRPE score was 8.5 ± 1.2. In phase 2, HR distribution was different between sessions 1-8 and 8-9 (p < 0.05). A strong correlation (r = 0.790) between the internal training load (ITL) and Training impulse (TRIMP) was observed. Conclusion: Our data demonstrated that the FTSESSION can be characterized as a high-intensity exercise, based on the pattern of HR responses and sRPE, and was reinforced by the [Lapeak]. Also, the TL monitoring methods (sRPE and TRIMP) proved to be valid for monitoring FT programs.