Dataset Information

Perceived Exertion during Exercise Is Associated with Children's Energy Intake.

ABSTRACT: PURPOSE:To examine the individual-level factors that predict energy intake (EI) after imposed exercise (EX) and sedentary time (SED) in children. METHODS:Healthy-weight children ages 9-12 yr (n = 20) reported to the laboratory for one baseline and two experimental visits (EX and SED) each separated by 1 wk in a randomized crossover design. Percent body fat, weight (kg), and height (m) were used to calculate fat-mass index (FM index) and fat-free mass index (FFM index; kg·m). On the EX day, children exercised at 70% estimated V?O2peak for 30 min on a cycle ergometer, whereas cardiovascular responses and RPE were measured. Objective EI (kcal) was measured at identical meals (breakfast, lunch, snack, and dinner) on the EX and SED days. RESULTS:Total EI was not statistically different between the EX and SED days (t = 1.8, P = 0.09). FFM index was positively associated with EI on the EX day (r = 0.54, P < 0.05). RPE was also positively associated with EI on the EX day (r = 0.82, P < 0.001). Together, FFM index and RPE explained 77% of the variability in EX day EI (F(2,17) = 26.4, P < 0.001). For each unit increase in RPE, children consumed approximately 270 more calories on the EX day. A similar pattern of associations was observed on the SED day. CONCLUSIONS:FFM index was positively associated with EI on the EX day. Despite experiencing the same 70% relative exercise intensity, increased perceived difficulty predicted greater EI on both the EX and SED day. These findings demonstrate a role for both FFM and RPE in explaining EI variability in children.

SUBMITTER: Fearnbach SN

PROVIDER: S-EPMC5357167 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

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Perceived Exertion during Exercise Is Associated with Children's Energy Intake.

Fearnbach S Nicole SN Masterson Travis D TD Schlechter Haley A HA Loken Eric E Downs Danielle S DS Thivel David D Keller Kathleen L KL

Medicine and science in sports and exercise 20170401 4

<h4>Purpose</h4>To examine the individual-level factors that predict energy intake (EI) after imposed exercise (EX) and sedentary time (SED) in children.<h4>Methods</h4>Healthy-weight children ages 9-12 yr (n = 20) reported to the laboratory for one baseline and two experimental visits (EX and SED) each separated by 1 wk in a randomized crossover design. Percent body fat, weight (kg), and height (m) were used to calculate fat-mass index (FM index) and fat-free mass index (FFM index; kg·m). On th ...[more]

PMID: 27902529

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Project description:BackgroundBorg developed scales for rating pain and perceived exertion in adults that have also been used in pediatric populations. Models describing functional relationships between perceived exertion and work capacity have not been studied in children. We compared different models and their fits to individual trajectories and assessed the variability in these trajectories.MethodsRatings of perceived exertion (RPE) were collected from 79 children. Progressive cycle ergonometric testing was performed to maximal work capacity with test duration ranging from 6- 12 minutes. Ratings were obtained during each 1-minute increment. Work was normalized to individual maximal work capacity (Wmax). A delay was defined as the fraction of Wmax at which point an increase in ratings of leg fatigue occurred. Such a delay term allows the characterization of trajectories for children whose ratings were initially constant with increasing work. Two models were considered, a delay model and a power model that is commonly used to analyze Borg ratings. Individual model fit was assessed with root mean squared error (RMSE). Functional clustering algorithms were used to identify patterns.ResultsLeg tiredness developed quickly for some children while for others there was a delay before an in- creased ratings of leg exertion occurred with increasing work. Models for individual trajectories with the smallest RMSE included a delay and a quadratic term (quadratic-delay model), or a power function and a delay term (power-delay model) compared to a simple power function. The median delay was 40% Wmax (interquartile range (IQR): 26-49%) in a quadratic-delay model, while the median exponent was 1.03 (IQR: 0.83-1.78) in a power-delay model. Nine clusters were identified showing linear or quadratic patterns with or without a delay. Cluster membership did not depend on age, gender or diagnosis.ConclusionChildren and adolescents vary widely in their capacity to rate their perceptions and exhibit different functional relationships between ratings of perceived exertion and work capacity normalized across individuals. Models including a delay term, a linear component, or a power function can describe these individual trajectories of perceived leg exertion during incremental exercise to voluntary exhaustion.

Project description:BackgroundThe validity of ratings of perceived exertion (RPE) during aerobic training is well established; however, its validity during resistance exercise is less clear. This meta-analysis used the known relationships between RPE and exercise intensity (EI), heart rate (HR), blood lactate (BLa), blood pressure (BP) and electromyography (EMG) to determine the convergent validity of RPE as a measure of resistance exercise intensity and physiological exertion, during different forms of resistance exercise. Additionally, this study aims to assess the effect of several moderator variables on the strength of the validity coefficients, so that clearer guidance can be given on the use of RPE during resistance exercise.MethodsAn online search of 4 databases and websites (PubMed, Web of Science SPORTDiscus and ResearchGate) was conducted up to 28 February 2020. Additionally, the reference lists of the included articles were inspected manually for further unidentified studies. The inclusion criteria were healthy participants of any age, a rating scale used to measure RPE, resistance exercise of any type, one cohort receiving no other intervention, and must present data from one of the following outcome measures: EI, HR, BP, EMG or BLa. Weighted mean effect sizes (r) were calculated using a random-effects model. Heterogeneity was assessed using the τ2 and I2 statistics. Moderator analysis was conducted using random-effects meta-regression.ResultsOne-hundred and eighteen studies were included in the qualitative synthesis, with 75 studies (99 unique cohorts) included in the meta-analysis. The overall weighted mean validity coefficient was large (0.88; 95% CI 0.84-0.91) and between studies heterogeneity was very large (τ2 = 0.526, I2 = 96.1%). Studies using greater workload ranges, isometric muscle actions, and those that manipulated workload or repetition time, showed the highest validity coefficients. Conversely, sex, age, training status, RPE scale used, and outcome measure no significant effect.ConclusionsRPE provides a valid measure of exercise intensity and physiological exertion during resistance exercise, with effect sizes comparable to or greater than those shown during aerobic exercise. Therefore, RPE may provide an easily accessible means of prescribing and monitoring resistance exercise training. Trial Registration The systematic review protocol was registered on the PROSPERO database (CRD42018102640).

Project description:ObjectiveThe intensity of barbell bench press exercise is generally prescribed as the load to be lifted for a specific number of repetitions; however, other factors (e.g., execution velocity) can affect bench press exercise intensity. Moreover, no study assessed whether load distribution (i.e., the distance between the disc stacks on the two sides of the barbell) affects exercise intensity. The present study aims to assess how different combinations of load, velocity, and barbell load distribution affect the number of repetitions to failure (REPfailure), and rating of perceived exertion (RPEfatigue) and number of repetitions (REPfatigue) at fatigue onset.MethodsTen males (age 23.3±1.8 years) performed bench press exercises to exhaustion using random combinations of three loads (50%, 65%, and 80% of 1 repetition maximum), three execution velocities (50%, 70%, and 90% of maximal concentric velocity), and two load distributions (narrow and wide). Three separate three-way repeated-measures ANOVAs were performed to assess the effect of load, velocity, and load distribution on REPfailure, RPEfatigue, and REPfatigue expressed as a percentage of REPfailure.ResultsREPfailure was affected by load (p<0.001), velocity (p<0.001), and distribution (p = 0.005). The interactions between load and velocity (p<0.001) and load and distribution (p = 0.004) showed a significant effect on REPfailure, whereas the interaction between velocity and distribution was not significant (p = 0.360). Overall, more REPfailure were performed using lower loads, higher velocities, and a wider distribution. RPEfatigue and REPfatigue were affected by load (p<0.001 and p = 0.007, respectively) and velocity (p<0.001 and p<0.001, respectively), and not by distribution (p = 0.510 and p = 0.571, respectively) or the two-way interaction effects. Overall, using higher loads yielded higher RPEfatigue but lower REPfatigue, while RPEfatigue and REPfatigue were higher when slower velocities were used.ConclusionThe current investigation shows that not only load but also velocity and barbell load distribution may influence bench press training volume and perceived exertion.

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Perceived Exertion during Exercise Is Associated with Children's Energy Intake.

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Perceived Exertion during Exercise Is Associated with Children's Energy Intake.

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