Purpose: Elite athletes experience chronic sleep insufficiency due to training and competition schedules. However, there is little research on sleep and caffeine use of elite youth athletes and a need for a more nuanced understanding of their sleep difficulties. This study aimed to (1) examine the differences in sleep characteristics of elite youth athletes by individual and team sports, (2) study the associations between behavioral risk factors associated with obstructive sleep apnea and caffeine use with sleep quality, and (3) characterize the latent sleep profiles of elite youth athletes to optimize the sleep support strategy. Methods: A group (N = 135) of elite national youth athletes completed a self-administered questionnaire consisting of the Pittsburgh Sleep Quality Index (PSQI) and questions pertaining to obstructive sleep apnea, napping behavior, and caffeine use. K-means clustering was used to characterize unique sleep characteristic subgroups based on PSQI components. Results: Athletes reported 7.0 (SD = 1.2) hours of sleep. Out of the total group, 45.2% of the athletes had poor quality sleep (PSQI global >5), with team-sport athletes reporting significantly poorer sleep quality than individual-sport athletes. Multiple logistic regression analysis indicated that sport type significantly correlated with poor sleep quality. The K-means clustering algorithm classified athletes’ underlying sleep characteristics into 4 clusters to efficiently identify athletes with similar underlying sleep issues to enhance interventional strategies.Conclusion: These findings suggest that elite youth team-sport athletes are more susceptible to poorer sleep quality than individual-sport athletes. Clustering methods can help practitioners characterize sleep-related problems and develop efficient athlete support strategies.
Haresh T. Suppiah, Richard Swinbourne, Jericho Wee, Vanes Tay, and Paul Gastin
Henning T. Langer, Agata A. Mossakowski, Suraj Pathak, Mark Mascal, and Keith Baar
Cannabidiol (CBD) has proven clinical benefits in the treatment of seizures, inflammation, and pain. The recent legalization of CBD in many countries has caused increased interest in the drug as an over-the-counter treatment for athletes looking to improve recovery. However, no data on the effects of CBD on the adaptive response to exercise in muscle are available. To address this gap, we eccentrically loaded the tibialis anterior muscle of 14 rats, injected them with a vehicle (n = 7) or 100 mg/kg CBD (n = 7), and measured markers of injury, inflammation, anabolic signaling, and autophagy 18 hr later. Pro-inflammatory signaling through nuclear factor kappa B (NF-kB) (Ser536) increased with loading in both groups; however, the effect was significantly greater (36%) in the vehicle group (p < .05). Simultaneously, anabolic signaling through ribosomal protein S6 kinase beta-1 (S6K1) (Thr389) increased after eccentric contractions in both groups with no difference between vehicle and CBD (p = .66). The ribosomal protein S6 phosphorylation (240/244) increased with stimulation (p < .001) and tended to be higher in the CBD group (p = .09). The ubiquitin-binding protein p62 levels were not modulated by stimulation (p = .6), but they were 46% greater in the CBD compared with the vehicle group (p = .01). Although liver weight did not differ between the groups (p = .99) and levels of proteins associated with stress were similar, we did observe serious side effects in one animal. In conclusion, an acute dose of CBD decreased pro-inflammatory signaling in the tibialis anterior without blunting the anabolic response to exercise in rats. Future research should determine whether these effects translate to improved recovery without altering adaptation in humans.
Jacopo A. Vitale, Matteo Bonato, Lorenzo Petrucci, Giorgio Zucca, Antonio La Torre, and Giuseppe Banfi
Purpose: Little is known about the effect of sleep restriction (SR) on different domains of athletes’ physical performance. Therefore, the aim of this randomized, counterbalanced, and crossover study was to evaluate the effect of acute SR on sport-specific technical and athletic performance in male junior tennis players. Methods: Tennis players (N = 12; age 15.4 ± 2.6 y) were randomly allocated to either a sleep-restriction condition (SR, n = 6), where they experienced acute sleep restriction the night before the test session (≤5 h of sleep), or to a control condition (CON, n = 6), where they followed their habitual sleep–wake routines. Testing procedures included 20 left and right serves, 15 forehand and backhand crosscourt shots, and a repeated-sprint-ability test (RSA). The accuracy of serves and shots was considered for further analysis. One week later, players of SR joined CON, and players of CON experienced SR, and all test procedures were repeated. Results: Significant decrease in the accuracy of right (−17.5%, P = .010, effect size [ES] = 1.0, moderate) and left serve (−14.1%, P = .014, ES = 1.2, large), crosscourt backhand (−23.9%, P = .003, ES ≥ 2.0, very large), and forehand shot (−15.6%, P = .014, ES = 1.1, moderate) were observed in SR compared to CON, while RSA was similar in both conditions. Conclusion: Coaches and athletes at the team and individual level should be aware that 1 night of SR affects sport-specific but not athletic performance in tennis players.
Fernando G. Beltrami, Elena Roos, Marco von Ow, and Christina M. Spengler
Purpose: To compare the cardiorespiratory responses of a traditional session of high-intensity interval training session with that of a session of similar duration and average load, but with decreasing workload within each bout in cyclists and runners. Methods: A total of 15 cyclists (maximal oxygen uptake [
Naoya Takei, Jacky Soo, Hideo Hatta, and Olivier Girard
Background: Compared with normoxia, repeated short (5–10 s) sprints (>10 efforts) with incomplete recovery (≤30 s) in hypoxia likely cause substantial performance reduction accompanied by larger metabolic disturbances and magnitude of neuromuscular fatigue. However, the effects of hypoxia on performance of repeated long (30 s) “all-out” efforts with near complete recovery (4.5 min) and resulting metabolic and neuromuscular adjustments remain unclear. Purpose: The intention was to compare acute performance, metabolic, and neuromuscular responses across repeated Wingates between hypoxia and normoxia. Methods: On separate visits, 6 male participants performed 4 × 30-second Wingate efforts with 4.5-minute recovery in either hypoxia (fraction of inspired oxygen: 0.145) or normoxia. Responses to exercise (muscle and arterial oxygenation trends, heart rate, and blood lactate concentration) and the integrity of neuromuscular function in the knee extensors were assessed for each exercise bout. Results: Mean (P = .80) and peak (P = .92) power outputs, muscle oxygenation (P = .88), blood lactate concentration (P = .72), and perceptual responses (all Ps > .05) were not different between conditions. Arterial oxygen saturation was significantly lower, and heart rate higher, in hypoxia versus normoxia (P < .001). Maximal voluntary contraction force and peripheral fatigue indices (peak twitch force and doublets at low and high frequencies) decreased across efforts (all Ps < .001) irrespective of conditions (all Ps > .05). Conclusion: Despite heightened arterial hypoxemia and cardiovascular solicitation, hypoxic exposure during 4 repeated 30-second Wingate efforts had no effect on performance and accompanying metabolic and neuromuscular adjustments.
Peter Leo, James Spragg, Iñigo Mujika, Verena Menz, and Justin S. Lawley
Purpose: The aim of this study was to investigate changes in the power profile of U23 professional cyclists during a competitive season based on maximal mean power output (MMP) and derived critical power (CP) and work capacity above CP (W′) obtained during training and racing. Methods: A total of 13 highly trained U23 professional cyclists (age = 21.1 [1.2] y, maximum oxygen consumption = 73.8 [1.9] mL·kg–1·min–1) participated in this study. The cycling season was split into pre-season and in-season. In-season was divided into early-, mid-, and late-season periods. During pre-season, a CP test was completed to derive CPtest and W′test. In addition, 2-, 5-, and 12-minute MMP during in-season were used to derive CPfield and W′field. Results: There were no significant differences in absolute 2-, 5-, and 12-minute MMP, CPfield, and W′field between in-season periods. Due to changes in body mass, relative 12-minute MMP was higher in late-season compared with early-season (P = .025), whereas relative CPfield was higher in mid- and late-season (P = .031 and P = .038, respectively) compared with early-season. There was a strong correlation (r = .77–.83) between CPtest and CPfield in early- and mid-season but not late-season. Bland–Altman plots and standard error of estimates showed good agreement between CPtest and in-season CPfield but not between W′test and W′field. Conclusion: These findings reveal that the power profile remains unchanged throughout the in-season, except for relative 12-minute MMP and CPfield in late-season. One pre-season and one in-season CP test are recommended to evaluate in-season CPfield and W′field.
Patrick C. Maughan, Niall G. MacFarlane, and Paul A. Swinton
Purpose: To quantify and describe relationships between subjective and external measures of training load in professional youth soccer players. Methods: Data from differential ratings of perceived exertion (dRPE) and 7 measures of external training load were collected from 20 professional youth soccer players over a 46-week season. Relationships were described by repeated-measures correlation, principal component analysis, and factor analysis with oblimin rotation. Results: Significant positive (.44 ≤ r ≤ .99; P < .001) within-individual correlations were obtained across dRPE and all external training load measures. Correlation magnitudes were found to decrease when training load variables were expressed per minute. Principal component analysis provided 2 components, which described 83.3% of variance. The first component, which described 72.9% of variance, was heavily loaded by all measures of training load, while the second component, which described 10.4% of the variance, appeared to have a split between objective and subjective measures of volume and intensity. Exploratory factor analysis identified 4 theoretical factors, with correlations between factors ranging from .5 to .8. These factors could be theoretically described as objective volume, subjective volume, objective running, and objective high-intensity measures. Removing dRPE measures from the analysis altered the structure of the model, providing a 3-factor solution. Conclusions: The dRPE measures are significantly correlated with a range of external training load measures and with each other. More in-depth analysis showed that dRPE measures were highly related to each other, suggesting that, in this population, they would provide practitioners with similar information. Further analysis provided characteristic groupings of variables.
Thimo Wiewelhove, Constantin Thase, Marcel Glahn, Anthony Hessel, Christoph Schneider, Laura Hottenrott, Tim Meyer, Michael Kellmann, Mark Pfeiffer, and Alexander Ferrauti
Purpose: To identify whether the use of active recovery (ACT) the day after high-intensity interval training (HIIT) benefits recovery and to assess whether individual responses to ACT are repeatable. Methods: Eleven well-trained, male intermittent-sport athletes (age: 25.5 ± 1.8 y) completed 4 HIIT sessions, each separated by a 2-week washout period. Of the 4 sessions, 2 were followed by passive recovery (PAS) and 2 by 60 minutes of moderate biking (ACT) 24 hours postexercise in the following sequences: ACT→PAS→ACT→PAS or PAS→ACT→PAS→ACT. Before and after HIIT and after 24 and 48 hours of recovery, maximal voluntary isometric strength (MVIC), countermovement jump height (CMJ), tensiomyographic markers of muscle fatigue (TMG), serum concentration of creatine kinase (CK), muscle soreness (MS), and perceived stress state (PS) were determined. Results: A 3-way repeated-measure analysis of variance with a triple-nested random effects model revealed a significant (P < .05) fatigue-related time effect of HIIT on markers of fatigue (MVIC↓; CMJ↓; TMG↑; CK↑; MS↑; PS↑). No significant (P > .05) main effect of recovery strategy was detected. In 9 subjects, the individual results revealed inconsistent and nonrepeatable responses to ACT, while a consistent and repeatable positive or negative response to ACT was found in 2 individuals. Conclusions: The repeated failure of ACT to limit the severity of fatigue was found both at the group level and with most individuals. However, a small percentage of athletes may be more likely to benefit repeatedly from either ACT or PAS. Therefore, the use of ACT should be individualized.
Brandon J. Shad, Janice L. Thompson, James Mckendry, Andrew M. Holwerda, Yasir S. Elhassan, Leigh Breen, Luc J.C. van Loon, and Gareth A. Wallis
The impact of resistance exercise frequency on muscle protein synthesis rates remains unknown. The aim of this study was to compare daily myofibrillar protein synthesis rates over a 7-day period of low-frequency (LF) versus high-frequency (HF) resistance exercise training. Nine young men (21 ± 2 years) completed a 7-day period of habitual physical activity (BASAL). This was followed by a 7-day exercise period of volume-matched, LF (10 × 10 repetitions at 70% one-repetition maximum, once per week) or HF (2 × 10 repetitions at ∼70% one-repetition maximum, five times per week) resistance exercise training. The participants had one leg randomly allocated to LF and the other to HF. Skeletal muscle biopsies and daily saliva samples were collected to determine myofibrillar protein synthesis rates using 2H2O, with intracellular signaling determined using Western blotting. The myofibrillar protein synthesis rates did not differ between the LF (1.46 ± 0.26%/day) and HF (1.48 ± 0.33%/day) conditions over the 7-day exercise training period (p > .05). There were no significant differences between the LF and HF conditions over the first 2 days (1.45 ± 0.41%/day vs. 1.25 ± 0.46%/day) or last 5 days (1.47 ± 0.30%/day vs. 1.50 ± 0.41%/day) of the exercise training period (p > .05). Daily myofibrillar protein synthesis rates were not different from BASAL at any time point during LF or HF (p > .05). The phosphorylation status and total protein content of selected proteins implicated in skeletal muscle ribosomal biogenesis were not different between conditions (p > .05). Under the conditions of the present study, resistance exercise training frequency did not modulate daily myofibrillar protein synthesis rates in young men.