Effects of training volume on sleep, psychological, and selected physiological profiles of elite female swimmers

Habitual Nocturnal Sleep, Napping Behavior, and Recovery Following Training and Competition in Elite Water Polo: Sex-Related Effects

PURPOSE

To examine nocturnal sleep patterns, napping behaviors, and subjective wellness responses of elite water polo players within an in-season week and to identify whether sleeping patterns differ between men and women.

METHODS

Sleep characteristics of 10 male and 17 female professional water polo players were objectively assessed during 1 week of the in-season period, including 5 training days, 1 match day, and 1 day of rest. Internal load (rating of perceived exertion × duration of training or match) was assessed 30 minutes posttraining or postmatch, and the total quality of recovery was recorded every morning. A series of multilevel models were used to analyze the data.

RESULTS

Time in bed and wake-up time were earlier on both training (P < .001) and rest days (P < .001) than on the day of the match. Internal workload did not predict any of the players' sleeping patterns. Midday naps predicted less time in bed (P = .03) and likely less sleep time (P = .08). The total quality of recovery was predicted only by the total sleep time (P < .01). Women exhibited higher sleep efficiency (P < .001), less waking after sleep onset (P = .01), and a lower number of awakenings (P = .02) than men.

CONCLUSIONS

The current results indicate that the nocturnal sleep patterns of elite water polo players are not associated with internal load and that women display better nocturnal sleep quality compared with men. As long naps interfere with nocturnal sleep, and total nocturnal sleep time predicts total quality of recovery, we suggest that athletes follow hygiene sleep strategies to facilitate adequate nocturnal sleep and next-day recovery.

Routine, Routine, Routine: Sleep Regularity and its Association with Sleep Metrics in Professional Rugby Union Athletes

BACKGROUND

Maintaining a consistent sleep and wake time is often reported as a key component of circadian rhythmicity and quality sleep. However, the impact of sleep onset and offset time variability on overall sleep outcomes are underreported in elite athlete populations. This study investigated the relationship between sleep onset and offset time variability using the sleep regularity index (SRI) and measures of sleep and well-being in professional rugby union athletes. Twenty-three professional male rugby union athletes (mean ± SD, age: 23 ± 3 y) underwent sleep monitoring via wrist actigraphy for three weeks during a pre-season phase of training and completed a daily wellness questionnaire. Median SRI was calculated and used to stratify the trainees into two quantile groups: >76.4 SRI (Regular, n = 11) and < 76.4 SRI (Irregular, n = 12).

RESULTS

The regular sleep group showed significantly longer total sleep duration (p = 0.02, d = 0.97) compared to the irregular group (7:42 ± 0:29 vs. 7:18 ± 0:20 h: min per night, respectively). Furthermore, while not statistically significant, the regular sleep group showed greater sleep efficiency and less wake episodes compared to irregular sleepers, as demonstrated by moderate effect sizes (d = 0.71 and 0.69, respectively).

CONCLUSIONS

The results from this study indicate that minimizing variability in sleep onset and offset time is beneficial for increasing sleep duration and may improve sleep efficiency during pre-season training in elite male rugby union athletes. This study provides evidence for the importance of including sleep-wake routines as a key component of sleep education interventions.

Increased training load promotes sleep propensity and slow-wave sleep in endurance runners: Can a high-heat-capacity mattress topper modulate this effect?

The present study aimed to: (1) investigate sleep architecture in response to an overload training and taper periods among endurance runners; and (2) assess the sleep benefits of a high-heat-capacity mattress topper. Twenty-one trained male endurance runners performed a 2-week usual training regimen (baseline) followed by 2-week overload and taper periods. From overload to the end of the taper period, they were assigned into two groups based on the mattress topper used: high-heat-capacity mattress topper (n = 11) or low-heat-capacity mattress topper (n = 10). Training load was assessed daily using the session rating of perceived exertion. Following each period, sleep was monitored by polysomnography, and nocturnal core body temperature was recorded throughout the night. Irrespective of the group, awakening episodes > 5 min decreased following overload compared with baseline (-0.48, p = 0.05). Independently of mattress topper, each 100 A.U. increase in 7-day training load prior to polysomnographic recording was associated with higher slow-wave sleep proportion (β = +0.13%; p = 0.05), lower sleep-onset latency (β = -0.49 min; p = 0.05), and a reduction in the probability of transition from N1 sleep stage to wakefulness (β = -0.12%; p = 0.05). Sleeping on a high-heat-capacity mattress topper did not affect any sleep variable compared with a low-heat-capacity mattress topper. Increased training loads promote slow-wave sleep and sleep propensity, highlighting the adaptative nature of sleep to diurnal activity and the role of sleep in physiological recovery. Further studies are required on the potential benefits of high-heat-capacity mattress toppers on sleep architecture among athletes.

Sleep patterns before and after competition: A real-world examination of elite athletes

Good sleep before and after competitions is crucial to cognitive, physiological performance and recovery. Yet, elite athletes face a unique set of challenges when acquiring good sleep before and after competitions, and indeed commonly report sleep problems when it matters most. This study examined the sleep of elite athletes before and after competition compared to before and after free days. A total of 1808 unique nights of actigraphy (n = 1495) and sleep diary (n = 1335) data from elite Australian Football League and National Rugby League male athletes (N = 85, M-age = 24.4 ± 3.6) were collected and analysed using multi-level mixed models. On nights before competitions, athletes advanced sleep timings (p < .001, d = 0.63) and increased total sleep time (p < .001, d = 0.65) compared to nights before free days. On nights after competitions, athletes delayed sleep timings (p < .001, d = 1.64), reduced total sleep time (p < .001, d = 1.28), and had significantly worse quality sleep (p < .001, d = 0.71) compared to nights after free days. Sleep was especially worse following night competitions. While elite athletes and organisations may be implementing effective sleep strategies to optimise sleep the night before competitions, strategies to improve sleep after competitions may be lacking. We discuss potential factors contributing to this asymmetry and propose areas for research moving forward.

Daytime sleepiness in Chinese professional, semi professional and students soccer players in the Shanghai lockdown

PURPOSE

April-May 2021 Shanghai city was under strict lockdown. Soccer players suffered from the restrictions, being unable to train and have a social life. The aim of this study was to compare differences in daytime sleepiness between genders and qualification levels in a cohort university Chinese soccer player under 0 Covid policy restrictions in the urban area of Shanghai.

METHODS

491 questionnaires of Epworth Sleepiness Scales (ESS) were compiled online by male and female Soccer Students (SS), Semi-Professional players (SP) and Professional Players (PP) during the ongoing restriction measures post Shanghai lockdown. ANOVA was performed for players levels and gender.

RESULTS

Significant differences were found between the 3 levels and between males and females. PP showed a very low score in the ESS (5,97) well below the threshold of 8 for daytime sleepiness, while SS and SP showed an ESS score above the threshold. Female showed higher scores in comparison to males. Differences between males and females reflect the confinement conditions in the ESS items, showing more difference in the item of ESS which are related with indoor situations.

CONCLUSIONS

This study shows the first data on sleepiness in Chinese soccer players of different level of qualification immediately post lockdown condition. Professional male's players sleepiness was lower, than females, SS and SP after the exceptional lockdown measures. The reasons can reside in the more ordered lifestyle of PP in comparison to SS and SP, which mitigated the effects of the lockdown. Our results suggest that measures to improve sleep in females' soccer player should be adopted if these exceptional conditions will happen again.

Comparing Perceived Sleep Quality, Practices, and Behaviors of Male and Female Elite Rugby Union Athletes with the Use of Sleep Questionnaires

Objective  To evaluate the differences in subjective sleep quality, quantity, and behaviors among male and female elite rugby union athletes through two common sleep questionnaires. Materials and Methods  A sample of 38 male and 27 female elite rugby union athletes filled out the Athlete Sleep Behavior Questionnaire (ASBQ) and the Pittsburgh Sleep Quality Index (PSQI). Global scores and individual items for each questionnaire were compared to assess differences between sexes. Results  Male athletes reported significantly longer sleep duration (7 h 50 m ± 50 m versus 7h 12 m ± 58 m respectively; p ≤ 0.01; d  = 0.70) and higher habitual sleep efficiency (88% versus 83% respectively; p  < 0.05; d  = 0.54) when compared with female athletes. Individual items of the ASBQ revealed significant differences between male and female athletes for five questions. Male athletes displayed higher instances of taking stimulants before training or competition and consuming alcohol within 4 hours of going to bed. Conversely, female athletes expressed greater thought or worry while in bed and a higher instance of training late at night. Discussion  Male athletes displayed better self-reported sleep quality and quantity than female athletes; however, the present study highlighted that male and female elite rugby union athletes face specific challenges that differ. It appears that the differences observed between male and female elite rugby union athletes may be due to differing levels of professionalism or differences in training or competition schedules.

Sleep and Sport Performance

SUMMARY

Elite athletes and coaches believe sleep is the most important recovery strategy and widely consider it critical to optimal performance. Despite this perceived importance, there are numerous circumstances that can reduce sleep quantity and quality in athletic populations. Because of the effects of sleep loss on various physical, neurophysiological, and cognitive parameters, such perturbations can have consequences for performance and recovery outcomes. Although peer-reviewed literature examining the interaction between sleep, performance, and recovery in athletes is increasing, understanding of these issues remains equivocal. Perhaps most pertinently, the effect of sleep on sport performance does not align with a one-size-fits-all approach and rather depends on numerous factors such as type of sport, scheduling, time of the season, and the intraindividual requirements for sleep. The relationship between brain plasticity and memory, which in turn can influence learning processes and long-term memory consolidation, suggests that sleep may play an important role in learning new skills and tactics for both elite and developing athletes. The aim of this special issue review was to analyze the evidence of sleep loss on sport performance and recovery, with a specific focus on elite athletes. An assessment of these sleep-compromising situations that elite athletes may face during a typical season and practical considerations for alleviating these issues is also provided to further the understanding for medical professionals, scientists, and applied sporting practitioners alike.

Sleep disorders in dermatology - a comprehensive review

Sleep is a normal physiological process that accounts for approximately one third of a person's life. Disruption of the normal sleep cycle, which maintains physiological homeostasis, can lead to pathology. It is not known whether sleep disturbance causes skin disease or skin disease causes sleep impairment, but a bidirectional influence is suspected. We have compiled the data from published articles on "sleep disorders in dermatology" in PubMed Central from July 2010 to July 2022 (with the option "full text available") and provide an overview of sleep disorders associated with dermatological conditions and certain drugs used in dermatology as well as sleep disturbances for which some drugs used can cause itch or dermatological issues. Atopic dermatitis, eczema and psoriasis have been shown to be exacerbated by sleep problems and vice versa. Sleep deprivation, night-time pruritus and disrupted sleep cycles are often used to assess treatment response and quality of life in these conditions. Some medications used primarily for dermatological conditions have also been associated with alterations in the sleep-wake cycle. Addressing patients sleep disorders should be an integral part of the management of dermatological conditions. More studies are needed to further investigate the influence of sleep and skin disorders.

The Psychology of Athletic Tapering in Sport: A Scoping Review

Taper is a common training strategy used to reduce fatigue and enhance athletic performance. However, currently, no review has summarised what psychological research has been conducted examining taper, what this research shows and what future research needs to be undertaken to extend the field. Consequently, a scoping review was conducted with three aims: (a) to determine the characteristics of psychological research examining taper, (b) to summarise psychological research collected during taper with adult athletes and coaches, and (c) to identify gaps in psychological research examining taper. Forty-eight articles were identified following an exhaustive search strategy and charted following scoping review guidelines. Results showed most research was quantitative, used a longitudinal design, was conducted in swimming, triathlon, cycling or across multiple sports, and used a university-, regional- or national-level male athlete sample. Eight themes were developed to summarise the research: Mood, Perception of Effort, Perceived Fatigue and Wellness, Recovery-Stress, Taper as a Stressor, Stress Tolerance, Psychological Preparation and Cognitive Functioning. Additionally, four research recommendations were identified: (a) conducting exploratory research that examines the impact taper has on athletes' and coaches' competition preparation and stress experience, (b) asking more advanced psychological questions and conducting multi-disciplinary research, (c) including a more diverse participant sample in studies and (d) examining the impact of psychological interventions during taper. Overall, this scoping review has highlighted the limited research examining the psychology of taper and the need for focused research that asks more complex questions across diverse populations.

Intensified Olympic Preparation: Sleep and Training-Related Hormonal and Immune Responses in Water Polo

PURPOSE

To investigate whether sleeping activity, hormonal responses, and wellness are altered in elite water polo players during their preparation toward the Tokyo Olympics.

METHODS

Eight elite-level water polo players participated in 3 consecutive training phases: (1) before the commencement of a residential-based conditioning camp (PRE-CAMP; 3 d), (2) residential-based conditioning camp (5 d), and (3) a congested period of training and competition (POST-CAMP; 8 d). Nocturnal sleep was monitored for 14 consecutive days in PRE-CAMP (2 d), CAMP (5 d), and POST-CAMP (7 d). Postawakening salivary cortisol, immunoglobulin-A, and subjective wellness were measured during PRE-CAMP, CAMP, and POST-CAMP, and internal training/match load (ITL) was calculated daily. The averaged values for dependent variables were compared among training phases and analyzed using linear mixed models.

RESULTS

At CAMP compared with PRE-CAMP, ITL was higher (P < .01), and sleep onset and offset were earlier (P < .01). At this period, sleep interruptions and salivary cortisol were higher (P < .01, d = 1.6, d = 1.9, respectively), and subjective wellness was worsened (P < .01, d = 1.3). At POST-CAMP, the reduction of workload was followed by increased sleep efficiency, reduced sleep interruptions, and moderately affected salivary cortisol, yet overall wellness remained unaltered. In POST-CAMP, 2 of the players demonstrated severe symptoms of illness.

CONCLUSIONS

At the highest level of the sport and prior to the Olympics, large increments in workload during a training camp induced meaningful sleep interruptions and salivary cortisol increases, both of which were reversed at POST-CAMP. We suggest that the increased workload alongside the inadequate recovery affects sleep patterns and may increase the risk of infection.

Case Report: Effect of low energy availability and training load on sleep in a male combat sport athlete

Purpose

The aim of this case report was to describe the sleep responses in a male combat sport athlete, who was engaging in both chronic (CWL) and acute (AWL) weight loss practices in order to reduce body mass for a national competition.

Methods

During the first seven weeks of training (Phases 1 and 2), the athlete adhered to a daily energy intake (EI) equating to their resting metabolic rate (1700 kcal·day^-1) followed by a reduction in EI (915-300 kcal·day^-1) in the 5 days before weighing in (Phase 3). Nocturnal sleep was monitored throughout the 8-week training period using wristwatch actigraphy and frequent measurements of body mass/composition, daily exercise energy expenditure and training load (TL) were taken.

Results

The athlete was in a state of low energy availability (LEA) during the entire training period. There was a very large decrease in LEA status during phase 3 compared with phases 1 and 2 (3 vs. 20 kcal·kgFFM·day^-1) and there was a small decrease in TL during phase 3 compared with phase 2 (410 vs. 523 AU). The athlete's sleep efficiency increased throughout the training period, but total sleep time displayed a small to moderate decrease in phase 3 compared with phases 1 and 2 (386 vs. 429 and 430 min). However, correlational analysis demonstrated trivial to small, non-significant relationships between sleep characteristics and the athlete's LEA status and TL.

Conclusion

These findings suggest that CWL and AWL practices that cause fluctuations in LEA and TL may be implemented without compromising the sleep of combat sport athletes.

SLEEP RESPONSES OF YOUNG SWIMMERS TO TRAINING LOAD AND RECOVERY DURING TAPERING

ABSTRACT Introduction: Tapering is a decisive phase in planning a young swimmer's preparation for competition. During this period, not only training loads, but also recovery, which includes sleep quality, must be constantly monitored. Objective: This study aims to investigate sleep behavior as a variable directly influenced by training load during the tapering phase of training for young swimmers. Methods: A polysomnography test was performed at the beginning of the tapering phase, as a baseline for sleep variables. In each daily training session, the overload and recovery variables were measured. The internal training load was evaluated in the PSE session and the external load by quantifying the training. The recovery variables were divided into the recovery variable, assessed using the TQR questionnaire, and sleep variables, which included sleepiness, scored using the Karolinska scale, and sleep behavior, using an actigraph and a sleep diary. Conclusion: It is concluded that there is no significant influence between training loads and sleep variables. However, a strong association was observed between TST and EL (External load), in the irregular sleep group. Level of evidence III, Study of behavior.

Primum non nocere; It's time to consider altitude training as the medical intervention it actually is!

Sleep is one of the most important aspects of recovery, and is known to be severely affected by hypoxia. The present position paper focuses on sleep as a strong moderator of the altitude training-response. Indeed, the response to altitude training is highly variable, it is not a fixed and classifiable trait, rather it is a state that is determined by multiple factors (e.g., iron status, altitude dose, pre-intervention hemoglobin mass, training load, and recovery). We present an overview of evidence showing that sleep, and more specifically the prolonged negative impact of altitude on the nocturnal breathing pattern, affecting mainly deep sleep and thus the core of physiological recovery during sleep, could play an important role in intra- and interindividual variability in the altitude training-associated responses in professional and recreational athletes. We conclude our paper with a set of suggested recommendations to customize the application of altitude training to the specific needs and vulnerabilities of each athlete (i.e., primum non nocere). Several factors have been identified (e.g., sex, polymorphisms in the TASK2/KCNK5, NOTCH4 and CAT genes and pre-term birth) to predict individual vulnerabilities to hypoxia-related sleep-disordered breathing. Currently, polysomnography should be the first choice to evaluate an individual's predisposition to a decrease in deep sleep related to hypoxia. Further interventions, both pharmacological and non-pharmacological, might alleviate the effects of nocturnal hypoxia in those athletes that show most vulnerable.

Effect of Training/Competition Load and Scheduling on Sleep Characteristics in Professional Rugby League Athletes

ABSTRACT

Conlan, G, McLean, B, Kemp, J, and Duffield, R. Effect of training/competition load and scheduling on sleep characteristics in professional rugby league athletes. J Strength Cond Res 36(12): 3390-3397, 2022-This study examined the effect of training/competition load, scheduling, and associated factors on sleep behavior in professional rugby league athletes. Sleep characteristics were assessed in 26 professional rugby league athletes using wrist-mounted actigraphy and nightly sleep diaries. Sleep actigraphy assessed the time into and out of bed, the duration in bed, sleep duration, efficiency, latency, wake after sleep onset, number of awakenings, and the awakening length. Sleep was measured during 3 different weeks: (a) preseason low training load (TL) (2,356 ± 322 AU), (b) preseason high TL (3,542 ± 445 AU), and (c) in-season match week (1,526 ± 409 AU). The influences of internal TL (session rating of perceived exertion load), training schedule, age, and training location on sleep behavior were analyzed. Repeated-measures 2-way analysis of variance and effect size analyses (d) compared sleep variables between training weeks. The mean weekly sleep duration was significantly lower during high TL week (5 hours 53minutes ± 14 min/night; p = 0.015, d = 0.59) compared with the low TL (6 hours 25minutes ± 8 min·night -1 ) or match weeks (6 hours 26minutes ± 10 min·night -1 ; p = 0.02, d = 2.04). Reduced sleep duration in the high TL week occurred alongside earlier out-of-bed times compared with the low TL ( p = 0.003, d = 1.46) and match weeks ( p = 0.001, d = 5.99). Regardless, the lowest sleep duration was on match night ( p = 0.0001, d = 1.22). Earlier training start times resulted in earlier wake times ( p = 0.003, d = 4.84), shorter in-bed durations ( p = 0.0001, d = 0.62), and shorter sleep durations ( p = 0.002, d = 0.32). Younger athletes slept for longer durations ( p = 0.029, d = 1.70) and perceived their sleep quality to be superior ( p = 0.006, d = 14.94) compared with older athletes. Sleep attained by rugby league athletes is influenced by training and competition schedules, with early training start times and late-night matches being primary drivers of sleep behavior. Coaching staff should have awareness surrounding the implications of training and playing schedules on athlete sleeping patterns.

COVID-19 Lockdowns: A Worldwide Survey of Circadian Rhythms and Sleep Quality in 3911 Athletes from 49 Countries, with Data-Driven Recommendations

Objective

In a convenience sample of athletes, we conducted a survey of COVID-19-mediated lockdown (termed ‘lockdown’ from this point forward) effects on: (i) circadian rhythms; (ii) sleep; (iii) eating; and (iv) training behaviors.

Methods

In total, 3911 athletes [mean age: 25.1 (range 18–61) years, 1764 female (45%), 2427 team-sport (63%) and 1442 elite (37%) athletes] from 49 countries completed a multilingual cross-sectional survey including the Pittsburgh Sleep Quality Index and Insomnia Severity Index questionnaires, alongside bespoke questions about napping, training, and nutrition behaviors.

Results

Pittsburgh Sleep Quality Index (4.3 ± 2.4 to 5.8 ± 3.1) and Insomnia Severity Index (4.8 ± 4.7 to 7.2 ± 6.4) scores increased from pre- to during lockdown (p < 0.001). Pittsburgh Sleep Quality Index was predominantly influenced by sleep-onset latency (p < 0.001; + 29.8%), sleep efficiency (p < 0.001; − 21.1%), and total sleep time (p < 0.001; − 20.1%), whilst Insomnia Severity Index was affected by sleep-onset latency (p < 0.001; + 21.4%), bedtime (p < 0.001; + 9.4%), and eating after midnight (p < 0.001; + 9.1%). During lockdown, athletes reported fewer training sessions per week (− 29.1%; d = 0.99). Athletes went to bed (+ 75 min; 5.4%; d = 1.14) and woke up (+ 150 min; 34.5%; d = 1.71) later during lockdown with an increased total sleep time (+ 48 min; 10.6%; d = 0.83). Lockdown-mediated circadian disruption had more deleterious effects on the sleep quality of individual-sport athletes compared with team-sport athletes (p < 0.001; d = 0.41), elite compared with non-elite athletes (p = 0.028; d = 0.44) and older compared with younger (p = 0.008; d = 0.46) athletes.

Conclusions

These lockdown-induced behavioral changes reduced sleep quality and increased insomnia in athletes. Data-driven and evidence-based recommendations to counter these include, but are not limited to: (i) early outdoor training; (ii) regular meal scheduling (whilst avoiding meals prior to bedtime and caffeine in the evening) with appropriate composition; (iii) regular bedtimes and wake-up times; and (iv) avoidance of long and/or late naps.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40279-021-01601-y.

Cumulative Effects of a Week's Training Loads on Shoulder Physical Qualities and Wellness in Competitive Swimmers

BACKGROUND

Competitive swimmers are exposed to high training loads, which can contribute to the development of shoulder pain. There is a lack of research investigating the interactions between the accumulation of training loads and factors associated to shoulder pain in swimmers.

PURPOSE

The primary objective was to analyze the changes in shoulder physical qualities and wellness factors over a week of training in competitive swimmers. A secondary objective was to compare the changes in these variables between different swim-training volumes performed during the week.

DESIGN

Cross-sectional.

METHODS

Thirty-one national and regional-level swimmers were included (18 females, 13 males; age= 15.5 ± 2.2 years). Active shoulder external rotation (ER) range of motion (ROM), shoulder-rotation isometric torque, and wellness factors using the Hooper questionnaire were measured twice over the week: a baseline measurement (before Monday´s training session) and a follow-up during the week. Participants were divided into a high-volume group (HVG) and low-volume group (LVG) based on the day follow-up was performed. HVL (n= 15) was tested at the end of the training week (after Saturday´s session) and LVG (n= 16) during the week (after Thursday or Friday´s session). Rating of perceived exertion (RPE) of the whole week was recorded after the follow-up session.

RESULTS

At follow-up, the LVG averaged a volume of 26.2 ± 2.2 km, whereas the HVG averaged a volume of 37.5 ± 3.7 km. LVG and HVG participants decreased active shoulder ER ROM on dominant (p= 0.002; p= 0.006) and nondominant sides (p= 0.001; p= 0.004), displayed increased muscular soreness (p= 0.001; p= 0.007) and worsened overall wellness (p< 0.001; p= 0.010). Fatigue (p= 0.008) and poor sleep quality were increased (p= 0.023) in HVG, but not in LVG. There were no changes in shoulder-rotation torque and stress in any group. Regarding between-groups differences, only weekly RPE was higher (p= 0.004) in HVG.

CONCLUSIONS

The accumulation of training loads over the week negatively affect physical and wellness factors. Greater swim-volumes were associated with an increase perception of training loads. The regular monitoring of multiple factors to assess swimmers' response to training might be necessary.

LEVEL OF EVIDENCE

3.

International survey of training load monitoring practices in competitive swimming: How, what and why not?

OBJECTIVE

The purpose of this study is to identify the training load (TL) monitoring practices employed in real-world competitive swimming environments. The study explores data collection, analysis and barriers to TL monitoring.

DESIGN

Cross-sectional.

SETTING

Online survey platform.

PARTICIPANTS

Thirty-one responders working in competitive swimming programmes.

MAIN OUTCOME MEASURES

Methods of data collection, analysis, level of effectiveness and barriers associated with TL monitoring.

RESULTS

84% of responders acknowledged using TL monitoring, with 81% of responders using a combination of both internal and external TL, in line with current consensus statements. Swim volume (mileage) (96%) and session rate of perceived exertion (sRPE) (92%) were the most frequently used, with athlete lifestyle/wellness monitoring also featuring prominently. Thematic analysis highlighted that "stakeholder engagement", "resource constraints" or "functionality and usability of the systems" were shared barriers to TL monitoring amongst responders.

CONCLUSIONS

Findings show there is a research-practice gap. Future approaches to TL monitoring in competitive swimming should focus on selecting methods that allow the same TL monitoring system to be used across the whole programme, (pool-based training, dryland training and competition). Barriers associated with athlete adherence and coach/National Governing Body engagement should be addressed before a TL system implementation.

Sleep, health, and well-being in elite athletes from different sports, before, during, and after international competition

Objectives: Limited research has been conducted on sleep problems in elite athletes at international competition, and how this relates to their general health and well-being. Methods: Sixty-five elite international athletes (37 males, 28 females, 21.8 ± 2.1 years) from different sports completed validated sleep (Athlete Sleep Screening Questionnaire), health (Subjective Health Complaints Inventory) and well-being (Sports Profile of Mood States) questionnaires; 1 month pre-competition, at the end of international competition, and 1 month post-competition. Results: Twenty-three percent of the elite athletes were identified as having a moderate or severe clinically significant sleep problem during competition, with 82% reporting less than 8 h of sleep per night. Athletes with a moderate or severe clinically significant sleep problem during competition had significantly greater general health complaints (p = 0.002), mood disturbance (p = 0.001) and poorer sleep hygiene (p = 0.002). Swimmers had more sleep difficulty pre and during competition compared to athletics and soccer (p = 0.009). Conclusion: Sleep disturbance during international competition is common and associated with poorer health and lower mood. Swimmers may be more at risk of sleep difficulty pre and during competition compared to those competing in athletics and soccer. Sleep services may be required to support elite athletes at international competition.

The impact of daytime napping on athletic performance - A narrative review

Mid-day napping has been recommended as a countermeasure against sleep debt and an effective method for recovery, regardless of nocturnal sleep duration. Herein, we summarize the available evidence regarding the influence of napping on exercise and cognitive performance as well as the effects of napping on athletes' perceptual responses prior to or during exercise. The existing studies investigating the influence of napping on athletic performance have revealed equivocal results. Prevailing findings indicate that following a normal sleep night or after a night of sleep loss, a mid-day nap may enhance or restore several exercise and cognitive performance aspects, while concomitantly provide benefits on athletes' perceptual responses. Most, but not all, findings suggest that compared to short-term naps (20-30 min), long-term ones (>35-90 min) appear to provide superior benefits to the athletes. The underlying mechanisms behind athletic performance enhancement following a night of normal sleep or the restoration after a night of sleep loss are not clear yet. However, the absence of benefits or even the deterioration of performance following napping in some studies is likely the result of sleep inertia. The present review sheds light on the predisposing factors that influence the post-nap outcome, such as nocturnal sleep time, mid-day nap duration and the time elapsed between the end of napping and the subsequent testing, discusses practical solutions and stimulates further research on this area.

Contemporary Variables that Impact Sleep and Development in Female Adolescent Swimmers and Gymnasts

The effects of sleep on elite athletes in late adolescence and early adulthood have been well documented in a myriad of sports. However, there is underrepresentation of pre-pubertal and young female adolescent athlete research between the ages of 11-17, and specifically female gymnast and swimmers. Neglecting to understand how high energy demand at a young age relates to sleep and restoration may lead to developmental ramifications for this group, as they display physiological dysfunctions like delayed puberty, amenorrhea and are at risk for the female athlete triad or components of the triad. This review aims to summarize the contemporary variables of blue light emitting screens, social media, and caffeine on quality and quantity of sleep in young athletes while identifying gaps in the literature on how these factors impact the target group of young female swimmers and gymnasts.  The implications of this work include sleep hygiene recommendations for increasing duration and quality of sleep, as well as future research with respect to electronic device usage, social media participation, caffeine consumption, and sport engagement in female early adolescent athletes.

Slow Wave Sleep of Elite and Nonelite Gymnasts Is Influenced by Weekly Training Hours, Not by Fitness Level

PURPOSE

This study aimed to determine the influencing factors of potential differences in sleep architecture between elite (EG) and nonelite (NEG) female artistic gymnasts.

METHODS

Twelve EG (15.1 [1.5] y old) and 10 NEG (15.3 [1.8] y old) underwent a nocturnal polysomnography after a regular training day (5.8 [0.8] h vs 2.6 [0.7] h), and, on a separate test day, they performed an incremental treadmill test after a rest day in order to determine physical fitness status. A multiple linear regression assessed the predictive value of training and fitness parameters toward the different sleep phases. Total sleep time and sleep efficiency (proportion of time effectively asleep to time in bed), as well as percentage of nonrapid eye movement sleep phase 1 (NREM1) and 2 (NREM2), slow wave sleep (SWS), and rapid eye movement sleep (REM), during a single night were compared between EG and NEG using an independent-samples t test.

RESULTS

Peak oxygen uptake influenced NREM1 (β = 1.035, P = .033), while amount of weekly training hours predicted SWS (β = 1.897, P = .032). No differences were documented between EG and NEG in total sleep time and sleep efficiency. SWS was higher in EG (36.9% [11.4%]) compared with NEG (25.9% [8.3%], P = .020), compensated by a lower proportion of NREM2 (38.7% [10.2%] vs 48.4% [6.5%], P = .017), without differences in NREM1 and REM.

CONCLUSIONS

The proportion of SWS was only predicted by weekly training hours and not by training hours the day of the polysomnography or physical fitness, while NREM1 was linked with fitness level. Sleep efficiency did not differ between EG and NEG, but in EG, more SWS and less NREM2 were identified.

Deconstructing athletes' sleep: A systematic review of the influence of age, sex, athletic expertise, sport type, and season on sleep characteristics

PURPOSE

This systematic review aimed to describe objective sleep parameters for athletes under different conditions and address potential sleep issues in this specific population.

METHODS

PubMed and Scopus were searched from inception to April 2019. Included studies measured sleep only via objective evaluation tools such as polysomnography or actigraphy. The modified version of the Newcastle-Ottawa Scale was used for the quality assessment of the studies.

RESULTS

Eighty-one studies were included, of which 56 were classified as medium quality, 5 studies as low quality, and 20 studies as high quality. A total of 1830 athletes were monitored over 18,958 nights. Average values for sleep-related parameters were calculated for all athletes according to sex, age, athletic expertise level, training season, and type of sport. Athletes slept on average 7.2 ± 1.1 h/night (mean ± SD), with 86.3% ± 6.8% sleep efficiency (SE). In all datasets, the athletes' mean total sleep time was <8 h. SE was low for young athletes (80.3% ± 8.8%). Reduced SE was attributed to high wake after sleep onset rather than sleep onset latency. During heavy training periods, sleep duration and SE were on average 36 min and 0.8% less compared to pre-season and 42 min and 3.0% less compared to in-season training periods, respectively.

CONCLUSION

Athletes' sleep duration was found to be short with low SE, in comparison to the general consensus for non-athlete healthy adults. Notable sleep issues were revealed in young athletes. Sleep quality and architecture tend to change across different training periods.

Sleep and Performance during a Preseason in Elite Rugby Union Athletes

Background: Preseason training optimises adaptations in the physical qualities required in rugby union athletes. Sleep can be compromised during periods of intensified training. Therefore, we investigated the relationship between sleep quantity and changes in physical performance over a preseason phase in professional rugby union athletes. Methods: Twenty-nine professional rugby union athletes (Mean ± SD, age: 23 ± 3 years) had their sleep duration monitored for 3 weeks using wrist actigraphy. Strength and speed were assessed at baseline and at week 3. Aerobic capacity and body composition were assessed at baseline, at week 3 and at week 5. Participants were stratified into 2 groups for analysis: <7 h 30 min sleep per night (LOW, n = 15) and >7 h 30 min sleep per night (HIGH, n = 14). Results: A significant group x time interaction was determined for aerobic capacity (p = 0.02, d = 1.25) at week 3 and for skinfolds at week 3 (p < 0.01, d = 0.58) and at week 5 (p = 0.02, d = 0.92), in favour of the HIGH sleep group. No differences were evident between groups for strength or speed measures (p ≥ 0.05). Conclusion: This study highlights that longer sleep duration during the preseason may assist in enhancing physical qualities including aerobic capacity and body composition in elite rugby union athletes.

Effect of the Depth of Cold Water Immersion on Sleep Architecture and Recovery Among Well-Trained Male Endurance Runners

Introduction: The aim of the present study was to investigate the effect of the depth of cold water immersion (CWI) (whole-body with head immersed and partial-body CWI) after high-intensity, intermittent running exercise on sleep architecture and recovery kinetics among well-trained runners. Methods: In a randomized, counterbalanced order, 12 well-trained male endurance runners ( V . O₂max = 66.0 ± 3.9 ml·min^-1·kg^-1) performed a simulated trail (≈18:00) on a motorized treadmill followed by CWI (13.3 ± 0.2°C) for 10 min: whole-body immersion including the head (WHOLE; n = 12), partial-body immersion up to the iliac crest (PARTIAL; n = 12), and, finally, an out-of-water control condition (CONT; n = 10). Markers of fatigue and muscle damage-maximal voluntary isometric contraction (MVIC), countermovement jump (CMJ), plasma creatine kinase [CK], and subjective ratings-were recorded until 48 h after the simulated trail. After each condition, nocturnal core body temperature (T _core) was measured, whereas sleep and heart rate variability were assessed using polysomnography. Results: There was a lower T _core induced by WHOLE than CONT from the end of immersion to 80 min after the start of immersion (p < 0.05). Slow-wave sleep (SWS) proportion was higher (p < 0.05) during the first 180 min of the night in WHOLE compared with PARTIAL. WHOLE and PARTIAL induced a significant (p < 0.05) decrease in arousal for the duration of the night compared with CONT, while only WHOLE decreased limb movements compared with CONT (p < 0.01) for the duration of the night. Heart rate variability analysis showed a significant reduction (p < 0.05) in RMSSD, low frequency (LF), and high frequency (HF) in WHOLE compared with both PARTIAL and CONT during the first sequence of SWS. No differences between conditions were observed for any markers of fatigue and muscle damage (p > 0.05) throughout the 48-h recovery period. Conclusion: WHOLE reduced arousal and limb movement and enhanced SWS proportion during the first part of the night, which may be particularly useful in the athlete's recovery process after exercise. Future studies are, however, required to assess whether such positive sleep outcomes may result in overall recovery optimization.

Evidence That Sleep Is an Indicator of Overtraining during the Competition Phase of Adolescent Sprinters

Although sleep disturbance is a common complaint in overtrained athletes, the role of sleep in the overtraining process is not clear. This study aimed (i) to compare sleep efficiency/quantity at the start of a competition phase in elite adolescent sprinters who adapted to prior training with that in those who maladapt and (ii) to examine the influence of prior training, fatigue, and sleep on performance through a moderated mediation model. Fatigue (via Profile of Mood State) and internal training load (via session rating of perceived exertion and duration of training as volume) were measured in 20 sprinters (mean age: 15.9 ± 1.7 years) across 4 mesocycles (baseline (T1); preparatory (T2); precompetitive (T3); and competitive (T4) phases), over 26 weeks. Performances were assessed during the competitive period (T3, T4), while sleep was monitored (via actigraphy) for a week during T4. It was inferred that sprinters who had increasingly greater fatigue and concomitant decrements in performance (35%) were maladapted to training and the remaining sprinters who improved fatigue and performance (65%) were adapted to training. Sleep efficiency (91 ± 3% vs. 82 ± 3%, p < 0.001) and quantity (425 ± 33 min vs. 394 ± 20 min, p < 0.001) at the start of T4 were significantly greater in sprinters who adapted. Moreover, higher prior training volume (mean of T1 to T3 training volume) was associated with lower sleep efficiency at the start of T4 (R² = 0.55, p < 0.001) which was associated with poorer performance (R² = 0.82, p < 0.001). Fatigue moderated the indirect effect of prior training volume on performance through its moderation of the effect of sleep efficiency on performance (R² = 0.89, p < 0.001). Impaired sleep as a result of greater prior training volume may be related to performance decrements through fatigue. Athletes should improve sleep during periods of higher training volume to reduce fatigue for better adaptation to training.

The Association Between Sleep and In-Game Performance in Basketball Players

Purpose:To investigate the associations between sleep and competitive performance in basketball.Methods:A total of 7 semiprofessional, male players were monitored across the in-season. On nights prior to competition, sleep duration and quality were assessed using actigraphs and sleep diaries. The data were accumulated over 1 (night 1), 2 (nights 1–2 combined), 3 (nights 1–3 combined), and 4 (nights 1–4 combined) nights prior to competition. Performance was reported as player statistics (field goal and free-throw accuracy, rebounds, assists, steals, blocks, and turnovers) and composite performance statistics (offensive rating, defensive rating, and player efficiency). Linear regression analyses with cluster-robust standard errors using bootstrapping (1000 replications) were performed to quantify the association between sleep and performance.Results:The night before competition, subjective sleep quality was positively associated with offensive rating and player efficiency (P < .05).Conclusions:Strategies to increase subjective sleep quality the night before competition should be considered to increase the likelihood of successful in-game performance, given its association with composite performance metrics.

Sleep quality monitoring in individual sports athletes: parameters and definitions by systematic review

In the present review, we identify which instruments and parameters are used for sleep quality monitoring in individual sport athletes and which definitions were used for sleep quality parameters in this literature field. Systematic searches for articles reporting the qualitative markers related to sleep in team sport athletes were conducted in PubMed, Scopus and Web of Science online databases. The systematic review followed the Preferred Reporting Items for Systematic Reviews. The initial search returned 3316 articles. After the removal of duplicate articles, eligibility assessment, 75 studies were included in this systematic review. Our main findings were that the most widely used measurement instruments were Actigraphy (25%), Rating Likert Scales (16%) and Sleep Diary (13%). On sleep quality parameters (Sleep duration = 14%; Wake after sleep onset = 14%; Sleep Quality = 12%; Sleep Effciency = 11% and Sleep Latency = 9%), the main point is that there are different definitions for the same parameters in many cases reported in the literature. We conclude that the most widely used instruments for monitoring sleep quality were Actigraphy, Likert scales and Sleep diary. Moreover, the definitions of sleep parameters are inconsistent in the literature, hindering the understanding of the sleep-sport performance relationship.

A critical review on sleep assessment methodologies in athletic populations: factors to be considered

A growing body of research focus on athletes' sleep in order to investigate the effects of sleep in sports performance and recovery or the prevalence of sleep disorders in athletes. At the same time, several sleep monitoring tools have been developed and used in athletic populations for fulfilling these purposes. This review aimed to provide critical assessment to the most used by athletes' methodological approaches and compared them with the gold standard approach. Advantages and disadvantages of the various sleep monitoring tools were critically discussed. Literature related to aspects of athletes' sleep was reviewed. From the shortlisted studies, several factors that seem to affect sleep in athletes were identified using objective methods such as polysomnography/electroencephalography and actigraphy. These factors were associated to sleep (eg such as sleep environment, familiarization procedures and napping) and daily habits (eg nutrition, fluid consumption, alcohol and caffeine intake, tobacco use). The selected studies that evaluated sleep objectively were screened according the reporting rates of these variables. The majority of the screened studies were found to underreport these variables. Practical issues were addressed and recommendations about reporting sleep-related factors were made in order to improve studies' quality assessment and allow for more robust comparisons between studies.

Global Research Output on Sleep Research in Athletes from 1966 to 2019: A Bibliometric Analysis

This study examined sleep research in athletes published between 1966 and 2019, through a bibliometric analysis of research output in the Scopus database. Following a robust assessment of titles, the bibliometric indicators of productivity for studies included in the final analysis were: Distribution of publications and citations (excluding self-citations), top ten active journals, countries, institutions and authors, single- and multi-country collaboration, and 25 top-cited papers. Out of the 1015 papers, 313 were included in the final analysis. The majority of the papers were research articles (n = 259; 82.8%) and published in English (n = 295; 94.3%). From 2011, there was a dramatic increase in papers published (n = 257; 82.1%) and citations (n = 3538; 91.0%). The number of collaborations increased after 2001, with papers published through international (n = 81; 25.9%) and national (n = 192; 61.3%) collaboration. Australia was the most prolific country in terms of number of publications (n = 97; 31.0%), and citations (n = 1529; 15.8%). In conclusion, after the beginning of the twenty-first century, the scientific production on sleep research in athletes has seen significant growth in publication and citation output. Future research should focus on interventions to improve sleep in athletes.

Effect of an Innovative Mattress and Cryotherapy on Sleep after an Elite Rugby Match

INTRODUCTION

This study aimed to explore the relationship between elite rugby union match and postmatch sleep architecture and to investigate the effects of a high-heat capacity mattress (MAT) and a whole-body cryotherapy (WBC) session on postmatch sleep architecture.

METHODS

Nineteen elite male U23 rugby union players performed in three official matches, followed by three experimental conditions, in a randomized order: MAT, WBC, and no intervention (CONT). Match load was evaluated using GPS trackers and video analyses. Sleep architecture was assessed by polysomnography (PSG). Core body temperature (CBT) and mattress surface temperature were monitored during sleep. Linear mixed-effects models were conducted to assess the effects of each experimental condition on sleep, with match load variables as covariates.

RESULTS

A lower wake after sleep onset (β = -10.5 min, P < 0.01) and higher rapid eye movement sleep proportion (β = +2.8%, P < 0.05) were reported for MAT compared with CONT. Moreover, lower mean CBT (β = -0.135°C, P < 0.001) and mean mattress surface temperature (β = -2.736°C, P < 0.001) during sleep were observed for MAT compared CONT. WBC did not affect nocturnal CBT nor interfere with sleep architecture. For every 100-m increase in high-speed running distance, a higher slow wave sleep (β = +1.1%, P = 0.05) and lower light sleep proportion (β = -1.2%, P < 0.05) proportion were observed. Conversely, for every 10 supplementary collisions, lower slow wave sleep (β = -1.9, P = 0.09) and higher light sleep (β = +2.9%, P < 0.001) proportion were observed.

CONCLUSION

MAT use had a positive effect on sleep architecture after an elite rugby union match, potentially through a more efficient nocturnal heat transfer.

Training Schedule and Sleep in Adolescent Swimmers

PURPOSE

Insufficient sleep duration may affect athletic performance and health. Inconsistent sleep pattern also has negative health effects, but studies on athletes' intraindividual sleep variability are scarce. The aim of this research was to compare total sleep time (TST) and variability (TST-variability), wakening after sleep onset, and sleep efficiency, during nights preceding early morning practices with other nights, and to investigate sleep characteristics of nights following a day with early morning only, evening only, or both a morning and an evening session in adolescent swimmers.

METHODS

Wrist-worn accelerometers were used to measure 1 week of sleep in 108 swimmers (mean age 16.1 [2.6] y) in Iceland. Adjusted regression analyses and linear mixed models were used to explore associations of training schedules with TST, TST-variability, wakening after sleep onset, and sleep efficiency.

RESULTS

Mean TST was 6:32 (h:min) (±39 min) and TST-variability was 63 minutes (±25 min). TST decreased and TST-variability increased with more early morning practices. TST preceding early training was 5:36 and 5:06 in <16- and ≥16-year-olds, respectively, shorter than on nights preceding later or no morning training (P < .001).

CONCLUSION

Swimmers have extremely short TST preceding early morning sessions and increased TST-variability with more early morning sessions.

The effect of night-time exercise on sleep architecture among well-trained male endurance runners

The aim of the present study was to investigate the effects of night-time (21:00 hours) high-intensity, intermittent exercise on sleep architecture among well-trained athletes in a laboratory setting. In a randomized, counterbalanced order, 11 well-trained male runners completed a simulated trail-running exercise (TRAIL) on a motorized treadmill and a resting condition (REST; no exercise during the day). After each condition, nocturnal autonomic nervous system activity and core body temperature (CBT) were measured and sleep was analysed using polysomnography and actigraphy. Markers of muscle damage (maximal voluntary contraction [MVC], plasma creatine kinase concentration [CK] and perceived muscle soreness) were recorded before and immediately (POST), 24 hr (H24) and 48 hr (H48) after exercise. TRAIL induced a high level of fatigue and mild exercise-induced muscle damage, as determined by a reduction in MVC (-9.4%, p < .01, d = -1.36) and increases in [CK] (+176.0%, p < .01, d = 1.49) and perceived muscle soreness (+4.5 UA, p < .01, d = 2.17) compared with REST at H24. A trend for increased non-rapid eye movement (+4.2%; p = .10; d = 0.86) and reduced rapid eye movement (-4.4%; p = .07; d = -0.87) during sleep was observed for TRAIL compared with the REST condition. Moreover, compared with REST, TRAIL significantly increased CBT and nocturnal HR during the first part of the night. In conclusion, sleep architecture was modified after night-time, high-intensity exercise among well-trained runners.

Portable PSG for sleep stage monitoring in sports: Assessment of SOMNOwatch plus EEG

Current sport-scientific studies mostly neglect the assessment of sleep architecture, although the distribution of different sleep stages is considered an essential component influencing an athlete's recovery and performance capabilities. A mobile, self-applied tool like the SOMNOwatch plus EEG might serve as an economical and time-friendly alternative to activity-based devices. However, self-application of SOMNOwatch plus EEG has not been validated against conventional polysomnography (PSG) yet. For evaluation purposes, 25 participants (15 female, 10 male; M _age = 22.92 ± 2.03 years) slept in a sleep laboratory on two consecutive nights wearing both, conventional PSG and SOMNOwatch plus EEG electrodes. Sleep parameters and sleep stages were compared using paired t-tests and Bland-Altman plots. No significant differences were found between the recordings for Sleep Onset Latency, stages N1 to N3 as well as Rapid Eye Movement stage. Significant differences (Bias [95%-confidence interval]) were present between Total Sleep Time (9.95 min [-29.18, 49.08], d = 0.14), Total Wake Time (-13.12 min [-47.25, 23.85], d = -0.28), Wake after Sleep Onset (-11.70 min [-47.25, 23.85], d = -0.34) and Sleep Efficiency (2.18% [-7.98, 12.34], d = 0.02) with small effect sizes. Overall, SOMNOwatch plus EEG can be considered a valid and practical self-applied method for the examination of sleep. In sport-scientific research, it is a promising tool to assess sleep architecture in athletes; nonetheless, it cannot replace in-lab PSG for all clinical or scientific purposes.

Sleep Profiles of Elite Swimmers During Different Training Phases

Walsh, JA, Sanders, D, Hamilton, DL, and Walshe, I. Sleep profiles of elite swimmers during different training phases. J Strength Cond Res 33(3): 811-818, 2019-This study aims to describe the sleeping patterns during different training phases in competitive swimmers. Twelve national- and international-level swimmers (3 females and 9 males) were monitored during 4 different phases, consisting of a preparation training phase, a taper phase, a competition phase, and a rest phase. Sleep parameters were assessed using wrist activity monitors and self-reported sleep diaries. There was a moderately higher (d = 0.70-1.00) sleep onset latency during the competition phase compared with taper, train, and rest phases. Trivial to small differences were observed for total sleep time between phases (d = 0.05-0.40). Sleep efficiency was moderately higher (d = 0.60-0.75) in the training and taper phases compared with competition and rest. Restfulness and fragmentation index (FI) were lowest in the rest with differences between phases being small (d = 0.43-0.51) for restfulness and small to moderate (d = 0.43-0.62) for FI. Time in and out of bed was very largely later (d = 1.96-2.34) in rest compared with the other phases. Total nap time was moderately lower in rest (d = 1.13-1.18) compared with the training and competition phases, whereas there was a small difference (d = 0.46) compared with taper. To conclude, while there were trivial to small differences in sleep quantity between phases, there are small to moderate differences in other sleep parameters. Specifically, sleep onset latency was higher during the competition phase. In addition, this study highlights the substantial between-individual variations in sleep responses during different training phases.

Partial-body cryostimulation after training improves sleep quality in professional soccer players

Objective

The aim of the present investigation was to determine whether using cryostimulation (partial-body cryostimulation) impacts sleep quality in professional soccer players. Different exposure durations at − 180 °C were tested randomly after standardized training sessions in nine professional soccer players (no cryostimulation, 180-s exposure, two 90-s exposures separated by a 5-min rest at room temperature, and 90-s exposure), and the effects on sleep quality using 3-dimensional accelerometers worn during sleep were assessed.

Results

The number of movements during the night after partial-body cryostimulation was significantly reduced only in the 180-s exposure condition (p < 0.05, very large effect size) compared with the control condition. Partial-body cryostimulation seems to induce a positive impact on sleep quality that may be dose-dependent.

Trial registration Australia and New Zealand Clinical Trials Registry (ANZCTR), ACTRN12619000330145, date of registration: 4/03/2019. Retrospectively registered

Athletes' rest-activity circadian rhythm differs in accordance with the sport discipline

The correct expression of circadian rhythmicity is crucial for the body homeostasis. The rest-activity circadian rhythms (RARs) are involved in the control of the sleep-wake cycle and altered RARs could lead to a compromised health status. Many studies focused on examining sleep behavior and circadian rhythms in physically active subjects or athletes but, unexpectedly, no data on RARs are available. Therefore, we studied the existence of the RAR in athletes and the possible difference in RAR's characteristics among sport disciplines. The study had a prospective observational design and RARs were recorded for five consecutive training days through actigraphy (Actiwatch 2 actigraph; Philips Respironics, OR, USA) in 43 athletes (mean age: 25.6 ± 3.2 years). Athletes competed in three different disciplines and had different training schedules and competition levels: professional triathletes (N = 10; 6 females and 4 males) had 2 morning (08:30-12:00) and 1 afternoon (15:00-17:00) training sessions, professional volleyball players (N = 19; 12 females and 7 males) used to train once in the morning (09:00-11:30) and once in the afternoon (15:00-18:00), and non-professional soccer players (N = 14; all males) trained always late in the evening (20:30-22:30). To determine the existence of RARs, the activity counts (A.C.) data were analyzed using the single and the population mean cosinor method; a one-way analysis of variance (ANOVA) followed by the Tukey-Kramer post-hoc test was used for the comparison of RAR characteristics among soccer, volleyball and triathlon athletes. Partial eta squared (ή_p²) was used to determine the magnitude of the effect for significant outcomes (α = 0.05) in ANOVA. The presence of a significant RAR both for each of the 43 athletes (p < 0.001) and for the three categories of athletes (p < 0.001) was observed. RARs differed among sport disciplines: the Midline Estimating Statistic of Rhythm (MESOR) was significantly higher in triathletes (mean: 347 A.C. with 95% Confidence Interval [CI]: 314-379) compared to both volleyball (mean: 188 A.C. with 95% CI: 173-203; p < 0.001) and soccer players (mean: 289 A.C. with 95% CI: 267-312; p < 0.01) with ή_p² = 0.72. Amplitude (A) values showed the same significant trend of MESOR data (ANOVA: p < 0.001; ή_p² = 0.65) while the acrophase (Φ) occurred at 18:28 for soccer players, significantly later than triathlon (15:20 h; p < 0.001) and volleyball players (16:24 h; p < 0.001) (ANOVA: p < 0.001; ήp2 = 0.84). The higher training duration and intensity reached by triathlon athletes in the morning sessions caused a phase advance of their RAR's acrophase Φ and higher MESOR and A amplitude compared to volleyball players and triathletes. Therefore, different sport disciplines require different training schedules, training loads and intensities that translate into different RARs. Strength coaches and medical staff of professional teams should strongly consider actigraphy as a practical and powerful tool to monitor RARs, sleep behavior, and the activity levels of their athletes; highlighting potential circadian disruptions through actigraphy could be helpful to prevent musculoskeletal injuries.

When research leads to learning, but not action in high performance sport

Research from sports science and related clinical and scientific fields produces knowledge that is often highly relevant to high performance sport. However, there exists a gap between current science and applied coaching or sports science practice. Addressing, and bridging, this gap from both sides of the research-application divide is an important ambition. In this commentary we discuss the wonderful, yet often unforgiving challenge of improving athlete performance as a practitioner or coach in high performance sport. Blending existing knowledge (that which we know works), transferable knowledge (that which has worked elsewhere), anecdotal observations (that which we have seen work) and innovation (where the risk: reward ratio of it working at all is high), to find the right solution, at the right time, for the specific (and often unique) individual is the challenging "art" of application. Here we explore this challenge related to the high performance sports system and the people within it, then more specifically to coaching and learning, and finally to practitioners and athletes using a case study example of applying sleep science to the high performance environment.

Effects of training and competition on the sleep of elite athletes: a systematic review and meta-analysis

Objectives

To characterise the sleep of elite athletes and to identify factors associated with training and competition that negatively affect sleep.

Design

Prognosis systematic review.

Data sources

Three databases (PubMed, SCOPUS and SPORTDiscus) were searched from inception to 26 February 2018.

Eligibility criteria for selecting studies

Included studies objectively reported total sleep time (TST) and/or sleep efficiency (SE) in elite athletes. Studies were required to be observational or to include an observational trial.

Results

Fifty-four studies were included. During training, many studies reported athletes were unable to achieve TST (n=23/41) and/or SE (n=16/37) recommendations. On the night of competition, most studies reported athletes were unable to achieve TST (n=14/18) and/or SE (n=10/16) recommendations. TST was shorter (60 min) the night of competition compared with previous nights. SE was lower (1%) the night of competition compared with the previous night. TST was shorter the night of night competition (start ≥18:00; 80 min) and day competition (20 min) compared with the previous night. SE was lower (3%–4%) the night of night competition but unchanged the night of day competition compared with previous nights. Early morning training (start <07:00), increases in training load (>25%), late night/early morning travel departure times, eastward air travel and altitude ascent impaired sleep.

Conclusion

Athletes were often unable to achieve sleep recommendations during training or competition periods. Sleep was impaired the night of competition compared with previous nights. Early morning training, increases in training load, travel departure times, jet lag and altitude can impair athletes’ sleep.

PROSPERO registration number

CRD42017074367.

Tapering Practices of Strongman Athletes

Winwood, PW, Dudson, MK, Wilson, D, Mclaren-Harrison, JKH, Redjkins, V, Pritchard, HJ, and Keogh, JWL. Tapering practices of strongman athletes. J Strength Cond Res 32(5): 1181-1196, 2018-This study provides the first empirical evidence of how strongman athletes taper for strongman competitions. Strongman athletes (n = 454) (mean ± SD: 33.2 ± 8.0 years, 178.1 ± 10.6 cm, 108.6 ± 27.9 kg, 12.6 ± 8.9 years general resistance training, 5.3 ± 5.0 years strongman implement training) completed a self-reported 4-page internet survey on tapering practices. Analysis by sex (male and female), age (≤30 and >30 years), body mass (≤105 and >105 kg), and competitive standard (local/regional amateur, national amateur and professional) was conducted. Eighty-seven percent (n = 396) of strongman athletes reported that they used a taper. Athletes stated that their typical taper length was 8.6 ± 5.0 days, with the step taper the most commonly performed taper (52%). Training volume decreased during the taper by 45.5 ± 12.9%, and all training ceased 3.9 ± 1.8 days out from competition. Typically, athletes reported that training frequency and training duration stayed the same or decreased and training intensity decreased to around 50% in the last week. Athletes generally stated that tapering was performed to achieve recovery, rest, and peak performance; the deadlift, yoke walk, and stone lifts/work took longer to recover from than other lifts; assistance exercises were reduced or removed in the taper; massage, foam rolling, nutritional changes, and static stretching were strategies used in the taper; and, poor tapering occurred when athletes trained too heavy/hard or had too short a taper. These data will assist strongman athletes and coaches in the optimization of tapering variables leading to more peak performances. Future research could investigate the priming and preactivation strategies strongman athletes use on competition day.

The Variability of Sleep Among Elite Athletes

Practicing sport at the highest level is typically accompanied by several stressors and restrictions on personal life. Elite athletes’ lifestyle delivers a significant challenge to sleep, due to both the physiological and psychological demands, and the training and competition schedules. Inter-individual variability of sleep patterns (e.g., sleep requirements, chronotype) may have important implications not only for recovery and training schedules but also for the choice of measures to possibly improve sleep. This article provides a review of the current available literature regarding the variability of sleep among elite athletes and factors possibly responsible for this phenomenon. We also provide methodological approaches to better address the inter-individual variability of sleep in future studies with elite athletes. There is currently little scientific evidence supporting a specific influence of one particular type of sport on sleep; sleep disorders may be, however, more common in strength/power and contact sports. Sleep behavior may notably vary depending on the athlete’s typical daily schedule. The specificity of training and competition schedules possibly accounts for the single most influential factor leading to inconsistency in sleep among elite athletes (e.g., “social jet lag”). Additionally, athletes are affected by extensive exposure to electric light and evening use of electronic media devices. Therefore, the influence of ordinary sleep, poor sleep, and extended sleep as important additional contributors to training load should be studied. Future experimental studies on sleep and elite sport performance should systematically report the seasonal phase. Boarding conditions may provide a good option to standardize as many variables as possible without the inconvenience of laboratory. The use of interdisciplinary mixed-method approaches should be encouraged in future studies on sleep and elite sport. Finally, high inter- and intra-individual variability in the athletes’ sleep characteristics suggests a need for providing individual responses in addition to group means.

A Subjective Assessment of the Prevalence and Factors Associated with Poor Sleep Quality Amongst Elite Japanese Athletes

Background

The amount, quality, and timing of sleep are considered important for athletes’ ability to train, maximize training responses, and recover. However, some research has shown that elite athletes do not obtain sufficient sleep. Based on this background, researchers recently started to assess and manage sleep in elite athletes.

The purpose of this study was to clarify the prevalence of poor sleep quality and its associated factors amongst elite Japanese athletes.

Methods

Eight hundred and ninety-one candidates for the 17th Asian Games Incheon 2014, who were over 20 years old, participated in this study. They completed a questionnaire that included the Pittsburgh Sleep Quality Index (PSQI), Epworth Sleepiness Scale, two-question case-finding instruments, and a checklist for sleep hygiene. Data from 817 of the 891 athletes (91.7%) with no missing values were analyzed.

Results

The mean time in bed was 7 h and 29 min. Two hundred and twenty-nine (28.0%) athletes showed a PSQI global score above the clinical criteria. A multiple logistic analysis revealed that sleep quality was significantly associated with five factors: “time in bed,” “eating breakfast every morning,” “avoiding the use of electronic devices (PC, smartphone, etc.) just before bedtime,” “depressive mood”, and “not thinking about troubles while in bed.” Forty percent of athletes reported they had been informed by someone about “snoring loudly” and/or “leg twitching or jerking during sleep.”

Conclusions

The results of this study demonstrate that 28% of the athletes showed the PSQI score above the cutoff for poor sleep quality (> 5.5), which suggests that there may be a high prevalence of poor sleep quality in this population of athletes. To improve athletes’ sleep, the five factors associated with sleep quality should be emphasized in athletes’ sleep education. Furthermore, in medical evaluations of athletes, it may be desirable to include screening for sleep disorders.

Tapering Practices of Strongman Athletes: Test-Retest Reliability Study

BACKGROUND

Little is currently known about the tapering practices of strongman athletes. We have developed an Internet-based comprehensive self-report questionnaire examining the training and tapering practices of strongman athletes.

OBJECTIVE

The objective of this study was to document the test-retest reliability of questions associated with the Internet-based comprehensive self-report questionnaire on the tapering practices of strongman athletes. The information will provide insight on the reliability and usefulness of the online questionnaire for use with strongman athletes.

METHODS

Invitations to complete an Internet questionnaire were sent via Facebook Messenger to identified strongman athletes. The survey consisted of four main areas of inquiry, including demographics and background information, training practices, tapering, and tapering practices. Of the 454 athletes that completed the survey over the 8-week period, 130 athletes responded on Facebook Messenger indicating that they intended to complete, or had completed, the survey. These participants were asked if they could complete the online questionnaire a second time for a test-retest reliability analysis. Sixty-four athletes (mean age 33.3 years, standard deviation [SD] 7.7; mean height 178.2 cm, SD 11.0; mean body mass 103.7 kg, SD 24.8) accepted this invitation and completed the survey for the second time after a minimum 7-day period from the date of their first completion. Agreement between athlete responses was measured using intraclass correlation coefficients (ICCs) and kappa statistics. Confidence intervals (at 95%) were reported for all measures and significance was set at P<.05.

RESULTS

Test-retest reliability for demographic and training practices items were significant (P<.001) and showed excellent (ICC range=.84 to .98) and fair to almost perfect agreement (κ range=.37-.85). Moderate to excellent agreements (ICC range=.56-.84; P<.01) were observed for all tapering practice measures except for the number of days athletes started their usual taper before a strongman competition (ICC=.30). When the number of days were categorized with additional analyses, moderate reliability was observed (κ=.43; P<.001). Fair to substantial agreement was observed for the majority of tapering practices measures (κrange=.38-.73; P<.001) except for how training frequency (κ=.26) and the percentage and type of resistance training performed, which changed in the taper (κ=.20). Good to excellent agreement (ICC=.62-.93; P<.05) was observed for items relating to strongman events and traditional exercises performed during the taper. Only the time at which the Farmer's Walk was last performed before competition showed poor reliability (ICC=.27).

CONCLUSIONS

We have developed a low cost, self-reported, online retrospective questionnaire, which provided stable and reliable answers for most of the demographic, training, and tapering practice questions. The results of this study support the inferences drawn from the Tapering Practices of Strongman Athletes Study.

Does Elite Sport Degrade Sleep Quality? A Systematic Review

BACKGROUND

Information on sleep quality and insomnia symptomatology among elite athletes remains poorly systematised in the sports science and medicine literature. The extent to which performance in elite sport represents a risk for chronic insomnia is unknown.

OBJECTIVES

The purpose of this systematic review was to profile the objective and experienced characteristics of sleep among elite athletes, and to consider relationships between elite sport and insomnia symptomatology.

METHODS

Studies relating to sleep involving participants described on a pre-defined continuum of 'eliteness' were located through a systematic search of four research databases: SPORTDiscus, PubMed, Science Direct and Google Scholar, up to April 2016. Once extracted, studies were categorised as (1) those mainly describing sleep structure/patterns, (2) those mainly describing sleep quality and insomnia symptomatology and (3) those exploring associations between aspects of elite sport and sleep outcomes.

RESULTS

The search returned 1676 records. Following screening against set criteria, a total of 37 studies were identified. The quality of evidence reviewed was generally low. Pooled sleep quality data revealed high levels of sleep complaints in elite athletes. Three risk factors for sleep disturbance were broadly identified: (1) training, (2) travel and (3) competition.

CONCLUSION

While acknowledging the limited number of high-quality evidence reviewed, athletes show a high overall prevalence of insomnia symptoms characterised by longer sleep latencies, greater sleep fragmentation, non-restorative sleep, and excessive daytime fatigue. These symptoms show marked inter-sport differences. Two underlying mechanisms are implicated in the mediation of sport-related insomnia symptoms: pre-sleep cognitive arousal and sleep restriction.

Total Energy Expenditure, Energy Intake, and Body Composition in Endurance Athletes Across the Training Season: A Systematic Review

BACKGROUND

Endurance athletes perform periodized training in order to prepare for main competitions and maximize performance. However, the coupling between alterations of total energy expenditure (TEE), energy intake, and body composition during different seasonal training phases is unclear. So far, no systematic review has assessed fluctuations in TEE, energy intake, and/or body composition in endurance athletes across the training season. The purpose of this study was to (1) systematically analyze TEE, energy intake, and body composition in highly trained athletes of various endurance disciplines and of both sexes and (2) analyze fluctuations in these parameters across the training season.

METHODS

An electronic database search was conducted on the SPORTDiscus and MEDLINE (January 1990-31 January 2015) databases using a combination of relevant keywords. Two independent reviewers identified potentially relevant studies. Where a consensus was not reached, a third reviewer was consulted. Original research articles that examined TEE, energy intake, and/or body composition in 18-40-year-old endurance athletes and reported the seasonal training phases of data assessment were included in the review. Articles were excluded if body composition was assessed by skinfold measurements, TEE was assessed by questionnaires, or data could not be split between the sexes. Two reviewers assessed the quality of studies independently. Data on subject characteristics, TEE, energy intake, and/or body composition were extracted from the included studies. Subjects were categorized according to their sex and endurance discipline and each study allocated a weight within categories based on the number of subjects assessed. Extracted data were used to calculate weighted means and standard deviations for parameters of TEE, energy intake, and/or body composition.

RESULTS

From 3589 citations, 321 articles were identified as potentially relevant, with 82 meeting all of the inclusion criteria. TEE of endurance athletes was significantly higher during the competition phase than during the preparation phase (p < 0.001) and significantly higher than energy intake in both phases (p < 0.001). During the competition phase, both body mass and fat-free mass were significantly higher compared to other seasonal training phases (p < 0.05).

CONCLUSIONS

Limitations of the present study included insufficient data being available for all seasonal training phases and thus low explanatory power of single parameters. Additionally, the classification of the different seasonal training phases has to be discussed. Male and female endurance athletes show important training seasonal fluctuations in TEE, energy intake, and body composition. Therefore, dietary intake recommendations should take into consideration other factors including the actual training load, TEE, and body composition goals of the athlete.