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      Sleep Regularity and Predictors of Sleep Efficiency and Sleep Duration in Elite Team Sport Athletes

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          Abstract

          Background

          Many elite athletes have suboptimal sleep duration and efficiency, potentially due to factors that may impact sleep onset and offset times. Variability in sleep onset and offset may negatively influence sleep. The sleep regularity index (SRI) is a novel metric for sleep regularity, however there are no published descriptions of SRI in elite athletes. Further, contributors to sleep efficiency and duration in elite athletes using objective measures have not been explored.

          Methods

          Sleep was monitored over a minimum of seven consecutive days (7 to 43)—in 203 elite team sport athletes (age range = 19–36 years; female, n = 79; male, n = 124, total sleep nights = 1975) using activity monitoring and sleep diaries. The sleep regularity index (SRI) was calculated to reflect the night-to-night shifts in sleep by accounting for changes in sleep onset and sleep offset. Sleep characteristics were compared between regular and irregular sleepers and important contributors to sleep efficiency and total sleep time were assessed using multiple linear regression models.

          Results

          The median sleep regularity index and interquartile range were 85.1 (81.4 to 88.8). When compared to irregular sleepers, regular sleepers demonstrated (1) significantly greater sleep efficiency ( p = 0.006; 0.31 medium effect size [ES]), (2) significantly less variability in total sleep time (−  p ≤ 0.001; − 0.69, large ES) and sleep efficiency (− 0.34, small ES), (3) similar total sleep time and (4) significantly less variation in sleep onset ( p ≤ 0.001; − 0.73, large ES) and offset ( p ≤ 0.001; − 0.74, large ES) times. Sleep characteristics explained 73% and 22% of the variance in total sleep time and sleep efficiency, respectively. The most important contributor to total sleep time was a later sleep offset time, while the most important contributors to sleep efficiency were an earlier bedtime and less variable sleep onset times.

          Conclusions

          Bedtime and a consistent sleep onset time are important factors associated with sleep efficiency in athletes, while sleep offset is an important factor for total sleep time. Coaches and staff can assist their athletes by providing training schedules that allow for both regularity and sufficiency of time in bed where possible.

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          Most cited references26

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          Irregular sleep/wake patterns are associated with poorer academic performance and delayed circadian and sleep/wake timing

          The association of irregular sleep schedules with circadian timing and academic performance has not been systematically examined. We studied 61 undergraduates for 30 days using sleep diaries, and quantified sleep regularity using a novel metric, the sleep regularity index (SRI). In the most and least regular quintiles, circadian phase and light exposure were assessed using salivary dim-light melatonin onset (DLMO) and wrist-worn photometry, respectively. DLMO occurred later (00:08 ± 1:54 vs. 21:32 ± 1:48; p < 0.003); the daily sleep propensity rhythm peaked later (06:33 ± 0:19 vs. 04:45 ± 0:11; p < 0.005); and light rhythms had lower amplitude (102 ± 19 lux vs. 179 ± 29 lux; p < 0.005) in Irregular compared to Regular sleepers. A mathematical model of the circadian pacemaker and its response to light was used to demonstrate that Irregular vs. Regular group differences in circadian timing were likely primarily due to their different patterns of light exposure. A positive correlation (r = 0.37; p < 0.004) between academic performance and SRI was observed. These findings show that irregular sleep and light exposure patterns in college students are associated with delayed circadian rhythms and lower academic performance. Moreover, the modeling results reveal that light-based interventions may be therapeutically effective in improving sleep regularity in this population.
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            Beyond the mean: A systematic review on the correlates of daily intraindividual variability of sleep/wake patterns.

            Features of an individual's sleep/wake patterns across multiple days are governed by two dimensions, the mean and the intraindividual variability (IIV). The existing literature focuses on the means, while the nature and correlates of sleep/wake IIV are not well understood. A systematic search of records in five major databases from inception to November 2014 identified 53 peer-reviewed empirical publications that examined correlates of sleep/wake IIV in adults. Overall, this literature appeared unsystematic and post hoc, with under-developed theoretical frameworks and inconsistent methodologies. Correlates most consistently associated with greater IIV in one or more aspects of sleep/wake patterns were: younger age, non-White race/ethnicity, living alone, physical health conditions, higher body mass index, weight gain, bipolar and unipolar depression symptomatology, stress, and evening chronotype; symptoms of insomnia and poor sleep were associated with higher sleep/wake IIV, which was reduced following sleep interventions. The effects of experimentally reduced sleep/wake IIV on daytime functioning were inconclusive. In extending current understanding of sleep/wake patterns beyond the mean values, IIV should be incorporated as an additional dimension when sleep is examined across multiple days. Theoretical and methodological shortcomings in the existing literature, and opportunities for future research are discussed.
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              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. Electronic supplementary material The online version of this article (doi:10.1007/s40279-016-0650-6) contains supplementary material, which is available to authorized users.
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                Author and article information

                Contributors
                shona.halson@acu.edu.au
                Journal
                Sports Med Open
                Sports Med Open
                Sports Medicine - Open
                Springer International Publishing (Cham )
                2199-1170
                2198-9761
                17 June 2022
                17 June 2022
                December 2022
                : 8
                : 79
                Affiliations
                [1 ]GRID grid.411958.0, ISNI 0000 0001 2194 1270, School of Behavioural and Health Sciences, , Australian Catholic University, ; McAuley at Banyo, Brisbane, Australia
                [2 ]GRID grid.411958.0, ISNI 0000 0001 2194 1270, Sports Performance, Recovery, Injury and New Technologies (SPRINT) Research Centre, , Australian Catholic University, ; Brisbane, QLD Australia
                [3 ]GRID grid.10346.30, ISNI 0000 0001 0745 8880, Carnegie Applied Rugby Research Centre, Institute for Sport, Physical Activity and Leisure, , Leeds Beckett University, ; Leeds, UK
                [4 ]Western Australia Institute of Sport, Mt Claremont, Australia
                [5 ]GRID grid.411958.0, ISNI 0000 0001 2194 1270, School of Behavioural and Health Sciences, , Australian Catholic University, ; Melbourne, Australia
                [6 ]GRID grid.1023.0, ISNI 0000 0001 2193 0854, Appleton Institute for Behavioural Science, , Central Queensland University, ; Wayville, Australia
                Author information
                http://orcid.org/0000-0002-1047-3878
                Article
                470
                10.1186/s40798-022-00470-7
                9206056
                35713743
                0e344094-daff-45db-973f-f976e06452e8
                © The Author(s) 2022

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 6 February 2022
                : 1 June 2022
                Categories
                Original Research Article
                Custom metadata
                © The Author(s) 2022

                sleep regularity index,athlete,team sport,variability
                sleep regularity index, athlete, team sport, variability

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