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      Sleep habits and strategies of ultramarathon runners

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          Abstract

          Among factors impacting performance during an ultramarathon, sleep is an underappreciated factor that has received little attention. The aims of this study were to characterize habitual sleep behaviors in ultramarathon runners and to examine strategies they use to manage sleep before and during ultramarathons. Responses from 636 participants to a questionnaire were considered. This population was found to sleep more on weekends and holidays (7–8 h to 8–9 h) than during weekdays (6–7 h to 7–8 h; p < 0.001). Work was a mediator of napping habits since 19–25% reported napping on work days and 37–56% on non-work days. There were 24.5% of the participants reporting sleep disorders, with more women (38.9%) reporting sleep problems than men (22.0%; p < 0.005). Mean (±SD) sleepiness score on the Epworth Sleepiness Scale was 8.9 ± 4.3 with 37.6% of respondents scoring higher than 10, reflecting excessive daytime sleepiness. Most of the study participants (73.9%) had a strategy to manage sleep preceding an ultramarathon, with 54.7% trying to increase their opportunities for sleep. Only 21% of participants reported that they had a strategy to manage sleep during ultramarathons, with micronaps being the most common strategy specified. Sub-analyses from 221 responses indicated that sleep duration during an ultramarathon was correlated with finish time for races lasting 36–60 h (r = 0.48; p < 0.01) or > 60 h (r = 0.44; p < 0.001). We conclude that sleep duration among ultramarathon runners was comparable to the general population and other athletic populations, yet they reported a lower prevalence of sleep disorders. Daytime sleepiness was among the lowest rates encountered in athletic populations, which may be related to the high percentage of nappers in our population. Sleep extension, by increasing sleep time at night and daytime napping, was the main sleep strategy to prepare for ultramarathons.

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          Reliability and factor analysis of the Epworth Sleepiness Scale.

          The Epworth Sleepiness Scale (ESS) is a self-administered eight-item questionnaire that has been proposed as a simple method for measuring daytime sleepiness in adults. This investigation was concerned with the reliability and internal consistency of the ESS. When 87 healthy medical students were tested and retested 5 months later, their paired ESS scores did not change significantly and were highly correlated (r = 0.82). By contrast, ESS scores that were initially high in 54 patients suffering from obstructive sleep apnea syndrome returned to more normal levels, as expected, after 3-9 months' treatment with nasal continuous positive airway pressure. The questionnaire had a high level of internal consistency as measured by Cronbach's alpha (0.88). Factor analysis of item scores showed that the ESS had only one factor for 104 medical students and for 150 patients with various sleep disorders. The ESS is a simple and reliable method for measuring persistent daytime sleepiness in adults.
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            Sleep and athletic performance: the effects of sleep loss on exercise performance, and physiological and cognitive responses to exercise.

            Although its true function remains unclear, sleep is considered critical to human physiological and cognitive function. Equally, since sleep loss is a common occurrence prior to competition in athletes, this could significantly impact upon their athletic performance. Much of the previous research has reported that exercise performance is negatively affected following sleep loss; however, conflicting findings mean that the extent, influence, and mechanisms of sleep loss affecting exercise performance remain uncertain. For instance, research indicates some maximal physical efforts and gross motor performances can be maintained. In comparison, the few published studies investigating the effect of sleep loss on performance in athletes report a reduction in sport-specific performance. The effects of sleep loss on physiological responses to exercise also remain equivocal; however, it appears a reduction in sleep quality and quantity could result in an autonomic nervous system imbalance, simulating symptoms of the overtraining syndrome. Additionally, increases in pro-inflammatory cytokines following sleep loss could promote immune system dysfunction. Of further concern, numerous studies investigating the effects of sleep loss on cognitive function report slower and less accurate cognitive performance. Based on this context, this review aims to evaluate the importance and prevalence of sleep in athletes and summarises the effects of sleep loss (restriction and deprivation) on exercise performance, and physiological and cognitive responses to exercise. Given the equivocal understanding of sleep and athletic performance outcomes, further research and consideration is required to obtain a greater knowledge of the interaction between sleep and performance.
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              Relationships between the Pittsburgh Sleep Quality Index (PSQI), Epworth Sleepiness Scale (ESS), and clinical/polysomnographic measures in a community sample.

              1) To characterize PSQI and ESS scores, and their relationship to each other, in an adult community sample; 2) To determine whether PSQI and ESS scores, in combination with each other, were associated with distinct demographic, clinical, and sleep characteristics. The PSQI, ESS, clinical rating scales, sleep diaries, actigraphy, and home polysomnography were collected from 187 community-dwelling adults (mean age 59.5 years, 47.1% women, 41.2% African Americans) as part of a study investigating novel cardiovascular risk factors. Correlations, cluster analysis, principal components analysis, MANOVA, ANOVA, and regressions were used to characterize the relationships between the PSQI, ESS, and other study variables Mean PSQI score was 6.3 (3.4), and mean ESS score was 8.2 (3.9). PSQI and ESS correlated weakly with each other (r = 0.16, p = 0.03), but segregated from each other on principal components analysis. Groups of participants categorized by either cluster analysis of PSQI and ESS scores, or by scores above or below traditional cut-off values, differed from each other on psychological/stress symptoms and quantitative and qualitative sleep diary measures, but not on actigraphic or polysomnographic measures. Specifically, higher PSQI scores were associated with female sex, greater psychological distress, and greater sleep disturbance on sleep diaries. The PSQI and ESS measure orthogonal dimensions of sleep-wake symptoms, but neither is related to objective sleep measures. The PSQI is more closely related to psychological symptom ratings and sleep diary measures than the ESS. These instruments are not likely to be useful as screening measures for polysomnographic sleep abnormalities.
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                Author and article information

                Contributors
                Role: Data curationRole: Formal analysisRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: MethodologyRole: ValidationRole: VisualizationRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ValidationRole: VisualizationRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                9 May 2018
                2018
                : 13
                : 5
                : e0194705
                Affiliations
                [1 ] Human Performance Laboratory, Faculty of Kinesiology, University of Calgary, Calgary, Canada
                [2 ] Rhythm, San Francisco, CA, United States of America
                [3 ] Department of Physical Medicine & Rehabilitation, Department of Veteran Affairs, Northern California Health Care System, Sacramento, CA, United States of America
                [4 ] University of California Davis Medical Center, Sacramento, CA, United States of America
                [5 ] Ultra Sports Science Foundation, Sacramento, CA, United States of America
                Norwegian University of Science and Technology, NORWAY
                Author notes

                Competing Interests: We have the following interests: PJA is an employee of Rythm Company. There are no patents, products in development or marketed products to declare. This does not alter our adherence to all the PLOS ONE policies on sharing data and materials.

                Article
                PONE-D-17-31396
                10.1371/journal.pone.0194705
                5942705
                29742118
                8ab9b545-421d-448b-86d5-2ec83f8865f9
                © 2018 Martin et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 25 August 2017
                : 8 March 2018
                Page count
                Figures: 4, Tables: 4, Pages: 18
                Funding
                This material is the result of work supported with resources and the use of facilities at the VA Northern California Health Care System. Rythm Company provided support in the form of salary for author PJA, but did not play any role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of this author are articulated in the ‘author contributions’ section.
                Categories
                Research Article
                Biology and Life Sciences
                Physiology
                Physiological Processes
                Sleep
                Medicine and Health Sciences
                Physiology
                Physiological Processes
                Sleep
                Medicine and Health Sciences
                Neurology
                Sleep Disorders
                Medicine and Health Sciences
                Neurology
                Sleep Deprivation
                Biology and Life Sciences
                Behavior
                Recreation
                Sports
                Biology and Life Sciences
                Sports Science
                Sports
                Biology and Life Sciences
                Behavior
                Habits
                Research and Analysis Methods
                Research Design
                Survey Research
                Questionnaires
                Biology and Life Sciences
                Chronobiology
                Circadian Rhythms
                Physical Sciences
                Chemistry
                Chemical Compounds
                Alkaloids
                Caffeine
                Custom metadata
                All relevant data are within the paper and its Supporting Information files.

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