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Train hard, sleep well? Perceived training load, sleep quantity and sleep stage distribution in elite level athletes.
Journal of Science and Medicine in Sport 2018 April
OBJECTIVES: Sleep is essential for recovery and performance in elite athletes. While it is generally assumed that exercise benefits sleep, high training load may jeopardize sleep and hence limit adequate recovery. To examine this, the current study assessed objective sleep quantity and sleep stage distributions in elite athletes and calculated their association with perceived training load.
DESIGN: Mixed-methods.
METHODS: Perceived training load, actigraphy and one-channel EEG recordings were collected among 98 elite athletes during 7 consecutive days of regular training.
RESULTS: Actigraphy revealed total sleep durations of 7:50±1:08h, sleep onset latencies of 13±15min, wake after sleep onset of 33±17min and sleep efficiencies of 88±5%. Distribution of sleep stages indicated 51±9% light sleep, 21±8% deep sleep, and 27±7% REM sleep. On average, perceived training load was 5.40±2.50 (scale 1-10), showing large daily variability. Mixed-effects models revealed no alteration in sleep quantity or sleep stage distributions as a function of day-to-day variation in preceding training load (all p's>.05).
CONCLUSIONS: Results indicate healthy sleep durations, but elevated wake after sleep onset, suggesting a potential need for sleep optimization. Large proportions of deep sleep potentially reflect an elevated recovery need. With sleep quantity and sleep stage distributions remaining irresponsive to variations in perceived training load, it is questionable whether athletes' current sleep provides sufficient recovery after strenuous exercise.
DESIGN: Mixed-methods.
METHODS: Perceived training load, actigraphy and one-channel EEG recordings were collected among 98 elite athletes during 7 consecutive days of regular training.
RESULTS: Actigraphy revealed total sleep durations of 7:50±1:08h, sleep onset latencies of 13±15min, wake after sleep onset of 33±17min and sleep efficiencies of 88±5%. Distribution of sleep stages indicated 51±9% light sleep, 21±8% deep sleep, and 27±7% REM sleep. On average, perceived training load was 5.40±2.50 (scale 1-10), showing large daily variability. Mixed-effects models revealed no alteration in sleep quantity or sleep stage distributions as a function of day-to-day variation in preceding training load (all p's>.05).
CONCLUSIONS: Results indicate healthy sleep durations, but elevated wake after sleep onset, suggesting a potential need for sleep optimization. Large proportions of deep sleep potentially reflect an elevated recovery need. With sleep quantity and sleep stage distributions remaining irresponsive to variations in perceived training load, it is questionable whether athletes' current sleep provides sufficient recovery after strenuous exercise.
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