4.6 Article

Natural history of excessive daytime sleepiness: a population-based 5-year longitudinal study

Journal

SLEEP
Volume 43, Issue 3, Pages -

Publisher

OXFORD UNIV PRESS INC
DOI: 10.1093/sleep/zsz249

Keywords

cohort studies; epidemiology; sleepiness; remission; natural history; insomnia; chronic disease; psychological factors

Funding

  1. Canadian Institutes of Health Research grant [42504]
  2. Idorsia

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Study Objectives: To document the rates of persistent, remitted, and intermittent excessive daytime sleepiness (EDS) in a longitudinal 5-year community study of adults and to assess how changes in risk factors over time can predict improvement of daytime sleepiness (DS). Methods: Participants were recruited in 2007-2008 as part of a population-based epidemiological study implemented in Canada. They completed postal assessments at baseline and at each yearly follow-up. An Epworth Sleepiness Scale total score >10 indicated clinically significant EDS; a 4-point reduction between two consecutive evaluations defined DS improvement. Socio-demographic, lifestyle, health characteristics, and sleep-related measures (e.g. insomnia symptoms, sleep duration, sleep medication) were self-reported at each time point. Cox proportional-hazard models were used to predict EDS and DS remissions over 5 years. Results: Among the 2167 participants, 33% (n = 714) met criteria for EDS at baseline, of whom 33% had persistent EDS, 44% intermittent EDS, and 23% remitted EDS over the follow-up. Furthermore, 61.4% of 2167 initial participants had stable DS, 27.1% sustained DS improvement and 8.5% transient improvement over the follow-up. The main predictors of EDS remission or DS improvement were normal weight, taking less hypnotics, having hypertension, increased nighttime sleep duration, and decreased insomnia, and depressive symptoms. Conclusions: EDS waxes and wanes over time with frequent periods of remission and is influenced by behavioral characteristics and changes in psychological, metabolic, and nighttime sleep patterns. Targeting these predictors in future interventions is crucial to reduce DS in the general adult population.

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