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DOI: 10.5935/1984-0063.20170019
Retrospectively reported month-to-month variation in sleeping problems of people naturally exposed to high-amplitude annual variation in daylength and/or temperature


ABSTRACT
Compared to literature on seasonal variation in mood and well-being, reports on seasonality of trouble sleeping are scarce and contradictive. To extend geography of such reports on example of people naturally exposed to high-amplitude annual variation in daylength and/or temperature. Participants were the residents of Turkmenia, West Siberia, South and North Yakutia, Chukotka, and Alaska. Health and sleep-wake adaptabilities, month-to-month variation in sleeping problems, well-being and behaviors were self-assessed. More than a half of 2398 respondents acknowledged seasonality of sleeping problems. Four of the assessed sleeping problems demonstrated three different patterns of seasonal variation. Rate of the problems significantly increased in winter months with long nights and cold days (daytime sleepiness and difficulties falling and staying asleep) as well as in summer months with either long days (premature awakening and difficulties falling and staying asleep) or hot nights and days (all 4 sleeping problems). Individual differences between respondents in pattern and level of seasonality of sleeping problems were significantly associated with differences in several other domains of individual variation, such as gender, age, ethnicity, physical health, morning-evening preference, sleep quality, and adaptability of the sleep-wake cycle. These results have practical relevance to understanding of the roles playing by natural environmental factors in seasonality of sleeping problems as well as to research on prevalence of sleep disorders and methods of their prevention and treatment in regions with large seasonal differences in temperature and daylength.
Publikationsverlauf
Eingereicht: 12. April 2017
Angenommen: 25. Juli 2017
Artikel online veröffentlicht:
11. Oktober 2023
© 2023. Brazilian Sleep Association. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)
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