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Seasonal Sleep Variations and Their Association With Meteorological Factors: A Japanese Population Study Using Large-Scale Body Acceleration Data

Authors
  • Li, Li1, 2
  • Nakamura, Toru1
  • Hayano, Junichiro3
  • Yamamoto, Yoshiharu4
  • 1 Graduate School of Engineering Science, Osaka University, Toyonaka, Osaka , (Japan)
  • 2 Intasect Communications, Inc., Tokyo , (Japan)
  • 3 Graduate School of Medical Sciences, Nagoya City University, Nagoya , (Japan)
  • 4 Graduate School of Education, The University of Tokyo, Tokyo , (Japan)
Type
Published Article
Journal
Frontiers in Digital Health
Publisher
Frontiers Media S.A.
Publication Date
Jul 02, 2021
Volume
3
Identifiers
DOI: 10.3389/fdgth.2021.677043
Source
Frontiers
Keywords
Disciplines
  • Digital Health
  • Original Research
License
Green

Abstract

Seasonal changes in meteorological factors [e.g., ambient temperature (Ta), humidity, and sunlight] could significantly influence a person's sleep, possibly resulting in the seasonality of sleep properties (timing and quality). However, population-based studies on sleep seasonality or its association with meteorological factors remain limited, especially those using objective sleep data. Japan has clear seasonality with distinctive changes in meteorological variables among seasons, thereby suitable for examining sleep seasonality and the effects of meteorological factors. This study aimed to investigate seasonal variations in sleep properties in a Japanese population (68,604 individuals) and further identify meteorological factors contributing to sleep seasonality. Here we used large-scale objective sleep data estimated from body accelerations by machine learning. Sleep parameters such as total sleep time, sleep latency, sleep efficiency, and wake time after sleep onset demonstrated significant seasonal variations, showing that sleep quality in summer was worse than that in other seasons. While bedtime did not show clear seasonality, get-up time varied seasonally, with a nadir during summer, and positively correlated with the sunrise time. Estimated by the abovementioned sleep parameters, Ta had a practically meaningful association with sleep quality, indicating that sleep quality worsened with the increase of Ta. This association would partly explain seasonal variations in sleep quality among seasons. In conclusion, Ta had a principal role for seasonality in sleep quality, and the sunrise time chiefly determined the get-up time.

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