Seasonal Sleep Variations and Their Association With Meteorological Factors: A Japanese Population Study Using Large-Scale Body Acceleration Data
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 assoc...
Main Authors: | , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2021-07-01
|
Series: | Frontiers in Digital Health |
Subjects: | |
Online Access: | https://www.frontiersin.org/articles/10.3389/fdgth.2021.677043/full |
id |
doaj-a211a21a867d498f957ae6186330d073 |
---|---|
record_format |
Article |
spelling |
doaj-a211a21a867d498f957ae6186330d0732021-07-02T04:25:40ZengFrontiers Media S.A.Frontiers in Digital Health2673-253X2021-07-01310.3389/fdgth.2021.677043677043Seasonal Sleep Variations and Their Association With Meteorological Factors: A Japanese Population Study Using Large-Scale Body Acceleration DataLi Li0Li Li1Toru Nakamura2Junichiro Hayano3Yoshiharu Yamamoto4Graduate School of Engineering Science, Osaka University, Toyonaka, Osaka, JapanIntasect Communications, Inc., Tokyo, JapanGraduate School of Engineering Science, Osaka University, Toyonaka, Osaka, JapanGraduate School of Medical Sciences, Nagoya City University, Nagoya, JapanGraduate School of Education, The University of Tokyo, Tokyo, JapanSeasonal 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.https://www.frontiersin.org/articles/10.3389/fdgth.2021.677043/fullsleep seasonalitymeteorological factorsbig dataacceleration dataJapanese |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Li Li Li Li Toru Nakamura Junichiro Hayano Yoshiharu Yamamoto |
spellingShingle |
Li Li Li Li Toru Nakamura Junichiro Hayano Yoshiharu Yamamoto Seasonal Sleep Variations and Their Association With Meteorological Factors: A Japanese Population Study Using Large-Scale Body Acceleration Data Frontiers in Digital Health sleep seasonality meteorological factors big data acceleration data Japanese |
author_facet |
Li Li Li Li Toru Nakamura Junichiro Hayano Yoshiharu Yamamoto |
author_sort |
Li Li |
title |
Seasonal Sleep Variations and Their Association With Meteorological Factors: A Japanese Population Study Using Large-Scale Body Acceleration Data |
title_short |
Seasonal Sleep Variations and Their Association With Meteorological Factors: A Japanese Population Study Using Large-Scale Body Acceleration Data |
title_full |
Seasonal Sleep Variations and Their Association With Meteorological Factors: A Japanese Population Study Using Large-Scale Body Acceleration Data |
title_fullStr |
Seasonal Sleep Variations and Their Association With Meteorological Factors: A Japanese Population Study Using Large-Scale Body Acceleration Data |
title_full_unstemmed |
Seasonal Sleep Variations and Their Association With Meteorological Factors: A Japanese Population Study Using Large-Scale Body Acceleration Data |
title_sort |
seasonal sleep variations and their association with meteorological factors: a japanese population study using large-scale body acceleration data |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Digital Health |
issn |
2673-253X |
publishDate |
2021-07-01 |
description |
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. |
topic |
sleep seasonality meteorological factors big data acceleration data Japanese |
url |
https://www.frontiersin.org/articles/10.3389/fdgth.2021.677043/full |
work_keys_str_mv |
AT lili seasonalsleepvariationsandtheirassociationwithmeteorologicalfactorsajapanesepopulationstudyusinglargescalebodyaccelerationdata AT lili seasonalsleepvariationsandtheirassociationwithmeteorologicalfactorsajapanesepopulationstudyusinglargescalebodyaccelerationdata AT torunakamura seasonalsleepvariationsandtheirassociationwithmeteorologicalfactorsajapanesepopulationstudyusinglargescalebodyaccelerationdata AT junichirohayano seasonalsleepvariationsandtheirassociationwithmeteorologicalfactorsajapanesepopulationstudyusinglargescalebodyaccelerationdata AT yoshiharuyamamoto seasonalsleepvariationsandtheirassociationwithmeteorologicalfactorsajapanesepopulationstudyusinglargescalebodyaccelerationdata |
_version_ |
1721340160224788480 |