Li Li, Nakamura Toru, Hayano Junichiro, Yamamoto Yoshiharu
Graduate School of Engineering Science, Osaka University, Toyonaka, Osaka, Japan.
Intasect Communications, Inc., Tokyo, Japan.
Front Digit Health. 2021 Jul 2;3:677043. doi: 10.3389/fdgth.2021.677043. eCollection 2021.
Seasonal changes in meteorological factors [e.g., ambient temperature (), 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, had a practically meaningful association with sleep quality, indicating that sleep quality worsened with the increase of . This association would partly explain seasonal variations in sleep quality among seasons. In conclusion, had a principal role for seasonality in sleep quality, and the sunrise time chiefly determined the get-up time.
气象因素的季节性变化[如环境温度（）、湿度和阳光]可能会显著影响人的睡眠，可能导致睡眠特性（时间和质量）的季节性变化。然而，基于人群的睡眠季节性或其与气象因素关联的研究仍然有限，尤其是那些使用客观睡眠数据的研究。日本季节分明，各季节气象变量变化显著，因此适合研究睡眠季节性以及气象因素的影响。本研究旨在调查日本人群（68,604人）睡眠特性的季节性变化，并进一步确定导致睡眠季节性的气象因素。在此，我们使用通过机器学习从身体加速度估计的大规模客观睡眠数据。总睡眠时间、睡眠潜伏期、睡眠效率和睡眠开始后的清醒时间等睡眠参数表现出显著的季节性变化，表明夏季的睡眠质量比其他季节差。虽然就寝时间没有明显的季节性，但起床时间随季节变化，夏季最低，且与日出时间呈正相关。根据上述睡眠参数估计，与睡眠质量存在实际有意义的关联，表明睡眠质量随着的增加而恶化。这种关联将部分解释各季节睡眠质量的季节性变化。总之，对睡眠质量的季节性变化起主要作用，日出时间主要决定起床时间。
