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Abstract Introduction Epidemiological studies have revealed that sleep complaints are prevalent among older adults. Poor sleep quality in older adults is linked with higher levels of depression, anxiety, agitation, and falls as well as diminished cognitive and memory performance. Previous inquiries reported lighting and thermal conditions in residential spaces as important environmental factors impacting sleep in various populations. This study aims to explore how daily lighting exposure and thermal conditions within the residences of older adults influence their sleep quality. Methods A three-day cross-sectional study was conducted. Participants were 18 older adults (age 54 years old) living independently in a senior living facility in Phoenix, AZ. Data collection was conducted in the participants’ residence unit in the facility without any intervention. Non-invasive wearable devices, including actigraphs and light trackers, were employed to measure sleep quality (duration and efficiency) and daily light exposure (intensity, correlated color temperature (CCT), and Melanopic Equivalent Daylight Illuminance (MEDI)) over the course of three consecutive days. In addition, sensors installed in living rooms and bedrooms continuously monitored indoor temperature and light intensity. The data underwent rigorous analysis, employing statistical tools such as ANOVA and correlation, executed using software platforms like SPSS, Minitab, and SAS. Predictive models were developed utilizing machine learning algorithms and deep learning techniques within Python's TensorFlow framework. Results The results revealed that average daytime MEDI predicted total sleep time significantly. Average daytime CCT and nighttime bedroom temperature had no significant impact on sleep duration. Higher average nighttime bedroom temperature was associated with reduced sleep fragmentation (b = -.493, t(8.52) = -.314, p = .0128) and improved sleep efficiency (b = .025, t(11.6) = 2.89, p = .0141). In terms of temperature and sleep duration, nighttime temperature displayed a significant negative correlation with sleep hours. The regression model explained 31% of the variance in sleep hours, highlighting the significance of nighttime temperature in sleep duration. Conclusion This study underscores the importance of optimizing bedroom temperature and increasing daytime light exposure to enhance sleep quality. These findings offer practical strategies for improving the sleep patterns and overall well-being of older adults in residential settings. Support (if any) National Science Foundation (Grant Number:R-23-0018)
Son et al. (Sat,) studied this question.
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