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. 2024 Mar 24:10:20552076241241509.
doi: 10.1177/20552076241241509. eCollection 2024 Jan-Dec.

Sensing the impact of extreme heat on physical activity and sleep

So-Min Cheong  1 , Irina Gaynanova  2
Affiliations

Sensing the impact of extreme heat on physical activity and sleep

So-Min Cheong et al. Digit Health. .

Abstract

Introduction: This study assesses the person-specific impact of extreme heat on low-income households using wearable sensors. The focus is on the intensive and longitudinal assessment of physical activity and sleep with the rising person-specific ambient temperature.

Methods: This study recruited 30 participants in a low-income and predominantly Black community in Houston, Texas in August and September of 2022. Each participant wore on his/her wrist an accelerometer that recorded person-specific ambient temperature, sedentary behavior, physical activity intensity (low and moderate to vigorous), and sleep efficiency 24 h over 14 days. Mixed effects models were used to analyze associations among physical activity, sleep, and person-specific ambient temperature.

Results: The main findings include increased sedentary time, sleep impairment with the rise of person-level ambient temperature, and the mitigating role of AC.

Conclusions: Extreme heat negatively affects physical activity and sleep. The negative consequences are especially critical for those with limited use of AC in lower-income neighborhoods of color. Staying home with a high indoor temperature during hot days can lead to various adverse health outcomes including accelerated cognitive decline, higher cancer risk, and social isolation.

Keywords: Extreme heat; accelerometer; ambient temperature; physical activity; sleep.

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Conflict of interest statement

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Figures

Figure 1.
Figure 1.
The predicted percentage of sedentary time as a function of person-specific ambient temperature (with 95% CI) for age = 70 (black) and age = 35 (blue) based on Model 1.
Figure 2.
Figure 2.
The predicted sleep efficiency as a function of person-specific ambient temperature (with 95% CI) on sleep efficiency for age = 70 (black) and age = 35 (blue) based on Model 2. The lines overlap as the estimated effect size for age was small (βage = 0.06) and not significant (p-value = .719).
Figure 3.
Figure 3.
The predicted person-specific ambient temperature as a function of outside temperature for weekday (black) and weekend (red) separated by AC use (straight—frequent, pointed—infrequent) based on Model 3. Age effect is not shown as it was not significant after adjusting for the day type (p-value = .2475) with a small estimated effect size (βage = 0.02). A significant interaction exists between AC use and day type, with a stronger correlation between person-specific ambient and outside temperatures with frequent AC use on the weekends (red straight line) compared to weekdays (black straight line).
See this image and copyright information in PMC

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