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Observational Study
. 2023 Jun;9(3):253-263.
doi: 10.1016/j.sleh.2023.02.010. Epub 2023 Apr 18.

Associations of bedroom PM2.5, CO2, temperature, humidity, and noise with sleep: An observational actigraphy study

Mathias Basner  1 , Michael G Smith  2 , Christopher W Jones  2 , Adrian J Ecker  2 , Kia Howard  2 , Victoria Schneller  2 , Makayla Cordoza  2 , Marc Kaizi-Lutu  2 , Sierra Park-Chavar  2 , Alexander C Stahn  2 , David F Dinges  2 , Haochang Shou  3 , Jonathan A Mitchell  4 , Aruni Bhatnagar  5 , Ted Smith  5 , Allison E Smith  5 , Cameron K Stopforth  5 , Ray Yeager  5 , Rachel J Keith  5
Affiliations
Observational Study

Associations of bedroom PM2.5, CO2, temperature, humidity, and noise with sleep: An observational actigraphy study

Mathias Basner et al. Sleep Health. 2023 Jun.

Abstract

Objective: Climate change and urbanization increasingly cause extreme conditions hazardous to health. The bedroom environment plays a key role for high-quality sleep. Studies objectively assessing multiple descriptors of the bedroom environment as well as sleep are scarce.

Methods: Particulate matter with a particle size <2.5 µm (PM2.5), temperature, humidity, carbon dioxide (CO2), barometric pressure, and noise levels were continuously measured for 14 consecutive days in the bedroom of 62 participants (62.9% female, mean ± SD age: 47.7 ± 13.2 years) who wore a wrist actigraph and completed daily morning surveys and sleep logs.

Results: In a hierarchical mixed effect model that included all environmental variables and adjusted for elapsed sleep time and multiple demographic and behavioral variables, sleep efficiency calculated for consecutive 1-hour periods decreased in a dose-dependent manner with increasing levels of PM2.5, temperature, CO2, and noise. Sleep efficiency in the highest exposure quintiles was 3.2% (PM2.5, p < .05), 3.4% (temperature, p < .05), 4.0% (CO2, p < .01), and 4.7% (noise, p < .0001) lower compared to the lowest exposure quintiles (all p-values adjusted for multiple testing). Barometric pressure and humidity were not associated with sleep efficiency. Bedroom humidity was associated with subjectively assessed sleepiness and poor sleep quality (both p < .05), but otherwise environmental variables were not statistically significantly associated with actigraphically assessed total sleep time and wake after sleep onset or with subjectively assessed sleep onset latency, sleep quality, and sleepiness. Assessments of bedroom comfort suggest subjective habituation irrespective of exposure levels.

Conclusions: These findings add to a growing body of evidence highlighting the importance of the bedroom environment-beyond the mattress-for high-quality sleep.

Keywords: Actigraphy; Air quality; CO(2); Noise; PM(2.5); Temperature.

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Conflict of interest statement

Declaration of conflict of interest The authors have no conflicts of interest to declare related to the work presented in this manuscript.

Figures

Figure 1:
Figure 1:
Bedroom environment by time of day. Values of mean fine particulate matter (PM2.5), mean relative humidity, mean temperature, mean CO2, mean barometric pressure, and median sound pressure levels are plotted against time of day (the median was chosen for sound pressure levels as they are strongly affected by outliers). Values were derived from all subjects with valid air quality and sound level data. Percent of participants sleeping is shown in gray. PM2.5 and sound pressure levels show decreasing trends, humidity and CO2 show increasing trends while temperature and barometric pressure show a slightly decreasing followed by a slightly increasing trend during participants’ sleep periods.
Figure 2:
Figure 2:
Associations of the bedroom environment with objectively assessed (via actigraphy) SE, total sleep time and wake after sleep onset. P-values reflect type-III tests for fixed effects. Estimates are based on the fully adjusted model (Model 4), using observed marginal means for all covariates. PM2.5: fine particulate matter; asterisks reflect statistical significance of post-hoc tests contrasting quintiles 2–5 to quintile 1 (after false-discovery rate adjustment; *adjusted p<0.05; **adjusted p<0.01; ***adjusted p<0.001; ****adjusted p<0.0001)
Figure 3:
Figure 3:
Associations of the bedroom environment with self-reported sleep onset latency, sleep quality and sleepiness (via daily morning surveys). P-values reflect type-III tests for fixed effects. Estimates are based on the fully adjusted model (Model 4) using observed marginal means for all covariates. PM2.5: fine particulate matter; Q1–5: quintiles 1–5; asterisks reflect statistical significance of post-hoc tests contrasting quintiles 2–5 to quintile 1 (after false-discovery rate adjustment; *adjusted p<0.05; **adjusted p<0.01; ***adjusted p<0.001; ****adjusted p<0.0001)
Figure 4:
Figure 4:
Associations of window opening behavior and the use of window air conditioning, central air conditioning or a fan with indoor measurements of fine particulate matter (PM2.5), relative humidity, temperature, CO2 and noise. * adjusted p<0.05; AC: air conditioning
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