BACKGROUND
The COVID-19 pandemic led to various containment strategies, such as work-from-home policies and reduced social contact, which significantly altered people's sleep routines. While previous studies have highlighted the negative impacts of these restrictions on sleep, they often overlook a comprehensive perspective that incorporates other factors that can also influence sleep, namely seasonal variations and physical activity.
OBJECTIVE
Our study aims to longitudinally examine the fine-grained changes in sleep patterns of working adults during the COVID-19 pandemic using a combination of repeated questionnaires and high-resolution passive measurements from wearable sensors. We investigate the association between sleep and 5 sets of variables capturing characteristics of individuals including (i) demographics, (ii) sleep-related habits, (iii) physical activity behaviors, and external factors including (iv) pandemic-specific constraints, and (v) seasonal variations during the study period.
METHODS
We recruited working adults in Finland to participate in our one-year-long study (June 2021 - June 2022) conducted in the late stage of the COVID-19 pandemic. We collected multisensor data from fitness trackers worn by the participants as well as work and sleep-related measures through monthly questionnaires. Additionally, we used the stringency index for Finland at different points in time to estimate the degree of the pandemic-related lockdown restrictions in place during the study duration. We applied linear mixed models to study the changes in sleep patterns during the late stage of the pandemic and their association with the aforementioned five sets of variables.
RESULTS
The sleep patterns of 27,350 nights from 111 working adults were analyzed. We observed that more stringent pandemic measures were associated with longer total sleep time (TST) (β= 0.004, 95% CI 0.002 to 0.006, P<.001) and later midpoint of sleep (MS) (β= 0.02, 95% CI 0.02 to 0.03, P<.001). Being a snoozer (i.e., snoozing the alarm when waking up from sleep) was associated with higher variability in both TST (β= 0.18, 95% CI 0.07 to 0.30, P=.002) and MS (β= 0.19, 95% CI 0.06 to 0.34, P=.008). Service staff slept more than academic staff (β= 0.36, 95% CI 0.10 to 0.61, P=.006) with also lower variability in TST (β= -0.16, 95% CI -0.27 to -0.04, P=.006). Engaging in physical activity later in the day correlated with longer sleep duration (β= 0.03, 95% CI 0.02 to 0.04, P<.001).
CONCLUSIONS
Our study provided a comprehensive view of the possible factors affecting sleep patterns during the late stage of the pandemic. Our results revealed that stringent measures implemented during the COVID-19 pandemic are associated with changes in sleep patterns. The more flexible work-life routine arising from the restriction is also linked with changes in sleep-related habits among different occupations.