Estimated sleep duration before and during the COVID-19 pandemic in major metropolitan areas on different continents: Observational study of smartphone app data

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Abstract

Background: Amid the COVID-19 pandemic, public health policies to curb the spread of SARS-CoV-2 and its associated disease, COVID-19, have resulted in significant alterations to daily routines (eg, work-from-home policies) that may have enabled longer sleep duration among the general population. Objective: We aimed to examine changes in estimated sleep duration in 5 major metropolitan areas before and after the start of the COVID-19 pandemic. Methods: We conducted a prospective observational study using estimated sleep duration data obtained from a smartphone app. The data were obtained from regular users of the smartphone app before and after the World Health Organization declared COVID-19 a pandemic in March 2020. We compared within-subject estimated sleep duration before and during the COVID-19 pandemic using generalized linear mixed models. Results: Among the 2,871,037 observations, 957,022 (33.3%) were from users in London; 549,151 (19.1%) were from users in Los Angeles; 846,527 (29.5%) were from users in New York City; 251,113 (8.7%) were from users in Seoul; and 267,224 (9.3%) were from users in Stockholm. The average age of the users in the sample was 35 years (SE 11 years). Prior to the COVID-19 pandemic, people residing in Seoul had the shortest estimated sleep duration (mean 6 hours 28 minutes, SE 11.6 minutes) and those residing in Stockholm had the longest estimated sleep duration (mean 7 hours 34 minutes, SE 9.9 minutes). The onset of the COVID-19 pandemic was associated with a 13.7 minute increase in estimated sleep duration when comparing March 2019 and March 2020 (95% CI 13.1-14.3, P

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Robbins, R., Affouf, M., Weaver, M. D., Czeisler, M., Barger, L. K., Quan, S. F., & Czeisler, C. A. (2021). Estimated sleep duration before and during the COVID-19 pandemic in major metropolitan areas on different continents: Observational study of smartphone app data. Journal of Medical Internet Research, 23(2). https://doi.org/10.2196/20546

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