BMC Public Health (Nov 2021)

Global trends and predictors of face mask usage during the COVID-19 pandemic

  • Elena Badillo-Goicoechea,
  • Ting-Hsuan Chang,
  • Esther Kim,
  • Sarah LaRocca,
  • Katherine Morris,
  • Xiaoyi Deng,
  • Samantha Chiu,
  • Adrianne Bradford,
  • Andres Garcia,
  • Christoph Kern,
  • Curtiss Cobb,
  • Frauke Kreuter,
  • Elizabeth A. Stuart

DOI
https://doi.org/10.1186/s12889-021-12175-9
Journal volume & issue
Vol. 21, no. 1
pp. 1 – 12

Abstract

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Abstract Background Guidelines and recommendations from public health authorities related to face masks have been essential in containing the COVID-19 pandemic. We assessed the prevalence and correlates of mask usage during the pandemic. Methods We examined a total of 13,723,810 responses to a daily cross-sectional online survey in 38 countries of people who completed from April 23, 2020 to October 31, 2020 and reported having been in public at least once during the last 7 days. The outcome was individual face mask usage in public settings, and the predictors were country fixed effects, country-level mask policy stringency, calendar time, individual sociodemographic factors, and health prevention behaviors. Associations were modeled using survey-weighted multivariable logistic regression. Results Mask-wearing varied over time and across the 38 countries. While some countries consistently showed high prevalence throughout, in other countries mask usage increased gradually, and a few other countries remained at low prevalence. Controlling for time and country fixed effects, sociodemographic factors (older age, female gender, education, urbanicity) and stricter mask-related policies were significantly associated with higher mask usage in public settings. Crucially, social behaviors considered risky in the context of the pandemic (going out to large events, restaurants, shopping centers, and socializing outside of the household) were associated with lower mask use. Conclusion The decision to wear a face mask in public settings is significantly associated with sociodemographic factors, risky social behaviors, and mask policies. This has important implications for health prevention policies and messaging, including the potential need for more targeted policy and messaging design.

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