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Year : 2022  |  Volume : 5  |  Issue : 1  |  Page : 3-9

Individual characteristics and demographics associated with mask wearing during the COVID-19 pandemic in the United States

Department of Health Management and Policy, Saint Louis University, Saint Louis, MO, USA

Correspondence Address:
Echu Liu
Ph.D., 3545 Lafayette Ave, Saint Louis, MO 63104
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/shb.shb_148_21

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Introduction: Many scientific studies provide evidence of mask wearing as an effective strategy to reduce the spread of the COVID-19 virus. However, US citizens do not adhere to this prevention practice universally. Although past studies have shown disparities in mask wearing by age, gender, ethnicity, and location, the literature lacks a work that uses large-scale national survey data to understand the mask-wearing resistors' characteristics and demographics. This study's purpose is to fill this gap. Methods: We obtained this study's data from the COVID-19 Impact Survey, a nationally representative survey conducted by NORC at the University of Chicago. This survey aims at generating national and regional statistics by surveying representative regional and national samples in three time periods: April 20–26, 2020, May 4–10, 2020, and June 1–8, 2020. Data for our analysis are from the public-use files of these three waves. We performed logistic regressions to estimate the adjusted risk ratio (ARR) of not wearing masks for several personal characteristics and demographics. Results: Our results suggest that younger (average ARR = 1.66) and lower-income (average ARR = 1.51) adults are more likely not to wear a face mask to prevent the coronavirus spread. On the other hand, unhealthy (average ARR = 0.81), female (average ARR = 0.68), and minority (average ARR = 0.65) adults are less likely not to wear a mask. Furthermore, residents in the Northeast region (average ARR = 0.34) and urban residents (average ARR = 0.54) are less likely not to wear a face mask. Conclusion: Mask-wearing behavior differs by age, income, health status, gender, race, region, and geographical residence in the US.

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