Predictors of student mask mandate policies in United States school districts during the COVID-19 pandemic
IntroductionAlthough factors such as urbanicity, population demographics, and political affiliation have been linked with COVID-19 masking behavior and policy in community settings, little work has investigated factors associated with school mask policies. We sought to characterize United States sta...
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Frontiers Media S.A.
2023-07-01
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Online Access: | https://www.frontiersin.org/articles/10.3389/fpubh.2023.1217638/full |
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author | Lauren M. Klein Sara B. Johnson Sara B. Johnson Sara B. Johnson Annette C. Anderson Kelly Beharry Kelly Beharry Ruth Faden Ruth Faden Xinxing Guo Medha Kallem Andrew Nicklin Alan Regenberg Azka Tariq Megan E. Collins Megan E. Collins Megan E. Collins Megan E. Collins Megan E. Collins |
author_facet | Lauren M. Klein Sara B. Johnson Sara B. Johnson Sara B. Johnson Annette C. Anderson Kelly Beharry Kelly Beharry Ruth Faden Ruth Faden Xinxing Guo Medha Kallem Andrew Nicklin Alan Regenberg Azka Tariq Megan E. Collins Megan E. Collins Megan E. Collins Megan E. Collins Megan E. Collins |
author_sort | Lauren M. Klein |
collection | DOAJ |
description | IntroductionAlthough factors such as urbanicity, population demographics, and political affiliation have been linked with COVID-19 masking behavior and policy in community settings, little work has investigated factors associated with school mask policies. We sought to characterize United States state and school district student COVID-19 masking policies during the 2021–22 school year and determine predictors of these mandates at four time points, including before and after federal guidance relaxed school mask recommendations in February 2022.MethodsStudent mask policies for US states and the District of Columbia, as well as a sample of 56 districts were categorized as prohibited, recommended, or required in September 2021, November 2021, January 2022, and March 2022 based on the Johns Hopkins eSchool+ Initiative School Reopening Tracker. Changes in policies over time were characterized. Generalized estimating equations and logistic regression were used to evaluate whether political affiliation of governor, urbanicity, economic disadvantage, and race/ethnic composition of district students, and county-level COVID-19 incidence predicted the presence of a district mask mandate at any time point and at all four time points.ResultsState and district policies changed over time. Districts that implemented student mandates at any point were more likely to be in states with Democratic governors (AOR: 5.52; 95% CI: 2.23, 13.64) or in non-rural areas (AOR: 8.20; 95% CI: 2.63, 25.51). Districts that retained mask mandates at all four time points were more likely to have Democratic governors (AOR: 5.39; 95% CI: 2.69, 10.82) and serve a smaller proportion of economically disadvantaged students (AOR: 0.97; 95% CI: 0.95, 0.99). Districts serving a larger proportion of students from minoritized racial/ethnic groups were more likely to have mask mandates at any or all timepoints. Notably, county-level COVID-19 prevalence was not related to the presence of a mask mandate at any or all time points. By March 2022, no factors were significantly associated with district mask policy.DiscussionPolitical, geographic, and demographic characteristics predicted the likelihood of student mask mandates in the 2021–22 school year. Public health promotion messages and policy must account for variation in these factors, potentially through centralized and consistent messaging and unbiased, trustworthy communication. |
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publishDate | 2023-07-01 |
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spelling | doaj.art-429db72322a84d168d94a4a3003ea1062023-07-31T11:16:52ZengFrontiers Media S.A.Frontiers in Public Health2296-25652023-07-011110.3389/fpubh.2023.12176381217638Predictors of student mask mandate policies in United States school districts during the COVID-19 pandemicLauren M. Klein0Sara B. Johnson1Sara B. Johnson2Sara B. Johnson3Annette C. Anderson4Kelly Beharry5Kelly Beharry6Ruth Faden7Ruth Faden8Xinxing Guo9Medha Kallem10Andrew Nicklin11Alan Regenberg12Azka Tariq13Megan E. Collins14Megan E. Collins15Megan E. Collins16Megan E. Collins17Megan E. Collins18Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD, United StatesDepartment of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD, United StatesDepartment of Population, Family, and Reproductive Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, United StatesDepartment of Mental Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, United StatesJohns Hopkins University School of Education, Baltimore, MD, United StatesUniversity of Michigan Medical School, Ann Arbor, MI, United StatesWilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, MD, United StatesJohns Hopkins Berman Institute of Bioethics, Baltimore, MD, United StatesDepartment of Health Policy and Management, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, United StatesWilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, MD, United StatesWilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, MD, United StatesBloomberg Center for Government Excellence, Baltimore, MD, United StatesJohns Hopkins Berman Institute of Bioethics, Baltimore, MD, United StatesWilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, MD, United StatesDepartment of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD, United StatesJohns Hopkins University School of Education, Baltimore, MD, United StatesJohns Hopkins Berman Institute of Bioethics, Baltimore, MD, United StatesDepartment of Health Policy and Management, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, United States0Department of Ophthalmology, Johns Hopkins University School of Medicine, Baltimore, MD, United StatesIntroductionAlthough factors such as urbanicity, population demographics, and political affiliation have been linked with COVID-19 masking behavior and policy in community settings, little work has investigated factors associated with school mask policies. We sought to characterize United States state and school district student COVID-19 masking policies during the 2021–22 school year and determine predictors of these mandates at four time points, including before and after federal guidance relaxed school mask recommendations in February 2022.MethodsStudent mask policies for US states and the District of Columbia, as well as a sample of 56 districts were categorized as prohibited, recommended, or required in September 2021, November 2021, January 2022, and March 2022 based on the Johns Hopkins eSchool+ Initiative School Reopening Tracker. Changes in policies over time were characterized. Generalized estimating equations and logistic regression were used to evaluate whether political affiliation of governor, urbanicity, economic disadvantage, and race/ethnic composition of district students, and county-level COVID-19 incidence predicted the presence of a district mask mandate at any time point and at all four time points.ResultsState and district policies changed over time. Districts that implemented student mandates at any point were more likely to be in states with Democratic governors (AOR: 5.52; 95% CI: 2.23, 13.64) or in non-rural areas (AOR: 8.20; 95% CI: 2.63, 25.51). Districts that retained mask mandates at all four time points were more likely to have Democratic governors (AOR: 5.39; 95% CI: 2.69, 10.82) and serve a smaller proportion of economically disadvantaged students (AOR: 0.97; 95% CI: 0.95, 0.99). Districts serving a larger proportion of students from minoritized racial/ethnic groups were more likely to have mask mandates at any or all timepoints. Notably, county-level COVID-19 prevalence was not related to the presence of a mask mandate at any or all time points. By March 2022, no factors were significantly associated with district mask policy.DiscussionPolitical, geographic, and demographic characteristics predicted the likelihood of student mask mandates in the 2021–22 school year. Public health promotion messages and policy must account for variation in these factors, potentially through centralized and consistent messaging and unbiased, trustworthy communication.https://www.frontiersin.org/articles/10.3389/fpubh.2023.1217638/fullschool healthCOVID-19mask policypublic healthhealth promotion |
spellingShingle | Lauren M. Klein Sara B. Johnson Sara B. Johnson Sara B. Johnson Annette C. Anderson Kelly Beharry Kelly Beharry Ruth Faden Ruth Faden Xinxing Guo Medha Kallem Andrew Nicklin Alan Regenberg Azka Tariq Megan E. Collins Megan E. Collins Megan E. Collins Megan E. Collins Megan E. Collins Predictors of student mask mandate policies in United States school districts during the COVID-19 pandemic Frontiers in Public Health school health COVID-19 mask policy public health health promotion |
title | Predictors of student mask mandate policies in United States school districts during the COVID-19 pandemic |
title_full | Predictors of student mask mandate policies in United States school districts during the COVID-19 pandemic |
title_fullStr | Predictors of student mask mandate policies in United States school districts during the COVID-19 pandemic |
title_full_unstemmed | Predictors of student mask mandate policies in United States school districts during the COVID-19 pandemic |
title_short | Predictors of student mask mandate policies in United States school districts during the COVID-19 pandemic |
title_sort | predictors of student mask mandate policies in united states school districts during the covid 19 pandemic |
topic | school health COVID-19 mask policy public health health promotion |
url | https://www.frontiersin.org/articles/10.3389/fpubh.2023.1217638/full |
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