Predictors of student mask mandate policies in United States school districts during the COVID-19 pandemic
Copyright © 2023 Klein, Johnson, Anderson, Beharry, Faden, Guo, Kallem, Nicklin, Regenberg, Tariq and Collins..
Introduction: Although 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.
Methods: Student 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.
Results: State 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.
Discussion: Political, 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.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:11 |
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| Enthalten in: |
Frontiers in public health - 11(2023) vom: 15., Seite 1217638 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Klein, Lauren M [VerfasserIn] |
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| Links: |
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| Themen: |
COVID-19 |
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| Anmerkungen: |
Date Completed 17.08.2023 Date Revised 17.01.2024 published: Electronic-eCollection Citation Status MEDLINE |
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| doi: |
10.3389/fpubh.2023.1217638 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM360831710 |
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| 245 | 1 | 0 | |a Predictors of student mask mandate policies in United States school districts during the COVID-19 pandemic |
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| 500 | |a Date Completed 17.08.2023 | ||
| 500 | |a Date Revised 17.01.2024 | ||
| 500 | |a published: Electronic-eCollection | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Copyright © 2023 Klein, Johnson, Anderson, Beharry, Faden, Guo, Kallem, Nicklin, Regenberg, Tariq and Collins. | ||
| 520 | |a Introduction: Although 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 | ||
| 520 | |a Methods: Student 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 | ||
| 520 | |a Results: State 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 | ||
| 520 | |a Discussion: Political, 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 | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Research Support, Non-U.S. Gov't | |
| 650 | 4 | |a COVID-19 | |
| 650 | 4 | |a health promotion | |
| 650 | 4 | |a mask policy | |
| 650 | 4 | |a public health | |
| 650 | 4 | |a school health | |
| 700 | 1 | |a Johnson, Sara B |e verfasserin |4 aut | |
| 700 | 1 | |a Anderson, Annette C |e verfasserin |4 aut | |
| 700 | 1 | |a Beharry, Kelly |e verfasserin |4 aut | |
| 700 | 1 | |a Faden, Ruth |e verfasserin |4 aut | |
| 700 | 1 | |a Guo, Xinxing |e verfasserin |4 aut | |
| 700 | 1 | |a Kallem, Medha |e verfasserin |4 aut | |
| 700 | 1 | |a Nicklin, Andrew |e verfasserin |4 aut | |
| 700 | 1 | |a Regenberg, Alan |e verfasserin |4 aut | |
| 700 | 1 | |a Tariq, Azka |e verfasserin |4 aut | |
| 700 | 1 | |a Collins, Megan E |e verfasserin |4 aut | |
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