Who was wearing a mask in 2021? Update on gender-, age-, and location-related differences during the COVID-19 pandemic

This article has been Reviewed by the following groups

Read the full article See related articles

Abstract

Previous observational work from 2020 demonstrated gender-, age-, and location-related differences in mask-wearing behavior, despite the efficacy and public health messaging that emphasized face coverings in combatting the spread of COVID-19. In 2021, COVID-19 vaccinations and a corresponding change in public health policy became new considerations in deciding personal protective behaviors. To provide an update on mask wearers and resistors approximately one year after our initial study, we observed shoppers ( n = 6,118) entering retail stores using the same experimental methodology. Approximately 26% of individuals wore a mask. Mask wearing has decreased across demographic groups compared to 2020. Aligning with previous findings, females were ∼1.5x more likely to be observed wearing a mask than males, and the odds of observing a shopper wearing a mask in a suburban or urban area was far greater than at rural stores (∼5.7x and ∼3.3x, respectively). Gender and location are confirmed to be significant and stable factors that impact mask-wearing behavior in the United States during the COVID-19 pandemic. The impact of age on mask wearing was heavily reduced compared to 2020, potentially due to the availability of COVID-19 vaccines and change in mask guidance for vaccinated individuals.

Article activity feed

  1. SciScore for 10.1101/2022.01.18.22269479: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    EthicsIRB: Summary observation sheets were crosschecked by other observers and all procedures involved public observation or information and did not require review by an Institutional Review Board.
    Sex as a biological variableAdjusted odds ratios (aOR) are expressed with respect to reference groups (gender: male, age: young, location: rural) with 95% confidence intervals and significance was determined at p < 0.05.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    All analyses were performed with either Microsoft Excel (Microsoft, Redmond, WA, USA) or IBM Statistical Package for Social Sciences version 26 (IBM, Armonk, NY, USA).
    Microsoft Excel
    suggested: (Microsoft Excel, RRID:SCR_016137)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).


    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Despite the limitations of estimating gender and age, and the availability of vaccines to individuals over 12 years, it can be roughly estimated that up to 25% of shoppers observed during data collection were not vaccinated and were also not wearing a mask. Even asymptomatic individuals may transmit the virus to other people [41-43] and unvaccinated persons likely transmit at a greater rate than vaccinated individuals [44-45]. Taken together with our results, the potentially large number of unvaccinated and unmasked persons in retail stores could have a substantial impact in prolonging the pandemic.

    Results from TrialIdentifier: No clinical trial numbers were referenced.


    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


    Results from JetFighter: We did not find any issues relating to colormaps.


    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.


    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.