Evidence map›Paper›PMID 34252284›Full record

ArticleRural and remote health2021

US trends in mask wearing during the COVID-19 pandemic depend on rurality.

George Pro, Krista Schumacher, Randolph Hubach, Nickolas Zaller, Zachary Giano, Ricky Camplain, Carolyn Camplain, Shane Haberstroh, Julie A Baldwin, Denna L Wheeler

Open access · diamondAbstract read
In one paragraph

Article in Rural and remote health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.7field-weighted citation impact, top 16% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 21 citations in OpenAlex.

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  12. Community Effectiveness of Masks and Vaccines.Socius : sociological research for a dynamic world
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 4 institutions in 2 countries.

George ProDepartment of Health Behavior and Health Education, Fay W. Boozman College of Public Health, University of Arkansas for Medical Sciences, 4301 West Markham Street, Little Rock, Arkansas, USA gcpro@uams.edu.
Krista SchumacherCenter for Rural Health, Oklahoma State University Center for Health Sciences, 1111 W. 17th St., Tulsa OK krista.schumacher@okstate.edu.
Randolph HubachCenter for Rural Health, Oklahoma State University Center for Health Sciences, 1111 W. 17th St., Tulsa OK randolph.hubach@okstate.edu.
Nickolas ZallerDepartment of Health Behavior and Health Education, Fay W. Boozman College of Public Health, University of Arkansas for Medical Sciences, 4301 West Markham Street, Little Rock, Arkansas, USA ndzaller@uams.edu.
Zachary GianoCenter for Rural Health, Oklahoma State University Center for Health Sciences, 1111 W. 17th St., Tulsa OK giano@okstate.edu.
Ricky CamplainCenter for Health Equity Research, Northern Arizona University, 1395 South Knoles Drive, Flagstaff, Arizona, USA; and Department of Health Sciences, Northern Arizona University, 1100 South Beaver Street, Flagstaff, Arizona, USA ricky.camplain@nau.edu.
Carolyn CamplainCenter for Health Equity Research, Northern Arizona University, 1395 South Knoles Drive, Flagstaff, Arizona, USA carolyn.camplain@nau.edu.
Shane HaberstrohDepartment of Educational Psychology, Northern Arizona University, 801 South Knoles Drive, Flagstaff, Arizona, USA shane.haberstroh@nau.edu.
Julie A BaldwinCenter for Health Equity Research, Northern Arizona University, 1395 South Knoles Drive, Flagstaff, Arizona, USA; and Department of Health Sciences, Northern Arizona University, 1100 South Beaver Street, Flagstaff, Arizona, USA julie.baldwin@nau.edu.
Denna L WheelerCenter for Rural Health, Oklahoma State University Center for Health Sciences, 1111 W. 17th St., Tulsa OK denna.wheeler@okstate.edu.
Northern Arizona University · USJames Cook University · AUOklahoma State University Center for Health Sciences · USUniversity of Arkansas for Medical Sciences · US

Funding

SSCIMA: Integrating Analysis of Socio-economic Sub-population Dynamics to Improve Spatial Models of Infectious DiseaseU54MD012388 · NIMHD · NORTHERN ARIZONA UNIVERSITY · PI Julie A. Baldwin · 2017 to 2026
$49.7M
NIMHD NIH HHS U54 MD012388
6 · The paper itself

Abstract

introductionFace masks are widely recommended as a COVID-19 prevention strategy. State mask mandates have generally reduced the spread of the disease, but decisions to wear a mask depend on many factors. Recent increases in case rates in rural areas following initial outbreaks in more densely populated areas highlight the need to focus on prevention and education. Messaging about disease risk has faced challenges in rural areas in the past. While surges in cases within some communities are likely an impetus for behavior change, rising case rates likely explain only part of mask-wearing decisions. The current study examined the relationship between county-level indicators of rurality and mask wearing in the USA.

methodsNational data from the New York Times' COVID-19 cross-sectional mask survey was used to identify the percentage of a county's residents who reported always/frequently wearing a mask (2-14 July 2020). The New York Times' COVID-19 data repository was used to calculate county-level daily case rates for the 2 weeks preceding the mask survey (15 June - 1 July 2020), and defined county rurality using the Index of Relative Rurality (n=3103 counties). Multivariate linear regression was used to predict mask wearing across levels of rurality. The model was adjusted for daily case rates and other relevant county-level confounders, including county-level indicators of age, race/ethnicity, gender, political partisanship, income inequality, and whether each county was subject to a statewide mask mandate.

resultsLarge clusters of counties with high rurality and low mask wearing were observed in the Midwest, upper Midwest, and mountainous West. Holding daily case rates and other county characteristics constant, the predicted probability of wearing a mask decreased significantly as counties became more rural (&beta;=-0.560; p<0.0001).

conclusionUpticks in COVID-19 cases and deaths in rural areas are expected to continue, and localized outbreaks will likely occur indefinitely. The present findings highlight the need to better understand the mechanisms underlying perceptions of COVID-19 risk in rural areas. Dissemination of scientifically correct and consistent information is critical during national emergencies.

Indexed as

Health Status DisparitiesCOVID-19Cross-Sectional StudiesFemaleHumansLinear ModelsMaleMasksRural PopulationSeverity of Illness IndexSocioeconomic FactorsCOVID-19disparitiesepidemiologypreventionUSA

Identifiers

PMID34252284
PMCPMC8827623
OpenAlexW3180294451

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.