Evidence map›Paper›PMID 42335197›Full record

ArticleAnnals of work exposures and health2026

N95 filtering facepiece respirator fit assessment outcomes by gender, age, race, and facial hair in a community population sample.

Majid Bagheri Hosseinabadi, Minji Yu, Ashley Petersen, Linsey Griffin, William Durfee, Susan Arnold

Abstract read
In one paragraph

Article in Annals of work exposures and health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Majid Bagheri HosseinabadiDivision of Environmental Health Sciences, School of Public Health, University of Minnesota, Minneapolis, MN 55455, United States.ORCID 0000-0002-5477-199X
Minji YuDepartment of Clothing and Textiles, College of Human Ecology, Yonsei University, Seoul 03722, Korea.ORCID 0000-0003-3997-6409
Ashley PetersenDivision of Biostatistics and Health Data Science, School of Public Health, University of Minnesota, Minneapolis, MN 55455, United States.ORCID 0000-0001-7711-9657
Linsey GriffinCollege of Design, University of Minnesota, 1985 Buford Avenue, 240 McNeal Hall, Saint Paul, MN 55108, United States.ORCID 0000-0003-4058-5106
William DurfeeDepartment of Mechanical Engineering, College of Science and Engineering, University of Minnesota, Minneapolis, MN 55455, United States.
Susan ArnoldDivision of Environmental Health Sciences, School of Public Health, University of Minnesota, Minneapolis, MN 55455, United States.ORCID 0000-0002-1465-3761

Funding

University of Minnesota Institute for Engineering in MedicineUniversity of Minnesota Office of Discovery and Translation
6 · The paper itself

Abstract

The necessity for respiratory protection has increased due to global threats such as pandemics, industrial accidents, and extreme weather events. The effectiveness of N95 filtering facepiece respirators depends on how well they fit the user's face and seal sufficiently. The objective of this study was to assess the critical issue of N95 filtering facepiece respirator fit test pass rates in the general population, specifically examining the influences of gender, age group, and race. Methods This cross-sectional study was conducted with Minnesota State Fair attendees in 2021 and 2022. Participants were asked to complete a demographic questionnaire, which included details on age, gender, race/ethnicity, and facial hair. A quantitative single-exercise fit assessment of N95 filtering facepiece respirators was conducted using a TSI PortaCount Pro+ (Model 8038). The assessment was based on the talking exercise derived from the Occupational Safety and Health Administration respiratory protection protocol, with a criterion of a fit factor ≥100 for passing the fit assessment. Descriptive statistics and multiple logistic regression analyses were performed using RStudio (version 4.4.2) to assess the influence of demographic variables on respirator fit assessment results. Results A total of 384 participants were enrolled, with 63.8% being female and 80.2% identifying as White. Respirator fit assessment pass rates were significantly lower for males with facial hair compared to females and males without facial hair. None of the participants with full beards achieved an acceptable fit. Participants aged 19 yrs or younger had the highest pass rates. Females were 83% more likely to pass the fit assessment compared with males without facial hair (odds ratio [OR] = 1.83, 95% CI: 1.02 to 3.38), while males with facial hair were 68% less likely to pass the fit assessment than males without facial hair (OR = 0.32, 95% CI: 0.13 to 0.73). Nonlinear age-related differences in fit assessment results were observed, with the lowest odds of passing among participants in their 30 and 40 s compared with those aged 19 yrs or younger. No significant differences in the fit assessment pass rates between racial and ethnic groups were observed. Conclusion Gender, age, and facial hair type were found to significantly affect the likelihood of participants passing the fit assessment for N95 filtering facepiece respirators. No significant disparities were observed among racial and ethnic groups. These findings underscore the importance of considering gender, age, and facial hair when developing public health guidelines for respirator protection.

Indexed as

N95 RespiratorsOccupational ExposureRespiratory Protective DevicesAdolescentAdultAgedAge FactorsCross-Sectional StudiesEquipment DesignFaceFemaleHairHumansMaleMiddle AgedMinnesotaage groupN95 respiratorquantitative fit testTSI PortaCount Pro+

Identifiers

PMID42335197
PMCPMC13289748

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.