Quantitative headform fit evaluation and predictive modeling to assist with selecting N95 filtering facepiece respirators to mitigate respiratory hazards.
Ensuring that respiratory protection is effective for all can be difficult if limited resources are available to assist with selecting a well-fitting respirator model and user guidance. To better understand how various N95® filtering facepiece respirator models fit on a variety of face sizes, a quan...
| Publicado en: | Journal of Occupational & Environmental Hygiene Vol. 22; no. 12; pp. 959 - 970 |
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| Autores principales: | , , , , , , |
| Formato: | pictorial research tables/charts Journal Article |
| Publicado: |
Taylor & Francis Ltd
Dec2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=190769451&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 190769451 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 15459624 V1L jtl: Journal of Occupational & Environmental Hygiene issn: 15459624 maglogo: Y pubinfo: dt: Dec2025 vid: 22 iid: 12 pid: 377 pub: Taylor & Francis Ltd place: Philadelphia, Pennsylvania artinfo: ui: 190769451 187546049 190769451 190769451 10.1080/15459624.2025.2540829 190769451 ppf: 959 ppct: 11 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Quantitative headform fit evaluation and predictive modeling to assist with selecting N95 filtering facepiece respirators to mitigate respiratory hazards. aug: au: Vollmer, Brooke Bergman, Michael S. Boyles, Harold Meyers, Jordan Payne, Nora Y. Pollard, Jonisha Zhuang, Ziqing affil: National Personal Protective Technology Laboratory, Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health, Pittsburgh, Pennsylvania sug: subj: Equipment Design Evaluation Respiratory Protective Devices Evaluation Occupational Exposure Prevention and Control N95 Respirators Respiratory Tract Diseases Prevention and Control Prediction Models Environmental Health Occupational Health Human United States Male Female Quantitative Studies Multiple Logistic Regression Occupational Safety Respiratory Protective Devices Standards Descriptive Statistics Anthropometry Confidence Intervals Male Female ab: Ensuring that respiratory protection is effective for all can be difficult if limited resources are available to assist with selecting a well-fitting respirator model and user guidance. To better understand how various N95® filtering facepiece respirator models fit on a variety of face sizes, a quantitative fit evaluation was performed on 12 different N95 respirators distributed by the Strategic National Stockpile using five manikin headform sizes representative of most of the U.S. worker population (540 total tests). Manikin fit factor results varied depending on the respirator model and headform combination. Four respirator models achieved passing fit results across all headform sizes. Predictive modeling was then initiated, where the headform most closely aligned to an individual's facial dimensions is determined and then used to identify N95 respirators that may provide an acceptable fit. A multinomial logistic regression model was trained and tested using NIOSH's 2003 Anthropometric U.S. Survey and was found to have an accuracy of 85%. To address potential risks associated with predicting only a single headform size, a modified model allowing for multiple headform size predictions was also assessed and found to have an improved accuracy rate of 98%. With further human subject validation and field testing, this modeling approach could be used as a tool to aid in making the fit testing process more efficient, less burdensome, and better enable individuals to use respirators that fit more effectively, thereby adequately protecting them from hazards. pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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