Demographic Differences in Facial Anthropometric Data from 3D Scans and Implications for Respirator Fit
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2025/05/01
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Description:Objective: In response to limitations in foundational anthropometric research efforts as well as the increasingly diversifying workforce, researchers have attempted to define the presence or absence of differences in respirator-related facial measurements between different demographic groups. The purpose of the present study was to assess the presence of differences in facial measurements from 3D scans related to respirator fit, based on demographic factors of gender, race/ethnicity, and age in a sample of 2,022 3D scans. Methods: Three-dimensional (3D) body scanning technology was used to gather facial measurement data. Principal components analysis (PCA) and multivariate analysis of variance (MANOVA) were employed to determine the presence or absence of differences in measurements from 3D scans between the demographic groups. Results: Results indicated that measurements from 3D scans related to respirator fit were significantly different for all groups within each demographic category (gender, race/ethnicity, and age). Conclusion: The findings suggest that demographic factors such as gender, race/ethnicity, and age have a significant impact on facial measurements from 3D scans, which has implications for respirator fit and design considerations. [Description provided by NIOSH]
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ISSN:2398-7308
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Pages in Document:442-452
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Volume:69
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Issue:4
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NIOSHTIC Number:nn:20070698
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Citation:Ann Work Expo Health 2025 May; 69(4):442-452
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Contact Point Address:Kayna Hobbs-Murphy, Department of Design and Merchandising, Colorado State University, 1574 Campus Delivery, Fort Collins, CO 80523-1574, United States
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Email:Kayna.Hobbs-Murphy@colostate.edu
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Federal Fiscal Year:2025
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Performing Organization:University of Colorado, Denver
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Peer Reviewed:True
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Start Date:20070701
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Source Full Name:Annals of Work Exposures and Health
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End Date:20250630
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Main Document Checksum:urn:sha-512:6940962edf7a6db14ceefdb4e1481791d2d572df20b76940bfec9ac662cf0c8b631dcda6157fe161144b44844738a2c1af031898a5e4a4dd068af7009793bbe4
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