title: An assessment of critical anthropometric dimensions for predicting the fit of a half-mask respirator.
abstract: The purpose of this study was to determine if facial dimensions for a group of subjects were predictive of the fit factors measured while one brand of half-mask respirator was worn. Fit factors and 12 facial dimensions measured on 30 female and 38 male subjects were analyzed by correlation coefficients; weighted, multiple linear regression; and discriminant analysis. Data were analyzed for all subjects, gender subgroups, a race subgroup (whites only), and race/gender subgroups. Significant correlation coefficients with the log-transformed fit factors were found for four dimensions; four dimensions had significant coefficients in four or more multiple linear regression models. Only two dimensions had significant coefficients in four or more discriminant analysis models. Menton-subnasale (lower face) length was the only dimension included in all three of these groups. Gender-specific regression models had very high coefficient of determination values (R2 > 0.85). Discriminant analysis of the data for all subjects and race/gender subgroups found very good predictive scores for statistical software-generated models and menton-subnasale length alone; these scores were significantly better than those for the model with the respirator test panel dimensions (face length and lip width). These analyses found that facial dimensions were good predictors of respirator fit for those subjects wearing one brand of half-mask respirator. Lower face length was consistently indicated as being correlated or associated with fit. These results would indicate that dimensions other than those currently used may be more appropriate to define a half-mask respirator test panel.
authors.affiliation: School of Public Health, University of Alabama, Birmingham 35294-0008.
authors.forename: R K
authors.initials: RK
authors.lastname: Oestenstad
authors.forename: L L
authors.initials: LL
authors.lastname: Perkins
mesh_terms: D000328:Adult; D000336:Aerosols; D002508:Cephalometry / Q000379:methods* / Q000706:statistics & numerical data; D004867:Equipment Design; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D012016:Reference Values; D012044:Regression Analysis; D012134:Respiratory Protective Devices
chemical_list: D000336:Aerosols