Four performance measures were used to evaluate the fitting characteristics of 18 models of N95 filtering-facepiece respirators: (1) the 5th percentile simulated workplace protection factor (SWPF) value, (2) the shift average SWPF value, (3) the h-value, and (4) the assignment error. The effect of fit-testing on the level of protection provided by the respirators was also evaluated. The respirators were tested on a panel of 25 subjects with various face sizes. Simulated workplace protection factor values, determined from six total penetration (face-seal leakage plus filter penetration) tests with re-donning between each test, were used to indicate respirator performance. Five fit-tests were used: Bitrex, saccharin, generated aerosol corrected for filter penetration, PortaCount Plus corrected for filter penetration, and the PortaCount Plus with the N95-Companion accessory. Without fit-testing, the 5th percentile SWPF for all models combined was 2.9 with individual model values ranging from 1.3 to 48.0. Passing a fit-test generally resulted in an increase in protection. In addition, the h-value of each respirator was computed. The h-value has been determined to be the population fraction of individuals who will obtain an adequate level of protection (i.e., SWPF >/=10, which is the expected level of protection for half-facepiece respirators) when a respirator is selected and donned (including a user seal check) in accordance with the manufacturer's instructions without fit-testing. The h-value for all models combined was 0.74 (i.e., 74% of all donnings resulted in an adequate level of protection), with individual model h-values ranging from 0.31 to 0.99. Only three models had h-values above 0.95. Higher SWPF values were achieved by excluding SWPF values determined for test subject/respirator combinations that failed a fit-test. The improvement was greatest for respirator models with lower h-values. Using the concepts of shift average and assignment error to measure respirator performance yielded similar results. The highest level of protection was provided by passing a fit-test with a respirator having good fitting characteristics.

Five fit-testing methods (Bitrex, ambient aerosol condensation nuclei counter using the TSI PortaCount Plus, saccharin, modified ambient aerosol condensation nuclei counter using the TSI PortaCount Plus with the N95-Companion, and generated aerosol using corn oil) were evaluated for their ability to identify poorly fitting N95 filtering-facepiece respirators. Eighteen models of NIOSH-certified, N95 filtering-facepiece respirators were tested by a panel of 25 subjects using each fit-testing method. The penetration of the corn oil and the ambient aerosols through the filter media of each respirator was measured in order to adjust the corresponding generated and ambient aerosol overall fit factors, reflecting only face-seal leakage. Fit-testing results were compared to 5th percentiles of simulated workplace protection factors. Beta errors (the chance of passing a fit-test in error) ranged from 3 percent to 11 percent. Alpha errors (the chance of failing a fit-test in error) ranged from 51 percent to 84 percent. The ambient aerosol using the TSI PortaCount Plus and the generated aerosol methods identified poorly fitting respirators better than the saccharin, the Companion, and Bitrex methods. These errors rates should be considered when selecting a fit-testing method for fitting N95 filtering-facepieces. When both types of errors were combined as an assignment error, the ambient aerosol method using the TSI PortaCount Plus had the lowest percentage of wearers being assigned a poor-fitting respirator.

Three fit test methods (Bitrex, saccharin, and TSI PortaCount Plus with the N95-Companion) were evaluated for their ability to identify wearers of respirators that do not provide adequate protection during a simulated workplace test. Thirty models of NIOSH-certified N95 half-facepiece respirators (15 filtering-facepiece models and 15 elastomeric models) were tested by a panel of 25 subjects using each of the three fit testing methods. Fit testing results were compared to 5th percentiles of simulated workplace protection factors. Alpha errors (the chance of failing a fit test in error) for all 30 respirators were 71% for the Bitrex method, 68% for the saccharin method, and 40% for the Companion method. Beta errors (the chance of passing a fit test in error) for all 30 respirator models combined were 8% for the Bitrex method, 8% for the saccharin method, and 9% for the Companion method. The three fit test methods had different error rates when assessed with filtering facepieces and when assessed with elastomeric respirators. For example, beta errors for the three fit test methods assessed with the 15 filtering facepiece respirators were < or = 5% but ranged from 14% to 21% when assessed with the 15 elastomeric respirators. To predict what happens in a realistic fit testing program, the data were also used to estimate the alpha and beta errors for a simulated respiratory protection program in which a wearer is given up to three trials with one respirator model to pass a fit test before moving onto another model. A subject passing with any of the three methods was considered to have passed the fit test program. The alpha and beta errors for the fit testing in this simulated respiratory protection program were 29% and 19%, respectively. Thus, it is estimated, under the conditions of the simulation, that roughly one in three respirator wearers receiving the expected reduction in exposure (with a particular model) will fail to pass (with that particular model), and that roughly one in five wearers receiving less reduction in exposure than expected will pass the fit testing program in error.

The fitting characteristics of particulate respirators are no longer assessed in the National Institute for Occupational Safety and Health respirator certification program. It is important for respirator program administrators to understand the implications of that change and the additional burden it may impose. To address that issue, a typical respirator fit-testing program is analyzed using a mathematical model that describes the effectiveness of a fit-testing program as a function of the fitting characteristics of the respirator and the accuracy of the fittesting method. The model is used to estimate (1) the respirator assignment error, the percentage of respirator wearers mistakenly assigned an ill-fitting respirator; (2) the number of fit-test trials necessary to qualify a group of workers for respirator use; and (3) the number of workers who will fail the fit-test with any candidate respirator model and thereby fail to qualify for respirator use. Using data from previous studies, the model predicts respirator assignment errors ranging from 0 to 20%, depending on the fitting characteristics of the respirator models selected and the fit-testing method used. This analysis indicates that when respirators do not necessarily have good fitting characteristics, respirator program administrators should exercise increased care in the selection of respirator models and increased care in fit-testing. Also presented are ways to assess the fitting characteristics of candidate respirator models by monitoring the first-time fit-testing results. The model demonstrates that significant public health and economic benefits can result when only respirators having good fitting characteristics are purchased and respirators are assigned to workers using highly accurate fit-testing methods.

This article, the second in a series of three, describes the method comparison testing portion of a study conducted to compare the fit factors from six quantitative fit-tests (QNFT) with a measure of a respirator wearer's actual exposure assessed by end-exhaled air analysis for 1,1,2-trichloro-1,2,2-trifluoroethane (Freon-113) under the same conditions. The six QNFT methods were (1) continuous low flow, flush probe; (2) continuous high flow, deep probe (CHD); (3) exhalation valve discharge (EVD); (4) controlled negative pressure; (5) 10-minute Ambient Aerosol 1 (AA1); and (6) 30-minute Ambient Aerosol 2. The first three methods utilized corn oil and a forward light scattering photometer. The last two methods used the TSI Portacount. Respirators used in the study were both disposable and elastomeric organic vapor/high efficiency half-masks. The characterization equations from the preliminary research (described previously) were used to determine the actual exposure to Freon-113 during the method comparison testing. The fit factors resulting from the QNFT methods were then individually correlated with the Freon-113 exposures using the coefficient of determination, R2. The lowest R2 value, 0.20, was found with the EVD method. The highest R2 values, 0.81 and 0.78, were associated, respectively, with the CHD and AA1 methods. This study suggests that some QNFT methods may be used to estimate actual respirator performance under laboratory conditions.