Variability in respiratory protection and the assigned protection factor

被引:26
|
作者
Nicas, M
Neuhaus, J
机构
[1] Univ Calif Berkeley, Sch Publ Hlth, Ctr Occupat & Environm Hlth, Berkeley, CA 94720 USA
[2] Univ Calif San Francisco, Dept Biostat & Epidemiol, San Francisco, CA 94143 USA
关键词
assigned protection factor; protection factor variability; respiratory protection;
D O I
10.1080/15459620490275821
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The workplace protection factor (WPF) for a given respirator wearer shows substantial variability from wearing to wearing; this variability is commonly assumed to be lognormal in nature. Further, when multiple WPFs are measured for each of multiple wearers, the aggregated WPFs appear to follow a lognormal distribution. However, the analysis typically applied to WPF data does not apportion variability within versus between wearers. We present an analytical framework based on a normal random effects model of log-transformed penetration P values (P = 1/WPF). Data from seven studies of negative-pressure air-purifying half-mask respirators, and from two studies of hemlet-and-visor type powered air-purifying respirators were analyzed by the method of maximum likelihood in the context of the Model. More specifically, analyses were performed for long-transformed P values and for logit-transformed P values. Parameter estimates included within-wearer and between-wearer variance components. In general, the within-wearer component dominated the between-wearer component. We also propose a method for establishing an assigned protection factor; APF, that properly accounts for these variance components. Our method provides an APF satisfying two criteria: (1) for a given wearer, an acceptable WPF distribution has no more than 5% of WPFs below the APF value; and (2)for a wearer population, no more than 5% of wearers have unacceptable WPF distributions. The method incorporates an one-sided confidence limit to account for sampling variability. Alternative confidence limits were computed based on large sample variance estimates of random effects model parameters versus a bootstrap method. In general, there was good agreement between the APF values based on log-transformed versus logit-transformed P data, and between APF values based on the large sample variance estimates versus the bootstrap method. Based on large sample variance estimates for the logit-transformed P data from the seven half-mask studies, estimated APFs ranged from 1.4 to 250, with 5/7 studies yielding an APFless than or equal to 5.3. Given these results and related considerations, we recommend that the current half mask APF be reduced from 10 to 5.
引用
收藏
页码:99 / 109
页数:11
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