National Institute for Occupational Safety and Health (NIOSH), Health Effects Laboratory Division (HELD), Exposure Assessment Branch (EAB), Morgantown, WV, USA.
Department of Environmental Health, Boston University School of Public Health, Boston, MA, USA.
Ann Work Expo Health. 2020 Jun 24;64(5):547-557. doi: 10.1093/annweh/wxaa023.
Selecting a proper respirator requires determining the ratio of an employee's maximum use concentration (MUC) divided by the occupational exposure limit of a chemical. Current industrial hygiene practice often is to obtain a percentile estimate (e.g. 95th) of the measured exposure distribution to apply as the MUC. However, practitioners who are not yet familiar with statistical or mathematical approaches may choose the highest exposure data point as the MUC, a method that is still considered appropriate by the Occupational Safety and Health Administration. Nonetheless, choosing a respirator using the highest exposure data point when only limited data are available may result in not always providing the most adequate respirator. Because some practitioners are not familiar with exposure assessment tools, our primary goal in this study was to demonstrate the best process when selecting respiratory protection by using a combination of exposure data and assessment tools. Three user-friendly tools, IHDataAnalyst, Advanced REACH Tool, and IHSTAT, were selected to demonstrate how to use different types of tool outputs when choosing a respirator. A decision logic was developed to help users navigate the combining of different data inputs. Personal full-shift exposure data collected in four different workplaces were used to describe four different outcomes generated when the maximum exposure data point and the tool's output are compared with the exposure limit of the chemical. Outcomes varied, from determinations of 'high confidence' (or final decision) to 'low confidence' (or indicating more data are needed) in the selection of a respirator recommendation. In conclusion, systematically adopting the combination of exposure data and assessment tools could increase practitioners' confidence in decision-making when choosing respirators from a limited exposure data set. These suggested guidelines will lead practitioners toward good industrial hygiene practices.
选择合适的呼吸器需要确定员工的最大使用浓度（MUC）与化学物质的职业接触限值的比值。目前，工业卫生实践通常是获取测量暴露分布的百分位数估计值（例如 95 百分位），将其作为 MUC。然而，对于那些尚未熟悉统计或数学方法的从业者来说，他们可能会选择最高暴露数据点作为 MUC，职业安全与健康管理局仍认为这种方法是合适的。尽管如此，当只有有限的数据可用时，选择使用最高暴露数据点的呼吸器可能并不总是提供最合适的呼吸器。由于一些从业者不熟悉暴露评估工具，我们在这项研究中的主要目标是展示在使用暴露数据和评估工具相结合选择呼吸保护时的最佳流程。选择了三种用户友好的工具，即 IHDataAnalyst、Advanced REACH Tool 和 IHSTAT，以演示如何在选择呼吸器时使用不同类型的工具输出。制定了决策逻辑来帮助用户在组合不同的数据输入时进行导航。使用在四个不同工作场所收集的个人全天暴露数据，描述了当最大暴露数据点和工具的输出与化学物质的暴露限值进行比较时生成的四种不同结果。结果从选择呼吸器建议的“高置信度”（或最终决策）到“低置信度”（或表示需要更多数据）不等。总之，系统地采用暴露数据和评估工具的组合可以提高从业者在从有限的暴露数据集选择呼吸器时的决策信心。这些建议的准则将引导从业者遵循良好的工业卫生实践。
