chapter  16
20 Pages

Occupational Exposure Assessment Strategies

The design of an exposure assessment strategy should be driven by the reason for obtaining samples, i.e., the question that needs to be answered or decision that needs to be made using the data. In Chapter 1, several reasons for carrying out sampling for air contaminants were discussed. The most common reason is routine monitoring of worker exposures to chemicals in a workplace and comparison of these exposures with occupational exposure limits (OELs). This can be carried out by occupational hygienists employed by the company to make decisions about restricting workplace exposures to acceptable levels, or by regulatory enforcement agencies to determine if worker exposures meet legal standards. Another important reason might be to determine a relationship between exposure and the health outcome in an occupational epidemiology study, which, in turn, might lead to the establishment of new standards. Although other special reasons might exist, they usually fall under the umbrella of the two reasons cited above. The sampling strategy includes the collection, statistical analysis, and interpretation of exposure data relative to an OEL. Several factors need to be considered in designing exposure assessment strategies. Exposure variability, which has been discussed at length in Chapter 15, is one of the most important factors. Exposures vary between workers, and over time, shift, and location. The sampling strategy should be effective in capturing this variability. At the same time, the strategy must be feasible and efficient in that it should not require an inordinately large number of samples. Occupational hygienists usually operate with limited resources that preclude large sample sizes. The dual requirements of effectiveness (i.e., the ability to provide correct exposure decisions) and efficiency (i.e., the need to minimize the number of measurements) have led to vigorous debate on the optimal sampling strategies. This debate also has implications regarding the “correct” interpretation of OELs. The following sections will address these issues of effectiveness and efficiency.