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Towards better exposure assessment strategies |
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 Top Towards better exposure... References |
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Exposure assessment (EA) is performed for various reasons and is contextually dependent. The most common reason is routine monitoring of worker exposures levels to chemical and physical hazards in comparison to an occupational exposure limit (OEL). Another reason is to determine exposure–response relationships in occupational epidemiology studies. The purpose of the EA determines the best choice for decision analysis statistic. For example, for EAs in epidemiological studies, some measure of central tendency such as the arithmetic mean is appropriate. However, where the EA is done to monitor worker exposure levels, then some upper percentile of the exposure distribution (e.g. 95th percentile) may be preferable.
Exposure variability is an important factor in EA strategy design. Exposures vary between workers with similar job title but with different tasks comprising the job; even for workers doing the same task, exposures vary between workers and over time, shift and location. Any sampling strategy must handle this variability. In addition, it must be effective (i.e. correct exposure decisions) and efficient (i.e. minimum resources). These requirements of effectiveness and efficiency often are at odds with each other, and a balance must be struck between these competing needs.
The National Institute for Occupational Safety and Health is updating its Occupational Exposure Sampling Strategies Manual (OESSM) [1] and Ramachandran [2] reviews the sampling strategy against contemporary requirement above.
The OESSM assesses compliance on a single day, for a single worker, e.g. a maximum risk employee. This is achieved typically by at most two measurements. Compliance is tested by measurement comparison with the OEL, requiring no understanding of exposure variability or underlying statistical analysis. Therefore, only sampling and analytical variability associated with each measurement is accounted for despite the much greater proportion from environmental variability [3].
Tuggle [4] found the OESSM unreliable for detecting poorly controlled exposures and while efficient (requiring few measurements), rated it ineffective at accurately identifying incompliant work scenarios. Rappaport [5] showed that compliance status depends on the number of measurements but the OESSM biases towards fewer measurements. Also substances with no OEL’s or dermal hazards cannot be evaluated. Also OESSM data cannot typically be used for other purposes, e.g. risk management or epidemiology. The emphasis on ‘maximum risk employees’ tends to overestimate exposures with underestimation of variability for epidemiological purposes.
Recent work has developed EA strategies that evaluate health risks from all substances, for all workers, all days, instead of a hypothetical maximum risk worker on a single day for substances with OELs. A well-formulated strategy contains the following elements:
- (i) A comprehensive EA characterizes exposures to all substances over an extended period of time, detailing exposure variability and producing data suitable for baseline monitoring, surveillance, controls evaluation and for epidemiology. It would estimate upper percentiles of exposure distribution (for risk management) as well as measures of central tendency (for epidemiology).
- (ii) Professional judgements by occupational hygienists or the outputs of exposure models can be used to create similarly exposed groups (SEGs), with stratification into exposure categories relative to an OEL. Exposure misclassification using professional judgements can be significant for some exposure categories; for these categories, extra readings better characterize the exposure profile. For critical SEGs, characterization of within- and between-worker variability is necessary.
- (iii) Bayesian statistics may offer a rational and transparent approach to exposure analysis, integrating monitoring data with occupational hygienist professional judgements. It allows the synthesis of information from several sources in probability terms. For example, subjectively assigned exposures or exposure categories (in probabilistic format) can be refined with information obtained from more objective but limited monitoring data.
- (ii) Professional judgements by occupational hygienists or the outputs of exposure models can be used to create similarly exposed groups (SEGs), with stratification into exposure categories relative to an OEL. Exposure misclassification using professional judgements can be significant for some exposure categories; for these categories, extra readings better characterize the exposure profile. For critical SEGs, characterization of within- and between-worker variability is necessary.
Research is needed on the accuracy of professional judgements, use of models in exposure decision making and the efficacy of task-based EAs in estimating full-shift exposures.
Measured endotoxin exposure levels show large variability partly caused by determinants that influence growth of bacteria. The findings of a recent study [6] have significant implications for the design of future occupational intervention and epidemiological studies.
Recent trend analyses of styrene breathing zone exposure data for open-mould workers in the European GRP industry shows that average concentrations decreased on average by 5.3% per year during from 1966 to 1990 and by 0.4% annually after 1990. Biological indicators of styrene (mandelic acid in post-shift urine) showed a steeper decline (8.9%) [7].
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TopTowards better exposure...References |
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- Leidel NA, Busch KA, Lynch JR. Occupational Exposure for Occupational Safety and Health (1977) NIOSH. Publication no. 77–173.
- Ramachandran G. Toward better exposure assessment strategies—The New NIOSH Initiative. Ann Occup Hyg (2008) 52:297–301.
[Abstract/Free Full Text] - Nicas M, Simmons BP, Spear RC. Environmental versus analytical variability in exposure measurements. Am Ind Hyg Assoc J (1991) 52:553–557.[Web of Science][Medline]
- Tuggle RM. The NIOSH decision scheme. Am Ind Hyg Assoc J (1981) 42:493–498.[Web of Science]
- Rappaport SM. The rules of the game: an analysis of OSHA's enforcement strategy. Am J Ind Med (1984) 35:61–121.
- Spann S, Schinkel J, Wouters IM, et al. Variability in endotoxin exposure levels and consequences for exposure assessment. Ann Occup Hyg (2008) 52:303–316.
[Abstract/Free Full Text] - Rooij JG, Kasper A, Triebig G, et al. Trends in occupational exposure to styrene in the European glass fibre-reinforced plastics industry. Ann Occup Hyg (2008) 52:337–349.
[Abstract/Free Full Text]
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