Asbestos-related diseases remain a major public health problem in the US and abroad due to the large reservoir of asbestos in built infrastructure and the continued global trade in the material. Occupational standards for asbestos exposure in the US are based on visual counting of particles by phase contrast microscopy (PCM). Only fibers long and thick enough to reliably count using that method are regulated. However, in most occupational settings the majority of asbestos fibers are too small to count by PCM. Of particular concern are long fibers that are too thin to be visible using PCM but are believed to be very hazardous when inhaled. If asbestos exposure estimates based upon PCM methods were strictly proportional to total exposure to all etiologically-relevant asbestos fibers then a policy that regulated asbestos exposure as measured by PCM might suffice to control etiologically-relevant occupational asbestos exposures. However, there is strong evidence that the proportion of asbestos fibers that are not counted by PCM varies by work activity, fiber quality, and other conditions. Therefore, workers may have relatively low PCM-based metrics but high total asbestos exposure due to a large fraction of fibers that are too short or thin to count by PCM. In such settings, workers face risk of occupational disease due to the unmeasured, unregulated fraction of asbestos fibers. This issue has been raised repeatedly by workers and their advocates, who have argued for regulating exposure to asbestos using methods and rules that permit quantification of short (<5 ?m) and thin (<0.25 ?m) fibers, such as transmission electron microscopy (TEM) analysis of air samples. However, one obstacle to this has been that most occupational studies of asbestos workers have classified people based on PCM estimates of exposure. Regulators noted that it was unclear what level of exposure, as quantified by TEM, would be acceptable, since TEM estimates of the total number of fibers may not be well correlated with PCM estimates of fiber counts. We propose to draw upon unique existing data for US asbestos workers for whom high-quality estimates of asbestos exposure have been derived by PCM and fiber-size specific estimates of exposure have been derived by TEM. We propose to: 1) Use hierarchical regression methods to estimate the effects of the unregulated fraction of fibers;2) Use G-methods to estimate TEM-based policies that would yield a comparable mortality to that obtained under current OSHA standards;and, 3) Use G- methods to estimate alternative TEM-based policies that would yield less mortality than that obtained under current OSHA standards.
Aim 1 will assess the effects of the unregulated fraction of fibers using methods show to perform well in settings of correlated environmental exposures.
Aims 2 and 3 draw upon contemporary methods to estimate public health impacts of policies in settings susceptible to bias due to the healthy worker survivor effect. The project, which addresses the NORA cross-sector priority to prevent work- related respiratory malignancies, applies innovative methods for estimating the effects of complex exposures. 1

Public Health Relevance

This work will improve understanding of the role of the unregulated fraction of asbestos fibers as a determinant of lung cancer, and will apply innovative methods to evaluate health effects of asbestos exposures. In 2011 NIOSH released a Roadmap for research to address persistent scientific uncertainties about the health effects of exposure to asbestos and other elongate mineral particles (Department of Health and Human Services 2011). The proposed work will address several goals of that Roadmap by improving understanding of the role of asbestos fiber dimension as a determinant of pathological effects and strengthening the scientific basis for policy recommendations by integrating evidence from experimental animals and in vitro studies.

National Institute of Health (NIH)
National Institute for Occupational Safety and Health (NIOSH)
Small Research Grants (R03)
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Safety and Occupational Health Study Section (SOH)
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Dearwent, Steve
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University of North Carolina Chapel Hill
Public Health & Prev Medicine
Schools of Public Health
Chapel Hill
United States
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