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A tiered asthma hazard characterization and exposure assessment approach for evaluation of consumer product
Andrew Maier1, Melissa J Vincent1, Ann Parker1
1Department of Environmental Health, University of Cincinnati College of Medicine, Cincinnati, OH, USA.
Abstract:
Asthma is a complex syndrome with significant consequences for those affected. The number of individuals affected is growing, although the reasons for the increase are uncertain. Ensuring the effective management of potential exposures follows from substantial evidence that exposure to some chemicals can increase the likelihood of asthma responses. We have developed a safety assessment approach tailored to the screening of asthma risks from residential consumer product ingredients as a proactive risk management tool. Several key features of the proposed approach advance the assessment resources often used for asthma issues. First, a quantitative health benchmark for asthma or related endpoints (irritation and sensitization) is provided that extends qualitative hazard classification methods. Second, a parallel structure is employed to include dose-response methods for asthma endpoints and methods for scenario specific exposure estimation. The two parallel tracks are integrated in a risk characterization step. Third, a tiered assessment structure is provided to accommodate different amounts of data for both the dose-response assessment (i.e., use of existing benchmarks, hazard banding, or the threshold of toxicological concern) and exposure estimation (i.e., use of empirical data, model estimates, or exposure categories). Tools building from traditional methods and resources have been adapted to address specific issues pertinent to asthma toxicology (e.g., mode-of-action and dose-response features) and the nature of residential consumer product use scenarios (e.g., product use patterns and exposure durations). A case study for acetic acid as used in various sentinel products and residential cleaning scenarios was developed to test the safety assessment methodology. In particular, the results were used to refine and verify relationships among tiered approaches such that each lower data tier in the approach provides a similar or greater margin of safety for a given scenario.
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