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Retrospective pesticide exposure assessment for studying multiple myeloma risk for farm work in British Columbia, Canada Garzia, Nichole A.

Abstract

Multiple myeloma (MM) is one of the cancer types that research has shown to be in excess among farm workers. Pesticides have been highly suspected as a risk factor, and much of the research aimed at understanding MM etiology in farm workers has focused on pesticides. However, certain methodological challenges related to the retrospective assessment of pesticide exposure have contributed to weak and at times, inconsistent, epidemiologic evidence. The aims of this research were to collect and understand the usefulness of exposure data from the literature for future exposure assessment, to develop a method for estimating cumulative pesticide exposure levels in farm workers when combined with self-reported information, and to apply this method to evaluate the relationship between pesticide exposure and MM risk among a sample of farm workers in British Columbia (BC), Canada. The first study used a systematic approach to collect and evaluate the literature to identify studies that provided quantitative dermal pesticide exposure information on farm workers. The data were extracted and evaluated for usefulness for exposure assessment development. The second study involved the development of a pesticide exposure algorithm, and its application to farm data previously collected as part of an MM case-control study conducted in BC. The results of this algorithm were compared to the results of two other methods, one of which was a previously developed and evaluated algorithm from a well-known prospective cohort of pesticide applicators. The third study was an epidemiologic analysis to evaluate the relationship between pesticide exposure and MM among farm workers identified in the BC case-control study. Pesticide exposure was assessed using dichotomous, simple metrics of exposure as well as the two algorithms from the second study to estimate cumulative pesticide exposure. Overall, the research from this dissertation contributed new knowledge and provided additional evidence to support existing knowledge on the methodological issues surrounding the study of pesticide exposure in relation to MM among farm workers. Additionally, it provided a new pesticide exposure algorithm that can be further evaluated and improved upon regarding its ability to accurately assess exposure among farm workers using self-reported historical exposure information.

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Attribution-NonCommercial-NoDerivatives 4.0 International