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An evaluation of metrics for assessing maternal exposure to agricultural pesticides

Abstract

We evaluate the use of three different exposure metrics to estimate maternal agricultural pesticide exposure during pregnancy. Using a geographic information system-based method of pesticide exposure estimation, we combine data on crop density and specific pesticide application amounts/dates to create the three exposure metrics. For illustration purposes, we create each metric for a North Carolina cohort of pregnant women, 2003–2005, and analyze the risk of congenital anomaly development with a focus on metric comparisons. Based on the results, and the need to balance data collection efforts/computational efficiency with accuracy, the metric which estimates total chemical exposure using application dates based on crop-specific earliest planting and latest harvesting information is preferred. Benefits and drawbacks of each metric are discussed and recommendations for extending the analysis to other states are provided.

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Acknowledgements

We thank Andrew Olshan, Professor of Epidemiology and Department Chair at UNC Chapel Hill, Kristy J. Michie, Supervising Public Health Epidemiologist at the Monterey County Health Department, and Leon S. Warren Jr., Agricultural Research Associate in the North Carolina State University Department of Crop Science for providing helpful input regarding the metric creation process and general pesticide/crop timing information. This research was supported in part by grants from the National Institute of Environmental Health Sciences (T32ES007018, P30ES010126).

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The views expressed in this paper are those of the authors and do not necessarily reflect the views or policies of the US Environmental Protection Agency.

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Correspondence to Joshua L Warren.

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Supplementary Information accompanies the paper on the Journal of Exposure Science and Environmental Epidemiology website

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Warren, J., Luben, T., Sanders, A. et al. An evaluation of metrics for assessing maternal exposure to agricultural pesticides. J Expo Sci Environ Epidemiol 24, 497–503 (2014). https://doi.org/10.1038/jes.2013.75

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