Abstract
The accuracy of the exposure assessment is a critical factor in epidemiological investigations of pesticide exposures and health in agricultural populations. However, few studies have been conducted to evaluate questionnaire-based exposure metrics. The Agricultural Health Study (AHS) is a prospective cohort study of pesticide applicators who provided detailed questionnaire information on their use of specific pesticides. A field study was conducted for a subset of the applicators enrolled in the AHS to assess a pesticide exposure algorithm through comparison of algorithm intensity scores with measured exposures. Pre- and post-application urinary biomarker measurements were made for 2,4-D (n=69) and chlorpyrifos (n=17) applicators. Dermal patch, hand wipe, and personal air samples were also collected. Intensity scores were calculated using information from technician observations and an interviewer-administered questionnaire. Correlations between observer and questionnaire intensity scores were high (Spearman's r=0.92 and 0.84 for 2,4-D and chlorpyrifos, respectively). Intensity scores from questionnaires for individual applications were significantly correlated with post-application urinary concentrations for both 2,4-D (r=0.42, P<0.001) and chlorpyrifos (r=0.53, P=0.035) applicators. Significant correlations were also found between intensity scores and estimated hand loading, estimated body loading, and air concentrations for 2,4-D applicators (r-values 0.28–0.50, P-values<0.025). Correlations between intensity scores and dermal and air measures were generally lower for chlorpyrifos applicators using granular products. A linear regression model indicated that the algorithm factors for individual applications explained 24% of the variability in post-application urinary 2,4-D concentration, which increased to 60% when the pre-application urine concentration was included. The results of the measurements support the use of the algorithm for estimating questionnaire-based exposure intensities in the AHS for liquid pesticide products. Refinement of the algorithm may be possible using the results from this and other measurement studies.
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Acknowledgements
The authors thank the AHS cohort members participating in this study for their considerable time and effort. Several EPA researchers provided significant contribution to the study including Ruth Allen, Ross Highsmith, and William Steen. Nyla Logsden-Sackett and Patti Gillette at the University of Iowa AHS Field Station and Joy Herrington, at the Battelle North Carolina AHS Field Station led participant screening activities. We thank Sydney Gordon at Battelle, Stephen Reynolds and Martin Jones at the University of Iowa, and James Raymer and Gerald Akland at the RTI International for leading the field studies. This work has been funded in part by the US Environmental Protection Agency under Contracts 68-D99-011 and 68-D99-012, through Interagency Agreement DW-75-93912801-0. It has been subjected to Agency administrative review and approved for publication. Mention of trade names or commercial products does not constitute endorsement or recommendation for use. This work has been supported in part by the Intramural Research Program of the NIH, National Cancer Institute (Z01-CP010119) and National Institute of Environmental Health Sciences (Z01-ES049030).
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Thomas, K., Dosemeci, M., Coble, J. et al. Assessment of a pesticide exposure intensity algorithm in the agricultural health study. J Expo Sci Environ Epidemiol 20, 559–569 (2010). https://doi.org/10.1038/jes.2009.54
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DOI: https://doi.org/10.1038/jes.2009.54
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