4.7 Article

Farmworker exposure to pesticides: Methodologic issues for the collection of comparable data

Journal

ENVIRONMENTAL HEALTH PERSPECTIVES
Volume 114, Issue 6, Pages 923-928

Publisher

US DEPT HEALTH HUMAN SCIENCES PUBLIC HEALTH SCIENCE
DOI: 10.1289/ehp.8531

Keywords

biomonitoring; data collection; environmental assessment; farmworker; health outcomes; pesticide exposure

Funding

  1. NIEHS NIH HHS [R13 ES013378] Funding Source: Medline
  2. NIOSH CDC HHS [R13 OH013378] Funding Source: Medline

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The exposure of migrant and seasonal farmworkers and their families to agricultural and residential pesticides is it continuing public health concern. Pesticide exposure research has been spurred on by the development of sensitive and reliable laboratory techniques that allow the detection of minute amounts of pesticides or pesticide metabolites. The power of research on farmworker pesticide exposure has been limited because of variability in the collection of exposure data, the predictors of exposure considered, the laboratory procedures used in analyzing the exposure, and the measurement of exposure. The Farmworker Pesticide Exposure Comparable Data Conference assembled 25 scientists from diverse disciplinary and organizational backgrounds to develop methodologic consensus in four areas of farmworker pesticide exposure research: environmental exposure assessment, biomarkers, personal and occupational predictors of exposure, and health outcomes of exposure. In this introduction to this mini-monograph, first, we present the rationale for the conference and its organization. Second, we discuss some of the important challenges in conducting farmworker pesticide research, including the definition and size of the farmworker population, problems in communication and access, and the organization of agricultural work. Third, we summarize major findings from each of the conference's four foci-environmental exposure assessment, biomonitoring, predictors of exposure, and health outcomes of exposure-as well as important laboratory and statistical analysis issues that cross-cut the four foci.

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