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Using multiple imputation to assign pesticide use for non-responders in the follow-up questionnaire in the Agricultural Health Study.
Heltshe SL; Lubin JH; Koutros S; Coble JB; Bu-Tian J; Alavanja MCR; Blair A; Sandler DP; Hines CJ; Thomas KW; Barker J; Andreotti G; Hoppin JA; Beane Freeman LE
J Expo Sci Environ Epidemiol 2012 Jul/Aug; 22(4):409-416
The Agricultural Health Study (AHS), a large prospective cohort, was designed to elucidate associations between pesticide use and other agricultural exposures and health outcomes. The cohort includes 57,310 pesticide applicators who were enrolled between 1993 and 1997 in Iowa and North Carolina. A follow-up questionnaire administered 5 years later was completed by 36,342 (63%) of the original participants. Missing pesticide use information from participants who did not complete the second questionnaire impedes both long-term pesticide exposure estimation and statistical inference of risk for health outcomes. Logistic regression and stratified sampling were used to impute key variables related to the use of specific pesticides for 20,968 applicators who did not complete the second questionnaire. To assess the imputation procedure, a 20% random sample of participants was withheld for comparison. The observed and imputed prevalence of any pesticide use in the holdout dataset were 85.7% and 85.3%, respectively. The distribution of prevalence and days/year of use for specific pesticides were similar across observed and imputed in the holdout sample. When appropriately implemented, multiple imputation can reduce bias and increase precision and can be more valid than other missing data approaches.
Health-surveys; Questionnaires; Surveillance-programs; Agriculture; Agricultural-workers; Agricultural-chemicals; Agricultural-industry; Pesticides; Pesticides-and-agricultural-chemicals; Epidemiology; Exposure-assessment; Mathematical-models; Sampling; Data-processing; Statistical-quality-control; Author Keywords: agriculture; cohort studies; missing data; pesticides; precision
Dr. Laura E. Beane Freeman, Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, 6120 Executive Boulevard, RM 8112, MSC 7240, Rockville, MD 20892, USA
Issue of Publication
Agriculture, Forestry and Fishing
Journal of Exposure Science and Environmental Epidemiology
MD; WA; NC; OH
Page last reviewed: March 25, 2022
Content source: National Institute for Occupational Safety and Health Education and Information Division