Agricultural crop density and risk of childhood cancer in the midwestern United States: an ecologic study

BACKGROUND There is limited evidence for an association between agricultural pesticide exposure and certain types of childhood cancers. Numerous studies have evaluated exposure to pesticides and childhood cancer and found positive associations. However, few studies have examined the density of agricultural land use as a surrogate for residential exposure to agricultural pesticides and results are mixed. We examined the association of county level agricultural land use and the incidence of specific childhood cancers. METHODS We linked county-level agricultural census data (2002 and 2007) and cancer incidence data for children ages 0-4 diagnosed between 2004 and 2008 from cancer registries in six Midwestern states. Crop density (percent of county area that was harvested) was estimated for total agricultural land, barley, dry beans, corn, hay, oats, sorghum, soybeans, sugar beets, and wheat. Rate ratios and 95% confidence intervals were estimated using generalized estimating equation Poisson regression models and were adjusted for race, sex, year of diagnosis, median household income, education, and population density. RESULTS We found statistically significant exposure-response relationships for dry beans and total leukemias (RR per 1% increase in crop density = 1.09, 95% CI = 1.03-1.14) and acute lymphoid leukemias (ALL) (RR = 1.10, 95% CI = 1.04-1.16); oats and acute myeloid leukemias (AML) (RR = 2.03, 95% CI = 1.25, 3.28); and sugar beets and total leukemias (RR = 1.11, 95% CI = 1.04, 1.19) and ALL (RR = 1.11, 95% CI = 1.02, 1.21). State-level analyses revealed some additional positive associations for total leukemia and CNS tumors and differences among states for several crop density-cancer associations. However, some of these analyses were limited by low crop prevalence and low cancer incidence. CONCLUSIONS Publicly available data sources not originally intended to be used for health research can be useful for generating hypotheses about environmental exposures and health outcomes. The associations observed in this study need to be confirmed by analytic epidemiologic studies using individual level exposure data and accounting for potential confounders that could not be taken into account in this ecologic study.