Our study results indicate an increased risk for many types of childhood cancers associated with residence at diagnosis in counties having a moderate to high level of agricultural activity, with a remarkably consistent dose–response effect seen for counties having ≥ 60% of the total county acreage devoted to farming. Further, the finding that patterns of risk for individual cancers varied by crop type suggests that the development of different childhood cancers is likely to be related to specific pesticides.
A variety of chemical classes are represented by the pesticides applied to the six crops evaluated (). These data are taken from the NASS Agricultural Chemical Use Database (
USDA 2006). Five of the six selected crops had one or more agricultural chemicals applied that have been designated by the U.S. Environmental Protection Agency as a possible carcinogen (
U.S. EPA 2004). Very few epidemiologic studies have been able to evaluate cancer risk in general and childhood cancer risk in particular for specific agricultural chemicals. In two studies based in California,
Reynolds et al. (2002,
2005) used information from California’s Department of Pesticide Regulation to examine risk associated with individual pesticides. The authors reported that neither analysis (one ecologic and one case–control) found consistent patterns of elevated risk for specific pesticides nor for classes of pesticides; however, only total cancers, leukemias, and central nervous system tumors were analyzed. Many of our more striking increased risk estimates were seen for cancers other than these leading types.
| Table 6Top five agricultural chemicals applied (by percent treated acres), by crop.a |
Epidemiologic studies have linked pesticide exposure to increased risk of several kinds of childhood cancers, generally through measurement of parental occupational exposures and/or residential pesticide use. Childhood leukemias and central nervous system tumors have been studied most extensively, perhaps because they are the more common types of what is a relatively rare disease, so the bulk of the epidemiologic evidence for a pesticide risk to children relates to these cancers. As noted in recent reviews, although study results have been mixed, overall this association has been most consistent for leukemias (
Nasterlack 2006;
Zahm and Ward 1998). Various studies have reported an elevated risk of brain tumors in farmers, with a recent meta-analysis finding an overall OR of 1.30 (95% CI, 1.09–1.56) for brain cancer and farming (
Khuder et al. 1998). Several studies of farm-related exposures among pregnant mothers and their children have reported a parallel increase in risk for childhood brain tumors (
Bunin et al. 1994;
Cordier et al. 1994;
Efird et al. 2003;
Holly et al. 1998). Speculation about farm-related exposures of interest for childhood brain tumors has centered largely on agricultural pesticides and on farm animals [as a surrogate for an undetermined viral agent(s)].
Among the lymphomas, epidemiologic studies of risk associated with pesticide exposures have largely focused on non-Hodgkin lymphoma, and predominantly for cases diagnosed in adults. In studies evaluating non-Hodgkin lymphoma diagnosed among children,
Zahm and Ward (1998) noted that several reported an apparent dose response to both agricultural and residential pesticide exposures.
The results for the few studies evaluating the possible risk associated with pesticide use and neuroblastomas in children have been equivocal; however, there is some evidence for an association for both occupational pesticide exposure of the parents and residential pesticide exposure of the family, particularly in studies that used specific pesticide exposure information rather than relying on parent’s job title (
Daniels et al. 2001;
Kristensen et al. 1996).
Retinoblastoma is a very low-incidence childhood tumor. There are two recognized types of retinoblastoma: one linked to genetic mutations and the other related to sporadic tumors. The heritable forms of retinoblastoma tend to be bilateral and occur during the first year of life. The sporadic nonheritable form is more likely to be unilateral and diagnosed after the first year of life (
Ries et al. 1999). Had the risk been confined to children ≥ 1 year of age, this would have indicated that any putative association with agricultural pesticides is most relevant to the sporadic form; however, we saw increased risk estimates for the group < 1 year of age and up through 9 years of age.
We also found a statistically significant association in this study for malignant melanoma. Reports indicate that incidence of this cancer has been increasing among children and adolescents in recent decades (
Hamre et al. 2002;
Strouse et al. 2005). Sun exposure (both intermittent and total accumulated) and number of melanocytic and dysplastic nevi are well-established risk factors for malignant melanoma in adults (
Armstrong and English 1996) and also appear to be related to risk in children (
Strouse et al. 2005). Many of the exposed counties in the study area were located in more northerly states not normally associated with prolonged, intense sunlight exposure, so it seems unlikely that the increased risk would be attributed primarily to sun exposure. There has been an inconsistent pattern seen for melanoma risk associated with farmers and farming.
Settimi et al. (1999,
2001) found an increased risk of melanoma in Italian farmers, but only among females. Another mortality study reported statistically significant lowered mortality risk for melanoma among Wisconsin farmers (
Hanrahan et al. 1996). Interestingly, a cancer mortality study among farmers in Iowa reported an increased mortality risk for melanoma, but only among younger farmers (20–64 years of age) (
Cerhan et al. 1998). There has been some speculation that insecticides in particular may have a link with development of malignant melanoma, possibly by affecting melanocytic function (
Burkhart and Burkhart 2000).
Very little is known about the etiology of renal carcinomas, but there has been some indication of increased risk of Wilms’ tumor, the most common type of renal tumor in childhood, associated with possible occupational pesticide exposures and home applications (
Sharpe et al. 1995;
Zahm and Ward 1998). Similarly, because of the very few existing studies, there is little evidence available to evaluate the potential for an association between pesticide exposures and risk of some of the rarer childhood cancers we evaluated, including soft-tissue sarcomas, malignant bone tumors, germ cell tumors, and hepatic tumors (
Nasterlack 2006;
Zahm and Ward 1998).
Several limitations to our approach must be considered when interpreting the data. The exposure variable used is an imprecise surrogate for agriculturally related chemical exposures. However, of the 563 counties we categorized as exposed using this surrogate (i.e., having ≥ 20% of their total acreage in cropland), 332 (59%) had > 50% of their total county acreage in cropland, and 124 (22%) had a full three-quarters or more of their total acreage in agricultural production. In contrast, of the 515 referent counties, 357 (69%) had < 10% of their total acreage in cropland, and 224 (43%) had < 5% in cropland. These distributions illustrate the heterogeneity of possible exposure across the study area and lend support to our key assumption that children residing in an exposed county had a higher probability of encountering agricultural pesticides through pesticide drift than did the children residing in a referent county. Still, because there were so few counties with no agricultural activity, our unexposed population did include counties with up to 20% of total acreage in crop production as well as those counties with no farming, leaving the potential for misclassification of the exposure. This misclassification would move the risk estimates toward the null, though, and is unlikely to have generated the magnitude of risk seen for most cancer sites.
Additionally, we acknowledge there are a variety of ways it would be feasible to use existing agricultural data to attempt to capture any crop-specific effects, each with slightly different advantages and disadvantages. We believe our approach is valid to address the very general question of whether risk of individual cancer types varied according to probable differences in pesticides used, as defined by different crops grown. We evaluated this specifically because we saw uniformly increased risk across all cancer types when considering the main effect of percent cropland. Epidemiologic case–control studies, in contrast to this ecologic study, would be better suited for creating more specific exposure definitions based on cropping patterns and could better evaluate questions of dose–response and exposure timing for any specific pesticide (or pesticide surrogate).
We deliberately chose not to use existing urban/rural classification systems such as Rural–Urban Continuum Codes (RUCC; previously termed Beale codes) or Urban Influence Codes for this analysis because these systems are based largely on economic or population density measures, not agricultural production. Our classification approach was chosen specifically to capture density of agricultural activity at the county level. To evaluate the effectiveness of this approach, we compared our percent cropland classification with the RUCC for metropolitan (metro) and non-metropolitan areas (nonmetro) in our data. In this comparison, we found that of the 752 counties in our referent (i.e., low percentage of cropland and presumably “urban”) category, 432 (57.4%) were classified as nonmetro by RUCC coding. Further, we found that of the 292 counties classified by us as high percentage of cropland, 77 (26.4%) were classified as metro. Clearly, these data indicate that our analysis is not equivalent to a standard “urban” versus “rural” comparison.
Use of county of residence at time of diagnosis may be considered another limitation of this study. If the exposures of interest are most pertinent during gestation, then, if available, mother’s county of residence at time of birth or time of conception would be the preferred measure for assessing the impact of exposure to agricultural chemicals. Because pesticides can act as either initiators or promoters, however, it is plausible that some pesticides may influence cancer development nearer to time of diagnosis.
We also had very few data available to address any potential confounding, always a concern in epidemiologic studies. The evidence for most putative risk factors for the different childhood cancers is conflicting, so any effect from potential confounders is likely to be weak, particularly when dispersed across the county, our unit of analysis, and when many different types of cancers are considered in the analysis, as in our study. Although there might be a specific concern about differential use of residential pesticides in the populations living in counties with low agricultural activity (i.e., more urban counties) versus those with medium or high agricultural activity (i.e., more rural), published reports agree that there is very little difference in household use of pesticides in urban versus nonurban settings (
Adgate et al. 2000;
U.S. EPA 2007)
In addition to general concerns regarding the ability to determine causality that apply to any ecologic study, our approach requires several assumptions, including
a) that mobility of study subjects is not sufficient to substantially affect risk estimates, and
b) that the cropland data derived from the 2 years of agricultural census information are consistent across the study years. Finally, we have no ready explanation for the lack of an effect seen when evaluating all cancer types together compared with our results for individual cancer types. Because the OR is not a linear transformation of these data, we cannot expect that the OR for all cancers would be the average of the ORs for the subgroups. It is possible that we may have experienced some form of Simpson’s paradox in our data set when combining the cancer types into one “super” group (
Simpson 1951).
The most notable strength of this study is the large number of counties included. This large sample size gave us the ability to evaluate rarer childhood cancers and resulted in stable risk estimates. In addition, the sample constituted a geographically diverse area and included states that produce a variety of crops, enabling us to evaluate whether risk differed by crop type.
Our finding of statistically significant increased risk across all cancer types evaluated for those counties having ≥ 60% of total acreage in cropland was unexpected and, given the ecologic design of the study, needs to be interpreted with considerable caution. Several factors, however, argue against this finding being an artifact of the data or the data analysis approach chosen. There was a consistent dose–response relationship seen between risk estimates for our medium- compared with our high-exposure categories. In contrast to the general focus in the epidemiologic literature on the more common childhood cancers, we were able to evaluate rarer childhood cancers. The growing regions for the different crops generally did not overlap, so it is unlikely that we simply captured a high-risk population. The patterns of risk varied according to crop type. Taken together, these features of the study indicate the potential for a relationship between pesticides, or at least agricultural activity in general, and childhood cancers, with the magnitude of the risk possibly being two or more times that of nonfarming areas.
The biological mechanisms by which pesticides may be involved in childhood cancers include acting as initiators (i.e., mutagens) or tumor promoters, affecting immune system regulation, or possibly through mimicking estrogen or otherwise disrupting endogenous hormonal activity (
Dich et al. 1997). Although it seems unlikely that any one pesticide would result in the range of risks reported in this study, it does seem plausible that many different pesticides, acting through a variety of mechanisms, could be linked to a variety of childhood cancers.
This study is meant to provide an alternative look at the possible impact of agricultural practices on cancer risk in surrounding communities, with our method being particularly amenable to childhood cancers, because these cancers have a much shorter latency period than do adult cancers. With data accumulating regarding the atmospheric transport of pesticides over long distances (
van den Berg et al. 1999) and reports indicating that some level of pesticide exposure is nearly ubiquitous in the U.S. population (
CDC 2005), it is likely that there will continue to be interest in the possible impact of long-term, low-level pesticide exposure in human populations, particularly among infants and young children.
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