This study represents a broad assessment of the relationship between agricultural pesticide use patterns and breast cancer incidence in women in a large and diverse agricultural state. The results provide no evidence that women living in areas of recent, high agricultural pesticide use experience higher breast cancer incidence rates. This lack of association was evident for all three age groups examined and did not differ between women living in urban and rural areas.
Much of the epidemiologic research on this topic has focused on examining the relationship between breast cancer and body burden levels of organochlorine pesticides (as measured in serum or adipose). Generally, results from these types of studies have been null (Adami et al. 1995
; Calle et al. 2002
; Laden et al. 2001
; Safe 1997
; Snedeker 2001
; Wolff and Weston 1997
), although a few well-designed studies have reported positive associations (Aronson et al. 2000
; Hoyer et al. 1998
; Romieu et al. 2000
). One of the notable limitations of these studies, however, has been that they were able to evaluate only the relatively small number of compounds that are persistent and detectable by current analytic methods, with most focused on dichlorodiphenyltrichlorethane (DDT) or its metabolite dichlorodiphenyldichloroethylene (DDE) (Bagga et al. 2000
; Charlier et al. 2003
; Cocco et al. 2000
; Dewailly et al. 1994
; Falck et al. 1992
; Hunter et al. 1997
; Krieger et al. 1994
; Laden et al. 2001
; Lopez-Carrillo et al. 1997
; Mendonca et al. 1999
; Millikan et al. 2000
; Olaya-Contreras et al. 1998
; Romieu et al. 2000
; Schecter et al. 1997
; Unger et al. 1984
; van’t Veer et al. 1997
; Wassermann et al. 1976
; Wolff et al. 1993
; Zheng et al. 1999
). Furthermore, many of these studies have measured these compounds in blood or adipose collected at the time of diagnosis, which may not reflect exposures occurring during more etiologically relevant time periods, such as prenatal or adolescent growth (Potischman and Troisi 1999
). Although the exposure estimates used in our analysis can account for a broader spectrum of potentially suspect agents, our lack of residential history information poses the same temporal limitation.
A number of limitations common to ecologic (aggregative) studies are worth noting. Because data are summarized for groups of individuals, inferences can be made only about populations rather than individuals (Greenland and Morgenstern 1989
; Morgenstern 1995
). The primary limitation of such study designs is that the heterogeneity of exposure and covariate levels within groups is not fully captured with ecologic data. This can lead to ecologic effect estimates that do no reflect the biologic effect at the individual level—commonly referred to as “ecologic bias” (Greenland and Morgenstern 1989
; Morgenstern 1995
). Although our study, by virtue of its design, cannot completely escape this limitation, the small unit of analysis used in our study helps reduce the within-group heterogeneity. Ecologic studies such as this one, however, have a number of advantages as well (Morgenstern 1995
; Walter 1991
). By using monitoring data, ecologic studies can estimate potential ambient exposures that do not lend themselves to subject recall. Furthermore, our study population was large and geographically dispersed. This provided variability in potential exposures not often available from other epidemiologic study designs. The variability in exposure and large sample size combine to offer statistical power sufficient to detect small risks that, if large numbers of people are exposed, may be very important from a public health standpoint. Thus, although our study certainly has some limitations, it also offers some advantages over other traditional epidemiologic study designs.
Our study has a number of advantages over many of the ecologic studies conducted to date. Because ours was a study of incidence rather than mortality, we could more directly evaluate potential risk relationships without potential confounding by factors related to prognosis. We were able to evaluate classes of chemicals and individual chemicals of interest specific to breast cancer, whereas many of the previous studies relied on measures that are more global (e.g., total pounds of all pesticides applied) or used acreage of specific crop types as proxy measures for classes of pesticide exposures. Additionally, we were able to evaluate pesticide applications on a small scale (census block group); most other ecologic studies have estimated exposures over larger areas, such as counties—a method that is likely to result in greater exposure misclassification (Rull and Ritz 2003
The ability to control for area differences in SES and urbanization is especially important, given that regions of intense agricultural pesticide use are often rural and of low SES, whereas breast cancer rates tend to be higher in upper SES (Hall and Rockhill 2002
; Heck and Pamuk 1997
; Reynolds et al. 2005
; Teppo 1984
; Yost et al. 2001
) and more urban areas (Doll 1991
; Mahoney et al. 1990
; Reynolds et al. 2005
). Because lifestyle factors related to breast cancer risk, such as physical activity, smoking, alcohol consumption, and childbearing patterns, are likely to differ between rural and urban areas in a way that would favor lower breast cancer rates in rural areas, where pesticide use is typically high (Reynolds et al. 2004a
), it is essential to account for urbanization in analyses of breast cancer and agricultural pesticide use. Because of our study’s large size, we were able to evaluate pesticide use and breast cancer separately among rural and urban women.
The results from our study agree with an earlier analysis of agricultural pesticide use we performed among members of the California Teachers Study (CTS) cohort (Reynolds et al. 2004b
). The CTS, a cohort of nearly 134,000 female California professional school employees geographically dispersed throughout the state, was specifically designed to study breast cancer (Bernstein et al. 2002
). Thus, in the CTS analysis we were able to adjust for known breast cancer risk factors, something we were not able to do in this statewide study. Furthermore, in the CTS analysis, we estimated potential pesticide exposures at a very small scale (within a half-mile radius for each individual). Evaluating the same toxicologic categorizations and individual pesticides as in the statewide study, we saw no evidence of an association with recent pesticide use and breast cancer incidence within the CTS cohort (Reynolds et al. 2004b
Both the statewide study presented here and our earlier analysis in the CTS cohort, are limited in that they are designed to determine whether breast cancer rates are higher in areas with recent high agricultural pesticide use. The results from both studies suggest not. The lack of an association in these studies, however, reflects only on reasonably concurrent exposure/outcome relationships and does not account for sources of broader exposures to pesticides or time windows of potential vulnerability. Furthermore, evaluating the long-term health effects of exposure to a single pesticide is difficult at the population level because of relatively low exposure levels, uncertainty regarding those exposure levels, and the use of many pesticides simultaneously in some census block groups.
Unfortunately, preexisting historical data on agricultural pesticide use, in conjunction with data on residential histories for those with or at risk of breast cancer, are neither readily available nor easy to collect. In California, agricultural pesticide use has been fairly consistent statewide, with basically the same counties, crops, and pesticides ranking highest in use year after year since full reporting was implemented in 1990 (Wilhoit et al. 1998
). Reporting was not required for all agricultural pesticide use in the 1980s, but the restricted pesticide use reporting data indicate a similar consistency of rankings throughout the decade (California Department of Pesticide Regulation 2000
). GIS mapping of pesticide use patterns in the 1980s compared with the 1990s, however, showed there has been some change at the neighborhood level because former cropland and surrounding buffers have been turned into residential areas.
Although the U.S. Census Bureau provides data on residential stability for households but not for individuals, these data suggest a fairly mobile population in California. Census 2000 data indicate that only 31% of occupied California households in 2000 were occupied by the same householder for more than 10 years (U.S. Census Bureau 2002b
). A previous analysis of participants in a breast cancer study among a cohort of California teachers, however, reported that residential stability may be greater among older women and women living in high SES neighborhoods (Hurley et al. 2005
The inability to incorporate information on residential mobility and historical use patterns in this study introduces an important source of potential exposure misclassification. Although this limits our ability to evaluate etiologic relationships, our study was designed in response to public concern about exposures to current agricultural pesticide applications (Solomon and Mott 1998
). Our results indicate that women living in areas of intense, recent agricultural pesticide use do not have higher breast cancer rates. Determining whether girls or young women living in these areas will be at greater risk of breast cancer in future years is a topic of continuing interest but beyond the scope of our study.
Recently, results were published from two case–control studies that tried to address the issue of historical agricultural pesticide exposures and breast cancer (Brody et al. 2004
; O’Leary et al. 2004
). A small case–control study (n
= 105 cases) nested within a cohort of long-term residentially stable women living on Long Island, New York, used several different data sources to estimate historical exposures to agricultural pesticides (O’Leary et al. 2004
). The authors reported an increased breast cancer risk associated with residence within a mile of a hazardous waste site containing pesticides [odds ratio (OR) = 2.9; 95% CI, 1.1–7.2] but no association with measures of residence on or near prior agricultural land (OR = 1.5; 95% CI, 0.8–2.9) or pesticides detected in drinking water (OR = 1.2; 95% CI, 0.6–2.1). These proxy exposure measures were not highly correlated, perhaps because they represent very different kinds of exposures and/or because of nonconcurrent time periods of measurement.
In a population-based case–control study of women living in Cape Cod, Massachusetts, exposure estimates were constructed dating back to 1948 from historical aerial photography and written pesticide spraying records (Brody et al. 2002
). Although the authors reported no overall association between pesticide use and breast cancer, modest (although not statistically significant) associations were reported for aerial applications of persistent pesticides on cranberry bogs and less persistent pesticides applied for tree pests or agriculture (Brody et al. 2004
). The Cape Cod study probably represents the most comprehensive evaluation of historical agricultural pesticide applications and breast cancer risk conducted to date, and it illustrates the complexity of constructing these kinds of risk indicators. Through GIS, the Cape Cod study was able to estimate the relative intensity of pesticide exposures associated with residences over a ≥ 40-year time span. Unlike our study, however, the Cape Cod study had limited variability in pesticide use and was not able to evaluate specific individual (or classes of) chemicals of interest.
The question of whether exposures to agricultural pesticide applications are a cause of breast cancer is obviously complex and likely to be answered only through a variety of complementary approaches. The recent advent of GIS-based technologies has enhanced our ability to characterize ambient exposures that are not easily reportable, or identifiable, on an individual basis. Studies that use GIS to integrate information across various domains, such as those being conducted on Long Island and Cape Cod, will be greatly improved by the availability of more comprehensive geographically referenced historical exposure data as they become available in the future.