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Environmental Health Perspectives

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Research September 2017 | Volume 125 | Issue 9

Environ Health Perspect; DOI:10.1289/EHP1295

Insecticide Use and Breast Cancer Risk among Farmers’ Wives in the Agricultural Health Study

Lawrence S. Engel,1 Emily Werder,1 Jaya Satagopan,2 Aaron Blair,3 Jane A. Hoppin,4,5 Stella Koutros,3 Catherine C. Lerro,3 Dale P. Sandler,6 Michael C. Alavanja,3 and Laura E. Beane Freeman3
Author Affiliations open

1Department of Epidemiology, UNC Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina, USA

2Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York, USA

3Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health (NIH), Department of Health and Human Services (DHHS), Bethesda, Maryland, USA

4Department of Biological Sciences, and

5Center for Human Health and the Environment, North Carolina State University, Raleigh, North Carolina, USA

6Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, DHHS, Research Triangle Park, North Carolina, USA

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  • Background:
    Some epidemiologic and laboratory studies suggest that insecticides are related to increased breast cancer risk, but the evidence is inconsistent. Women engaged in agricultural work or who reside in agricultural areas may experience appreciable exposures to a wide range of insecticides.
    We examined associations between insecticide use and breast cancer incidence among wives of pesticide applicators (farmers) in the prospective Agricultural Health Study.
    Farmers and their wives provided information on insecticide use, demographics, and reproductive history at enrollment in 1993–1997 and in 5-y follow-up interviews. Cancer incidence was determined via cancer registries. Among 30,594 wives with no history of breast cancer before enrollment, we examined breast cancer risk in relation to the women’s and their husbands’ insecticide use using Cox proportional hazards regression to estimate adjusted hazard ratios (HRs) and 95% confidence intervals (CIs).
    During an average 14.7-y follow-up, 39% of the women reported ever using insecticides, and 1,081 were diagnosed with breast cancer. Although ever use of insecticides overall was not associated with breast cancer risk, risk was elevated among women who had ever used the organophosphates chlorpyrifos [HR=1.4 (95% CI: 1.0, 2.0)] or terbufos [HR=1.5 (95% CI: 1.0, 2.1)], with nonsignificantly increased risks for coumaphos [HR=1.5 (95% CI: 0.9, 2.5)] and heptachlor [HR=1.5 (95% CI: 0.7, 2.9)]. Risk in relation to the wives’ use was associated primarily with premenopausal breast cancer. We found little evidence of differential risk by tumor estrogen receptor status. Among women who did not apply pesticides, the husband’s use of fonofos was associated with elevated risk, although no exposure–response trend was observed.
    Use of several organophosphate insecticides was associated with elevated breast cancer risk. However, associations for the women’s and husbands’ use of these insecticides showed limited concordance. Ongoing cohort follow-up may help clarify the relationship, if any, between individual insecticide exposures and breast cancer risk.
  • Received: 28 October 2016
    Revised: 25 April 2017
    Accepted: 08 May 2017
    Published: 06 September 2017

    Address correspondence to L. Engel, Dept. of Epidemiology, University of North Carolina, CB #7435, Chapel Hill, NC 27599-7435 USA. Telephone: 919-962-2756. Email:

    Supplemental Material is available online (

    The authors declare they have no actual or potential competing financial interests.

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Established environmental and genetic risk factors for breast cancer do not explain a large proportion of the ∼247,000 cases diagnosed annually in the United States (Siegel et al. 2016), nor the nearly 1.7 million cases diagnosed annually worldwide (Torre et al. 2015). Identifying more of the environmental risk factors for this disease could facilitate interventions to reduce the disease burden.

Pesticides have received particular attention in relation to breast cancer risk because of their ubiquity and because of the ability of certain pesticides to induce mammary tumors in animal models or to cause in vitro effects that may be related to breast cancer etiology (Rudel et al. 2007). The apparent endocrine-disrupting effects of some pesticides have raised particular concerns because of the hormonal nature of many known risk factors for breast cancer. Much research on pesticides and breast cancer has focused specifically on organochlorine insecticides because, in part, of their endocrine-disrupting activity; however, various classes of less-studied insecticides and other pesticides also exhibit such activity (McKinlay et al. 2008).

In 2007, 93 million pounds (42 million kg) of insecticide active ingredient were used in the United States, and 892 million pounds (405 kg) were used worldwide (U.S. EPA 2011). The public is exposed to insecticides and other pesticides, generally at low levels (CDC 2009), through the widespread use of these chemicals in agriculture and through their use in homes, yards, and public spaces. Women who are engaged in agricultural work or who reside in agricultural areas are likely to experience higher exposures to a greater range of pesticides. Such agricultural exposures can be direct, resulting from a woman’s handling of pesticides (i.e., mixing, applying, or both), or they can be indirect, resulting from working in fields containing pesticide residues. Other indirect pesticide exposures may result from spray drift, contaminated drinking water, or handling of items contaminated in or near areas of pesticide application.

Most epidemiologic studies of pesticide exposure and breast cancer risk among agriculturally exposed women have relied on nonspecific indicators of exposure, such as possession of a pesticide application license, job title, or residence on a farm (Band et al. 2000; Brophy et al. 2012; Fleming et al. 1999; Folsom et al. 1996; Franceschi et al. 1993; Hansen et al. 1992; Kristensen et al. 1996; Pukkala and Notkola 1997; Salerno et al. 2016; Wiklund and Dich 1994). Results from these studies have been mixed, with reports of increased risk (Band et al. 2000; Brophy et al. 2012; Salerno et al. 2016), no association (Blair et al. 1993; Folsom et al. 1996; Hansen et al. 1992), or decreased risk (Fleming et al. 1999; Franceschi et al. 1993; Kristensen et al. 1996; Pukkala and Notkola 1997; Wiklund and Dich 1994). Two case–control studies based on self-reported pesticide use and agricultural tasks among women in agricultural areas observed decreased risks of breast cancer associated with farming/agricultural work (Duell et al. 2000; Settimi et al. 1999), although one study (Duell et al. 2000) reported increased risk among women with the greatest likelihood of pesticide exposure; however, neither study presented pesticide-specific results. In contrast, a case–control study among Hispanic female farm workers observed an increased risk of breast cancer in relation to chlordane, malathion, and 2,4-dichlorophenoxyacetic acid (2,4-D) exposure (Mills and Yang 2005).

Epidemiologic studies of dichlorodiphenyltrichloroethane (DDT) and other organochlorine insecticides in relation to breast cancer, conducted primarily in the general population, have been largely null (Ingber et al. 2013; Khanjani et al. 2007), although timing of exposure may be important (Cohn et al. 2007; Fenton and Birnbaum 2015). Few studies have examined nonorganochlorine insecticide use and breast cancer risk among the general population, and the results have been inconsistent, with one study observing increased risk (Teitelbaum et al. 2007) and two studies observing no association (El-Zaemey et al. 2014; Farooq et al. 2010); importantly, these studies lacked data to investigate specific pesticides.

The present study follows up on a previous investigation of pesticide use/exposure and breast cancer risk among wives of farmers in the large, prospective Agricultural Health Study (AHS) cohort (Engel et al. 2005). It includes an additional 10–11 y of follow-up and substantially more incident cases. Although our earlier study found several suggestive associations, the relatively short follow-up duration and the modest number of cases limited interpretation of the results. However, the AHS remains one of the only studies with the necessary size and exposure data to examine individual pesticides in relation to breast cancer risk. Because of the extent and complexity of the exposure data, this paper presents risk estimates for a range of insecticides, and a separate paper will present findings for herbicides, fungicides, and fumigants.


Study Population

The Agricultural Health Study has been described in detail elsewhere (Alavanja et al. 1996). In brief, 52,394 private pesticide applicators, primarily farmers, in Iowa and North Carolina were enrolled in the cohort between 1993 and 1997 while attending mandatory certification sessions for applying restricted-use pesticides. Male private applicators who indicated that they were married were asked to have their wives complete two take-home questionnaires: an enrollment questionnaire focused on the wives’ farm exposures and general health and a questionnaire focused on the wives’ reproductive health history. A total of 32,126 wives (an estimated 75% of those eligible) enrolled in the cohort. Of these, 19,578 (61% of those enrolled) completed both questionnaires, and 12,548 (39% of those enrolled) completed only the enrollment questionnaire. In addition, 23,676 wives (74%) completed a 5-y follow-up telephone interview (Figure 1).

Flow diagram.
Figure 1. Flow diagram showing the study population for an analysis of insecticide use and incident breast cancer in wives enrolled in the Agricultural Health Study. Boxes with solid lines represent individuals who remained in the analysis after each step, and boxes with dashed lines represent individuals who were excluded after each step. Cancer and mortality follow-up was via registry linkage.

Exposure Assessment

Pesticide exposure information was obtained at enrollment and at the 5-y follow-up interview. At enrollment, the spouses were asked about ever/never use of 50 specific pesticides, including 22 insecticides. In the 5-y follow-up interview, they were asked whether they had used specific pesticides in the previous growing season and, if so, how many days per week they had typically used them. They were also asked detailed questions about their use of personal protective equipment and practices when handling pesticides. In addition, the questionnaires at both time periods elicited information on a range of demographic, lifestyle, health, and reproductive factors.

Enrollment questionnaires for the farmers elicited similar, but more detailed, information on lifetime pesticide use, including duration, frequency, and decade of first use of specific pesticides. In the 5-year follow-up interview, farmers were asked similar pesticide-related questions as were the spouses. This information was used to assess possible indirect pesticide exposure by the farmers’ wives. (Questionnaires are available at

Participant Follow-up and Case Ascertainment

Incident breast cancer cases were ascertained through population-based cancer registries in Iowa and North Carolina, using International Classification of Diseases for Oncology (3rd edition) codes C50.0–C50.9 (Fritz et al. 2013). Vital status was ascertained through state death registries and the National Death Index. The average duration of follow-up from enrollment was 14.7 y (through 31 December 2010 in North Carolina and 31 December 2011 in Iowa), with a total duration of 448,204 person-years.

Data Analysis

We used Cox proportional hazards regression to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for associations between several metrics of insecticide exposure, described below, and breast cancer risk, with age as the time scale and with left truncation at either enrollment or the 5-y follow-up interview, as appropriate. Participants with a breast cancer diagnosis before enrollment or, for certain analyses, before the 5-y follow-up interview, were excluded. The outcome of interest was first primary invasive breast cancer, with censoring at the time of any in situ breast cancer diagnosis. In all analyses, person-time was accrued until the earliest of breast cancer diagnosis, movement out of state, death, or end of follow-up. The proportional hazards assumption was evaluated for each exposure by including a time-varying interaction term, exposure×age, in each model.

Three primary exposure metrics were investigated for individual insecticides: 1) ever/never use by the women, reported at enrollment; 2) total intensity-weighted days of use in the previous growing season by the women, reported in the 5-y follow-up interview; and 3) cumulative potential exposure (days) from the husband’s use across the enrollment and follow-up interviews. Metrics 1 and 2 represent direct exposures, and metric 3 represents indirect exposures. We present results for the 20 insecticides that were included in the enrollment questionnaires and that were reported by ≥5 cases in analyses of direct or indirect exposure.

For analyses of ever/never use by the women, we examined risk associated with participants’ ever use, reported at enrollment, of each insecticide among the full analytic cohort of 30,594 women.

For analyses of total intensity-weighted days of use in the previous growing season by the women, which took into account the use of personal protective equipment and practices, we used data reported by the women in the 5-y follow-up interview. This analysis was restricted to the 22,271 wives who completed the 5-y interview, had no history of breast cancer prior to this interview, and were living in-state at the time of the interview. Exposure was estimated as intensity score×days of use of each pesticide in the prior growing season. The intensity score was derived from an algorithm that incorporates exposure measurement data from the literature and from the Pesticide Handlers Exposure Database (U.S. EPA 1995), together with self-reported data from each study participant on pesticide use and practices, including whether they mixed specific pesticides, the methods of application used, and the use of personal protective equipment (Coble et al. 2011). Pesticide-specific quantiles of exposure were determined using cut-points from the exposure distribution among noncases, with a minimum of 20 exposed cases per quantile; an exposure was treated as any/none if there were <20 exposed cases.

We examined the risk associated with cumulative potential lifetime exposure to each insecticide from the husband’s use among the 13,500 wives who reported no personal pesticide use before enrollment. Exposure was estimated as the average number of days per year that each pesticide was used×the number of years the pesticide was used after marriage. For wives missing data on the year of marriage (38.3%), we assumed the later of the year that the wife or husband was 20 y old. Exposure to each insecticide was assumed to begin at the latest of the husband’s reported decade of first use of the insecticide or the year of marriage. Exposure to each insecticide ended at the earliest of the husband’s self-reported last use of the insecticide, breast cancer diagnosis, censoring date, or end of follow-up. Insecticide-specific quantiles of exposure were defined as described above. Wives who reported first pesticide use at the 5-y interview or whose pesticide use at the 5-y interview could not be determined were censored at the midpoint between their date of enrollment and their 5-y interview (or the imputed date of the 5-y interview if they did not complete the interview). We used multiple imputation (n=5) to estimate use of individual pesticides at 5 y among the 37% of farmers who did not complete the 5-y interview (Heltshe et al. 2012).

All analyses were adjusted for time-varying menopausal status, race (white, other), state (Iowa, North Carolina), and combined parity/age at first birth (1 birth by 30 y old; ≥2 births, first by 30 y old; nulliparous or all births after 30 y old), with nulliparous women and those with first births after they were 30 y old combined because of the relatively small number of nulliparous cases (n=21 in analyses of indirect exposures). We also adjusted for all other pesticides (including noninsecticides) found to be associated with breast cancer in the present analysis with a demographics-adjusted HR≥1.50 or ≤0.67 and a minimum of five exposed cases. The set of adjustment pesticides was the same for all analyses within each exposure metric (e.g., for all analyses of ever/never use by the women reported at enrollment) but could vary across exposure metrics, as indicated in the table footnotes. Body mass index, age at menarche, family history of breast cancer, physical activity, cigarette smoking, alcohol consumption, education, usual daily sun exposure, and nonfarm employment were examined as potential confounders but were not included in the final models because they did not materially change risk estimates.

We performed additional analyses examining breast cancer risk associated with the relative extent of the women’s use of each insecticide by modeling, in a time-varying manner, whether the women reported its use at a) enrollment only, b) the 5-y follow-up interview only, c) enrollment and the follow-up interview, or d) neither. To account for likelihood of exposure (vs. use), we also examined breast cancer risk associated with each insecticide in models among the full analytic cohort that included, in a time-varying manner, both the husband’s use and the wife’s use of a given insecticide; exposure to each insecticide was defined as a) ever use by the husband only, b) ever use by the wife (regardless of husband’s use), and c) neither.

In addition, we conducted analyses stratified by state of residence, menopausal status, and tumor receptor status. We stratified analyses by state primarily to investigate consistency of direction, rather than of magnitude, of associations between states. We stratified menopausal analyses using a product interaction term between insecticide exposure and time-varying menopausal status, using median age at menopause in the cohort as a proxy for individual age at menopause when the latter information was missing. We also conducted analyses defining cases by their estrogen receptor (ER) and progesterone receptor (PR) status (positive or negative) using joint proportional hazards models (Xue et al. 2013). We conducted sensitivity analyses for direct exposures (metric 1, above) restricted to a) women who reported ever handling pesticides (n=17,094), to increase homogeneity for nonpesticide factors, and b) women who reported either never handling pesticides or handling pesticides for a minimum of 10 y (n=23,431), to increase exposure contrasts. In addition, we conducted subanalyses of indirect exposures lagged 5, 10, and 15 y (n=13,500) and, separately, excluded the imputed pesticide use data among the farmers who did not complete the 5-y follow-up interview. We conducted subanalyses of both direct (metric 1) and indirect (metric 3) exposures in which we excluded cases diagnosed within the first five years after enrollment (n=30,269 and n=13,339, respectively). We also performed analyses without adjustment for menopausal status to address concerns that pesticide exposure may affect timing of menopause.

Missing data for covariates were imputed using IVEware (University of Michigan, Ann Arbor, MI). Risk estimates that incorporated imputed data were similar to those that included only observed data, so we present risk estimates based on models incorporating imputed covariate data.

The institutional review boards of participating institutions approved the study, including the use of implied informed consent for enrollment. We performed all analyses using SAS (version 9.4; SAS Institute Inc.). Analyses were based on AHS data releases P1REL0906.00, P1REL201209.00, and P2REL201209.00.


In this analytic cohort of 30,594 women, 1,081 women were diagnosed with incident breast cancer during the follow-up period (Table 1). The median age at enrollment was 46 y. Over 98% of the women were white. Most (68.3%) were from Iowa. A majority (79.8%) reported one or more births. Nearly half (46.3%) were premenopausal, and nearly half (44.9%) were overweight or obese at baseline. Characteristics of the subgroup of spouses who never used pesticides were similar to those of the full cohort, although the women who never used pesticides were somewhat more likely to be from North Carolina. Estrogen receptor (ER) and progesterone receptor (PR) status was known for ∼83% of cases.

Table 1. Selected characteristics at enrollment (unless otherwise noted) of farmers’ wives in the Agricultural Health Study.
Characteristic All wives in the cohort Wives who never used pesticides
Cases (n=1,081) Noncases (n=29,513) Cases (n=376) Noncases (n=13,124)
n % n % n % n %
Age (y)
 18–39 142 13.1 9,410 31.9 43 11.4 4,594 35.0
 40–49 293 27.1 8,465 28.7 101 26.9 3,371 25.7
 50–59 377 34.9 6,861 23.2 126 33.5 2,738 20.9
 60–69 214 19.8 3,848 13.0 84 22.3 1,874 14.3
 70–91 55 5.1 929 3.1 22 5.9 547 4.2
 White 1,059 98.0 28,948 98.1 367 97.6 12,709 96.8
 Other 21 1.9 514 1.7 9 2.4 386 2.9
Missing 1 0.1 51 0.2 0 0.0 29 0.2
State of residence
 Iowa 703 65.0 20,182 68.4 224 59.6 8,121 61.9
 North Carolina 378 35.0 9,331 31.6 152 40.4 5,003 38.1
First-degree family history of breast cancer 206 19.1 3,253 11.0 73 19.4 1,393 10.6
Body mass index (kg/m2)
 <25.0 434 40.1 12,926 43.8 143 38.0 5,708 43.5
 25.0–29.9 331 30.6 8,343 28.3 112 29.8 3,536 26.9
 ≥30.0 217 20.1 4,822 16.3 85 22.6 2,105 16.0
Missing 99 9.2 3,422 11.6 36 9.6 1,775 13.5
Age at menarche (y)
 <12 144 13.3 3,836 13.0 46 12.2 1,604 12.2
 1214 721 66.7 19,071 64.6 253 67.3 8,260 62.9
 ≥15 98 9.1 2,566 8.7 37 9.8 1,185 9.0
Missing 118 10.9 4,040 13.7 40 10.6 2,075 15.8
 Nulliparous 48 4.4 1,563 5.3 21 5.6 740 5.6
 1 88 8.1 2,189 7.4 37 9.8 1,148 8.7
 ≥2 823 76.1 21,316 72.2 270 71.8 8,960 68.3
Missing 122 11.3 4,445 15.1 48 12.8 2,276 17.3
Age at first birth (y)a
 ≤20 255 24.7 6,674 23.9 77 21.7 2,888 23.3
 21–30 585 56.6 15,789 56.5 210 59.2 6,706 54.2
 >30 71 6.9 1,239 4.4 25 7.0 613 4.9
Missing 122 11.8 4,248 15.2 43 12.1 2,177 17.6
Menopausal status at enrollment
 Premenopausal 385 35.6 14,393 48.8 126 33.5 6,241 47.6
 Postmenopausal 584 54.0 11,262 38.2 210 55.9 4,916 37.5
Missing 112 10.4 3,858 13.1 40 10.6 1,967 15.0
Age at menopause (y)b
 Premenopausal 201 18.6 9,653 32.7 67 17.8 4,106 31.3
 <45 202 18.7 4,728 16.0 56 14.9 2,107 16.1
 45–49 171 15.8 3,361 11.4 70 18.6 1,456 11.1
 50–54 259 24.0 4,165 14.1 97 25.8 1,688 12.9
 ≥55 71 6.6 1,211 4.1 23 6.1 482 3.7
Missing 177 16.4 6,395 21.7 63 16.8 3,285 25.0
Highest educational attainment
 Less than high school 62 5.7 1,429 4.8 25 6.6 865 6.6
 High school 420 38.9 10,617 36.0 156 41.5 5,005 38.1
 More than high school 504 46.6 14,346 48.6 166 44.1 6,192 47.2
 Other 91 8.4 3,022 10.2 26 6.9 1,003 7.6
Missing 4 0.4 99 0.3 3 0.8 59 0.4
Smoking status
 Current 88 8.1 3,000 10.2 37 9.8 1,452 11.1
 Former 205 19.0 4,943 16.7 69 18.4 2,063 15.7
 Never 777 71.9 21,262 72.0 266 70.7 9,440 71.9
Missing 11 1.0 308 1.0 4 1.1 169 1.3
Tumor estrogen/progesterone receptor status
 ER+ 712 65.9 NA 243 64.6 NA
 ER− 190 17.6 NA 64 17.0 NA
Missing 179 16.6 NA 69 18.4 NA
 PR+ 619 57.3 NA 216 57.5 NA
 PR− 277 25.6 NA 90 23.9 NA
Missing 185 17.1 NA 70 18.6 NA
Lifetime number of insecticides used
 0 627 58.0 17,949 60.8 376 100.0 13,124 100.0
 1 178 16.5 4,851 16.4 0 0.0 0 0.0
 2 125 11.6 2,906 9.9 0 0.0 0 0.0
 ≥3 144 13.3 3,661 12.4 0 0.0 0 0.0
aRestricted to parous women.

bPrior to the earliest of breast cancer diagnosis, censoring, or end of follow-up.

Ever personally using (i.e., mixing or applying) any insecticide was reported by 39.0% of the women and was not associated with risk of breast cancer [HR=1.0 (95% CI: 0.9, 1.2)] (Table 2). There was no clear evidence of altered risk associated with ever use of any of the insecticide chemical classes examined, including carbamates, organochlorines, and organophosphates. We observed significant associations between breast cancer risk and ever use of chlorpyrifos [HR=1.4 (95% CI: 1.0, 2.0)] and terbufos [HR=1.5 (95% CI: 1.0, 2.1)]. Risk was nonsignificantly elevated in relation to ever use of coumaphos [HR=1.5 (95% CI: 0.9, 2.5)] and heptachlor [HR=1.5 (95% CI: 0.7, 2.9)] and was nonsignificantly reduced in relation to ever use of toxaphene [HR=0.6 (95% CI: 0.3, 1.5)]. Risk estimates adjusted only for demographic/reproductive factors were similar to those additionally adjusted for other pesticides associated with breast cancer in the present analysis, except for heptachlor and terbufos, whose risk estimates increased appreciably in the more fully adjusted models. Risk estimates for chlorpyrifos and terbufos decreased slightly when mutually adjusted for [HR=1.3 (95% CI: 0.9, 1.9) and HR=1.3 (95% CI: 0.9, 2.0), respectively].

Table 2. Associations between the wives’ ever use of individual insecticides at enrollment and risk of breast cancer among farmers’ wives in the Agricultural Health Study (n=30,594).
Exposure Exposed cases (n=1,081) Exposed noncases (n=29,513) Adjusted HRa 95% CI Adjusted HRb 95% CI
Any insecticide 447 11,420 1.0 0.9, 1.1 1.0 0.9, 1.2
Carbamates 353 9,089 1.0 0.9, 1.1 1.0 0.9, 1.1
 Carbaryl 342 8,884 1.0 0.8, 1.1 1.0 0.9, 1.1
 Carbofuran 20 535 0.9 0.6, 1.3 1.0 0.6, 1.7
Organochlorines 87 2,149 0.8 0.7, 1.0 0.9 0.7, 1.1
 Aldrin 8 232 0.7 0.3, 1.4 0.7 0.3, 1.8
 Chlordane 47 1,178 0.8 0.6, 1.1 0.9 0.6, 1.2
 DDT 48 997 0.9 0.7, 1.2 0.9 0.6, 1.3
 Dieldrin 6 102 1.2 0.5, 2.7 1.3 0.5, 3.6
 Heptachlor 11 215 1.1 0.6, 1.9 1.5 0.7, 2.9
 Lindane 15 425 0.8 0.5, 1.4 0.9 0.5, 1.6
 Toxaphene 6 198 0.6 0.3, 1.4 0.6 0.3, 1.5
Organophosphates 300 7,389 1.0 0.9, 1.2 1.1 0.9, 1.2
 Chlorpyrifos 51 1,130 1.2 0.9, 1.6 1.4 1.0, 2.0
 Coumaphos 18 356 1.3 0.8, 2.0 1.5 0.9, 2.5
 Diazinon 118 2,902 1.1 0.9, 1.3 1.1 0.9, 1.3
 Dichlorvos 32 712 1.1 0.8, 1.5 1.1 0.7, 1.6
 Fonofos 18 538 0.8 0.5, 1.3 0.9 0.5, 1.7
 Malathion 226 5,561 1.0 0.9, 1.2 1.0 0.8, 1.2
 Parathion 13 289 1.1 0.7, 1.9 1.3 0.7, 2.4
 Phorate 22 561 1.0 0.6, 1.5 1.1 0.7, 1.8
 Terbufos 37 814 1.2 0.8, 1.6 1.5 1.0, 2.1
Pyrethroids 45 1,360 0.9 0.7, 1.2 0.9 0.6, 1.3
 Permethrin for animals 32 977 0.9 0.7, 1.3 0.8 0.6, 1.3
 Permethrin for crops 17 568 0.8 0.5, 1.3 0.8 0.5, 1.5
Note: CI, confidence interval; DDT, dichlorodiphenyltrichloroethane; HR, hazard ratio.

aTime scale is attained age, with left truncation at enrollment. Adjusted for time-varying menopausal status, race, state, and combined parity/age at first birth.

bAdjusted as in (a) and additionally adjusted for use of benomyl, metribuzin, butylate, and toxaphene, except for “Any insecticide” and “Organochlorines,” which were additionally adjusted for use of benomyl, metribuzin, and butylate only.

We observed a nonsignificantly elevated risk of breast cancer associated with intensity-weighted days of diazinon use reported by the women at the 5-y follow-up interview [HR=1.4 (95% CI: 0.9, 2.1)] (Table 3). Risk estimates were similar when we adjusted for only demographic factors (i.e., reducing possible overfitting of models). However, analyses at the 5-y follow-up were limited by the relatively small number of women reporting use of insecticides at this interview, which precluded analysis of most insecticides. Moreover, the use of certain insecticides was sufficiently rare to permit comparisons only of exposed versus unexposed.

Table 3. Associations between the wives’ intensity-weighted days per year of use of individual insecticides at the 5-year follow-up and risk of breast cancer among farmers’ wives in the Agricultural Health Study (n=22,271).
Exposure Level (intensity-weighted days) Exposed cases (n=592) Exposed noncases (n=21,679) Adjusted HRa 95% CI Adjusted HRb 95% CI
Chlorpyrifos None 584 21,464 1 1
Any 8 215 1.4 0.7, 2.8 1.4 0.7, 2.8
Diazinon None 571 21,069 1 1
Any 21 610 1.3 0.9, 2.1 1.4 0.9, 2.1
Malathion None 567 20,896 1 1
Any 25 783 1.2 0.8, 1.8 1.2 0.8, 1.8
Carbarylc None 508 18,346 1 1
Any 84 3,333 0.9 0.7, 1.1 0.8 0.7, 1.1
Quartile 1 20 864 0.8 0.5, 1.3 0.8 0.5, 1.3
Quartile 2 21 856 0.9 0.6, 1.3 0.8 0.5, 1.3
Quartile 3 21 822 0.8 0.5, 1.3 0.8 0.5, 1.3
Quartile 4 22 791 0.9 0.6, 1.4 0.9 0.6, 1.4
p trend=0.23 p trend=0.16
Note: CI, confidence interval; HR, hazard ratio.

aTime scale is attained age, with left truncation at 5-year follow-up interview. Adjusted for time-varying menopausal status, race, state, and combined parity/age at first birth.

bAdjusted as in (a) and additionally adjusted for use of dicamba, cyfluthrin, Bacillus thuringiensis, and mecoprop-p.

cShowed evidence of nonproportional hazards (p=0.02–0.03).

The highest tertile of fonofos use by the husbands was associated with a significantly elevated breast cancer risk of 1.7 (95% CI: 1.0, 2.7) among the women who did not apply pesticides themselves; however, there was no apparent exposure–response trend (p=0.09) (Table 4). Ever use of malathion by the husband was associated with a reduced risk of 0.7 (95% CI: 0.5, 1.0) but also with no apparent exposure–response trend (p=0.23). Risk was nonsignificantly elevated in relation to the highest quartile of terbufos use by the husband [HR=1.4 (95% CI: 0.9, 2.2)]. Interpretation of the results did not change in sensitivity analyses that excluded imputed 5-y insecticide use data for the husbands (data not shown).

Table 4. Associations between the husbands’ use of individual insecticides and risk of breast cancer among farmers’ wives who never used pesticides in the Agricultural Health Study (n=13,500).
Exposure Level Exposed cases (n=376)a Exposed noncases (n=13,124) Adjusted HRb 95% CI Adjusted HRc 95% CI
 Aldicarb Never 313 10,858 1 1
Ever 10 539 0.6 0.3, 1.1 0.8 0.4, 1.5
 Aldrin Never 249 10,186 1 1
Ever 50 956 1.2 0.9, 1.7 1.2 0.8, 1.9
 Chlordane Never 238 9,391 1 1
Ever 43 1,041 0.9 0.7, 1.3 0.8 0.5, 1.3
 Dieldrin Never 306 11,499 1 1
Ever 18 255 1.6 0.9, 2.6 1.2 0.6, 2.3
 Heptachlor Never 268 10,514 1 1
Ever 41 762 1.2 0.9, 1.8 1.2 0.7, 1.9
 Lindane Never 270 9,970 1 1
Ever 39 785 1.2 0.8, 1.7 1.1 0.7, 1.7
 Toxaphene Never 287 10,632 1 1
Ever 27 658 0.9 0.6, 1.4 1.0 0.6, 1.7
 Coumaphos Never 305 10,766 1 1
Ever 18 743 0.7 0.4, 1.2 0.9 0.5, 1.6
 Diazinon Never 224 8,417 1 1
Ever 52 1,307 1.1 0.8, 1.5 1.2 0.8, 1.8
 Dichlorvos Never 291 10,765 1 1
Ever 29 917 1.0 0.7, 1.5 0.7 0.4, 1.3
 Parathion Never 283 10,447 1 1
Ever 17 440 1.0 0.6, 1.6 1.1 0.6, 2.0
 Permethrin for animals Never 292 10,361 1 1
Ever 32 1,440 0.9 0.6, 1.3 0.8 0.5, 1.3
 Permethrin for crops Never 291 10,155 1 1
Ever 31 1,415 0.9 0.6, 1.3 0.7 0.4, 1.2
 DDT None 230 9,296 1 1
Any 65 1,345 1.1 0.8, 1.5 0.8 0.5, 1.3
≤Median 26 505 1.1 0.7, 1.6 0.6 0.3, 1.1
>Median 24 504 1.0 0.7, 1.6 1.1 0.6, 1.8
p trend=0.88 p trend=0.58
 Phorate None 223 8,440 1 1
Any 58 1,779 0.9 0.7, 1.2 0.8 0.6, 1.2
≤Median 24 825 0.8 0.5, 1.2 0.8 0.5, 1.3
>Median 30 845 1.0 0.6, 1.4 0.9 0.5, 1.5
p trend=0.49 p trend=0.53
 Carbaryl None 138 5,616 1 1
Any 98 2,872 0.9 0.7, 1.2 0.8 0.5, 1.1
1 27 792 0.9 0.6, 1.3 0.9 0.5, 1.4
2 26 829 1.0 0.6, 1.6 0.7 0.4, 1.2
3 25 772 1.0 0.6, 1.5 1.0 0.6, 1.7
p trend=0.83 p trend=0.64
 Carbofuran None 238 9,091 1 1
Any 78 2,385 1.0 0.7, 1.2 1.1 0.8, 1.5
1 29 910 0.8 0.6, 1.2 0.9 0.5, 1.3
2 19 636 1.0 0.6, 1.8 1.2 0.6, 2.3
3 26 764 1.1 0.7, 1.6 1.3 0.8, 2.1
p trend=0.79 p trend=0.57
 Fonofos None 253 9,633 1 1
Any 71 2,142 1.1 0.9, 1.5 1.3 0.9, 1.8
1 21 696 1.1 0.8, 1.7 1.1 0.7, 1.8
2 25 758 1.0 0.6, 1.7 1.1 0.6, 2.0
3 23 640 1.2 0.8, 1.9 1.7 1.0, 2.7
p trend=0.36 p trend=0.09
 Malathion None 100 3,860 1 1
Any 121 3,997 0.8 0.6, 1.1 0.7 0.5, 1.0
1 31 1,194 0.7 0.5, 1.0 0.6 0.4, 1.0
2 35 1,178 1.3 0.8, 2.0 1.4 0.8, 2.4
3 29 1,185 0.8 0.5, 1.1 0.7 0.5, 1.2
p trend=0.21 p trend=0.23
 Chlorpyrifos None 218 7,611 1 1
Any 140 4,864 1.0 0.8, 1.3 1.0 0.8, 1.4
1 39 1,198 1.1 0.8, 1.5 1.0 0.6, 1.5
2 42 1,117 1.3 1.0, 1.9 1.5 1.0, 2.2
3 26 1,116 0.9 0.6, 1.3 0.8 0.4, 1.3
4 25 1,145 0.9 0.6, 1.3 1.0 0.6, 1.6
p trend=0.79 p trend=0.72
 Terbufos None 208 7,647 1 1
Any 116 4,098 1.0 0.8, 1.3 1.2 0.9, 1.6
1 30 976 1.1 0.8, 1.7 1.2 0.7, 1.9
2 20 977 0.7 0.5, 1.2 0.9 0.5, 1.5
3 29 985 1.0 0.7, 1.5 1.1 0.7, 1.8
4 31 979 1.1 0.8, 1.6 1.4 0.9, 2.2
p trend=0.86 p trend=0.26
Note: CI, confidence interval; DDT, dichlorodiphenyltrichloroethane; HR, hazard ratio.

aNumbers of exposed and unexposed may not sum to 100% for some insecticides owing to missing data.

bTime scale is attained age, with left truncation at enrollment. Adjusted for time-varying menopausal status, race, state, and combined parity/age at first birth.

cAdjusted as in (b) and additionally adjusted for use of 2,4,5-trichlorophenoxyacetic acid (2,4,5-T), 2-(2,4,5-trichlorophenoxy)propanoic acid (fenoprop; 2,4,5-TP), trifluralin, aldicarb, and dieldrin, except for “Organochlorines,” which was additionally adjusted for 2,4,5-T, 2,4,5-TP, and trifluralin only.

In analyses examining the relative extent of the women’s insecticide use, the risk associated with diazinon appeared to be stronger among women who reported its use at both enrollment and the 5-y follow-up [HR=1.9 (95% CI: 0.9, 4.1)] than at either enrollment [HR=1.1 (95% CI: 0.8, 1.5)] or the 5-y follow-up [HR=1.5 (95% CI: 0.8, 3.0)] alone (see Table S1). Risk was significantly elevated among women who reported use of malathion at both enrollment and the 5-y follow-up [HR=1.9 (95% CI: 1.1, 3.2)], but there were too few women who reported its use only at follow-up to estimate risk in this group.

In analyses that included ever use of insecticides by both the women and their husbands, risk was increased in relation to the women’s use of phorate [HR=2.0 (95% CI: 1.0, 4.1)], carbofuran [HR=1.7 (95% CI: 0.7, 4.4)], chlorpyrifos [HR=1.6 (95% CI: 0.9, 2.9)], and terbufos [HR=1.7 (95% CI: 0.9, 3.5)], although only the first was statistically significant (see Table S2). Risk was reduced in relation to the husbands’ use of DDT [HR=0.5 (95% CI: 0.3, 0.8)] and phorate [HR=0.7 (95% CI: 0.4, 0.9)].

The results were generally similar between states for insecticides with sufficient numbers of exposed to permit stratified analyses. For example, ever use of chlorpyrifos by the women was associated with similarly increased risks in Iowa [HR=1.5 (95% CI: 1.0, 2.2)] and North Carolina [HR=1.4 (95% CI: 0.8, 2.5)] (see Table S3). However, ever use of diazinon by the women was associated with an increased risk only in North Carolina [HR=1.4 (95% CI: 1.0, 1.9)] and not in Iowa [HR=0.9 (95% CI: 0.7, 1.2)]. Ever use of terbufos by the women was more strongly associated with risk in North Carolina [HR=2.5 (95% CI: 1.1, 5.5)] than in Iowa [HR=1.3 (95% CI: 0.9, 2.1)]. Ever use of lindane by the husband was associated with an elevated risk in North Carolina [HR=1.8 (95% CI: 0.9, 3.8)] but not in Iowa [HR=0.8 (95% CI: 0.5, 1.5)] (see Table S6). We observed a decreased risk associated with ever use of carbaryl and DDT by the husband in North Carolina [HR=0.5 (95% CI: 0.3, 1.0) and HR=0.5 (95% CI: 0.2, 1.0), respectively], but no such inverse association was observed in Iowa [HR=0.9 (95% CI: 0.6, 1.4) and HR=1.2 (95% CI: 0.7, 2.1), respectively].

Ever use of several insecticides by the women was associated with only premenopausal breast cancer, although the number of exposed premenopausal cases in most analyses was small (see Table S4). These included phorate [premenopausal HR=2.5 (95% CI: 1.0, 6.2); postmenopausal HR=0.9 (95% CI: 0.5, 1.6); pinteraction=0.05] and terbufos [premenopausal HR=2.6 (95% CI: 1.3, 5.4); postmenopausal HR=1.2 (95% CI: 0.8, 1.9); pinteraction=0.08], with weaker evidence for dichlorvos (pinteraction=0.15). Chlorpyrifos was associated with an increased risk of premenopausal breast cancer [HR=1.9 (95% CI: 1.0, 3.8)] and with a weaker, nonsignificantly increased risk of postmenopausal breast cancer [HR=1.3 (95% CI: 0.9, 1.9)]. Associations with ever use of fonofos by the husband appeared to differ by menopausal status [premenopausal HR=0.6 (95% CI: 0.3, 1.4); postmenopausal HR=1.5 (95% CI: 1.1, 2.2); pinteraction=0.04] (see Table S7).

In analyses stratified by tumor ER status, we observed no important differences in risk related to the women’s use of insecticides, but we found elevated risk associated with the husbands’ ever use of DDT only for ER– tumors [ER+ HR=0.8 (95% CI: 0.5, 1.4); ER− HR=1.9 (95% CI:0.7, 4.9); pinteraction=0.10] (see Tables S5 and S8). However, the low incidence of ER– tumors in this cohort limited our ability to identify such differences.

When we excluded cases diagnosed within the first five years after enrollment, risk estimates became stronger in relation to the women’s ever use of organophosphates [HR=1.3 (95% CI: 1.0, 1.5)] and parathion [1.9 (95% CI: 1.0, 3.4)] and to the husbands’ ever use of carbaryl [HR=0.6 (95% CI: 0.4, 1.0)]. Risk estimates were similar when we lagged the husbands’ insecticide use by up to 15 y, when we examined associations by joint ER+/PR+ status rather than by ER+ status alone, and when we did not adjust for menopausal status (data not shown).

When we simultaneously included in a model all significantly associated insecticide exposures (i.e., direct and indirect) among the full cohort, the HRs associated with the wives’ ever use of chlorpyrifos and terbufos were 1.8 (95% CI: 1.0, 3.3) and 1.4 (95% CI: 0.7, 2.8), respectively, and those associated with the husbands’ ever use of fonofos and malathion were 1.2 (95% CI: 0.9, 1.6) and 0.8 (95% CI: 0.6, 1.0), respectively.


The results from this large, prospective cohort study of women living or working on farms, or both, suggest that certain organophosphate insecticides may be associated with elevated risk of breast cancer. We observed modestly increased risks associated with the women’s use of the organophosphates chlorpyrifos and terbufos, with more limited evidence for coumaphos, diazinon, and heptachlor. However, there was little consistency between associations for direct and indirect exposures. None of the insecticides that were associated with increased breast cancer risk when used by the wives were significantly associated with increased risk when used by the husbands. Terbufos showed a nonsignificantly elevated risk in relation to the husbands’ use, and fonofos, which was not associated with risk in relation to the wives’ use, showed a significantly elevated risk in relation to the highest category of the husband’s use. It is noteworthy that chlorpyrifos and terbufos were associated with elevated risk in both Iowa and North Carolina. Risks associated with the organophosphates phorate, terbufos, and fonofos appeared to vary by menopausal status.

Many of the present findings differ from those of an earlier analysis of this cohort that used pesticide and covariate data only from enrollment and that included only the 309 cases identified during the first 5 y of follow-up (Engel et al. 2005). The present analysis improved upon the earlier analysis by including substantially more cases (n=1,081) and follow-up time and by incorporating data on changes in menopausal status over time since enrollment. It is noteworthy that in both studies, increased risks were associated with chlorpyrifos and terbufos and possibly with dichlorvos among premenopausal women. The elevated risks associated with chlorpyrifos and terbufos in the present study are also similar to those observed in a recent study of organophosphate insecticides and cancer incidence among applicators’ spouses in the AHS that used only exposure and demographic data collected at enrollment (Lerro et al. 2015).

There is little other epidemiologic research on specific nonpersistent insecticides in relation to breast cancer risk. A small, registry-based case–control study of breast cancer among Hispanic farm workers in California observed increased risk associated with use of the organophosphate malathion and the organochlorine chlordane, although malathion showed no exposure–response trend (Mills and Yang 2005). Another study observed increased risk among farming women most likely to be exposed to pesticides (Duell et al. 2000) but was unable to examine individual pesticide active ingredients.

The International Agency for Research on Cancer (IARC) recently classified parathion as “possibly carcinogenic to humans” (Group 2B) and malathion as “probably carcinogenic to humans” (Group 2A) based, in part, on induction of mammary gland adenocarcinomas in rats following subcutaneous injection (Guyton et al. 2015). In the present study, parathion was not associated with breast cancer risk, and malathion showed only limited and inconsistent evidence of association. In fact, malathion use by the husbands appeared to be associated with a slightly reduced risk. However, another organophosphate, chlorpyrifos, which was associated with increased breast cancer risk in this study, has been observed to act as a potential endocrine disruptor in vivo (Ventura et al. 2016) and in vitro (Andersen et al. 2002), altering levels of circulating and bioavailable sex hormones (Hodgson and Rose 2006). Chlorpyrifos also induces cell proliferation (Ventura et al. 2016), oxidative stress (Ventura et al. 2015), and genotoxicity (Rahman et al. 2002). However, a rodent bioassay of chlorpyrifos found no evidence of carcinogenicity (Yano et al. 2000). Terbufos and fonofos also alter steroid hormone metabolism (Hodgson and Rose 2006) and induce reactive oxygen species (Hung et al. 2015) and DNA damage (Wu et al. 2011).

The present study did not observe clear associations between any organochlorines and risk of breast cancer, but there was a slight, nonsignificant excess risk with heptachlor. The weight of evidence does not support links of DDT or other organochlorine insecticides with risk of breast cancer (Ingber et al. 2013; Khanjani et al. 2007), although IARC recently classified DDT as “probably carcinogenic to humans” (Group 2A) based on evidence of positive associations with non-Hodgkin lymphoma (NHL), testicular cancer, and liver cancer (Loomis et al. 2015), and limited evidence suggests that early-life exposure to DDT may be important for risk (Fenton and Birnbaum 2015).

The limited evidence in this study that the risks associated with certain pesticides differ by menopausal status, with associations observed primarily among premenopausal cases, may be due to chance or may reflect underlying and yet unclear biological mechanisms. A recent review and meta-analysis concluded that menopausal status did not appear to modify associations between organochlorine insecticides and breast cancer risk (Ingber et al. 2013). We are unaware of any studies that have examined this factor in relation to other insecticides.

This study had several limitations. Some associations may have occurred by chance, given the large number of insecticides investigated. However, we attempted to mitigate this concern by examining the consistency of risk estimates between states and between the wives’ and husbands’ use, although these are imperfect comparisons because of likely differences in the extent of exposure. In addition, we were unable to assess risk associated with the women’s lifetime cumulative use of individual insecticides because, although quantitative use information was collected for the postenrollment period, only ever/never use was assessed for the preenrollment period. Further, despite the large size of the cohort, the limited number of cases exposed to some insecticides precluded exposure–response analyses. We also lacked data on early-life exposures to insecticides, which may be important in breast cancer etiology (Fenton and Birnbaum 2015). These analyses were also unable to examine the main effects or confounding of so-called “inert” ingredients in pesticide formulations, which can show substantial biological activity (Defarge et al. 2016), but which are protected as trade secrets and only rarely disclosed. These are, however, exposures that are integral to the use of pesticides and not extraneous to it. Finally, we relied on self-reported pesticide use information, which may have resulted in some nondifferential exposure misclassification (Blair et al. 2011). In a prospective cohort study, such misclassification would tend to attenuate risk estimates and flatten exposure–response relationships (Blair et al. 2007). However, the reliability of self-reported ever use of specific pesticides (Blair et al. 2002) and the accuracy of the intensity score (Thomas et al. 2010) have been shown to be high among applicators in this cohort.

This study had several strengths over most previous investigations of insecticides and breast cancer risk. Exposure information was collected before disease diagnosis, mitigating concerns about bias resulting from differential reporting. The large cohort size, together with the wide range of pesticides used by the women or by their husbands, enabled investigation of many individual pesticides. We also had substantially more detailed information on the use of individual pesticides by both the women and their husbands than was available to most previous studies. We had extensive data on potential confounding factors and effect measure modifiers. Lastly, we had excellent follow-up of cohort members over ∼15y.


In conclusion, the results from this prospective cohort study suggest that the use of certain organophosphate insecticides, including terbufos, chlorpyrifos, and fonofos, and possibly coumaphos and the organochlorine heptachlor, may be associated with elevated risk of breast cancer. Among these insecticides and in this agricultural population, only terbufos appears to be associated with increased risk in relation to both the women’s and their husbands’ use, although terbufos and chlorpyrifos were associated with elevated risk in both Iowa and North Carolina. Risk may be greater among premenopausal women. Given the widespread use of these insecticides, further research—and potential replication—of these associations is needed.


We thank C. Sima (Memorial Sloan Kettering Cancer Center) for statistical assistance.

This research was supported by National Institutes of Health (NIH) grant R03CA137824 and by the Intramural Research Program of the NIH [National Cancer Institute (NCI; Z01-CP010119) and the National Institute of Environmental Health Sciences/NIH (Z01-ES049030)].


Alavanja MC, Sandler DP, McMaster SB, Zahm SH, McDonnell CJ, Lynch CF, et al. 1996. The Agricultural Health Study. Environ Health Perspect 104(4):362–369, PMID: 8732939, 10.1289/ehp.96104362.

Andersen HR, Vinggaard AM, Rasmussen TH, Gjermandsen IM, Bonefeld-Jorgensen EC. 2002. Effects of currently used pesticides in assays for estrogenicity, androgenicity, and aromatase activity in vitro. Toxicol Appl Pharmacol 179(1):1–12, 10.1006/taap.2001.9347.

Band PR, Le ND, Fang R, Deschamps M, Gallagher RP, Yang P. 2000. Identification of occupational cancer risks in British Columbia. A population-based case–control study of 995 incident breast cancer cases by menopausal status, controlling for confounding factors. J Occup Environ Med 42(3):284–310, PMID: 10738708.

Blair A, Dosemeci M, Heineman EF. 1993. Cancer and other causes of death among male and female farmers from twenty-three states. Am J Ind Med 23(5):729–742, PMID: 8506851, 10.1002/ajim.4700230507.

Blair A, Stewart P, Lubin JH, Forastiere F. 2007. Methodological issues regarding confounding and exposure misclassification in epidemiological studies of occupational exposures. Am J Ind Med 50(3):199–207, PMID: 17096363, 10.1002/ajim.20281.

Blair A, Tarone R, Sandler D, Lynch CF, Rowland A, Wintersteen W, et al. 2002. Reliability of reporting on life-style and agricultural factors by a sample of participants in the Agricultural Health Study from Iowa. Epidemiology 13(1):94–99, PMID: 11805592, 10.1097/00001648-200201000-00015.

Blair A, Thomas K, Coble J, Sandler DP, Hines CJ, Lynch CF, et al. 2011. Impact of pesticide exposure misclassification on estimates of relative risks in the Agricultural Health Study. Occup Environ Med 68(7):537–541, PMID: 21257983, 10.1136/oem.2010.059469.

Brophy JT, Keith MM, Watterson A, Park R, Gilbertson M, Maticka-Tyndale E, et al. 2012. Breast cancer risk in relation to occupations with exposure to carcinogens and endocrine disruptors: A Canadian case-control study. Environ Health 11:87, PMID: 23164221, 10.1186/1476-069X-11-87.

CDC (Centers for Disease Control and Prevention). 2009. “Fourth Report on Human Exposure to Environmental Chemicals.” Atlanta, GA:U.S. Department of Health and Human Services, Centers for Disease Control and Prevention. [accessed 18 March 2013].

Coble J, Thomas KW, Hines CJ, Hoppin JA, Dosemeci M, Curwin B, et al. 2011. An updated algorithm for estimation of pesticide exposure intensity in the Agricultural Health Study. Int J Environ Res Public Health 8(12):4608–4622, PMID: 22408592, 10.3390/ijerph8124608.

Cohn BA, Wolff MS, Cirillo PM, Sholtz RI. 2007. DDT and breast cancer in young women: New data on the significance of age at exposure. Environ Health Perspect 115(10):1406–1414, PMID: 17938728, 10.1289/ehp.10260.

Defarge N, Takacs E, Lozano VL, Mesnage R, Spiroux de Vendomois J, Seralini GE, et al. 2016. Co-formulants in glyphosate-based herbicides disrupt aromatase activity in human cells below toxic levels. Int J Environ Res Public Health 13(3):264, PMID: 26927151, 10.3390/ijerph13030264.

Duell EJ, Millikan RC, Savitz DA, Newman B, Smith JC, Schell MJ, et al. 2000. A population-based case-control study of farming and breast cancer in North Carolina. Epidemiology 11(5):523–531, PMID: 10955404.

El-Zaemey S, Heyworth J, Glass DC, Peters S, Fritschi L. 2014. Household and occupational exposure to pesticides and risk of breast cancer. Int J Environ Health Res 24(2):91–102, PMID: 23767826, 10.1080/09603123.2013.800958.

Engel LS, Hill DA, Hoppin JA, Lubin JH, Lynch CF, Pierce J, et al. 2005. Pesticide use and breast cancer risk among farmers’ wives in the Agricultural Health Study. Am J Epidemiol 161(2):121–135, PMID: 15632262, 10.1093/aje/kwi022.

Farooq U, Joshi M, Nookala V, Cheriyath P, Fischman D, Graber NJ, et al. 2010. Self-reported exposure to pesticides in residential settings and risk of breast cancer: A case-control study. Environ Health 9:30, PMID: 20579356, 10.1186/1476-069X-9-30.

Fenton SE, Birnbaum LS. 2015. Timing of environmental exposures as a critical element in breast cancer risk. J Clin Endocrinol Metab 100(9):3245–3250, PMID: 26214118, 10.1210/jc.2015-2848.

Fleming LE, Bean JA, Rudolph M, Hamilton K. 1999. Cancer incidence in a cohort of licensed pesticide applicators in Florida. J Occup Environ Med 41(4):279–288, PMID: 10224594, 10.1097/00043764-199904000-00010.

Folsom AR, Zhang S, Sellers TA, Zheng W, Kushi LH, Cerhan JR. 1996. Cancer incidence among women living on farms: findings from the Iowa Women’s Health Study. J Occup Environ Med 38(11):1171–1176, PMID: 8941908, 10.1097/00043764-199611000-00018.

Franceschi S, Barbone F, Bidoli E, Guarneri S, Serraino D, Talamini R, et al. 1993. Cancer risk in farmers: Results from a multi-site case–control study in north-eastern Italy. Int J Cancer 53(5):740–745, PMID: 8449597, 10.1002/ijc.2910530506.

Fritz AG, Percy C, Jack A, Shanmugaratnam K, Sobin L, Parkin DM, et al., eds. 2013. International Classification of Diseases for Oncology (3rd edition). Geneva, Switzerland:World Health Organization.

Guyton KZ, Loomis D, Grosse Y, El Ghissassi F, Benbrahim-Tallaa L, Guha N, et al. 2015. Carcinogenicity of tetrachlorvinphos, parathion, malathion, diazinon, and glyphosate. Lancet Oncol 16(5):490–491, PMID: 25801782, 10.1016/S1470-2045(15)70134-8.

Hansen ES, Hasle H, Lander F. 1992. A cohort study on cancer incidence among Danish gardeners. Am J Ind Med 21(5):651–660, PMID: 1609812, 10.1002/ajim.4700210505.

Heltshe SL, Lubin JH, Koutros S, Coble JB, Ji BT, Alavanja MC, et al. 2012. Using multiple imputation to assign pesticide use for non-responders in the follow-up questionnaire in the Agricultural Health Study. J Expo Sci Environ Epidemiol 22(4):409–416, PMID: 22569205, 10.1038/jes.2012.31.

Hodgson E, Rose RL. 2006. Organophosphorus chemicals: Potent inhibitors of the human metabolism of steroid hormones and xenobiotics. Drug metabolism reviews 38(1–2):149–162, PMID: 16684654, 10.1080/03602530600569984.

Hung JH, Chen CY, Omar HA, Huang KY, Tsao CC, Chiu CC, et al. 2015. Reactive oxygen species mediate Terbufos-induced apoptosis in mouse testicular cell lines via the modulation of cell cycle and pro-apoptotic proteins. Environ Toxicol 31(12):1888–1898, PMID: 26370073, 10.1002/tox.22190.

Ingber SZ, Buser MC, Pohl HR, Abadin HG, Murray HE, Scinicariello F. 2013. DDT/DDE and breast cancer: A meta-analysis. Regul Toxicol Pharmacol 67(3):421–433, PMID: 24021539, 10.1016/j.yrtph.2013.08.021.

Khanjani N, Hoving JL, Forbes AB, Sim MR. 2007. Systematic review and meta-analysis of cyclodiene insecticides and breast cancer. J Environ Sci Health C Environ Carcinog Ecotoxicol Rev 25(1):23–52, PMID: 17365341, 10.1080/10590500701201711.

Kristensen P, Andersen A, Irgens LM, Laake P, Bye AS. 1996. Incidence and risk factors of cancer among men and women in Norwegian agriculture. Scand J Work Environ Health 22(1):14–26, PMID: 8685669.

Lerro CC, Koutros S, Andreotti G, Friesen MC, Alavanja MC, Blair A, et al. 2015. Organophosphate insecticide use and cancer incidence among spouses of pesticide applicators in the Agricultural Health Study. Occup Environ Med 72(10):736–744, PMID: 26150671, 10.1136/oemed-2014-102798.

Loomis D, Guyton K, Grosse Y, El Ghissasi F, Bouvard V, Benbrahim-Tallaa L, et al. 2015. Carcinogenicity of lindane, DDT, and 2,4-dichlorophenoxyacetic acid. Lancet Oncol 16(8):891–892, PMID: 26111929, 10.1016/S1470-2045(15)00081-9.

McKinlay R, Plant JA, Bell JN, Voulvoulis N. 2008. Endocrine disrupting pesticides: Implications for risk assessment. Environ Int 34(2):168–183, PMID: 17881056, 10.1016/j.envint.2007.07.013.

Mills PK, Yang R. 2005. Breast cancer risk in Hispanic agricultural workers in California. Int J Occup Environ Health 11(2):123–131, PMID: 15875887, 10.1179/oeh.2005.11.2.123.

Pukkala E, Notkola V. 1997. Cancer incidence among Finnish farmers, 1979-93. Cancer Causes Control 8(1):25–33, PMID: 9051319.

Rahman MF, Mahboob M, Danadevi K, Saleha Banu B, Grover P. 2002. Assessment of genotoxic effects of chloropyriphos and acephate by the comet assay in mice leucocytes. Mutat Res 516(1–2):139–147, PMID: 11943619, 10.1016/S1383-5718(02)00033-5.

Rudel RA, Attfield KR, Schifano JN, Brody JG. 2007. Chemicals causing mammary gland tumors in animals signal new directions for epidemiology, chemicals testing, and risk assessment for breast cancer prevention. Cancer 109(12 suppl):2635–2666, 10.1002/cncr.22653.

Salerno C, Carcagnì A, Sacco S, Palin LA, Vanhaecht K, Panella M, et al. 2016. An Italian population-based case-control study on the association between farming and cancer: Are pesticides a plausible risk factor?. Arch Environ Occup Health 71(3):147–156, PMID: 25942634, 10.1080/19338244.2015.1027808.

Settimi L, Comba P, Carrieri P, Boffetta P, Magnani C, Terracini B, et al. 1999. Cancer risk among female agricultural workers: A multi-center case–control study. Am J Ind Med 36(1):135–141, PMID: 10361598, 10.1002/(SICI)1097-0274(199907)36:1%3C135::AID-AJIM19%3E3.0.CO;2-H.

Siegel RL, Miller KD, Jemal A. 2016. Cancer statistics, 2016. CA Cancer J Clin 66(1):7–30, PMID: 26742998, 10.3322/caac.21332.

Teitelbaum SL, Gammon MD, Britton JA, Neugut AI, Levin B, Stellman SD. 2007. Reported residential pesticide use and breast cancer risk on Long Island, New York. Am J Epidemiol 165(6):643–651, PMID: 17166928, 10.1093/aje/kwk046.

Thomas KW, Dosemeci M, Coble JB, Hoppin JA, Sheldon LS, Chapa G, et al. 2010. Assessment of a pesticide exposure intensity algorithm in the Agricultural Health Study. J Expo Sci Environ Epidemiol 20(6):559–569, PMID: 19888312, 10.1038/jes.2009.54.

Torre LA, Bray F, Siegel RL, Ferlay J, Lortet-Tieulent J, Jemal A. 2015. Global cancer statistics, 2012. CA Cancer J Clin 65(2):87–108, PMID: 25651787, 10.3322/caac.21262.

U.S. EPA (U.S. Environmental Protection Agency), Health and Welfare Canada, and American Crop Protection Association. 1995. Reference Manual Version 1.1 Versar; Pesticide Handlers Exposure Database. Springfield, VA, USA.

U.S. EPA (U.S. Environmental Protection Agnecy). 2011. “Pesticides Industry Sales and Usage: 2006 and 2007 Market Estimates.” Washington, DC: U.S. EPA. [accessed 3/20/2016 2016].

Ventura C, Nieto MR, Bourguignon N, Lux-Lantos V, Rodriguez H, Cao G, et al. 2016. Pesticide chlorpyrifos acts as an endocrine disruptor in adult rats causing changes in mammary gland and hormonal balance. J Steroid Biochem Mol Biol 156:1–9, PMID: 26518068, 10.1016/j.jsbmb.2015.10.010.

Ventura C, Venturino A, Miret N, Randi A, Rivera E, Nunez M, et al. 2015. Chlorpyrifos inhibits cell proliferation through ERK1/2 phosphorylation in breast cancer cell lines. Chemosphere 120:343–350, PMID: 25180937, 10.1016/j.chemosphere.2014.07.088.

Wiklund K, Dich J. 1994. Cancer risks among female farmers in Sweden. Cancer Causes Control 5(5):449–457, PMID: 7999967, 10.1007/BF01694759.

Wu JC, Hseu YC, Tsai JS, Chen LC, Chye SM, Chen CH, et al. 2011. Fenthion and terbufos induce DNA damage, the expression of tumor-related genes, and apoptosis in HEPG2 cells. Environ Mol Mutagen 52(7):529–537, PMID: 21538558, 10.1002/em.20652.

Xue X, Kim MY, Gaudet MM, Park Y, Heo M, Hollenbeck AR, et al. 2013. A comparison of the polytomous logistic regression and joint Cox proportional hazards models for evaluating multiple disease subtypes in prospective cohort studies. Cancer Epidemiol Biomarkers Prev 22(2):275–285, PMID: 23292084, 10.1158/1055-9965.EPI-12-1050.

Yano BL, Young JT, Mattsson JL. 2000. Lack of carcinogenicity of chlorpyrifos insecticide in a high-dose, 2-year dietary toxicity study in Fischer 344 rats. Toxicol Sci 53(1):135–144, PMID: 10653531, 10.1093/toxsci/53.1.135.

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