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APPENDIX B
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TABLE OF CONTENTS

APPENDIX B.1: MEMORANDUM IN SUPPORT OF 2003 EPA IRED SUMMARIZING EPA’S SYNTHESIS OF ATRAZINE 

CANCER EPIDEMIOLOGY DATA (OCTOBER 2003) ............................................................................................................3

APPENDIX B.2: LITERATURE REVIEW METHODOLOGY: ATRAZINE CANCER EPIDEMIOLOGY EVALUATION ...................17

APPENDIX B-3: REVIEW OF ATRAZINE CANCER EPIDEMIOLOGY STUDIES PUBLISHED PRIOR TO 2003 AND PREVIOUSLY 

REVIEWED BY EPA ........................................................................................................................................................18

APPENDIX B.4: REVIEW OF AGRICULTURAL HEALTH STUDY (AHS) NESTED CASE-CONTROL ANALYSES.........................41

APPENDIX B.5: REVIEW OF ATRAZINE CANCER EPIDEMIOLOGY STUDIES PUBLISHED SINCE 2003.................................48
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APPENDIX B.1: MEMORANDUM IN SUPPORT OF 2003 EPA IRED SUMMARIZING 

EPA’S SYNTHESIS OF ATRAZINE CANCER EPIDEMIOLOGY DATA (OCTOBER 

2003)

UNITED STATES ENVIRONMENTAL PROTECTION AGENCY

WASHINGTON, D.C. 20460

OFFICE OF PREVENTION, PESTICIDES AND TOXIC SUBSTANCES

October 28, 2003

MEMORANDUM

SUBJECT: Review of Atrazine Cancer Epidemiology 

DP Barcode D295200, Chemical #080803

FROM: Jerome Blondell, Ph.D., Health Statistician

Chemistry and Exposure Branch 

Health Effects Division (7509C)

Vicki Dellarco, Ph.D., Senior Science Advisor

Health Effects Division (7509C)

THRU: Francis B. Suhre, Chief

Chemistry and Exposure Branch 

Health Effects Division (7509C)

Margaret Stasikowski, Director

Health Effects Division (7509C)

TO: Eric Olson, Ph.D., PM Team Reviewer

Michael Goodis, Product Manager

Special Review and Reregistration Division (7508C)

This review summarizes scientific studies related to atrazine and cancer epidemiology including a 

consideration of animal mode of action related to selected cancers. The review starts with an 

examination of animal mode of action issues related to prostate and ovarian cancers and nonHodgkin’s lymphoma. This section is followed by a review of EPA findings concerning prostate 

cancer in a manufacturing plant, the Agricultural Health Study, and two California studies. The 

following section addresses the evidence concerning non-Hodgkin’s lymphoma and then, other 

cancers. The review concludes with a summary of three published reviews of atrazine and cancer 
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epidemiology published 1996-1999, followed by a listing of those studies published since 1999 and 

considering their impact on the weight-of-evidence. In order to be comprehensive all known 

epidemiologic studies of atrazine and triazines have been included. 

The U.S. Environmental Protection Agency (EPA) requested a review of atrazine and prostate 

cancer by the Scientific Advisory Panel (SAP) made up of outside experts. A report of the 

SAP findings (meeting minutes) from the July 17, 2003 meeting can be found at 

http://www.epa.gov/scipoly/sap/. This review considers the SAP findings and, where appropriate, 

revises the Agency’s findings related to atrazine and prostate cancer. This review also explains 

why studies of other cancers where not presented to the Panel at the July 2003 meeting. To assist 

the reader, an outline of this review is provided below:

I. Examination of prostate and ovarian cancers and NHL in the context of the animal mode of 

action

II. Atrazine and prostate cancer epidemiology

A. Prostate Cancer - Manufacturing plant study

B. Prostate Cancer - Agricultural Health Study in Iowa and North Carolina

C. Prostate Cancer - Pesticide use data and cancer incidence in California counties

D. Prostate Cancer - Overall conclusion

III. Atrazine and epidemiology of Non-Hodgkin’s Lymphoma

IV. Atrazine and epidemiology related to other cancers

V. Results of other reviews of cancer and atrazine through 1999

VI. Studies published since 1999 or not included in the three published reviews

VII. EPA Conclusion: Atrazine exposure and NHL and other cancers

I. Examination of prostate and ovarian cancers and NHL in the context of the animal mode 

of action

As discussed in the January 31, 2003 Interim Reregistration Eligibility Decision, atrazine’s mode of 

action (i.e., a decrease LH surge, failed ovulation and estrous cycle disruption) for induction of 

mammary gland tumors (the only tumor observed in animal bioassays) in SD female rats is not 

considered relevant to humans. Because the epidemiology literature on atrazine (triazines) report 

that atrazine exposure may be associated with an increased incidence of prostate and ovarian 

cancers and NHL, the available chronic toxicity animal bioassays were closely examined for any 

indication of either prostate, ovarian cancer or NHL, as well as the etiology of these tumor types.

The prostate glands in male laboratory animals do not appear to be a target of atrazine toxicity. 

Subchronic and chronic rodent and dog studies and the multigeneration rat studies conducted 

for atrazine and its major metabolites have not demonstrated treatment related tumors or 

prostatitis and only shown inconsistent changes in prostates weights. The SD and Fisher rats 

and CD-1 mice are poor models for evaluating prostate cancer. Atrazine has been shown to 

result in prostatic inflammation of the adult rat offspring (Stoker et al., 1999) but this is not due 

to direct treatment of the offspring, but rather treatment of the dams. In this case, atrazine leads 

to a decrease in early lactational exposure to prolactin (via treatment of the mothers). 

Alterations in neonatal prolactin regulation lead to hyperprolactemia, which in turns lead to the 

prostatic inflammation found in the adult offspring. This work supports the neuroendocrine 

mode of action for atrazine rather than a mode of action that would explain prostate cancer in 

adult male workers. Although the etiology of prostate cancer is not clearly understood, the 

hormonal changes caused by atrazine would be in the opposite direction (i.e., decreased 

prolactin) of what would be expected for the development of prostate cancer. Furthermore, it 

has not been clearly established that prostatitis increases the risk to prostate cancer. 

Therefore, the animal data do not support a mechanism for atrazine contributing to the onset or 

promotion of prostate cancer in humans. 
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5

Ovarian tumors in most laboratory animals are a rare occurrence (Damjanov, 1989). A doserelated increase in ovarian tumor incidence is not seen in any study using atrazine, simazine or 

propazine, and in all studies, the incidences of ovarian tumors are (as would be expected) very 

low. Although the causes of ovarian cancer are not definitively known, the key events in the 

mode of action established for atrazine, i.e., decreased serum LH levels and a decreased 

number of ovulations over a lifetime, are the opposite of the events hypothesized to be 

associated with ovarian carcinogenesis. Some hypotheses have been advanced for ovarian 

carcinogenesis with the predominant hypotheses being the "incessant ovulation" hypothesis and 

the "gonadotropin" hypothesis (e.g., Fathalla, 1971). This hypothesis suggests that damage to 

the ovarian epithelium, resulting from frequent ovulations, leads to increased risk of cancer as 

this leads to increased epithelial cell proliferation. It should be noted that epidemiology studies 

show that factors which decrease the number of lifetime ovulations - such as pregnancy, breastfeeding and oral contraceptive use - reduce ovarian cancer risk (Berchuck and Carney, 1997). 

Therefore, animal data do not support a biologically plausible mechanism for atrazine 

contributing to ovarian cancer in humans.

There was not an increase in any dose group for a lymphoma of any type, including nonHodgkin’s lymphomas (NHL) in atrazine treated SD or F344 rats. The simazine chronic 

bioassay using both sexes of SD rat also failed to see any lymphomas in any animal in any 

dose group (McCormick, 1988). Likewise, no animal in either of the two groups examined 

(control and high dose tested - 1000 ppm) in the propazine chronic bioassay, had a lymphoma 

of any type (Jessup, 1980). The alterations in reproductive hormones that atrazine exposure is 

associated with have not been linked to an increased risk of NHL. NHLs are a broad group of 

neoplasias which originate from lymphoid tissues such as B-cells, T-cells and histiocytes, 

though the vast majority are B-cell in origin. The etiology of NHLs are unclear. Generally 

speaking, increased risk of developing NHL appears to be associated with conditions or 

xenobiotic exposures that result in immune dysfunction (Scherr and Mueller, 1996). An 

association between NHL and reproductive hormones such as LH, FSH, estrogens and 

prolactin, does not appear to be present. A mechanistic role for atrazine contributing to NHL 

has not been identified in laboratory studies.

In summary, multiple animal bioassays do not reveal an increased incidence of tumors at any 

endocrine site other than mammary gland in female SD rats. Other endocrine tumors that have 

been raised in epidemiological studies can not be biologically tied to atrazine’s mode of action 

(i.e., decrease prolactin, decrease LH and suppression of ovulation). Thus, at this time, based 

on the available animal cancer and mode of action data and epidemiological studies, there is no 

tumor endpoint on which to base a cancer risk assessment for atrazine. EPA has considered 

other possible modes of action (e.g., stimulation of aromatase activity) and finds that there are 

inadequate data to support these hypotheses. EPA’s Office of Research and Development 

National Health and Environmental Effects Laboratory is currently conducting a detailed 

investigation of the effects of atrazine and related chlorotriazines on aromatase activity and 

steroidogenesis in an effort to determine whether or not these compounds can change estrone, 

estradiol and testostosterone synthesis in response to atrazine treatment in rats. As additional 

data become available, EPA will review them.

Berchuck A, Carney M. Human ovarian cancer of the surface epithelium. Biochem Pharmacol. 

1997 Sep 1;54(5):541_4.
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6

Bosland MC. Male reproductive system. In Carcinogenesis. Eds., MP Waalkes, JM Ward. 

New Your: Raven Press, Ltd., 1994, pp. 339-402.

Damjanov I., Ovarian tumours in laboratory and domestic animals. Curr Top Pathol. 

1989;78:1_10.

Fathalla MF. Incessant ovulation__a factor in ovarian neoplasia? Lancet. 1971 Jul 

17;2(7716):163. 

Jessup, D. 1980. Two year oral chronic toxicity study in rats. IRDC study no. 382-007. MRID 

00041408; Acc. No. 219502401.

McCormick, C.C. and Arthur, A.T. Simazine-Technical: 104-Week Oral Chronic Toxicity and 

Carcinogenicity Study in Rats. 1988. Study Number: 2-0011-09. MRID number: 406144-05. 

Pharmaceuticals Division, Ciba-Geigy Corp., Summit, NJ. 

Scherr PA and Mueller NE, Non-Hodgkin’s lymphomas, in Eds D. Schottenfeld and JF 

Fraumeni Jr.. Cancer Epidemiology and Prevention New York, Oxford University Press, 1996, 

pgs. 920-945.

Stoker, T.E., Robbinette, C.L., Cooper, R.L. 2000.Maternal exposure to atrazine during 

lactation suppresses suckling_induced prolactin release and results in prostatitis in the adult 

offspring. Toxicol Sci. 1999 Nov;52(1):68_79. 

II. Atrazine and prostate cancer epidemiology

The following review addresses epidemiology related to prostate cancer, non-Hodgkin’s lymphoma, 

other cancers and includes a brief summary of earlier reviews and the most recently submitted 

studies related to atrazine and triazines.

A. Prostate Cancer - Manufacturing plant study

An epidemiology study was conducted of workers at the Syngenta St. Gabriel plant where atrazine 

is manufactured. That study reported a statistically significant increase in the incidence of prostate 

cancer among plant workers. The Agency, upon review of this study, requested additional 

information on the exposure profile of the employees diagnosed with prostate cancer and this 

information was provided and reviewed. To further analyze the question of exposure a nested 

case-control study was proposed by Syngenta and conducted for them by Health Practice 

Exponent Inc. (Hessel et al. 2003). Preliminary results of this study, a review by the Agency, 

comments from four external peer reviewers, a Syngenta-sponsored expert panel review, and 

comments by the Natural Resources Defense Council were provided to the EPA’s Scientific 

Advisory Panel in July of 2003. EPA’s view of the study was that the increase in prostate cancer 
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observed in the St. Gabriel workers was probably due to the increase in PSA screening for these 

workers.

The Panel was requested to comment on the Agency’s conclusion regarding prostate cancer and 

particularly the results from this study. The specific Agency conclusion that EPA asked the SAP to 

comment on was: “Due to the lack of a detailed exposure analysis based on job history and the 

limited statistical power due to the small sample size, atrazine could not be ruled out as a potential 

cause but a role for atrazine seems unlikely.” 

The Panel’s analysis of the St. Gabriel study differed to a degree from the Agency’s conclusion. 

The SAP did conclude that “the increase in Prostate Specific Antigen (PSA) screening at the St. 

Gabriel plant likely led to an increase in the detection of cases of prostate cancer.” Further, the 

Panel noted that “[s]ubstantive and persuasive arguments have been made to support the EPA’s 

conclusion that PSA screening could explain the observed increase in prostate cancer incidence in 

the workers.” Nonetheless, the Panel did not believe there was sufficient evidence to conclude that 

it was “unlikely” that atrazine had a role in the increased prostate cancer cases “given the severe 

limitations of the St. Gabriel study, particularly those pertaining to small sample size, questionable 

exposure assessment and lack of an appropriate comparison group.” According to the SAP, PSA 

screening may be only a “partial explanation” for the increase in prostate cancer and that “atrazine 

cannot be ruled out as a potential cause.” 

The Agency agrees with the SAP’s analysis and has rewritten its conclusion as follows:

The increase in prostate cancer incidence at the St. Gabriel plant in Louisiana is consistent with 

the intensive PSA screening. This is because prostate cancer was found primarily in active 

employees who received intensive prostate specific antigen (PSA) screening, there was no 

increase in advanced tumors or mortality, and proximity to atrazine manufacturing did not 

appear to be correlated with risk. No evidence was identified that permit a determination that 

some of the increase was likely due to exposure to atrazine although atrazine exposure cannot 

be ruled out at this time. However, the study was insufficiently large and suffered from other 

limitations that prevent a determination that all of the increase in prostate cancer was probably 

due to the intensive screening program.

One of EPA’s external reviewers agreed with this finding regarding the role of PSA screening. 

Dr. Edward Giovannucci of the Harvard School of Public Health stated, “Thus, the increased 

excess of prostate cancer observed in the Novartis study is compatible with increases expected 

in a population that is receiving intensive PSA screening.” Another reviewer, Dr. Aaron Blair of 

the National Cancer Institute, though not in full agreement with Dr. Giovannucci, agreed that 

there was evidence to “suggest that PSA screening may well explain the excess incidence of 

prostate cancer in this cohort.”

The Scientific Advisory Panel suggested that the Agency consider additional analysis of the St. 

Gabriel cohort. However, the resulting sample size would still limit the opportunity to draw 

further conclusions. The Agency questions whether additional analysis is warranted for other 

potential risk factors (such as smoking, diet and previous work history, and non-occupational or 

pre-employment exposure to triazine herbicides). Because of the way the study was designed 
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this information is not available to investigators and it may not be feasible to obtain such 

information. The same applies to the suggested analysis of family history, history of prostate 

disease, (e.g., benign prostatic hypertrophy and prostatitis), and additional biologic samples that 

allow DNA extraction. The St. Gabriel study was a study based on available records and it 

might be difficult or impossible for investigators to obtain permission from all or most subjects or 

next-of-kin to get the additional information outlined by the SAP. The SAP repeatedly 

acknowledges “The St. Gabriel cohort study suffered from several limitations that could lead to 

negative findings in epidemiologic studies of similar design, particularly with regard to the very 

small sample size” which can greatly hinder the statistical power to detect an effect.

In October, 2003, Syngenta provided a completed report on the nested case-control study 

(cases and controls selected from within the cohort) by Health Practice Exponent Inc. that 

examined in more detail the exposure of 12 of 17 prostate cancer cases and examined the 

effect of screening on prostate cancer incidence (Hessel et al. 2003). EPA has not yet reviewed 

this study in depth, but a preliminary reading did not find any evidence that prostate cancers 

could be attributed to atrazine exposure. Statistical analysis suggest that PSA screening would 

explain some or all of the elevated rates of prostate cancer. The study authors concluded 

“There is no evidence for an association between atrazine exposure and prostate cancer among 

the workers at the Syngenta plant in St. Gabriel. The increased incidence of prostate cancer 

observed in the previous study could be explained by the PSA screening program.”

B. Prostate Cancer - Agricultural Health Study in Iowa and North Carolina

Tied into the assessment of atrazine and prostate cancer is the recently published study 

Alavanja et al. (2003). This large prospective cohort study of 55,332 male pesticide applicators, 

known as the Agricultural Health Study, reported on the risk of prostate cancer and computed 

odds ratios for individual pesticides within the cohort. For atrazine the reported odds ratio (ratio 

of odds in favor of disease among exposed to the odds of disease among the unexposed, an 

odds ratio of 1.0 implies no increased risk from exposure) was 0.94 for ever/never use reported 

by questionnaire with a 95% confidence interval of 0.78 to 1.14. The Agricultural Health Study 

has a number of advantages over other epidemiologic studies of pesticides. It is the largest 

study of its kind, determines exposure prior to disease (thus, eliminating recall bias), analyzes a 

wide variety of potential and known confounders including other pesticide exposures, and has 

greater statistical power to detect small effects. 

The Scientific Advisory Panel expressed concern that the use of ever/never use atrazine was 

“likely an inappropriate exposure metric” and that other factors such as measures of continuous 

or intermittent use should be considered. The Panel appeared to place little weight on the doseresponse analysis based on cumulative exposure which combined duration, frequency, and 

intensity into one metric that did not show any association between atrazine and prostate 

cancer. The Agency agrees that other exposure metrics might be considered but disagrees that 

ever/never use and cumulative exposure is an inappropriate measure. Available pesticide 

usage data suggest that the pattern of use of atrazine as a preharvest herbicide limits variability 

in duration, frequency, and intensity of use and the dose-response analysis is a sufficient 

measure to account for this source of variation. 

The Scientific Advisory Panel expressed concern that this study had a short follow-up period 

“with exposure information collected at the start of follow-up” and incorrectly stated this was less 
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than five years. Because study subjects were queried about past as well as present use of 

atrazine, the follow-up period was much longer than five years. The National Cancer Institute is 

planning to redo the prostate cancer study with a much larger cohort next year when the sample 

size will be approximately twice as large. However, given the relatively tight confidence interval 

on the current estimate and the lack of any evidence of dose-response, the Agency does not 

expect the new study to produce results different from those already reported. Nevertheless, 

the Agency will revisit and revise these conclusions if the updated prostate cancer study 

produces different results suggesting a risk from exposure to atrazine.

C. Prostate Cancer - Pesticide use data and cancer incidence in California counties

Two studies were conducted in California which has maintained a population-based cancer 

registry since 1988 and a state-wide pesticide use reporting system. Mills (1998) obtained 1993 

pesticide usage data for six pesticides with a suspicion of carcinogenicity based on other 

toxicologic and epidemiologic studies. These data were compared using regression analysis 

with county age- and race- adjusted cancer incidence rates (1988-92). A borderline statistically 

significant correlation was found between atrazine usage and prostate cancer in black males, 

but not among Hispanic, White, or Asian males. This study is subject to aggregation bias 

because the exposure of individuals in the county was not measured. EPA considers such 

studies useful for guiding future studies, but not for reaching conclusions about causation. 

A second study by Mills and Yang (2003) examined the effect of simazine rather than atrazine 

on prostate cancer among members of the United Farm Workers of America. The study found a 

borderline significant association between high simazine use and prostate cancer. Like the 

earlier Mills (1998) study, this study suffers from aggregation bias and a crude measure of 

exposure (total poundage of active ingredient by crop and county for a given time period) which 

may not reflect exposure among farmworkers, 90% of whom are not actively involved in 

applying or handling pesticides (1999-2002 data from presentation on National Agricultural 

Workers Survey by S. Gabbard, J. Nakamoto, and D. Carroll, September 24, 2003, funded by 

the Department of Labor). The use of total poundage of active ingredient by county was not 

normalized by number of workers and is especially problematic because it correlates with the 

size of the crop and acreage in the county and many other factors which might have little to do 

with exposure of farmworkers. For example, a county with double the poundage would be 

counted as having double exposure, even if it also had double the number of farmworkers and 

their exposure was the same in both counties.

D. Prostate Cancer - Overall conclusion

Studies of manufacturing and farming populations do not support a finding that atrazine is a 

likely cause of prostate cancer. The Scientific Advisory Panel stated that neither the Syngenta 

St. Gabriel Plant study or the Agricultural Health Study were “sufficient for EPA to conclude that 

there is no causal association between atrazine exposure and prostate cancer.” However, the 

Agency does not find any results among these studies that would lead us to conclude that 

potential cancer risk is likely from exposure to atrazine.

III. Atrazine and epidemiology of non-Hodgkin’s lymphoma
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The National Cancer Institute has performed a number of studies of non-Hodgkin’s lymphoma 

(NHL) in farming populations. The key findings related to atrazine are noted below.

A study by Schroeder et al. 2001 examined two subtypes of NHL for association with pesticide 

exposure based on earlier data from Iowa and Minnesota. The negative NHL subtype was 

significantly associated with 5 pesticides. For atrazine, the odds ratio was borderline significant 

(Odds ratio = 1.7 with 95% confidence interval 1.0-2.8). The Schroeder study cautiously stated 

“In conclusion, we found weak to relatively strong associations between many agricultural 

exposures and t(14;18)-positive, but not t(14;18)-negative NHL.” and “Causal relationships . . . 

are plausible, but associations should be confirmed in a larger study.” 

The study by Schroeder et al. (2001) contrasted with an earlier study by Zahm et al. (1993) 

conducted in these same two states plus Kansas and Nebraska which concluded, “In our 

judgment, these data provide little evidence that atrazine is associated with NHL among white 

men.” 

Added to these two conflicting studies is a study by DeRoos et al. (2003) published 

electronically in September 2003. EPA has not had time to review this study in depth, but did 

not find evidence sufficient to implicate atrazine as a likely cause of NHL. This study stated 

that “Reported use of several individual pesticides was associated with increased NHL 

incidence” but that “limitations of our data hinder the inferences we can make regarding specific 

pesticides”. The hierarchical regression odds ratio (odds ratio adjusted for the effect of 

exposure to other pesticides) for atrazine was 1.5 (95% CI = 1.0 to 2.2) which, like the study by 

Schroeder et al (2001), has borderline significance. Studies with borderline significance 

increase the likelihood that chance or some confounder may be an explanation for the observed 

findings. The authors caution that “some of the positive results could be due to chance” though 

adjustment for the influence of other pesticides in the analysis makes this somewhat less likely. 

Given the conflicting results and the extreme caution exhibited by the National Cancer Institute 

(NCI) in making its conclusion regarding specific pesticides, the EPA has concluded that 

evidence is not sufficient to implicate atrazine as a likely cause of non-Hodgkin’s lymphoma. 

Nevertheless, EPA will consider these studies in conjunction with other evidence and may 

request additional external review. An exhaustive and thorough analysis of non-Hodgkin’s 

lymphoma and pesticide use is planned by NCI for 2004-5. This analysis will include 

consideration of NHL subtypes and many other factors as well. Absent compelling information 

in the interim, EPA has determined that a thorough review of atrazine and NHL should be 

conducted when the NCI data are available. 

IV. Atrazine and epidemiology related to other cancers

Other cancers besides prostate and non-Hodgkin’s lymphoma were found to have an elevated, 

though not statistically significant, increase in risk at the St. Gabriel plant (Delzell et al. 2001). 

Other studies have suggested an increased risk for ovarian, breast, and other cancers. 

However, these studies are at best preliminary and should not serve as a basis for implicating 

atrazine as a human carcinogen due to their methodological limitations and the absence of 

replication in other populations. The National Cancer Institute is planning a review of atrazine 

and all types of cancers in 2004. Given the much larger sample size and strengths of this 
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Agricultural Health Study, the Agency has decided further review of other cancers and atrazine 

should take place when results from this planned analysis are available. However, if other 

studies or additional compelling evidence becomes available in the interim, the Agency will 

expeditiously review the new evidence and the potential risk resulting from exposure to atrazine. 

A summary of evidence from previous reviews of atrazine and cancer epidemiology, and studies 

published subsequently, are reviewed in the following section

V. Results of other reviews of cancer and atrazine through 1999

Three reviews of triazines including atrazine and cancer epidemiology have been reported in the 

1996-1999 time period:

IARC. 1999. IARC Monographs on the evaluation of carcinogenic risks to humans. Volume 

73: Some chemicals that cause tumours of the kidney or urinary bladder in rodents and some 

other substances. World Health Organization, Lyon, France. 

Neuberger JS. 1996. Atrazine and/or triazine herbicides exposure and cancer: an 

epidemiologic review. Journal of Agromedicine 3(2):9-30.

Sathiakumar N, Delzell E. 1997. A review of epidemiologic studies of triazine herbicides and 

cancer. Critical Reviews in Toxicology 27:599-613.

These three reviews identified the 10 case-control studies (see numbered references at the end 

of this review, 1-10) and two published cohort studies of workers exposed to triazines at 

manufacturing plants (11-12).

Neuberger (1996) concluded “based on the data to date . . . there is no convincing evidence of a 

causal association between atrazine and/or triazine(s) and colon cancer, soft tissue sarcoma, 

Hodgkin’s disease, multiple myeloma, or leukemia. . . .There is a suggestion of a possible 

association between atrazine and/or triazine(s) with ovarian cancer and non-Hodgkin’s 

lymphoma. However, the ovarian cancer study needs to be replicated and the NHL studies fall 

short of providing conclusive evidence of risk because the results could be due to chance, bias, 

or confounding.”

Sathiakumar and Delzell (1997) concluded “The available epidemiologic studies, singly and 

collectively, do not provide any consistent, convincing evidence of a causal relationship between 

exposure to triazine herbicides and cancer in humans.”

The International Agency for Research on Cancer (1999) summarized the human 

carcinogenicity data as follows:

A combined analysis of results of two cohort studies of agricultural chemical production workers 

in the United States showed decreased mortality from cancers at all sites combined among the 

subset of workers who had had definite or probable exposures to triazine. Site-specific 

analyses in this subset of workers yielded no significant findings; a non-significant increase in 
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the number of deaths from non-Hodgkin’s lymphoma was seen, but was based on very few 

observed cases.

A pooled analysis of the results of three population-based case-control studies of men in 

Kansas, eastern Nebraska and Iowa-Minnesota, United States, in which the risk for nonHodgkin’s lymphoma in relation to exposure to atrazine and other herbicides on farms was 

evaluated, showed a significant association; however, the association was weaker when 

adjustment was made for reported use of phenoxyacetic acid herbicides or organophosphate 

insecticides. A sub-analysis of results for farmers in Nebraska, the State in which the most 

detailed information on atrazine use was available, showed no excess risk for non-Hodgkin’s 

lymphoma among farmers who had used atrazine for at least 15 years, after adjustment for use 

of other pesticides. In a case-control study of non-Hodgkin’s lymphoma among women in 

eastern Nebraska, a slight, nonsignificant increase in risk was seen. In all these studies, the 

farmers tended to have an increased risk for non-Hodgkin’s lymphoma, but the excess could not 

be attributed to atrazine.

Less information was available to evaluate the assoication between exposure to atrazine and 

other cancers of the lymphatic and haematopoietic tissues. One study of Hodgkin disease in 

Kansas, one study of leukaemia in Iowa-Minnesota and one study of multiple myeloma from 

Iowa gave no indication of excess risk among persons handling triazine herbicides.

In a population-based study in Italy, definite exposure to triazines was associated with a two- to 

threefold increase of borderline significance in the risk for ovarian cancer. The study was small, 

and potential confounding by exposure to other herbicides was not controlled in the analysis.

Based on these findings the IARC concluded “There is inadequate evidence in humans for the 

carcinogenicity of atrazine.” In a critique of IARC monographs, Huff (2002) questioned the 

decision on atrazine and animal carcinogenicity and based this partly on the Delzell et al. (2001) 

report showing increased risk for prostate cancer and above expected levels for certain cancers 

including buccal cavity (3 observed, 2.1 expected), esophagus (2 observed, 0.7 expected), 

stomach (2 observed, 0.9 expected), bladder (3 observed, 1.6 expected), thyroid (2 observed, 

0.6 expected) and leukemia/lymphomas (7 observed, 4.5 expected). These data are based on 

Table 7 of the Syngenta report by Delzell et al. (2001). This table shows 9 different estimates of 

risk, not counting prostate (already discussed) and certain grouped categories. Therefore, 6 of 

9 categories exhibited an excess, though statistically insignificant risk. Chance alone is a 

possible explanation for such findings. In addition, bias and confounding could produce such 

results. Therefore, these elevated, nonsignficant incidence ratios must be considered 

preliminary findings. Until these findings are replicated in other studies that address the serious 

methodological limitations (especially the low statistical power) of the present study, they should 

be regarded as spurious or suggestive at best. Therefore, the EPA disagrees with Huff (2002) 

that the epidemiology studies provide support for a revision of the IARC classification for 

atrazine.

Independent of these three reviews, EPA has performed internal reviews of all of the above 

studies which had statistically significant findings relevant to atrazine or triazines including 

additional updates to the manufacturing plant studies submitted to EPA but not published. With 

the exception of the possible association with ovarian cancer, which EPA reviewers stated 

needed to be confirmed in other populations, the Agency did not find convincing evidence of an 

association between triazines or atrazine and cancer.
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Huff J. 2002. IARC monographs, industry influence, and upgrading, downgrading, and 

under_grading chemicals: a personal point of view. International Agency for Research on 

Cancer. Int J Occup Environ Health. 8(3):249-70.

VI. Studies published since 1999 or not included in the three published reviews

The following six studies were reviewed by EPA and submitted to the Scientific Advisory Panel 

for review in July 2003.

Alavanja MCR, Samanic C, Dosemeci M, et al. 2003. Use of agricultural pesticides and prostate 

cancer risk in the Agricultural Health Study cohort. Am J Epidemiol 157:800-814.

Delzell E, et al. 2001. Cancer Incidence Among Workers in Triazine-related Operations at the 

Novartis St. Gabriel Plant” Oct. 12, 2001. MRID# 451521-01 and 455184-01, Chemical 

#080803. [Technical Report 170 pp.]

MacLennan PA, Delzell E, Sathiakumar N, et al. 2002. Cancer incidence among triazine 

herbicide manufacturing workers. J Occup Environ Med. 44:1048-1058.

MacLennan PA, Delzell E, Sathiakumar N, et al. 2003. Mortality among triazine herbicide 

manufacturing workers. J Toxicol Environ Health A 66(6):501-517.

Mills PK. 1998. Correlation analysis of pesticide use data and cancer incidence rates in 

California counties. Arch Environ Health. 53:410-3. 

Mills PK, Yang R. Prostate cancer risk in California farm workers. 2003. J Occup Environ Med. 

45:249-258.

Results from the Alavanja (2003), Delzell (2001), Mills (1998), and Mills and Yang (2003) have 

already been discussed above. The two reports by MacLennan et al. are updates to the two 

earlier reports by Sathiakumar (1992, 1995). Most of the results in these two studies are 

covered in much more detail by Delzell et al. (2001) which has already been discussed above in 

the sections on prostate cancer and other cancers. The mortality study (MacLennan et al. 

2003) did find a borderline significant result for non-Hodgkin’s lymphoma based on 4 observed 

deaths versus 1.1 deaths expected. The authors noted, however, that “one of the decedents 

whose death certificate included a diagnosis of NHL had medical records, including a biopsy 

report that indicated a diagnosis of poorly differentiated nasopharyngeal cancer. This case was 

not removed from our analysis. To have done so would have introduced a bias because there 

is no satisfactory procedure for removing similarly misclassified cases from the numerator of 

general population mortality rates used to calculate the expected number of deaths. Our data 

were not of adequate statistical precision to demonstrate trends in NHL rates or SMRs by years 

worked and years since hire.” This acknowledgment of bias based on a misclassified case 

means that borderline statistically significant finding would no longer be significant if the case 

were excluded. As stated above, this evidence is not sufficient to support a finding that atrazine 

is a likely cause of non-Hodgkin’s lymphoma.

The following six studies, including two published since July 2003 meeting were not submitted 

to the Scientific Advisory Panel.
Page 14 of 76

De Roos AJ, Zahm SH, Cantor KP, Weisenburger DD, Holmes FF, Burmeister LF, Blair A. 

2003. Integrative assessment of multiple pesticides as risk factors for non-Hodgkin’s lymphoma 

among men. Occup Environ Med 60:e11.(http://www.occenvmed.com/cgi/content/full/60/9/e11)

Hessel PA, Kalmes R, Smith TJ, Lau E, Mink P, Mandel J. 2003. A Nested Case-Control Study 

of Prostate Cancer and Atrazine Exposure. Final Report, October 3, 2003 performed by Health 

Practice Exponent, Inc. and submitted by Syngenta Crop Protection, Inc.

Hopenhayn-Rich C, Stump ML, Browning SR. 2002. Regional assessment of atrazine exposure 

and incidence of breast and ovarian cancers in Kentucky. Arch Environ Contam Toxicol 42:127-

136.

Kettles MA, Browning SR, Prince TS, Horstman SW. 1997. Triazine herbicide exposure and 

breast cancer incidence: an ecologic study of Kentucky counties. Environmental Health 

Perspectives 105:1222-1227.

Schroeder JC, Olshan AF, Baric R, et al. 2001. Agricultural risk factors for t(14;18) subtypes of 

non-Hodgkin's lymphoma. Epidemiology 12:701-709.

Van Leeuwen JA, Waltner-Toews D, Abernathy T, et al. 1999. Associations between stomach 

cancer incidence and drinking water contamination with atrazine and nitrate in Ontario (Canada) 

agroecosystems, 1987-1991. Int J Epidemiol. 28:836-40.

DeRoos et al. (2003), Hessel et al. (2003), Schroeder et al. (2001) have already been discussed 

above. Hessel et al. (2003) is discussed at the end of the section on “Prostate Cancer -

Manufacturing Plant Study”. DeRoos et al. (2003) and Schroeder et al. (2001) are discussed in 

the section on non-Hodgkin’s lymphoma. 

The other three studies by Hopenhayn-Rich et al. (2002), Kettles et al. (1997), and Van 

Leeuwen et al. (1999) are ecological studies where the unit of analysis are populations or 

groups of people rather than individuals. An earlier study by Kettles et al (1997) suggested an 

association between triazine exposure and breast cancer in Kentucky. However, a later followup study by Hopenhayn-Rich et al. (2002) did not support this finding for Kentucky and instead 

found results suggesting a protective effect for atrazine for ovarian cancer and no effect on 

breast cancer. The Hopenhayn-Rich et al. study was based on 5 year, age-adjusted cancer 

rates which are likely to be more stable than the two year rates used by Kettles et al. A study by 

Van Leeuwen et al. (1999) found a positive association between atrazine water contamination 

levels and stomach cancer among 40 ecodistricts in Ontario, Canada, and a negative 

association with colon cancer suggesting a protective effect for atrazine. The authors “noted that 

so-called ‘ecologic studies’, the type of analysis conducted in this research, have a number of 

weaknesses, including ecologic fallacy and multiple collinearity.” Stomach cancer has been 

declining for many years and is likely associated with a number of dietary and lifestyle factors, 

not controlled for in the Van Leewen et al. (1999) study (Cancer Rates and Risks, 4th edition, 

National Cancer Institute 1996). All of these studies are subject to aggregation bias because 

the actual exposures of individuals in the county/district or how long they resided there is not 

known. As noted in standard epidemiology texts, ecologic studies “can suggest avenues of 

research that may be promising . . . In and of themselves, however, they do not demonstrate 

that a causal association exists” (Gordis L. Epidemiology. W.B. Saunders Company, 

Philadelphia, 1996). The authors themselves warn “conclusions concerning causality cannot be 

drawn” (Kettles et al. 1997). An ecologic study in Kentucky of similar design to those above, 
Page 15 of 76

found a whole host of factors that vary across an urban-rural gradient (Blondell JM. Urban-rural 

factors affecting cancer mortality in Kentucky, 1950-1969. Cancer Detection and Prevention 

11:209-223, 1988). Persons living in rural areas differ not only in terms of pesticide exposures, 

but also diet, parity, physical activity, exposure to viruses, and other lifestyle factors. 

Appropriate controls are critical when studying the relationship between pesticide exposure and 

cancer.

VII. EPA Conclusion: Atrazine exposure and NHL and other cancers

The Agency does not find any results among the available studies that would lead us to 

conclude that potential cancer risk is likely from exposure to atrazine. EPA plans to revisit this 

conclusion upon receipt of new studies, especially those from NCI’s Agricultural Health Study on 

atrazine and all cancers, prostate cancer, and non-Hodgkin’s lymphoma, all of which are 

planned for completion in the next 1-2 years.
Page 16 of 76

Numbered references

1. Brown LM, Blair A, Gibson R, et al. 1990. Pesticide exposures and other agricultural risk 

factors for leukemia among men in Iowa and Minnesota. Cancer Research 50:6585-6591.

2. Brown LM, Burmeister LF Everett GD, et al. 1993. Pesticide exposures and multiple 

myeloma in Iowa men. Cancer Causes Control 4:153-156.

3. Burmeister LF. 1990. Cancer in Iowa farmers: recent results. Am J Ind Med 18:295-301.

4. Cantor KP, Blair A, Everett G, et al. 1992. Pesticides and other agricultural risk factors for 

non-Hodgkin’s lymphoma among men in Iowa and Minnesota. Cancer Research 52:2447-2455.

5. Donna A, Crosignani P, Robutti F, et al. 1989. Triazine herbicides and ovarian epithelial 

neoplasms. Scan J Work Environ Health 15:47-53.

6. Hoar SK, Blair A, Holmes FF, et al. 1986. Agricultural herbicide use and risk of lymphoma 

and soft-tissue sarcoma. JAMA. 256:1141-7.

7. Hoar SK, Blair A, Holmes FF, et al. 1985. Herbicides and colon cancer. Lancet. 

1(8440):1277-8.

8. Hoar-Zahm S, Weisenburger DD, Babbitt PA, et al. 1988. Case-control study of nonHodgkin’s lymphoma and agricultural factors in eastern Nebraska (abstract). Am J Epidemiol

128:901.

9. Zahm SH, Wisenburger DD, Cantor KP, et al. 1993a. Role of the herbicide atrazine in the 

development of non-Hodgkin’s lymphoma. Scan J Work Environ Health 19:108-114.

10. Zahm SH, Weisenburger DD, Saal RC, et al. 1993b. The role of agricultural pesticide use 

in the development of non- Hodgkin's lymphoma in women. Arch Environ Health. 48(5):353-358.

11. Sathiakumar N, Delzell E, Austin H, Cole P. 1992. A follow-up study of agricultural chemical 

production workers. American Journal of Industrial Medicine 21:320-330.

12. Sathiakumar N, Delzell E, Cole P. 1995. Mortality among workers at two triazine 

manufacturing plants. American Journal of Industrial Medicine 29:143-151.

cc: atrazine file (080803)

Catherine Eiden (7509C)
Page 17 of 76

APPENDIX B.2: LITERATURE REVIEW METHODOLOGY: ATRAZINE CANCER 

EPIDEMIOLOGY EVALUATION

To identify the epidemiological investigations of the association between atrazine exposure and 

adverse health effects (both cancer and non-cancer), we queried PubMed/Medline and the 

Institute of Scientific Information’s Web of Science. We also performed limited searches using 

Google.Scholar. Querying these three search engines is considered a comprehensive way to 

identify relevant articles (Falagas, 2008). A forth biomedical/scientific search engine Scopus is 

not available to EPA scientists at this time. PubMed is the most commonly used biomedical 

search engine used by researchers today, however Web of Science offers similar journal 

coverage in addition to citation mapping capabilities. We performed citation mapping using Web 

of Science, examining other articles which referenced the articles included in the literature 

review, to identify additional relevant research articles. 

We generated the following search strings. Emphasis was placed upon identification of 

all possible epidemiological studies available, and the ability to use the identical search string in 

both PubMed/Medline and Web of Science. Regarding Google.Scholar, we attempted use of 

similar search strings as well as the advanced search capabilities available 

[http://scholar.google.com/advanced_scholar_search?hl=en&as_sdt=20000]. 

The search strings are found below:

PubMed: (atrazine[tw] OR (triazine*[tw] AND (pesticide*[tw] OR herbicide*[tw]))) AND 

(epidemiolog*[tw] OR cohort*[tw] OR case-control*[tw] OR cluster*[tw] OR environmental 

exposure*[tw] OR occupational exposure*[tw] OR ecologic stud*[tw] OR aggregate 

stud*[tw])

Web of Science

After elimination of duplicates with identical citations between the two search engines, 

we initially identified 386 articles of potential interest. Upon review of the titles, we determined 

that 135 were investigations of human health effects, in contrast to environmental science or 

biology research papers. Of these 135, we eliminated an additional 46 studies that reported on 

exposure assessment methodology only; these are not further evaluated in the chapter. We 

then performed an abstract review of the remaining 89 papers and eliminated an additional 22 

that were review articles or editorial or other opinion narratives published in the open literature. 

Therefore, there were 67 epidemiological investigations of the cancer and non-cancer health 

effects of atrazine. 

: atrazine OR (triazine* AND (pesticide* OR herbicide*))) AND 

(epidemiolog* OR cohort* OR (case-control OR case-control's OR case-controled OR 

case-controlled OR case-controlling OR case-controls) OR cluster* OR "environmental 

exposure" OR "environmental exposures" OR "occupational exposure" OR 

"occupational exposures" OR "ecologic study" OR "ecologic studies" OR "aggregate 

study" OR "aggregate studies")

In the review reflected herein (the July 2011 FIFRA SAP), we are only considering the cancer 

related epidemiology studies. EPA repeated the literature search using similar methodology 
Page 18 of 76

through April 2011 to assure that all relevant atrazine cancer studies are included in the current 

cancer epidemiology evaluation. There were 38 cancer epidemiology studies included in our 

full-text review of the epidemiology literature based upon this literature search. Through 

reference review, EPA identified three additional studies, however these were ultimately 

excluded because the three studies measured simazine, and not atrazine or triazine exposure, 

in association with cancers (breast and gastric cancers measured) that also used an aggregate 

exposure assessment method (P. K. Mills & Yang, 2007; Reynolds et al., 2004; Reynolds et al., 

2005). One additional study from the Agricultural Health Study (AHS) published subsequent to 

April 2011 was also included (Beane-Freeman et al. 2011), and one study was added based 

upon reference list review (Ruder et al. 2004). The list below delineates the articles included in 

our full-text review:

APPENDIX B-3: REVIEW OF ATRAZINE CANCER EPIDEMIOLOGY STUDIES 

PUBLISHED PRIOR TO 2003 AND PREVIOUSLY REVIEWED BY EPA

Table B-3a: Summary of Epidemiology Studies

Study Health 

Outcome

Study Design Study Population Exposure Relevant 

Association

Hoar, Holmes 

Boysen et al. 

(1985)

Colon Cancer Retrospective, 

Case-Control

Cases: Cancer 

patients diagnoses in 

Kansas during 1976-

82

Controls: Individuals 

recruited by random 

digit dialing from 

Medicare and State 

mortality files

Self-Reported 

Pesticide Use

1.4 (0.2 – 7.9)

Triazine OR 

(95%CI):

Hoar, Blair, 

Holmes, et al. 

(1986) 

Lymphoma,

Soft-Tissue 

Sarcoma

Retrospective 

Case-Control

Cases: White, male 

cancer patients 

diagnoses in Kansas 

during 1976-82

Controls: Frequencymatched controls 

recruited by random 

digit dialing from 

Medicare and State 

mortality files

Self-Reported 

Pesticide Use, 

Telephone 

Interview (1982-

1984)

STS: null, not 

shown 

Triazine OR 

(95% CI):

Hodgkin’s 

Disease: null, 

not shown

NHL: 2.5 

(1.2, 5.4)

NHL (never 

use phenoxy 

herbicide): 2.2 

(0.4, 9.1)

Brown, Blair, 

and Gibson et 

al. (1990)

Leukemia Retrospective 

Case-Control

Cases: Male cases 

identified through 

Iowa Tumor Registry 

and Minnesota 

surveillance of 

hospital/labs

Controls: Frequencymatched sample of 

men 

In-Person 

Interview –SelfReported 

Pesticide Use 

Triazine OR 

(95% CI)

1.1 (0.8-1.5)

: 
Page 19 of 76

Study Health 

Outcome

Study Design Study Population Exposure Relevant 

Association

Brown, 

Burmeister, 

Everett, and 

Blair (1993)

Multiple 

Myeloma

Retrospective 

Case-Control

Cases: Male cases 

identified through 

Iowa Tumor Registry

Controls: Frequencymatched sample of 

men general 

population

In-Person 

Interview-Selfreported 

Pesticide Use

 0.80 

(0.40-1.6)

Atrazine OR 

95% CI):

Cantor, Blair, 

Everett et al.

(1992)

Non-Hodgkin’s 

Lymphoma

Retrospective, 

Case-Control

Cases: Male cases 

identified through 

Iowa Tumor Registry 

and Minnesota 

surveillance of 

hospital/labs

Controls: Frequencymatched sample of 

men

In-Person 

Interview –SelfReported 

Pesticide Use

Triazine OR 

(95% CI)

1.1 (0.8-1.6)

: 

Zahm, 

Weisenburger, 

Cantor et al.

(1993)

Non-Hodgkin’s 

Lymphoma

Retrospective, 

Pooled CaseControl

Cases: White males 

ascertained from 

registries/surveillance 

programs in 

Nebraska, IowaMinnesota, and 

Kansas

Controls: Individuals 

randomly selected 

from the same 

geographic location 

as cases and 

frequency matched 

by race, gender, age 

group, and vital 

status

In-Person 

Interview –SelfReported 

Pesticide Use Unadjusted

Pooled 

Atrazine OR 

(95% CI):

1.4 (1.1 – 1.8)

Adjusted for 

OP pesticides

1.2 (0.9 – 1.7)

Zahm and 

Babbit (1993)

Non-Hodgkin’s 

Lymphoma

Retrospective, 

Case-Control

Cases: Women, 

aged 21 years or 

older, who were from 

eastern Nebraska 

and were diagnosed 

during July 1 1983 

and June 30, 1986

Controls: Individuals 

recruited using 

random digit dialing 

and 3:1 frequency 

matched by race, 

sex, vital status, and 

age

Telephone 

Interview –SelfReported 

Pesticide Use

1.2 (0.6 – 2.6) 

Triazine Class 

OR (95% CI):

Clavel, 

Hemon, and 

Mandereau et 

al. (1996)

Hairy-cell 

Leukemia

Retrospective, 

Case-Control

Cases: Male cases 

identified through 18 

French hospitals

Controls: Hospital 

matched men that 

were primarily 

admitted to 

orthopedic and 

rheumatology 

departments

In-Person 

Interview –SelfReported 

Pesticide Use

Triazine 

ORs(95% CI)

“Possible of 

Definite”

: 

1.9 (1.0-3.5)

“Definite”

2.4 (1.2-4.8)
Page 20 of 76

Study Health 

Outcome

Study Design Study Population Exposure Relevant 

Association

Donna, 

Crosignani, 

Robutti et al.

(1989)

Ovarian 

Epithelial 

Neoplasms

Retrospective, 

Case-Control

Cases: Female 

cases ascertained 

from Alessandria 

Hospital Cancer 

Register

Controls: Agematched females, 

randomly selected 

from electoral rolls of 

municipalities in the 

study area 

Self-Reported 

Pesticide Use

Triazine ORs 

(90% CI)

“Definite”

:

2.7 (1.0-6.9)

“Possibly”

1.8 (0.9-3.5)

Kettles, 

Browning, and 

Prince et al.

(1997)

Breast Cancer Ecologic Individuals living in 

Kentucky during 

1991-1994

Exposure 

indices based 

on trizaine 

ground and 

drinking water 

levels, corn 

acreage, and 

atrazine sales

1.07 (1.01-

1.14)

High Exposed 

Category OR 

(95% CI)

1.2 (1.13-

1.28)

HopenhaynRich, Stump, 

and Browning 

(2002)

Breast and 

ovarian cancer

Ecologic Individuals living in 

Kentucky during 

1993-1997

Aggregate 

exposure 

indices based 

on atrazine 

drinking water 

levels, corn 

acreage, and 

atrazine sales

Null 

association 

reported

Sathiakumar , 

Delzell , and 

Cole (1996)

Mortality Retrospective, 

pooled cohort

Employees from two 

atrazine production 

plants located in 

Alabama and 

Louisiana

Exposure 

classifications 

based on job 

title and 

function

“Definite of 

probable”

Overall SMR 

(95% CI)

87 (75 – 99)

“Possible”

99 (83 – 117)

“Definite of 

probable”

Cancer SMR 

(95% CI)

85 (46 – 142)

“Possible”

120 (80 –

172)

MacLennan, 

Delzell , 

Sathiakumar 

et al. (2002)

All Cancers, 

but emphasis 

on prostate 

cancer

Retrospective 

cohort

LA atrazine plant 

workers ascertained 

from employment 

records and followed 

from 1985-1997

Not Applicable

114 ( 83 –

152)

All Cancer 

SIRs (95% CI)

All Employees

Prostate 

Cancer SIRs 

(95% CI)

217 ( 94 –

428)

Active 

Employees 

Only

300 (110 –

652)
Page 21 of 76

Study Health 

Outcome

Study Design Study Population Exposure Relevant 

Association

MacLennan, 

Delzell, Nalini, 

and Myers 

(2003)

Mortality, by 

Cause of 

Death

Retrospective, 

mortality

LA atrazine plant 

workers ascertained 

from employment 

records and followed 

from 1970-1997

Not Applicable

160 (95% CI: 

66 – 160)

All Cancer 

SMR (95% 

CI)

329 (95% CI: 

40 – 1190)

NHL SMR 

(95% CI)

Hessel, 

Kalmes, Smith 

et al. (2004)

Prostate 

Cancer

Prospective, 

Nested CaseControl

Cases: Workers in 

LA atrazine 

production facility 

who were diagnosed 

with prostate cancer

Controls: Randomly 

selected workers 

from same facility 

who were matched to 

cases on race and 

year of birth

Atrazine 

exposure index 

based on job 

title/department, 

categories 

based on job 

title and 

department 

All subjects 

OR (95% CI)

Average 

exposure 

: 

0.87 (0.46–

1.30)

Duration of 

exposure

1.30 (1.06–

1.66)

Cumulative 

exposure

1.30 (1.06–

1.66)

OR for those 

≥1 PSA test 

(95% CI)

Average 

exposure

: 

0.82 (0.36–

1.47)

Duration of 

exposure

0.96 (0.71–

1.30)

Cumulative 

exposure

0.98 (0.91–

1.05)

Mills (1998) County-level 

Cancer 

Incidence

Ecologic Individuals living in 

CA counties during 

1988-1992

County-level 

Atrazine Usage

Hispanic Only

Atrazine 

Usage 

Correlation 

Coefficients

Leukemia – r 

= 0.40

brain cancer –

r = 0.54

testicular 

cancer – r = 

0.41

Blacks Only

Prostate 

Cancer– r = 

0.67
Page 22 of 76

Study Health 

Outcome

Study Design Study Population Exposure Relevant 

Association

Mills (2003) Prostate 

Cancer

Nested Case 

Control study

Cases: Ascertained 

through CA cancer 

registry among 

United Farmworkers 

Union members 

(1987-1999)

Controls: Frequency 

matched Union 

members (age, vital 

status)

Union records 

and state 

pesticide use 

reporting (PUR) 

records 

(simazine, not 

atrazine)

OR Simazine: 

1.5 (1.0, 2.28)

Schroeder 

Olshan, Baric 

et al. (2001)

Non-Hodgkin’s 

Lymphoma

Retrospective, 

Case-Control

Cases: Males aged 

30 years or older 

diagnosed with NHL 

during March 1981-

October 1983 and 

identified through the 

State Health Registry 

of Iowa.

Controls: Males 

recruited through 

random-digit dialing, 

Medicare files, and 

state death 

certificates

In-Person 

Interview –SelfReported 

Pesticide Use

1.7 (1.0-2.8)

Atrazine OR

(95% CI)

Van Leeuwen 

JA, WaltnerToews D, 

Abernathy T, 

Smi B, 

Shoukri M 

(1999).

Cancer of the 

stomach, 

colon, ovaries, 

bladder, and 

Non-Hodgkin’s 

Lymphoma

Ecologic 40 Ecodistricts in 

Ontario, Canada 

during 1987-1991

Ecodistrict-level 

water 

contamination 

and agricultural 

practice data

-Atrazine and 

Stomach 

Cancer

Positive 

Association:

-Atrazine and 

Colon Cancer

Negative 

Association:
23

Hoar SK, Blair A, Holmes FF, Boysen C, Robel RJ (1985). Herbicides and Colon Cancer. 

Lancet; 1(8440):1277-1278.

Health Outcome Study Design Study Population Exposure Reported 

Association

Colon Cancer Population-based 

Case-Control

Cases: Cancer patients 

diagnoses in Kansas 

during 1976-82

Controls: Individuals 

recruited by random digit 

dialing from Medicare and 

State mortality files

Self-Reported 

Pesticide Use

Triazine OR

1.4 (0.2 – 7.9)

Hoar, Holmes, Boysen et al. (1985) conducted a population-based case-control study to 

investigate the association between colon cancer and exposure to herbicides. Cases (n=57) 

were diagnosed with colon cancer in Kansas during 1976-82 and controls (n=948) were 

selected by random digit dialing from Medicare and State mortality records. Hoar, Holmes 

Boysen et al. (1985) did not describe their data collection methods or statistical methods used to 

evaluate the association between colon cancer and exposure to herbicides. While this was the 

case, investigators reported odds ratios (OR) for both years of herbicide use and herbicide 

group (i.e., Phenoxys, Uracil, Triazine, and Amides). 

EPA Review of Results

Hoar, Holmes Boysen et al. (1985) reported that employment on a farm was associated with a 

non-significant increase in colon cancer risk (OR = 1.6, 95% CI: 0.8 – 3.5), which was similar to 

the risk in farmers who did not report using herbicides. With regard to self-reported use of 

herbicides, the investigators reported that the risk of colon cancer among farmers who reported 

mixing herbicides was similar to the risk in farmers who never reported using herbicides, and 

there was a lack of dose-response relationship between years of herbicide use and colon 

cancer risk. Investigators reported specific associations for classes of herbicides including 

triazines (OR 1.4, 95% CI 0.2, 7.9), and although elevated, positive associations were observed, 

confidence bounds were wide, sample size was small to make these estimate with precision. 

Based on these reported findings, the investigators suggest that the study results do not support 

an association between colon cancer and herbicide exposure. Given the limitations, namely 

small sample size and inadequate information in this report concerning study design and 

methods, the study should be considered exploratory. The report does not provide strong 

evidence as to the possible association between colon cancer and self-reported herbicide use.
24

Hoar SK, Blair A, Holmes FF, Boyse CD, Robel RJ, Hoover R, Fraumeni JF. Agricultural 

Herbicide Use and Risk of Lymphoma and Soft-Tissue Sarcoma (1986). JAMA. 9;256: 

1141-1147.

Health Outcome Study Design Study Population Exposure Reported 

Association

Hoar, Blair, Holmes, 

et al. (1986) 

Lymphoma,

Soft-Tissue Sarcoma

Population-based CaseControlCases: White, male 

cancer patients 

diagnoses in Kansas 

during 1976-82

Controls: 

Frequency-matched 

controls recruited by 

random digit dialing 

from Medicare and 

State mortality files

Self-Reported

Pesticide Use, 

Telephone Interview 

(1982-1984), 

validated through 

sales records

Hoar et al. (1985) conducted a case-control study to investigate the association between 

lymphomas and soft-tissue sarcoma with exposure to herbicides. Cases were diagnosed in 

Kansas during 1976-82 and controls were selected by random digit dialing from Medicare and 

State mortality records. Cases of soft-tissues sarcoma (n=200), Hodgkin’s disease (n=173), 

and non-Hodgkin lymphoma (NHL) (n=200) were identified, and 87% of cancers were reviewed 

by pathologist. Pesticide exposure information was collected through telephone interview during 

1982-1984 time period and included information about farm practices, pesticide and herbicide 

use as well as use of personal protective equipment (PPE). Investigators achieved a 93% 

response rate among those eligible for inclusion. Importantly, a small validation study (n=130) 

was performed within this study in which authors compared reported pesticide usage with 

pesticide sales records. Authors performed both age-stratified analyses and unmatched logistic 

regression techniques to evaluate the relation between herbicide use and these cancer 

outcomes.

EPA Review of Results:

Authors reported a border-line statistically significant association between farming and NHL (OR 

1.4, 95% CI 0.9, 2.1), and authors observed a trend by years and days per year of herbicide 

use. Elevated odds of NHL were reported comparing ever- and never use of triazines (OR 2.5, 

95% CI 1.2, 5.4), however adjusting for use of other pesticides (through restriction), and the risk 

estimate was attenuated, and was not statistically different from the null (OR 2.2, 95% CI 0.40, 

9.1). Authors did not observe a trend by number of acres treated with herbicide, or with days 

per year participants reported mixing and loading herbicides. Overall, the results of this initial 

analysis were not strongly suggestive of a link between herbicides and/or triazines and NHL or 

other lymphohematopoietic cancers evaluated. Small sample size, numerous statistical 

comparisons, and non-specific nature of exposure measurement were key limitations. 
25

Brown LM, Blair A, Gibson R, Everett GD, Cantor KP, Schuman LM, Burmeister LF, Van 

Lier SF, and Dick F (1990). Pesticide Exposures and Other Agricultural Risk Factors for 

Leukemia among Men in Iowa and Minnesota. Cancer Research; 50:6585-6591.

Health Outcome Study Design Study Population Exposure Reported 

Association

Leukemia Retrospective CaseControlCases: Male cases 

identified through Iowa 

Tumor Registry and 

Minnesota surveillance of 

hospital/labs

Controls: Frequencymatched sample of men 

In-Person Interview 

–Self-Reported 

Pesticide Use

Triazine OR (95% 

CI):

1.1 (0.8-1.5)

 

Atrazine OR 

(95%CI):

1.0 (0.6-1.5)

Brown, Blair, and Gibson et al. (1990) conducted a case-control study to investigate the 

association between pesticide exposure and leukemia. Authors recruited white, male 

participants at least age 30 years into the study, given known role of age, gender and racial the 

epidemiology of these cancers. In Iowa, cases were ascertained from March 1982 to October 

1983 using the Iowa Tumor Registry. In Minnesota, cases were identified through a 

surveillance network of hospitals and pathology laboratories within October 1980 to September 

1982. Controls were recruited separately using random digit dialing, Medicare records, or state 

death certificates. Cases and controls were frequency matched by 5-year age group, vital status 

at interview, and state of residence. Upon selection into the study, in-person interviews were 

conducted using a standardized questionnaire to obtain information on residential history, 

drinking water sources, non-farm occupational history, smoking and alcohol usage, medical 

conductions, family cancer history, and farm activities. In order to assess pesticide exposure, 

subjects were asked to recall their use of 24 animal insecticides, 34 crop insecticides, 38 

herbicides, and 16 fungicides. Subjects reporting pesticide usage were then asked to recall the 

first and last year the pesticide was used and whether they personally mixed or applied the 

pesticide. In addition, supplemental interviewers were performed to ascertain frequency and 

duration of pesticide use among a sub-set of the sample (n=92 cases, n=211 controls). 

Interviews were completed for 86% of cases and 77% of controls, resulting in a final study 

population of 578 cases and 1,245 controls. Logistic regression was used to estimate the 

association between leukemia and self-reported atrazine use, adjusting for potential 

confounders, including vital status, age, state, tobacco use, family history of lymphopoietic 

cancer, high-risk occupations, and high-risk exposures (i.e., self reported exposure to benzene, 

naphtha, and hair dyes). 

EPA Review of Results

Overall, Brown, Blair, and Gibson et al. (1990) reported a small significant risk for all 

leukemia (OR 1.2, 95%CI: 1.0 – 1.5) among men who lived or worked on a farm as an 

adult, but did not identify significant associations for fungicide, herbicide, or insecticide 

pesticide classes. Similarly, neither the ORs reported for the Trizaine Herbicides (OR 

1.1, 95% CI: 0.8 – 1.5) nor atrazine (OR 1.0, 95%CI: 0.6 – 1.5) statistically differed from 

unity. While the study did not report significantly elevated ORs for Triazine Herbicides or 

atrazine, Brown, Blair, and Gibson et al. (1990) was primarily an exploratory study that 

focused broadly on the potential association between pesticide exposure and leukemia 

and performed multiple statistical comparisons involving both broad pesticide classes 

and particular pesticides with each class. Several suggestive findings were reported, 

however results concerning atrazine were unremarkable with respect to the magnitude 

and direction of association, and lack of an exposure-response relation overall. Given 
26

the study’s exploratory focus, the study does not provide strong evidence concerning 

the association between leukemia and atrazine use specifically.

Brown LM, Burmeister LF, Everett GD ,and Blair A. Pesticide Exposure and Multiple 

Myeloma in Iowa Men (1993). Cancer Causes and Control. 4:153 -156. 

Health 

Outcome

Study Design Study 

Population

Exposure Reported Association

Multiple 

Myeloma

Retrospective 

Case-Control

Cases: Male 

cases identified 

through Iowa 

Tumor Registry

Controls: 

Frequencymatched 

sample of men 

general 

population

In-Person 

Interview-Selfreported 

Pesticide Use

 0.80 (0.40-1.6)

Atrazine OR 95% CI):

Brown, Blair, and Gibson et al. (1993) conducted a case-control study to investigate the 

association between pesticide exposure and multiple myeloma. The study was conducted 

within the same overall series of population-based case-control studies noted above in Brown et 

al (1990). Authors recruited white males, residing in Iowa, aged 30 years or older diagnosed 

with multiple myeloma into the study as the case series. In Iowa, cases were ascertained from 

March 1982 to October 1983 using the Iowa Tumor Registry. Controls were recruited 

separately using random digit dialing, Medicare records, or state death certificates and 

frequency matched to cases by 5-year age group, vital status at interview, and state of 

residence. After recruiting cases and controls, in-person interviews were conducted using a 

standardized questionnaire to obtain information on residential history, drinking water sources, 

non-farm occupational history, smoking and alcohol usage, medical conductions, family cancer 

history, and farm activities. In order to assess pesticide exposure, subjects were asked to recall 

their use of 24 animal insecticides, 34 crop insecticides, 38 herbicides, and 16 fungicides. 

Subjects reporting pesticide usage were then asked to recall the first and last year the pesticide 

was used and whether they personally mixed or applied the pesticide. Information concerning 

frequency and duration of use was available for a small subset of the study population. 

Interviews were completed for 86% of cases and 77% of controls, resulting in a final study 

population of 173 cases and 650 controls. Authors performed logistic regression to estimate the 

association between multiple myeloma and self-reported atrazine, adjusting for vital status, age, 

other suspected factors were not confounders in this association. 

Brown et al. (1993) reported an inverse association between number of years on the farm and 

multiple myeloma risk in this study. The results for any use of herbicide and use of atrazine 

specifically were similarly unremarkable (OR atrazine use 0.80, 95% CI 0.40, 1.6), based upon 

12 and 74 atrazine exposed cases of multiple myeloma, respectively. Authors did not observe 

evidence of an association with multiple myeloma in this study. Authors noted that for other 

pesticide-cancer association, the risk estimate (OR) for living participants was lower than for 

proxies for cases, indicating recall bias or exposure measurement error in the recall of pesticide 

use by proxy respondents may have affected these results. The role of chance due to multiple 

statistical comparisons cannot be excluded either, although the results for atrazine are 

unremarkable. EPA notes that the median last year of farming in this study sample is 1968; 

atrazine was first introduced into the marketplace in 1959. Therefore, it is possible that atrazine 

exposure potential was low within this sample. Given the lack of evidence of an association, and 

EPA Review of Results:
27

the exploratory nature of the study including evaluation of many different pesticide-multiple 

myeloma risk combinations, this study provides limited evidence as to the nature of the 

association between atrazine and multiple myeloma. 

Cantor KP, Blair A, Everett G, Gibson R, Burmeister LF, Brown LM, Schuman L, 

and Dick FR (1992). Pesticide and Other Agricultural Risk Factors for NonHodgkin’s Lymphoma among Men in Iowa and Minnesota. Cancer Research; 

52:2447-2455.

Health Outcome Study Design Study Population Exposure Reported 

Association

Non-Hodgkin’s 

Lymphoma

Retrospective, CaseControlCases: Male cases 

identified through Iowa 

Tumor Registry and 

Minnesota surveillance of 

hospital/labs

Controls: Frequencymatched sample of men

Self-Reported 

Pesticide Use

Triazine OR (95% 

CI)

1.1 (0.8-1.6)

: 

Cantor, Blair, Everett et al. (1992) conducted a case-control study using the same design as 

Brown, Blair, and Gibson et al. (1990) to investigate the link between pesticide exposure and 

non-Hodgkin lymphoma (NHL). NHL cases among white males aged 30 years or older were 

ascertained using the Iowa State Health Registry and Minnesota surveillance program of 

hospitals and pathology laboratory records. Similarly, controls were recruited through either 

random digit dialing, Medicare records, or state death certificates and frequency matched by 5-

year age group, vital status at interview, and state of residence. After recruiting cases and 

controls, in-person interviews were conducted using a standardized questionnaire that was 

similar to the instrument used in Brown, Blair, and Gibson et al. (1990). As part of the 

questionnaire, subjects were asked to recall their use of 23 animal insecticides, 34 crop 

insecticides, 38 herbicides, and 16 fungicides. If subjects recalled using a particular pesticide, 

they were subsequently asked to recall the first and last year the pesticide was used, the 

method of application, and whether they personally mixed or applied the pesticide. Interviews 

were completed for 89% of cases and 77% of controls, resulting in a final study population of 

622 cases and 1,245 controls after pathology reviews to confirm each subject’s NHL status. 

Logistic regression was then used to control for potential confounders and calculate ORs for 

NHL by specific classes of pesticides, including triazine herbicides. In addition to this analysis, 

the investigators also evaluated odds of disease by year of first use of pesticides, before and 

after 1965. According to the investigators, 1965 was selected as a cut-off in this analysis 

because “it was 15-18 years prior to diagnosis, a reasonable minimal period for latency.”

EPA Review of Results

Cantor, Blair, Everett et al. (1992) reported that there was a small, marginally significant 

association between NHL and ever living or working on a farm as an adult (OR = 1.2, 95% CI: 

1.0 – 1.5). While this overall association was observed, the investigators also reported that 

there was non-statistically significant association between NHL and the variables first year 

farmed, last year farmed, and average number of acres farmed. With regard to NHL and selfreported pesticide use, the investigators reported that several positive associations were 

observed, but that no single family of herbicides was significantly associated with overall NHL 

risk. Similarly, there was no statistical association between NHL and self-reported triazine use 

(OR 1.2, 95% CI: 0.8 – 1.6). Authors did not observe significant differences in estimates when 

stratifying by year of first use. Limitations of the study include the broad nature of the 

investigation estimating the association between NHL and self-reported use of multiple types of 

pesticides including triazines, the small number of exposed cases, and limited exposure 
28

assessment based upon self-reported questionnaire. However strengths include relatively low 

potential for several potential biases (selection, recall bias) through design and analysis. 

Overall, this study does not suggest a statistical association between atrazine and NHL. 

Clavel J, Hemon D, Mandereau L, Delemotte B, Severin F, Flandrin G (1996). Farming, 

Pesticide Use, and Hairy-Cell Leukemia. Scand J Work Environ Health; 22:2985-93.

Health Outcome Study Design Study Population Exposure Reported Association

Hairy-cell Leukemia Retrospective, CaseControlCases: Male cases 

identified through 18 

French hospitals

Controls: Hospital 

matched men that were 

primarily admitted to 

orthopedic and 

rheumatology departments

Self-Reported 

Pesticide Use

Triazine ORs

“Possible of Definite”

:

1.9 (1.0-3.5)

“Definite”

2.4 (1.2-4.8)

Adjusted for OP 

Pesticides

2.0 (0.7-5.6)

Clavel, Hemon, and Mandereau et al. (1992) conducted a hospital-based case-control study to 

investigate the association between farming and pesticide use and hairy-cell leukemia (HCL). 

Researchers included male, HCL cases who had been diagnosed within one of 18 French 

hospitals during January 1980 to January 1990. The cases were then matched to controls who 

were admitted to the same hospital but different clinical departments, primarily in orthopedic and 

rheumatology departments, during the same period. After recruitment, study subjects were 

mailed a self-administered questionnaire that included questions on sociodemographic 

characteristics, smoking status, occupation history, and leisure-time activities. Following this 

self-administered questionnaire, subjects who had been employed as farmers were given an inperson interview by a trained study staff member to obtain more detailed information on 

pesticide usage. Based on this secondary interview, two of the investigators, who were blinded 

to subject’s case-control status, classified subjects as “possibly” or definitely” exposed to 

pesticides. In addition to these exposure categories, the investigators also attempted to create 

a quantitative exposure index using respondent data and professional judgment on potential 

spray height, equipment, and relevant exposure route. Interviews were completed for 60% of 

cases and 52% of controls, resulting in a final study population of 226 NHL cases and 425 

hospital-matched controls. Logistic regression was then used to estimate the association, 

adjusting for age, state, vita status, smoking history, family history, and non-farm jobs. 

EPA Review of Results

Clavel, Hemon, and Mandereau et al. (1992) reported that that NHL cases were more likely to 

have worked at six months on a farm, resulting in an overall OR for all farmers of 1.5 (95%CI: 

1.0 – 2.2). When further stratified into farm owner and agricultural laborer groups, the 

investigators observed the same general association, although only the OR estimate for 

farmworkers was statistically significant (Farm Owner OR = 1.9, 95% CI: 1.1 – 3.2; Agricultural 

Laborer OR = 1.2, 95% CI: 0.7 – 1.9). With regard to self-reported pesticide use, the 

investigators reported similar associations. Specifically, the overall OR of possible or definite 

pesticide exposure was 1.5 (95%CI: 1.0 – 2.3) and OR estimates for 19 more specific types of 

insecticides, fungicides, and herbicides were all elevated. Similarly, the same general 

association was observed between HCL and triazine herbicides (Possible or Definite Triazine 

OR = 1.9, 95% CI: 1.0 – 3.5; Definite Triazine OR = 2.4, 95% CI: 1.2 – 4.8). However, when 

restricting to only those who reported never using organophosphate pesticides, the association 

was no longer significantly elevated. Authors stated that controls were similar to the general 

population of the area in terms of major demographic and other characteristics, and that cases 

were selected from all cases identified in this time period, arguing against a role of selection 

bias in these findings. However, authors did not provide information as to the comparability of 
29

the included and excluded cases; authors noted deceased cases were not considered for 

inclusion by proxy. Participants were blinded to study hypothesis, reducing the potential for 

recall bias as an explanation for findings. Adjustment for confounding by organophosphate 

exposure, through restriction, is a strength of the study and decreases uncertainties concerning 

the results. Limitations of the study for the purpose of information the nature of the causal 

association, if any, include the exploratory nature of the design, small number of exposed 

cases, and residual uncertainties surrounding the hospital based selection process. Overall, the 

study does not offer compelling evidence in support of an association between triazines and 

HCL in this population.

Donna A, Crosignani P, Robitta F, Betta PG, Bocca R, Mariani N, Ferrario F, Fissi R, and 

Berrine F (1989). Trazine herbicides and ovarian epithelial noeplasms. Scand J Work 

Environ Health; 15:47-53.

Health Outcome Study Design Study Population Exposure Reported 

Association

Ovarian Epithelial 

Neoplasms

Case-Control Cases: Female cases 

ascertained from 

Alessandria Hospital 

Cancer Register

Controls: Age-matched 

females, randomly 

selected from electoral 

rolls of municipalities in the 

study area 

Self-Reported 

Pesticide Use

Triazine RRs (90% 

CI)

“Definite”

:

2.7 (1.0-6.9)

“Possibly”

1.8 (0.9-3.5)

Donna, Crosignani, Robutti et al. (1989) conducted a population-based case-control study to 

investigate the association between ovarian epithelial neoplasms and exposure to triazine 

herbicide exposure. The study population consisted of women from Alessandria Province, Italy, 

who (i) had at least one ovary, (ii) were in the age range 20 to 69 years olds, and (iii) were 

residents of the municipality during the study period July 1, 1980 to June 30, 1985. Cases were 

ascertained from the study population using the Alessandria Hospital Cancer Registry and age 

matched controls were recruited randomly using electoral rolls of municipalities within the study 

area. After recruiting cases and controls, a questionnaire was used to obtain information on 

reproductive factors that may be risk factors for ovarian cancer. As part of the questionnaire, 

occupational history information was obtained and triazine herbicide exposure was assessed by 

requesting study participants to recall herbicide use. Subjects were designated as “definitely 

exposed” to triazine herbicides if they were involved in the preparation or use of triazine 

herbicides or who worked in corn cultivation with reported use of herbicides. Some subjects did 

not meet this definition, but were designated as “possibly exposed” because according to local 

agricultural experts, triazines were used in all herbicide- treated corn cultivation in Allesandria 

Province after 1964. Lastly, subjects were designated as “unexposed” if the investigators 

determined that professional or domestic triazine exposure was unlikely. In addition to these 

exposure categories, the investigators also considered the possible duration of exposure by 

considering the number of years each individual had an occupation that could have resulted in 

trizaine herbicide exposure. After obtaining questionnaire response data, the investigators used 

logistic regression to calculate rate ratios and 90% CIs. 

EPA Review of Results

This study built upon initial investigations by the same researchers reported in Donna et al. 

(1984). However, in the original investigation, herbicide use and not specific types, were 

evaluated in association with ovarian cancer. Donna, Crosignani, Robutti et al. (1989) reported 

a positive association between those “definitely” (OR 2.7, 95% CI 1.0, 6.9) and “possibly” 
30

triazine exposed (OR 1.8, 95% CI 0.90, 3.5) groups and ovarian epithelial neoplasms. Elevated 

odds ratios were also observed in association with women who reported agricultural use only, 

however precision was reduced: definite exposed triazines 2.8 (95% CI 0.90, 8.1), probably 

triazine exposed 2.1 (95% CI 0.8, 5.4). Estimates were adjusted for ovarian cancer risk factors 

including age, number of live births and use of oral contraceptives. Authors were able to recruit 

a high proportion of the eligible population, 94% of cases and 91% of controls. In addition, 

pesticide exposure questionnaire data were relatively detailed and included information 

concerning many different aspects of farming and other pesticide exposures. However, authors 

did not adjust for use of other pesticides, which is a limitation of the study. The probabilistic 

nature of the exposure assessment method likely results in some misclassification, however this 

may be comparable to the potential recall issues inherent in remembering past exposures. 

Another strength of the study is the use of blinding measures for the interviewer, reducing this 

potential bias in the study, and the use of two separate exposure measurement experts who 

independently rated participants as “definitely” or “probably” exposed to triazines. The major 

limitation of this investigation is the relatively small number of triazine exposed ovarian cancer 

cases and the lack of adjustment for other pesticides in the risk estimate. Overall, the study 

provided some evidence of a possible association between triazine exposure and ovarian 

cancer, however limitations of the study present some uncertainty in interpretation to inform 

causal inference.

Zahm SH, Babbit PA (1993). The Role of Agricultural Pesticide Use in the development of 

Non-Hodgkin’s Lymphoma in Women. Archives of Environmental Health; 48(5): 353-358.

Health Outcome Study Design Study Population Exposure Reported Association

Non-Hodgkin’s 

Lymphoma

Retrospective, CaseControlCases: Women, aged 21 

years or older, who were 

from eastern Nebraska 

and were diagnosed 

during July 1 1983 and 

June 30, 1986

Controls: Individuals 

recruited using random 

digit dialing and 3:1 

frequency matched by 

race, sex, vital status, and 

age

Telephone 

Interview –SelfReported 

Pesticide Use

Triazine Class OR (95% 

CI):

1.2 (0.6 – 2.6) 

Zahm and Babbit (1993) conducted a case-control study to investigate the association between 

non-Hodgkin lymphoma (NHL) and agricultural pesticide use. The study was conducted among 

the same series of population-based case control studies conducted by the NCI in the early 

1980s and reported earlier (See Brown et al. 1990 and 1993; Cantor et al. 1992). Nebraska was 

the only study site within these series of studies that ascertained outcome and exposure 

information for females. Therefore, this study population included women aged 21 years or older 

who resided in 66 counties in eastern Nebraska ascertained through the state Lymphoma Study 

Group. Controls were recruited using random digit dialing and 3:1 frequency matched by race, 

sex, vital status, and age. After recruiting cases and controls, telephone interviews were 

conducted with cases and controls or a proxy respondent. As part of the telephone interview, 

study subjects were asked to recall their pesticide usage, application method, and use of 

personal protective equipment. In total, 184 cases and 707 controls were successfully 

interviewed (response rate of 89% and 86% for cases and controls, respectively). The 

investigators then evaluated the association between NHL and agricultural pesticide exposure 

by calculating age-stratified ORs. 
31

EPA Review of Results

Overall, Zahm and Babbit (1993) reported that neither use of insecticides nor herbicides was 

associated with NHL. With regard to herbicide use on farms, the investigators reported nonsignificant ORs for self-reported use of both any herbicide (OR = 0.7, 95% CI: 0.4 – 1.2) and 

triazines in particular (OR = 1.2, 95% CI: 0.6 – 2.6). The latter estimate was based upon 12 

exposed cases and 38 exposed controls. The relation between atrazine and NHL among 

women was positively elevated, but based upon only 1 and 2 exposed cases and controls 

respectively, and is therefore an unstable estimate of the association. As with other studies in 

this series, the results should also be interpreted with caution because of the broad focus of the 

study in which multiple associations were evaluated, and no hypothesis for atrazine was 

specifically identified. Similarly, the investigators also relied on study subjects to recall past 

pesticide usage to assess exposure to triazines and other pesticides, which may have resulted 

in exposure misclassification, but likely non-differential in nature as participants were blinded to 

the study hypothesis. In addition, as acknowledged by the investigators, the basic survey 

questions on pesticide usage may not adequately reflect the activities through which farm 

women are exposed to pesticides, leading to additional potential for exposure measurement 

error. In this exploratory study among women, authors did not observe evidence of an

association with pesticides overall or triazines specifically. The small sample size, exposure 

measurement error due to the differences in exposure profile between men and women, and 

hypothesis-generating nature of the study limit use of these data to inform the nature of the 

atrazine-NHL association among women. Authors did not observe evidence of a link in this 

study. 

Zahm SH, Weisenburger DD, Cantor KP, Holmes FF, Blair A (1993). Role of the herbicide 

atrazine in the development of non-Hodgkin’s lymphoma. Scand J Work Environ Health; 

19:108-114.

Health Outcome Study Design Study Population Exposure Reported 

Association

Non-Hodgkin’s 

Lymphoma

Retrospective, Pooled 

Case-Control

Cases: White males 

ascertained from 

registries/surveillance 

programs in Nebraska, 

Iowa-Minnesota, and 

Kansas

Controls: Individuals 

randomly selected from 

the same geographic 

location as cases and 

frequency matched by 

race, gender, age group, 

and vital status

In-Person Interview 

–Self-Reported 

Pesticide Use

Pooled Atrazine Use 

OR (95%Ci):

Unadjusted

1.4 (1.1 – 1.8)

Adjusted for OP 

pesticides

1.2 (0.9 – 1.7)

Zahm, Weisenburger, Cantor et al. (1993) conducted a pooled case-control analysis of the 

association between non-Hodgkin lymphoma (NHL) and atrazine exposure using data from the 

three population-based case-controls studies performed by the NCI in the early 1980s (See 

Brown et al. 1990, 1993; Cantor et al. 1992; Hoar et al. 1986). Details of the design and 

methods of these studies have been discussed above. Briefly, cases were identified using 

separate state disease registries and/or surveillance programs. The matched controls were 

randomly selected from the same geographic location as cases and frequency matched by race, 

gender, age group, and vital status at time of interview. In each of the three study groups, 

interviews were conducted with study subjects or a proxy respondent. Questions regarding 

atrazine use varied slightly between study groups. In particular, questions on atrazine use were 

open-ended in both the Nebraska and Kansas study groups (i.e., specific herbicides were not 
32

named when asking questions) whereas a direct was questions on the use of atrazine was 

included in the Iowa-Minnesota study group interview. After collecting questionnaire data, the 

investigators then evaluated the association between NHL and atrazine by calculating ORs, 

stratified by age and state. The investigators also adjusted their atrazine ORs for other potential 

agricultural exposures by stratifying their results by use of 2,4-D and organophosphate(OP) 

insecticides.

EPA Review of Results

Zahm, Weisenburger, Cantor et al. (1993) reported that atrazine use was associated with a 

significant 40% excess risk of NHL, based on a pooled OR of 1.4 (95% CI: 1-1 -1.8). The 

investigators noted, however, that other pesticides were associated with NHL and attempted to 

adjust their OR for use of 2,4-D and OP insecticides. Based on this adjustment, the 

investigators reported that the OR for atrazine was reduced to a non-significant association of 

1.2 (95% CI: 0.9 – 1.7). Similarly, the investigators also performed additional analysis using 

data from the Nebraska study, which obtained the most detailed data. Based on this analysis, 

the investigators reported that increased ORs were generally observed for duration of atrazine 

use, average number of days atrazine was handled, and year of first use of atrazine. When 

these results were adjusted for OP use, however, the OR estimates were below unity, 

suggesting that atrazine is not associated with NHL. Overall, the investigators conducted a 

pooled study that enabled the investigators to conduct a more thorough investigation of the 

association between atrazine exposure and NHL. Strengths and limitations of individual studies 

are noted above and not repeated herein. Concerning the pooled analysis, authors maximized 

use of all available data, at the time, and results supported a conclusion of no association 

between atrazine and NHL due to the lack of an observed association in the presence of use of 

other pesticides, lack of a trend by duration and frequency of use, and inclusion of a large 

sample through the pooling analysis. 

Kettles MA, Browning SR, Prince TS, and Horstman SW (1997). Triazine Herbicide 

Exposure and Breast Cancer Incidence: An Ecologic Study of Kentucky Counties. 

Environmental Health Perspectives; 105(11): 1222-1227.

Health Outcome Study Design Study Population Exposure Reported 

Association

Breast Cancer Ecologic Individuals living in 

Kentucky during 1991-

1994

Exposure indices 

based on trizaine 

ground and drinking 

water levels, corn 

acreage, and 

atrazine sales

1.07 (1.01-1.14)

High Exposed 

Category OR (95% 

CI)

1.2 (1.13-1.28)

Kettles, Browning, and Prince et al. (1997) conducted an ecologic study to examine the 

association between breast cancer incidence and triazine herbicide exposure. The study was 

designed using county-level data from 120 counties in Kentucky. County breast cancer 

incidence rates were calculated using Kentucky’s statewide cancer registry for the years 1991-

1994. Triazine herbicide exposure was then assessed using data on ground and drinking water 

contamination, corn acreage, and pesticide usage by applicators. Ground water data was 

obtained from the Kentucky Geological Survey, which conducted a voluntary study of wells in 

Kentucky during 1990 to 1991, representing 2.3% of the state’s wells. Triazine contaminant 

data for drinking water was obtained from Kentucky’s Division of Water, which is responsible for 

performing water testing of faucets from non-randomly selected homes in Kentucky counties. 

Kentucky’s Division of Water only reports results as positive or negative, so actual concentration 

data was available for the investigators analysis. Corn acreage, pesticide usage data were both 

reported on the county-level, so additional analysis was needed to estimate county-level values. 
33

Using these four data sources, the investigators determined the quartile distribution for each 

exposure variable and assigned each county a score from 0 to 4 for each exposure category. 

The investigators then created a composite exposure variable by summing each county’s four 

separate scores, producing a range of county scores from 3 to 16. After performing their 

exposure assessment, the investigators performed two Poisson regression analyses to estimate 

odds ratios for the four exposure categories and composite exposure variable. 

EPA Review of Results

Kettles, Browning, and Prince et al. (1997) report a small statistically significant association 

between breast cancer and the water contaminants. However, the investigators also indicate 

that the results were not consistent between 1991-92 and 1993-94, with a significant association 

between surface water and breast cancer during 1991-92 and a significant association between 

ground water and breast cancer during 1993-94. While the water contaminant associations 

were not consistent between time periods, the investigators did report that their composite 

exposure variable was associated with breast cancer during both 1991-92 and 1993-94 (i.e., 

Medium and High Exposed County ORs = 1.09 (1.04-1.14), 1.07 (1.01-1.14) and 1.14 (1.08-

1.19), 1.20 (1.13-1.28) for 1991-92 and 1993-94, respectively). Overall, the study provides 

exploratory results that suggest there may be an association between atrazine exposure and 

breast cancer. While this is the case, the study’s ecologic design limits its application in 

establishing direct casual inference because of the exploratory nature of ecologic studies. For 

example, as discussed by the investigators, the ecologic exposure assessment may bias the 

results if county-level characteristics do not accurately reflect individual characteristics within 

counties. 

Hopenhayn-Rich C, Stump ML, and Browning SR (2002). Regional Assessment of 

Atrazine and Incidence of Breast and Ovarian Cancers in Kentucky. Arch. Environ. 

Contam. Toxicol.; 42:127-136.

Health Outcome Study Design Study Population Exposure Reported 

Association

Breast and ovarian 

cancer

Ecologic Individuals living in 

Kentucky during 1993-

1997

Aggregate exposure 

indices based on 

atrazine drinking 

water levels, corn 

acreage, and 

atrazine sales

Null association 

reported

Based similar methods as Kettles, Browning, and Prince et al. (1997), Hopenhayn-Rich, Stump, 

and Browning (2002) conducted an ecologic study to investigate the association between the 

county-level incidence of breast/ovarian cancer and potential atrazine exposure. The study 

population was individuals in Kentucky, grouped by county and 15 Area Development Districts. 

Based on the population in each county and ADD, the investigators used the Kentucky Cancer 

Registry to estimate five-year ovarian and breast cancer age-adjusted incidence rates for the 

period 1993-1997. When assessing atrazine exposure, the investigators considered Kentucky 

data on atrazine levels in drinking water, acreage of corn planted, and atrazine sales. Drinking 

water data was obtained from Kentucky’s Division of Water and contained information on 

ground and surface water sources of drinking water in Kentucky. Using this data, mean atrazine 

levels were calculated for individual counties in Kentucky. County-level corn acreage data was 

obtained from Kentucky’s Department of Agriculture. The investigators considered all available 

acreage data from the 1970 -2000, but only used data from the 1970s in their analysis because 

of the latency period from the time of exposure to development of cancer. Lastly, county-level 

atrazine sales data from 1997 was obtained from Kentucky’s Department of Agriculture. The 

investigators then determined the quartile distribution and assigned a score to each county (0-3 
34

corresponding to each county). Using these scores, the investigators calculated a composite 

score based on all three data sources to give a total score of 0-9. After performing their 

exposure assessment, the investigators used Poisson regression to estimate crude rate ratios 

and adjusted rate ratios, controlling for demographic covariates, at both the county and ADDlevel. 

EPA Review of Results

Hopenhayn-Rich, Stump, and Browning (2002) report that their study did not provide evidence 

that supports an association between atrazine exposure and county level incidence of breast or 

ovarian cancer and further suggest that their data suggest an inverse association between their 

corn acreage metric and ovarian cancer. As with most ecologic studies, however, these results 

should be considered exploratory findings that should be interpreted with caution because 

characteristics at the county-level may not represent individual-level characteristics. 

Additionally, as highlighted by the investigators, there was limited variability in county-level 

drinking water, with weighted mean atrazine concentrations ranging from 0.21μg/L to 1.19μg/L. 

Therefore, the small range drinking water levels may have been insufficient for performing 

county-level comparisons. The authors also indicate that there was a weak correlation between 

corn acreage and atrazine sales, which was unexpected. As such, the study provides 

exploratory information on the aggregate relation between atrazine exposure and breast or 

ovarian cancer in Kentucky.

Sathiakumar N, Delzell E, and Cole P (1996). Mortality among Workers at Two Triazine 

Herbicide Manufacturing Plants. American Journal of Industrial Medicine; 29:143-151.

Health Outcome Study Design Study Population Exposure Reported Association

Mortality Retrospective, pooled 

cohort

Employees from two 

atrazine production plants 

located in Alabama and 

Louisiana

Exposure 

classifications 

based on job 

title and 

function

Overall SMR (95% CI)

“Definite of probable”

87 (75 – 99)

“Possible”

99 (83 – 117)

Cancer SMR (95% CI)

“Definite of probable”

85 (46 – 142)

“Possible”

120 (80 – 172)

Sathiakumar , Delzell , and Cole (1996) conducted a pooled analysis of two previous studies 

(Sathiakumar et al., 1992; Delzell et al., 1989) that examined the incidence of mortality of 

employees in two triazine production plants in Alabama (AL) and Louisiana (LA). Based on 

these two previous studies, Sathiakumar , Delzell , and Cole (1996) excluded employees who 

worked in managerial positions and were not exposed to triazines and obtain employment and 

vital status data on 3,675 male employees and 1,472 male and female employees from the AL 

and LA plants, respectively. The investigators then developed a triazine exposure classification 

system, based on job titles and functions, and classified study subjects’ exposure as either 

“definite,” “probable,” or “possible.” Based on this classification system, disease mortality rates 

of each group were compared with the general population of men in the U.S., in Alabama, or in 

Louisiana by calculating standardized mortality ratios (SMR). 

EPA Review of Results

Sathiakumar , Delzell , and Cole (1996) reported that the overall mortality in the entire cohort of 

AL and LA plant workers was lower than the general U.S. population of men (SMR = 87, 95%CI: 

75 – 99). The investigators also reported that study subjects that performed “definite” or 

“probable” triazine-related work had similar patterns of mortality as the overall population of 
35

workers. These results were statistically imprecise, however, because of the small number of 

deaths for most types of cancer and other causes of death. As a result, the study may have had 

insufficient statistical power to observe differences between the study population and general 

population of the men in the U.S. or respective study states. In addition to this limitation, 

Sathiakumar , Delzell , and Cole (1996) also noted that study subjects were relatively young, 

with only 13% of the total person-years in the 45+ year age group. As such, the study may 

have limited ability to evaluate cancer and other disease with long latency periods. Due these 

limitations, the study findings are inconclusive with regard the nature of the relation between 

occupational (manufacturing) triazine exposure and overall mortality. 

MacLennan PA, Delzell E, Sathiakumar N, Myers SL, Cheng H, Grizzle W, Chen VW, and 

Wu XC (2002). Cancer Incidence among Triazine Herbicide Manufacturing Workers. 

Journal of Occupational and Environmental Medicine; 44(11):1048-1058.

Health Outcome Study Design Study Population Exposure Reported Association

All Cancers, but 

emphasis on prostate 

cancer

Retrospective cohort LA atrazine plant workers 

ascertained from 

employment records and 

followed from 1985-1997

Not Applicable SIR = 114, 95% CI: 83 –

152

SIR = 217, 95% CI: 94 –

428

SIR = 300, 95% CI: 110 –

652

MacLennan, Delzell , Sathiakumar et al. (2002) evaluated the cancer incidence and 

characteristics of a prostate-specific antigen (PSA) screening program among workers at an 

atrazine production plant in St. Gabriel, Louisiana (LA). The study population included 2,045 

plant employees who had lived in LA in or after 1985, worked at the plant for at least six months 

by 1992, and performed a job activity that could have involved contact with triazines or 

precursor chemicals. The study population consisted of three general groups of employees –

company employees, contract production employees, and contract maintenance employees, 

who worked at the company since 1970, 1977, and 1985, respectively. The investigators then 

used the LA Tumor Registry to identify cancer cases during the follow-up period January 1, 

1985 through December 31, 1997. In addition to examining the LA Tumor Registry, the 

investigators also reviewed medical examination records and PSA testing at the LA plant. After 

identifying employees and obtaining medical information, the investigators compared the study 

subjects’ cancer incidence rates with the rates of the general population of the LA industrial 

corridor. This comparison was performed by calculating standardized cancer incidence ratios 

for all employees and then stratified by race, gender, years worked, and employees group. The 

investigators then determined the proportion of male employees that received PSA tests, 

restricting the analysis to only men with no previous prostate cancer diagnosis, and calculated 

the prostate cancer detection rate among active LA plant employees.

EPA Review of Results

MacLennan, Delzell , Sathiakumar et al. (2002) reported that the study population had a total of 

46 cancer cases, compared with 40 expected cases based on the general population in the LA 

industrial corridor (SIR = 114, 95% CI: 83 – 152). With regard to prostate cancer, the 

investigators reported that there was a larger than expected number of prostate cancer cases in 

company employees, although this increase was not statistically significant (SIR = 217, 95% CI: 

94 – 428). When stratified by employment status (active/inactive), however, the investigators 

reported that active employees had a significantly higher number of prostate cancer cases than 

the general population in the LA industrial corridor (SIR = 300, 95% CI: 110 – 652). Based on 

this reported association, the investigators suggest that there was an increased incidence of 

prostate cancer in the study population of LA atrazine plant employees, but also caution that the 

increased incidence was observed primarily in active employees who may have had greater 
36

access to medical screenings than the general population in the LA industrial corridor. As a 

result, medical screening for prostate cancer may explain part of the excess of prostate cancer 

cases in the study population. Additionally, the study did not specifically evaluate individual 

worker’s exposure to atrazine, making it difficult to determine if employees performed job 

functions that resulted in greater atrazine exposure than other employees in the study 

population. In summary, the study provides exploratory information on the incidence of cancer 

in a LA plant where employees may contact atrazine, but suggest the role of cancer screening 

program, detection bias, may influence these findings.

MacLennan P, Delzell E, Nalini S, and Myers S (2003). Mortality Among Triazine 

Herbicide Manufacturing Workers. Journal of Toxicology and Environmental Health, Part 

A; 66:501-517.

Health Outcome Study Design Study Population Exposure Reported 

Association

All Mortality Retrospective cohort LA atrazine plant workers 

ascertained from 

employment records and 

followed from 1970-1997

Not Applicable

160 (95% CI: 66 –

160)

All Cancer SMR (95% 

CI)

329 (95% CI: 40 –

1190)

NHL SMR (95% CI)

MacLennan, Delzell, Nalini, and Myers (2003) conducted a retrospective study of a triazine 

manufacturing plant in Louisiana (LA) to investigate if workers exposed to triazines have greater 

mortality rates than the general population in the LA industrial corridor. The study population 

consisted of individuals who worked at the plant for at least six months by the end of 1992 and 

had worked in a job that could involve potential contact triazines or raw materials used to make 

triazines. The follow-up start years of the study were 1970, 1977, and 1983 for company 

employees, contract production workers, and contract maintenance workers (due to differences 

in employment records), respectively, and the follow-up end date was December 31, 1997. As 

part of follow-up, the investigators used personnel records to identify workers in three employee 

groups and ascertain work history information, including age and demographic information, and 

start/end dates for employment periods. After identifying the study population, the investigators 

determined each subject’s vital status as of December 31, 1997 by reviewing records of the 

plant, Social Security Administration, the National Death Index, and LA and Texas Division of 

Motor Vehicle. After determining the vital status of study subjects, the investigators compared 

the study group’s mortality rates with the general population of the LA industrial corridor using 

standardized mortality ratios (SMRs). 

EPA Review of Results

MacLennan, Delzell, Nalini, and Myers (2003) report that the overall SMR for all diseases was 

72 (95% CI: 57 – 89), suggesting that the study group’s mortality rate was 28% lower than the 

rate for the general population in the LA industrial corridor. With regard to cancer, the 

investigators reported the SMR for all cancers combined was 160 (95% CI: 66 – 160), indicating 

that there was not a significant difference between the rate of cancer deaths in the study group 

and general population in the LA industrial corridor. Similarly, the investigators also reported 

that white males included in this study were observed to have lower mortality rate from cancer 

(SMR = 82 (95% CI: 41 – 147), whereas non-white men and women in the study group had 

elevated SMRs (SMRs = 139 (95% CI: 60 – 274) and 348 (95% CI: 72 – 1018), although none 

of these SMRs were statistically significant. The investigators also reported that there were 

increased deaths of non-Hodgkin lymphoma in the study group (SMR = 329 (95% CI: 40 –
37

1190). The validity of this conclusion is questionable, however, because the SMR estimate is 

non-significant and unstable due to the small number of NHL cases (n<5) in both the study 

group and general population in the LA industrial corridor. Moreover, only 18% of the study 

group was 45 years or older. As a result, the study may have a somewhat limited ability to 

evaluate associations with cancer and other diseases with long latency periods. Based on the 

investigators’ findings, the results suggest that the overall mortality rate in the cohort of LA 

atrazine plant workers was lower than general population in the LA industrial corridor. The 

study provided only limited information on cancer mortality, however, because of the relatively 

small number of cancer deaths that occurred in both the study group and reference population. 

Hessel PA, Kalmes R, Smith TJ, Lau E, Mink PJ, Mandel J (2004). A Nested Case-Control 

Study of Prostate Cancer and Atrazine Exposure. Journal of Occupational and 

Environmental Medicine; 46(4):379-385.

Health Outcome Study Design Study Population Exposure Reported Association

Prostate Cancer Prospective, 

Nested CaseControl

Cases: Workers in 

LA atrazine 

production facility 

who were diagnosed 

with prostate cancer

Controls: Randomly 

selected workers 

from same facility 

who were matched to 

cases on race and 

year of birth

Atrazine exposure 

categories based 

on job title and 

department 

Average exposure: 0.87 (0.46–

1.30)

All subjects (12 cases, 130 

controls)

Duration of exposure: 1.30 (1.06–

1.66)

Cumulative exposure: 1.01 (0.95–

1.07)

Those with≥1 PSA test (10 cases, 

48 controls)

Average exposure: 0.82 (0.36–

1.47)

Duration of exposure: 0.96 (0.71–

1.30)

Cumulative exposure: 0.98 (0.91–

1.05)

Hessel, Kalmes, Smith et al. (2004) performed a follow-up nested case-control study within the 

triazine manufacturing plant cohort noted above (Sathiakumar et al. 1996, MacLennan et al. 

2002 and 2003) to investigate the association between prostate cancer and atrazine exposure, 

while accounting for the potential influence of an on-site prostate screening program. All study 

subjects were males who worked in an atrazine production plant in Louisiana. A total of 14 

prostate cancer cases were identified through the company’s medical screening program (8 

cases among company workers identified in previous study through 1997 and 6 additional cases 

identified in 1998 and 1999). Controls were then randomly recruited and matched to cases 

based on race and year of birth. After recruiting cases and controls, the investigators assessed 

atrazine exposure using a tiered exposure index using (i) time-weighted exposure intensity 

scores, based on five exposure categories and monitoring data that suggested that dust and 

airborne atrazine concentrations in the plant were higher in 1970-1984 relative to 1985-1999, (ii) 

duration of exposure in days, and (iii) cumulative exposure, which was calculated as the product 

of the time-weighted intensity scores and duration of exposure. The investigators then 

performed an analysis to evaluate the role of prostate screening on cancer patterns and used 

logistic regression to evaluate the association between prostate cancer and atrazine exposure.

EPA Review of Results

Hessel, Kalmes, Smith et al. (2004) reported that while cases and controls were comparable in 

their year of hire, controls were more likely to have terminated employment before 1990. As a 

result of this finding, the investigators indicated that cases were more likely to have received the 

PSA testing that was introduced in the plant in the 1990s. As a result, the investigators suggest 
38

that the increased PSA testing alone could have accounted for the increased prostate cancer 

incidence reported in MacLennan, Delzell, Nalini, and Myers (2003). The investigators further 

report that the results suggest that PSA testing may influence the association between atrazine 

exposure and prostate cancer in the plant study. More specifically, the investigators reported 

that duration of atrazine exposure was significantly associated with prostate cancer (OR = 1.30, 

95% CI: 1.06 – 1.66) when study subject PSA testing was not considered. When the 

investigators excluded individuals with more than one PSA test, however, the significant 

association was no longer observed (OR = 0.96, 95% CI: 0.71 – 1.30). Based on this finding 

the results suggest that increased PSA testing may have resulted in the observed association 

between atrazine exposure and prostate cancer.

Mills PK (1998). Correlation Analysis of Pesticide Use Data and Cancer Incidence Rates 

in California Counties. Archives of Environmental health; 53(6): 410-13.

Health Outcome Study Design Study Population Exposure Reported Association

County-level Cancer 

Incidence

Ecologic Individuals living in CA 

counties during 1988-1992

County-level 

Atrazine Usage

Atrazine Usage 

Correlation Coefficients

Hispanic Only

Leukemia – r = 0.40

brain cancer – r = 0.54

testicular cancer – r = 

0.41

Blacks Only

Prostate Cancer– r = 

0.67

Mills (1998) conducted ecologic study to examine the association between county-level cancer 

incidence rates and pesticide use. The study focused on lymphoma, leukemia, soft tissue 

sarcoma, prostate cancer, brain cancer, and testicular cancer and used the California Cancer 

Registry to calculate age-adjusted incidence rates for each county in California during 1988-

1992. Pearson correlation coefficients were then calculated to evaluate the correlation between 

county-level incidence rates and 1993 county-level pesticide usage data on atrazine, 2-4-D, 

Captan, Diazinon, Difocol, and Trifluraline, which is collected by California’s Department of 

Pesticide Regulation.

EPA Review of Results

Overall, Mills (1998) reported that the majority of correlation coefficients calculated implied there 

was no correlation between pesticide use and cancer-incidence rates, i.e., the correlation 

coefficients were low. With regard to atrazine, the Mills reported that there were somewhat 

elevated correlation coefficients between county-level atrazine usage and leukemia, brain 

cancer, and testicular cancer for Hispanics ( r = 0.40, 0.54, and 0.41, respectively). Similarly, 

Mills also reported that the correlation between county-level atrazine usage and prostate cancer 

in black males was r = 0.67. While these correlations are reported in Mills (1998), the author 

also notes that the results should be interpreted due to the limitations of the studies ecologic 

design. Given the limitations of ecologic design for the purpose of informing the true nature of 

the relation between atrazine and these cancer sites, these data not informative. However, EPA 

considers these data in conjunction with other analytic studies performed subsequently. 

Mills PK and Yang R (2003). Prostate Cancer in California Farm Workers. Journal of 

Occupational and Environmental Medicine; 45(3):249-258.

Health Outcome Study Design Study Population Exposure Reported 

Association

Prostate Cancer Nested Case-Control Cases: United Farm 

Worker (UFW) members 

County-level 

pesticide usage data 

Simizine OR (95% 

CI)
39

ascertained through the 

California Cancer Registry

Controls: Randomly 

selected cancer-free UFW 

members, 5:1 frequency 

matched based on age

linked to cases and 

controls based on 

employment records

1.53 (1.02-2.28)

Mills and Yang (2003) conducted a nested case-control study to investigate the association 

between pesticide exposure and prostate cancer in a cohort of farmworkers in California. The 

study population selected for the study was California farmworkers that were members of the 

United Farm Workers (UFW) of America, a largely Hispanic labor union that has existed since 

the mid-1960s. Based on this study population, the investigators identified prostate cancer 

cases using the California Cancer Registry for the years 1987-1999. Controls were randomly 

selected from the remaining cancer-free member of UFW and matched to prostate cancers 

cases on a 5:1 ratio based on age. After identifying cases and controls, the investigators 

performed a pesticide exposure assessment for each study subject using pesticide usage data 

from the California County Agricultural Commission that included farmer reports on the type of 

pesticides applied, location and timing of application, application method, acres treated, and 

total amount of active ingredient applied. Using this pesticide data on 16 different pesticides, 

the investigators calculated county-level annual pesticide usage and linked UFW cases and 

controls to particular years and counties based on UFW employee records. This linked annual 

county-level usage data was then summed for each study subject and weighted scheme was 

applied in which heavier weights were assigned to chemicals with signal words indicating higher 

toxicity (i.e., danger/poison= 3, warning= 2, caution= 1).

EPA Review of Results

Mills and Yang (2003) reported that there was an increased risk of prostate cancer for 

dichlorovos, lindane, heptachlor, and simizine, but none of the other 12 pesticides evaluated in 

their study. Of the four pesticides with positive association, only the OR for simizine was 

statistically significant (OR = 1.53, 95% CI: 1.02-2.28). The investigators also analyzed the 

gradient of risk with use of simizine and the other pesticides. Based on this analysis, the 

investigators reported that the OR estimates increased non-significantly from 1.52 (95% CI: 

1.00-2.34) in Level 2 exposure category to 1.81 (95% CI: 0.93 – 3.53). While the investigators 

reported these positive associations, the study findings should generally be considered 

exploratory. As with several of the previous studies reviewed in this Appendix, the study had 

broad research focus that evaluated the association between prostate cancer and multiple 

different pesticides. Additionally, the investigators also utilized county-level pesticide use data 

to estimate each study subject’s potential pesticide exposure. While this approach takes 

advantage of existing data, it may also introduce uncertainty into the results because countylevel pesticide usage may not accurately reflect individual-level exposure. Further, this study 

provides no information about atrazine, only simazine, a member of the triazine common 

mechanism group; this study was discussed by EPA in the 2003 IRED. 

Schroeder JC, Loshan AF, Baric R, Dent GA, Weinberg CR, Yount B, Cerhan JR, Lynch 

CF, Scuman LM, Tolbert PE, Rothman N, Cantor KP, and Blair (2001). Agricultural Risk 

Factors for t(14;18) Subtypes of Non-Hodgkin’s Lymphoma. Epidemiology; 12(6): 701-

708.

Health Outcome Study Design Study Population Exposure Reported 

Association

Non-Hodgkin’s 

Lymphoma (NHL)

Retrospective, 

Case-Control

Cases: Males aged 30 years or 

older diagnosed with NHL during 

In-Person 

Interview –SelfAtrazine OR (95% CI)
40

March 1981-October 1983 and 

identified through the State 

Health Registry of Iowa.

Controls: Males recruited 

through random-digit dialing, 

Medicare files, and state death 

certificates

Reported 

Pesticide Use

1.7 (1.0-2.8)

Schroeder, Loshan, Baric et al. (2001) indicate that the t(14;18) translocation is common 

somatic mutation that is believed to be an early component step in the pathogenesis of 

particular NHL subtypes and suggest that t(14;18)-positive NHL cases may share a common 

casual factors. Based on this hypothesis, Schroeder, Loshan, Baric et al. (2001) conducted a 

case-control study to examine if t(14;18) subgrouping enhances the ability to identify NHL risk 

factors among participants in the NCI sponsored population-based case control studies 

mentioned above (See Brown et al. 1990, 1993; Cantor et al. 1992; Hoar Zahm 1993, 1993 

(women only)). Among this series of studies, 780 cases were identified in white men aged 30 

years or older, who were diagnosed between March 1981 and October 1983 and identified 

through the State health Registry of Iowa. Similarly, 1245 controls were recruited using random 

digit dialing, Medicare files, and state death certificate files and frequency matched to controls 

based on age, state, and vital status. After selecting cases and controls, the t(14;18) 

translocation status of cases was determined by analyzing archived biological samples. Based 

on this laboratory analysis, the investigators were able to determine NHL cases in which the 

t(14;18) translocation has occurred, i.e, positive cases. The investigators then conducted inperson interviews to collect information concerning sociodemographic characteristics, tobacco 

and alcohol use, hobbies, pets, medical history, and occupational history. Based on the 

interview, participants who were identified as farmers were asked more detailed questions about 

their past use of pesticides and other farm activities. The investigators then used statisticalbased simulation approach (i.e., Expectation-Maximization algorithm) to impute t(14;18) 

subtypes for cases because archived biological samples were not available for 70% of cases. 

After using this algorithm, unconditional logistic regression was used to evaluate the association 

between NHL t(14;18) subtypes and pesticide exposure with NHL.

EPA Review of Results

Given the study sample was derived from the NCI conducted population based case 

control studies, the strengths and weaknesses of these studies apply equally to this 

investigation. Schroeder et al. (2001) reported non-significantly elevated odds of NHL 

among those exposed to atrazine and with the t(14:18) translocation (OR 1.7, 95% CI 

1.0, 2.8), but not among those without the translocation (OR 1.0 (95% CI 0.60, 1.5). 

This is similar to the result reported in association with ever farming: OR for those with 

the t(14:18) translocation 1.4 (95% CI 0.9, 2.3), those without the t(14:18) translocation 

1.0 (95% CI 0.8, 1.4). Authors did not observe an exposure-response trend in these 

data, nor did they observe a link with duration of crop farming or livestock husbandry. 

Other pesticide-NHL associations were also modified by the t(14:18) translocation. 

Many suspected confounding variables were not associated with pesticide use or NHL 

in this study. Authors state the study offers some evidence of heterogeneity of effect by 

presence of the t(14:18) chromosomal translocation in the association between certain 

pesticides, possibly including atrazine, and NHL, however additional studies are needed 

to better understand whether effect modification is present, and present in other study 

populations. Results suggest future epidemiologic analyses may consider measurement 
41

of the t(14:18) translocation, when possible, to clarify the nature of the association 

between the putative exposure and NHL.

Van Leeuwen JA, Waltner-Toews D, Abernathy T, Smi B, Shoukri M (1999). 

Association between stomach cancer incidence and drinking water 

contamination with atrazine and nitrate in Ontario (Canada) agroecosystems, 

1987-1991. International Journal of Epidemiology; 28:836-840.

Health Outcome Study Design Study Population Exposure Reported Association

Cancer of the 

stomach, colon, 

ovaries, bladder, and 

Non-Hodgkin’s 

Lymphoma

Ecologic 40 Ecodistricts in Ontario, 

Canada during 1987-1991

Ecodistrict-level 

water contamination 

and agricultural 

practice data

-Atrazine and Stomach 

Cancer

Positive Association:

-Atrazine and Colon Cancer

Negative Association:

Van Leeuwen , Waltner-Toews D, Abernathy et al. (1999) conducted an ecologic study 

to investigate if there was an association cancer and atrazine and/or nitrate 

contamination and pesticide use practices during 1987-1991. The investigators used 

the Ontario Cancer Registry to estimate cancer incidence ratios in 40 ecodistricts in 

Ontario during 1987-1991. Using the Ontario Cancer Registry, age and sex-specific 

standardized incidence rates were estimated for cancer of the stomach, colon, ovaries, 

bladder, and Non-Hodgkin’s Lymphoma. The investigators evaluated population-level 

exposure in each ecodistrict using water contamination available through the Ontario 

Drinking Water Surveillance Program and the Ontario Farm Groundwater Quality 

Survey. Based on these data sources, weighted average atrazine and nitrate levels 

were calculated based on population served within each ecodistrict. In addition to water 

contamination, the investigators evaluated land-use data on pesticide, fertilizer, and 

manure applications that was available through the Canada Census of Agriculture and 

Survey of Pesticide Use in Ontario. The association between ecodistrict incidence of 

cancer and atrazine and nitrate levels was then evaluated using least squared 

regression analyses.

EPA Review of Results

As an ecologic analysis, this study aided hypothesis generation and is noted by several 

authors of analytic study designs as a rationale for their investigation. Independently, 

however, the study design does not offer evidence as to the nature of the association 

between triazine and various cancer sites evaluated. The relation with gastric and colon 

cancers is noted.

APPENDIX B.4: REVIEW OF AGRICULTURAL HEALTH STUDY (AHS) NESTED 

CASE-CONTROL ANALYSES

Background

Since 2003 there have been six nested case-control analyses within the AHS which 

evaluated use of a number of agricultural pesticides, including the herbicide atrazine, in 

association with specific anatomical cancer sites. These include investigations of 

prostate (Alavanja et al. 2003), lung (Alavanja et al. 2004) colorectal (Lee et al. 2007)
42

breast (among female spouses and female applicators in the AHS) (Engel et al. 2005)

pancreatic cancers (Andreotti et al., 2009) as well as cutaneous melanoma (Dennis, 

Lynch, Sandler, & Alavanja, 2010). Concerning the evaluation of cutaneous melanoma 

and lung cancer with atrazine use, authors stated they did not observe any evidence of 

an exposure-response trend, and, therefore, did not report atrazine-specific risk 

estimates. For this reason, these studies are not further discussed in this appendix. In 

combination, these studies provide an important database of epidemiologic evidence 

pertaining to atrazine carcinogenicity. However, it is important to note that these studies 

were hypothesis-generating in nature and did not posit a specific hypothesis or 

biological mechanism as to the carcinogenic mode of action of atrazine per se. 

Given the similarity in design and methods across these investigations nested within the 

AHS, they are considered together in this Appendix. Table B-3a summarizes these 

study results. A general overview of the AHS including study design and methods, as 

well as specific case-control study results is presented. EPA’s summary and review of 

these studies is also presented below.

Brief Overview of Design and Methods

The Agricultural Health Study (AHS) is a large, prospective cohort study comprised of 

private and commercial pesticide applicators in Iowa and North Carolina. The study 

includes 57,310 licensed pesticide applicators, comprising 52,394 private applicators 

and 4,916 commercial applicators, as well as 32,346 spouses of pesticide applicators. 

Researchers successfully recruited 82% of the target population into the AHS cohort 

which represents a high recruitment rate for an epidemiologic study. While farmer and 

pesticide applicator participants in the AHS are generally healthier than the overall U.S. 

population, AHS participants have a higher rate of some cancers including prostate, 

ovarian, lip, multiple myeloma (Alavanja et al., 2005; Koutros et al., 2010). Lower rates 

of smoking and alcohol use, and the physically demanding nature of the occupation are 

health protective factors in the AHS population, and pesticides, viruses (animals), 

bacteria, sunlight, and other non-pesticide chemicals may be putative risk factors for 

carcinogenesis among these farmers. 

Pesticide applicators must obtain a license from the state to purchase and use 

restricted-use pesticides. Participants in the AHS were enrolled into the study at county 

pesticide licensing facilities and were asked to complete a 21-page written enrollment 

questionnaire. Enrollment occurred over a period of 4-years, December 13, 1993 to 

December 31, 1997 (“Phase I”). The Phase 1 “enrollment” questionnaire solicited 

information concerning types of agricultural crops and livestock produced, types of 

pesticides used, pesticide application methods, use of personal protective equipment, 

and, lifestyle factors such as smoking and alcohol intake. A portion of the cohort also 

completed a “take-home” questionnaire (~40%) in which additional lifestyle (e.g., diet) 

and chemical exposure information (i.e., an additional 28 chemicals) was ascertained. 

To determine case- and vital-status, cohort members were linked to state cancer 

registries in Iowa and North Carolina and the state death registries and the National 

Death Index, respectively. Linking was accomplished through use of social security 
43

number, first and last name, date of birth, and gender. Study participants who were 

alive but no longer residing in either study states were identified through the Federal 

Internal Revenue Service address file, motor vehicle registration records, and the 

restricted-use pesticide license and certification records of the departments of 

agriculture in Iowa and North Carolina. Less than 2% of the cohort has been “lost-tofollow-up,” i.e., can no longer be located for purposes of the study. This is a very low 

percentage lost to follow-up, reducing the chance of selection bias in this prospective 

cohort study.

To measure atrazine exposure, AHS researchers considered three exposure metrics: (i) 

whether participants ever used the herbicide; (ii) the cumulative exposure days (the total 

number of exposure days per year, and total number of years in lifetime); and, (iii) an 

intensity weighted cumulative exposure metric. Exposure information was collected via 

self-report questionnaire responses. The “ever used” metric dichotomized atrazine 

exposure into ever/never categories where “ever used” reflects at least time use during 

the working lifetime. The lifetime exposure-days metric was calculated by taking the 

product of the total number of years atrazine was applied and the number of days per 

year atrazine was applied. The intensity-weighted lifetime exposure day metric 

includes: the frequency and duration of application (lifetime exposure days), application 

methods, mixing and equipment repair status, and use of personal protective 

equipment. These factors were weighted to reflect the intensity of the exposure based 

on monitoring data available in the published literature. Methods of pesticide exposure 

assessment used in the AHS have been reviewed extensively and shown to have high 

reliability and validity (Blair et al., 2002; Blair et al., 2011; Hoppin, Yucel, Dosemeci, & 

Sandler, 2002). 

Results of Nested Case-Control Analyses

Prostate Cancer

Alavanja et al. (2003) evaluated prevalence of pesticide usage between cases of 

prostate cancer (n=566) diagnosed through 1999, and AHS cohort members without a 

prostate cancer diagnosis (n=54,766). In this study, researchers examined 47 different 

pesticides in association with incident prostate cancer, including atrazine. The odds of 

prostate cancer comparing ever-users of atrazine to never users did not differ from the 

null (OR 0.94, 95% CI 0.78, 1.14). Across quintiles of cumulative pesticide exposure 

days, no evidence of a trend for atrazine was observed (p for linear trend 0.34), and 

odds ratios were not elevated: 1.0 (reference), 1.02 (95% CI 0.79, 1.31), 0.91 (95% CI 

0.71, 1.18), 0.89 (95% CI 0.65, 1.23), 0.82 (95% CI 0.54, 1.25), and 0.97 (95% CI 0.63, 

1.48). Further, there was no evidence of heterogeneity of results by presence of a firstdegree family history of prostate cancer; the interaction rate ratio was 1.52 (95% CI 

0.88, 2.62), p for interaction 0.13). Researchers were able to control for age, race and 

family history, in addition to use of other correlated pesticides and confounding 

variables in the analyses presented. Strengths of this study include the ability to adjust 

for prostate cancer risk factors as well as other potentially confounding variables, the 

sample size and ability to investigate atrazine exposure using several different exposure 

metrics, including the investigation of an exposure-response trend. In addition, as a 
44

nested study within the prospective cohort, issues regarding temporality of the 

exposure-disease relation are reduced. Overall, authors did not observe evidence of a 

statistical association between atrazine use and prostate cancer.

Breast Cancer

Engel et al. (2007) evaluated the risk of breast cancer in association with several 

pesticides including atrazine among female spouses in the AHS. Both direct and indirect 

pesticide exposure was estimated for wives based upon applicator husband’s 

questionnaire responses. There were 309 new cases of breast cancer diagnosed 

through 2000 among 30,454 female spouses. Overall as a group these women as a 

group experienced fewer cases of breast cancer than the general population of the 

respective AHS study states (IA and NC). Concerning atrazine use, women who 

reported directly applying atrazine ever in their lifetime were not observed to have an 

increased risk of breast cancer (OR 0.70, 95% CI 0.40, 1.2), however only 11 atrazine 

exposed breast cancer cases were included in the analysis (Engel et al., 2005). 

Similarly, among women whose husband’s reported ever-using atrazine as compared to 

women who never used atrazine, no increased risks were observed (OR 1.1, 95% 

CI0.70, 1.6). Analyses were adjusted for age, race and state of residence as other 

breast cancer risk factors were not confounding variables in this association. Authors 

attempted to stratify by state of residence, but there were too few direct users of 

atrazine in North Carolina, one of the two AHS study states, to perform this analysis. 

Authors did not report a difference in the indirect exposure to atrazine and breast cancer 

association by state of residence. Authors reported that overall a woman’s risk of breast 

cancer increased with closer residential home proximity to an agricultural field, however 

this finding is not specific to atrazine use. Strengths of the study include the quality of 

the outcome assessment, ability to adjust for several potential confounding variables, 

and study design which assures exposure precedes disease. However, the authors 

were only able to investigate ever-use of atrazine at this time, and no exposureresponse information was attempted. Overall, these data are not supportive of an 

association between atrazine use and breast cancer risk.

Colorectal Cancer

Lee et al. (2007) explored the association between use of many different pesticides and 

the odds of being diagnosed with colorectal cancer (analyzed separately as colon 

cancer, rectal cancer and colorectal cancer (grouping cancers of the colon and rectum). 

In a large nested case-control analysis within the cohort (n=56,813), investigators 

compared pesticide use including atrazine between 305 colorectal cancer cases, and all 

other non-colorectal cases in the AHS cohort who met the eligibility criteria. Cancer 

cases diagnosed through 2002 were included in the analysis. Overall, among the 50 

pesticides evaluated, researchers observed few instances of an association between 

pesticide use and this cancer. Concerning atrazine, authors did not observe evidence of 

an association between ever use of atrazine and colorectal cancer (OR 0.9, 95% CI 

0.70, 1.2), colon cancer (OR 0.80, 95% CI 0.60, 1.1), or rectum (OR 1.2, 95% CI 0.70. 

2.0), adjusting for age, smoking and total days of use of all pesticides. There were over 

30 atrazine exposed cancer cases in each analysis. In this investigation, authors only 
45

reported the atrazine ever-use exposure metric, as no evidence of an atrazine 

exposure-response trend was observed. Authors state that the reliable method of 

lifetime exposure assessment, high validity in the method of cancer ascertainment, the 

use of appropriate measurements of and adjustments for relevant confounders 

(including use of other pesticides), are strengths of this study. Overall, this study did not 

observe evidence of an association between atrazine use and colorectal cancer.

Pancreatic Cancer

Andreotti et al. (2009) compared pesticide use, including atrazine, between 93 

pancreatic cancer cases and 52,721 non-cancer private applicators and 29,782 

spouses of applicators. Cancer cases were diagnosed through 2004. Adjusting for age, 

smoking, diabetes status and applicator type, authors did not observe evidence of a 

statistical association with ever use of atrazine (OR 0.70, 95% CI 0.40, 1.2). Further, 

authors evaluated exposure response trends by comparing never users with those in 

the lower- and upper-half of the exposure distribution (intensity-weighted exposure days 

split at the median among controls) and did not observe evidence of a difference in 

odds by exposure category (1.0, lower OR 0.80, 95% CI 0.50, 1.5), upper OR 0.60, 95% 

CI 0.30, 1.2), nor did researchers report evidence of a trend (p for trend 0.12). Authors 

could not adjust for a family history of pancreatic cancer due to lack of specific 

information regarding family history of this type of cancer. Family history is a strong risk 

factor for pancreatic cancer. Authors posited no a priori association between atrazine 

use and pancreatic cancer, and authors did not observe evidence of a link between use 

of this herbicide and this anatomical cancer site. Strengths of this investigation are the 

relatively large sample size and number of exposed cases (n≥15) for a study of 

pancreatic cancer, a rare cancer outcome in the population. In addition, the prospective 

nature of the study design ameliorates concerns regarding the temporality of the 

exposure-disease relation, and the large amount of information collected through the 

AHS allowed investigators to investigate and statistical control for a number of 

confounding variables in the analysis. As a hypothesis-generating analysis, and lack of 

biologically plausible connection between atrazine and pancreatic cancer, or lack 

thereof, these data are considered preliminary at this time. The current study does not 

suggest an association between atrazine use and pancreatic cancer exists. 

Strengths and Weaknesses of AHS Studies

The AHS includes both strengths and weaknesses. The large sample size and sufficient 

statistical power to investigate the potential association between atrazine use and 

several cancer sites including prostate cancer is a strength of the study. In addition, 

given the prospective study design the potential for recall bias (differential exposure 

measurement error) is eliminated, as pesticide exposure information was collected prior 

to the identification of disease. Exposure measurement error exists in this study (Blair et 

al., 2011), however it is likely non-differential in nature and would attenuate, and not 

falsely inflate, measured risk estimates. This is particularly true for two-level exposure 

metrics. Selection bias is considered of low potential as very few participants have been 

lost to follow-up in this cohort (i.e., few participants dropped out of study or were unable 

to be followed through other means). In this cohort, cancer cases were ascertained 
46

through linkage with state cancer registries, and include histopathological confirmation 

as well as information as to stage and grade of cancer at diagnosis. High quality 

outcome ascertainment reduces the potential for outcome measurement error. The AHS 

collects a vast amount of information for use in statistical analysis including prostate 

cancer risk factors such as age, race and family history of prostate cancer; cancer risk 

factors such as smoking and alcohol use; and, use of other correlated pesticides. Lastly, 

the AHS exposure measurement tools have been illustrated to be valid (Hoppin et al., 

2002) and reliable (Blair et al., 2002), and provide a quantitative measure of pesticide 

exposure over the working lifetime.

In combination, these studies provide an important database of epidemiologic evidence 

pertaining to atrazine carcinogenicity. However, it is important to note that most of 

these studies are hypothesis-generating in nature and did not propose a specific 

biological mechanism as to the carcinogenic mode of action of atrazine per se. The 

recent evaluation (Beane Freeman et al., 2011) was able to test hypotheses related to 

prostate, breast, ovarian and NHL as these sites have been previously suggested to be 

related to atrazine use. This study extends research from the cohort initially reported in 

2004 (Rusiecki et al., 2004). These results are discussed within EPA study reviews 

included in Appendix B-5. 
47

Table B-4a: Summary of AHS Nested Case-Control Study Results

Cancer Endpoint Sample Size Exposure 

Assessment

Adjustment Risk Ratio

Prostate 566 cases, 

54,766 controls;

self-reported use 

atrazine 

age, family 

history of 

prostate cancer

ever-use 

atrazine: OR 0.94 

( 95% CI 0.78-

1.14) (OR per 

quintile LTED 

~1.0, p-trend, 

0.34)

Lung 57,284 pesticide 

applicators and 

32,333 spouses; 

300 Lung cancer 

cases

self-reported use 

atrazine 

n/a no exposureresponse trend 

observed 

triazines/atrazine; 

no results shown

Breast 309 cases, 

30,454 controls

self-reported use 

atrazine 

age, race OR 0.70 (95% CI 

0.4, 1.2) among 

wives who 

directly apply

Colorectal 305 cases, 

56,813 controls

self-reported use 

atrazine 

Age, smoking, 

state, total days 

of pesticide 

application 

among all 

enrolment 

applicators. 

Colorectal: everuse atrazine 

OR=0.9 (95% CI 

0.70, 1.2); Colon

OR=0.8 ( 95% CI 

0.60, 1.1); 

Rectum OR=1.2 

(95% CI 0.70, 

2.0)

Pancreatic 93 incident 

pancreatic 

cancer cases, 

82,503 cancerfree controls

self-reported use 

atrazine 

age, smoking, 

diabetes, 

applicator type, 5 

most highly 

correlated 

pesticides

OR 0.70 (95% CI 

0.4-1.2)

Cutaneous 

Melanoma

150 incident 

melanomas 

among 24,704 

applicators

self-reported use 

atrazine 

n/a no exposureresponse trend 

observed 

triazines/atrazine; 

no results shown
48

APPENDIX B.5: REVIEW OF ATRAZINE CANCER EPIDEMIOLOGY STUDIES 

PUBLISHED SINCE 2003

Beane-Freeman et al. (2011). Atrazine and Cancer Incidence Among Pesticide 

Applicators in the Agricultural Health Study (AHS)

Researchers with the Agricultural Health Study (AHS) recently updated their previous 

atrazine cohort analysis (Rusiecki et al., 2004) with approximately twice as many cancer 

cases (Beane Freeman et al., 2011). The recent evaluation included 3,146 cases of 

cancer whereas the preliminary atrazine cohort study included 1,785 cancer cases. In 

addition, as compared to the initial analysis Beane-Freeman et al. (2011) included use 

of an updated exposure algorithm that increased the protective factor for use of 

chemical resistant gloves, and weighted more heavily the exposure potential for use of 

broadcast spray application methods, among other changes noted by authors.

In their updated analysis, Beane-Freeman et al. (2011) included 53,663 private and 

commercial pesticide applicators, after excluding participants due to prevalent cancers 

and missing information. Authors assigned atrazine exposure categories based upon all 

cancer cases combined, and reported results for atrazine-cancer associations for which 

20 atrazine exposed cancer cases were observed. In addition, based on a priori

information, authors also evaluated the relation between atrazine and breast and 

ovarian cancers. Authors were able to adjust for age, race, gender, smoking, alcohol 

use, education, state of residence, family history of specific cancers, applicator type 

(private or commercial), and ever-use of other pesticides highly correlated with atrazine 

use including dicamba, cyanazine, metolochlor, trifluralin, and 2,4-

dichlorophenoxyacetic acid (2,4-D). 

Concerning the evaluation of both lung and bladder cancer, authors further adjusted for 

smoking using various other metrics (e.g., pack years smoked). In the evaluation of both 

breast and ovarian cancers, authors used exact methods to calculate the confidence 

bounds as the number of female applicators who were exposed to atrazine and 

diagnosed with these cancers was small. Because the lowest exposed group, and not 

the no exposed group, was more similar to the upper quartiles of atrazine exposure, 

authors utilized the lowest exposed category as the referent. Authors stated that results, 

were similar using either reference group. Additionally, authors stratified by state and 

applicator type to learn whether evidence of effect modification by these factors was 

present. 

Authors noted that while more private than commercial applicators reported using 

atrazine, the number of exposure days was greater among commercial applicators. 

Overall, authors observed no association between atrazine use and all cancers 

combined, or with either prostate, or lung cancers which are among the most common 

cancers in the population. Among 29 male cases of thyroid cancer, authors observed 

some evidence of an association with both lifetime days (LTED) of use and intensityweighted lifetime days (IWED) of use, but no linear trends across quartiles of atrazine 

exposure (p for trend LTED 0.61, IWED 0.08). Comparing the upper-quartile to the 

lowest quartile, elevated odds of thyroid cancer were observed for both LTED (OR 2.32, 
49

95% CI 0.66, 8.22), and IWED (OR 4.84, 95% CI 1.31, 17.93). Authors also noted that 

adjustment for body mass index (BMI), a known risk factor for thyroid cancer, did not 

alter the inferences for the atrazine-thyroid cancer association. As noted by authors, 

there are several cautions to consider in the interpretation of these data including: the 

test for linear trend was not significant; the exposure-response trend was not monotonic 

in nature; the confidence bounds were wide and included 1.0 for some quartiles; and 

there were less than five exposed cases in some exposure groups. In addition, there 

were too few exposed cases to examine atrazine-thyroid cancer by gender, only one 

female atrazine exposed case of thyroid cancer, by state or by applicator type. This is 

the only point estimate identified in the atrazine cancer epidemiology literature for 

thyroid cancer.

Authors also investigated the association between atrazine exposure with breast and 

ovarian cancers among female pesticide applicators enrolled in the AHS. However, 

because there are few female cancer cases in the AHS, investigators were only able to 

consider ever-use of atrazine in association with these cancer outcomes; authors did 

not perform an exposure-response evaluation. Among 36 breast cancer cases in the 

cohort, authors observed a slight statistically association with atrazine (OR ever use 

atrazine 1.14 (95% CI 0.47, 2.50), compared to never users of atrazine), however 

results were not significant and confidence bounds was wide. Results were similar 

comparing the upper- and lower- exposed groups, divided at the median, according to 

the authors. Among nine cases of ovarian cancer, authors did observe evidence of an 

association: OR ever use atrazine 2.91 (95% CI 0.56, 13.60). There were four atrazine 

exposed ovarian cancer cases, and five never users of atrazine included in this 

analysis; authors stated that all nine of the cases reported days of atrazine use that 

were within the lower half of the exposure distribution, i.e., below the median (p50). 

Authors adjusted for age only in both the breast and ovarian cancer analysis, as other 

cancer risk factors were not confounders in the association with atrazine. 

Additionally, authors also observed that there were over 300 incident cases of 

lymphohematopoietic cancers diagnosed between enrollment and 2007 among 36, 357 

atrazine users. The authors observed no evidence of an association with any 

lymphohematopoietic cancer, including non-Hodgkin lymphoma (NHL), or NHL sub-type 

using with the cumulative exposure measure of the intensity-weighted exposure 

measure. Across quartiles of atrazine exposure and within specific 

lymphohematopoietic cancer sub-types, risk estimates with atrazine did not appreciably 

differ from the null. Specifically, confidence bounds included 1.0 in each comparison, 

and tests of linear trend were not statistically significant. In addition, authors did not 

observe evidence of interaction (supra-additive effects) between atrazine exposure and 

other pesticides (alachlor, carbofuran, diazinon) as noted in other population-based 

studies (De Roos et al., 2003). 

Concerning other anatomical cancer sites, some evidence of significant or borderline 

significant putative (esophageal, oral cavity) as well as protective (pancreatic, laryngeal) 

associations with atrazine were observed. However, given the lack of a priori

hypothesis, multiple statistical comparisons made within the study, and lack of biological 

plausible link, authors did not report these as notable results.
50

Beane-Freeman et al. (2011) observed some evidence of an association between 

atrazine and thyroid as well as ovarian cancer, but overall there was no evidence of an 

association with all cancers combined, or with most of the specific anatomical cancer 

sites evaluated. Authors noted that both thyroid and ovarian cancers are hormonallyresponsive, endocrine or reproductive system cancers, and given the understood mode 

of action of atrazine, neuroendocrine effects, these statistical associations were 

plausible. However, limited evidence in the experimental literature, as well as within 

other published epidemiology studies, suggest an association between atrazine and 

these cancer sites. Authors note that chance cannot be excluded as a rationale for 

these findings, however a limited number of other epidemiology studies have 

documented a possible link with ovarian cancer. EPA identified no other investigation of 

a link with thyroid cancer however. Concerning the ovarian cancer finding, as stated 

above, authors were only able to evaluate ever-use of atrazine in relation to this cancer 

site; no exposure-response analysis could be performed. Factors that support the 

association include the relative strength of the association, possible biological role, and 

lack of significant biases in the analysis including selection bias, or confounding bias, or 

temporal bias are strengths of this study. EPA notes that no specific mechanism for 

atrazine in the etiology of these cancers has been identified. The thyroid cancer finding 

requires replication and further study, as this point estimate is the only one available in 

the literature to EPA’s knowledge.

EPA Review

It is notable that authors observed no evidence of an association with prostate cancer in 

this study. This investigation, similar to the initial atrazine cohort analysis by Rusiecki et 

al. (2004), was sufficiently statistically powered to observe an association, if one 

existed. Similarly, authors did not observe evidence of a link with lung, breast (ever-use 

of atrazine only), or colorectal cancer, among the most common cancers in the U.S. In 

addition, the lack of evidence of a statistical association with leukemia or lymphomas, 

including several sub-types of these cancers, is notable given there was some weak 

evidence of a role for atrazine in these cancers published earlier in the literature, and 

reviewed by EPA within the Chapter.

Strengths and limitations of the AHS have been noted elsewhere (Appendix B-4). 

Briefly, the large sample size and prospective nature of the study, as well as the 

extensive exposure measurement and data collection allow robust epidemiological 

investigation of pesticide in association with atrazine. In addition, study design and 

methods significantly reduce the possibility for several systematic biases including 

selection bias (low loss to follow up rates), confounding bias (demographic, cancer risk 

factors, and use of other pesticide information available for use in statistical analysis), 

and high-quality retrospective exposure analysis reduces the potential for exposure 

measurement error. However, regarding exposure measurement error, authors 

acknowledge this likely occurred and have performed evaluations to determine the 

extent of the influence of this bias on risk estimates (Blair et al., 2011). Weaknesses 

include utilization of ever-use of atrazine exposure metric in the breast and ovarian 

cancer analysis, possibility of exposure measurement error which likely, but not always, 

results in non-differential exposure misclassification, and the possibility of unmeasured 
51

confounding variables in the estimation of this association. Further, the study is 

comprised of demographically white, male pesticide applicators. Therefore, information 

concerning the nature of the association between atrazine and cancer in other 

populations is also needed. 

Overall, the researchers observed some evidence of a possible association between 

atrazine and ovarian and thyroid cancers; however lack of an exposure-response 

analysis and small number of exposed cases as well as the lack of other corroborating 

information in the epidemiologic literature limit the ability to make a determination of 

causality at this time. Concerning other anatomical cancer sites inkling prostate, lung, 

colorectal, breast (ever-use of atrazine only), and lymphohematopoietic cancers 

including NHL and NHL sub-types, authors did not observe evidence of an association 

with lifetime use of atrazine in this cohort. 

Carreon et al. 2005. “Gliomas and Farm Pesticide Exposure in Women: The Upper 

Midwest Health Study.”

Ruder et al. 2004. “Gliomas and Farm Pesticide Exposure in Men: The Upper Midwest 

Health Study.”

Authors performed a population-based case control investigation of the association 

between pesticide exposure and gliomas, a type of brain cancers, among participants 

living in the upper mid-western states of Iowa, Michigan, Minnesota, and Wisconsin. 

Authors separately reported results for men (Ruder et al. 2004) and women (Carreon et 

al. 2005), but both reports emanated from the same study. The study by Carreon et al. 

(2005) provides complete detail regarding study design and methods. Therefore, these 

studies are considered together herein. 

Authors performed the study within several counties among the four study states with 

high agricultural use, and low population density, i.e., less than 250,000 persons within 

major population areas. Researchers included histopathologically confirmed glioma 

cases diagnosed between 1995-97 through rapid case ascertainment (case identified in 

the database within 3 weeks of diagnosis). Cases were identified through interaction 

with medical offices or neurosurgeons; authors reported that case ascertainment rates 

ranged from 65% to 86% across the four study states. Authors did not exclude 

participants who had a previous cancer diagnosis. Controls were women without a 

glioma diagnosis. Cases and controls were frequency-matched 1:1.5 on 10-year age 

categories, based upon the distribution of glioma cases in the state in previous years 

(expected distribution of cases based upon past population prevalence). Cases and 

controls resided in the same state, but not necessarily in the same counties within the 

state. Researchers identified controls through either state DMV (ages 18-65), or state 

health care files (ages 65-80). 

Upon receipt of physician consent, cases first received a letter of introduction, followed 

by an in person interview. Those who refused to participate were asked to complete a 
52

short questionnaire collecting information on relevant demographics. Women were 

asked whether they lived or worked on a farm, and if so when and how long. Among 

women who indicated they directly applied pesticides, a list of pesticides was provided. 

Researchers restricted the period of exposure assessment through 1993, as cases 

were diagnosed 1995-97 and pesticide exposures within 2 years of diagnosis were 

likely not relevant to the development of the disease, if an association exists. Authors 

used a previously validated questionnaire to collect information concerning pesticide 

exposure. Upon completion of the self-administered questionnaire, a trained industrial 

hygiene professional reviewed the responses, and participants were contacted again if 

additional information was needed. Researchers used a publicly available (NIOSH) 

database to identify the active ingredients associated with the reported trade names 

from the list provided to participants. Authors utilized the same information collection 

methods between cases and controls including a standardized interview, intermittent retraining of interviews within the study period, and blinding of interviews to the study 

hypothesis. If selected cases were unable to participate due to death or incapacitation, 

a first-degree relative was sought as a proxy respondent.

The final study sample included 341 cases and 527 controls which was 90% and 76% 

of the eligible cases and controls respectively. Most of the participants were nonHispanic white (97%). All statistical analyses were adjusted for age and state (matching 

variables). Analyses suggest the control series was comparable to the general 

population; cases were selected among all cases in the study area and ascertainment 

rates were moderate to high across the study states (65-82%). Forty-three percent of 

cases and 2% of controls responded by proxy. Cases were younger than controls and 

lived on a farm for a shorter period of time. Women were less likely to apply pesticides, 

but more likely to launder pesticides in the overall study sample. 

Authors reported little evidence of an association between triazine or atrazine use and 

gliomas. The results include: ever-use of an herbicide, OR 1.0 (95% CI 0.6, 1.5); 

triazine OR 1.0 (95% CI 0.6, 1.7); and atrazine OR 1.1 (95% CI 0.7, 1.8). The risk 

estimate for atrazine excluding proxy respondents was slightly higher, but did not reach 

statistical significance. Similarly, authors reported no evidence of an association 

between triazine use and glioma among men in a separate publication (Ruder et al. 

2004). 

EPA Review

Authors performed a hypothesis-generating evaluation of pesticide exposure in relation 

to glioma diagnosis. There are many strengths to this study. Investigators were able to 

compare characteristics of those included and excluded from the study and assess

potential systematic bias. Through design, authors modeled exposure information that 

preceded disease diagnosis, use of a 2-year lag in pesticide exposure. Authors used 

several quality assurance and control methods including standardized interview 

techniques, as well as interviewer training and blinding to study hypothesis to reduce 

observer bias. However, there are some limitations to consider including differential 
53

recruitment rates between cases and controls (90% and 76% between cases and 

controls), and the differential use of proxy respondents between cases and controls. 

These differences may lead to systematic biases in the study. While authors used 

expert judgment to assign exposure category which is an improvement over other 

commonly used methods, some exposure measurement error likely occurs. 

Selection bias in a case-control study could occur if the control series is not a good 

approximation of the population from which the cases arose. In this study, authors 

acknowledged some under-ascertainment of cases when compared to state cancer 

registries (14-35% under-ascertainment). Given the difficulty discerning symptoms of 

glioma, e.g., disrupted mental functioning, from other common morbidities of older age, 

there is a known under-ascertainment of glioma among the elderly. Authors did not 

comment as to the possible ways included and excluded cases compared. Differences 

between included and excluded cases could include dissimilarities in access to health 

care, health seeking behaviors, severity of symptoms possibly related to progression of 

tumor or severity. If these differences were related to pesticide exposure, a selection 

bias could have occurred, however this possibility has not been assessed.

Authors note that controls are similar to the underlying general population on several 

important characteristics indicating controls are a representative sample of the general 

population. However, cases may not be representative of all cases. 

It should be noted that brain cancers are a diverse group of brain cancers. In this study, 

authors restricted case selection to histopathologically confirmed cases of glioma. The 

homogeneity in case definition likely resulted in improved precision in the risk estimates 

presented, however there are sub-types of glioma. Authors did not restrict eligibility to 

only primary cancers, therefore secondary cancers may have been included in this 

study. Authors did not comment as to the possible effect of including primary and 

secondary cases in the study, however this decision may have obscured true 

associations.

Recall of pesticide exposure information over a lifetime is always a challenge. When 

studying brain tumors (glioma), it is possible that this recall is influenced by the disease, 

i.e., those with the disease would have a more difficult experience recalling exposure. 

Among 43% of the cases and 2 % of controls, family proxies were used to provide 

pesticide exposure recall. Non-differential recall bias is likely to have occurred, thereby 

reducing the magnitude of the risk estimate toward the null value. In addition, as authors 

acknowledge, given the large proportion of proxy respondents a differential recall bias 

cannot be completely excluded as an explanation for the findings, however the 

comparability of results between the direct respondents and the proxy and direct 

respondents grouped together somewhat lessens this concern. Overall, authors did not 

observe evidence of an association between atrazine and glioma in this hypothesisgenerating study, however the potential influence of systematic biases including 

information, and possibly selection bias, is not discussed by authors. The study 

provides insufficient information to assess whether an association exists.

De Roos et al. 2003, “Integrative assessment of multiple pesticides as risk factors for 

non-Hodgkin’s lymphoma among men.” [Occup Environ Med 2003;60:e11] 
54

Summary

Authors performed a pooled analysis of three population-based case control studies 

conducted by the National Cancer Institute in the Midwestern United States in the mid1980’s (See Appendix B-3) to investigate the link between pesticide use and nonHodgkin lymphoma (NHL). Analyses were largely hypothesis-generating and 

exploratory in nature, however authors note previous research regarding potential 

association between both lindane and atrazine with NHL cases as a priori hypotheses of 

interest in the pooled analysis.

Specific observations (data points) from three population case-control studies were 

“pooled” in this one analysis of the association between pesticide use and NHL. 

Hierarchal regression techniques use available information (pesticide class, functional 

group, carcinogenic classification) to estimate a “prior” distribution of the pesticide-NHL 

risk relations, and adjust observed associations (results of pooled analysis) toward the 

“prior” distribution, thereby using other information to inform the true shape of the 

exposure-response curve in the current evaluation using these techniques. Hierarchal 

regression can add precision and accuracy to risk estimates, reflective of the quality of 

the “prior” distribution.

Although each of the three population-based case-control studies reflected slightly 

different enrollment criteria, outcome ascertainment, exposure assessment methods, 

among other differences, authors determined it was appropriate to pool the data. As 

discussed briefly in Appendix B-3, cases were ascertained through either hospitalbased registries or state cancer registries in the mid-1980s. For this study, cases 

ascertained through the three afore mentioned studies, were matched to geographicspecific population controls on age, race, gender and whether a proxy respondent was 

used (if selected case or control had died). Authors excluded women (too few) and 

those who used pesticides less than 18 years of age only (no adult use). Only 

pesticides reported across all three studies, and for which at least 20 participants 

reported using were included. Participants with missing information for any of the 

pesticides included in the pooled study were also excluded. After exclusions, 650 NHL 

cases and 1933 matched controls were selected into the pooled analysis.

Based upon responses in the three studies and the degree of missing pesticide 

exposure data, authors selected 47 pesticides to be part of the hierarchal, multivariable, pesticide adjusted analyses. Logistic regression analyses were adjusted for 

age, geographic area. Hierarchal regression techniques included retaining the 

maximum likelihood estimates (MLE) of the pesticide-NHL logistic regression, and 

regressing those estimates on the “prior” distributions of NHL risk in association with 

specific pesticides. “Prior” distributions were defined considering pesticide class, 

functional group and cancer classification. These adjusted priors were then regressed 

on the coefficients from the first (logistic) regression model, to obtain an hierarchal 

adjusted estimate of specific pesticide- NHL combinations, while controlling for all other 

(47) pesticides and assuming a certain parameter for population variance, based upon 
55

the prior distribution. In sensitivity analyses, authors also ran models assuming no prior 

information, i.e., all pesticides had an equal probability of association with NHL, 

regardless of class, functional group or previous cancer classification. Researchers also 

modeled NHL risk in association with total number of pesticides ever used in the 

lifetime, and total number of “potentially carcinogenic” pesticides defined based upon 

previous research.

Overall, authors did not observe strong evidence of specific associations between 

pesticides and NHL in this pooled analysis. However, researchers reported statisticallysignificant 50% increased odds of NHL in association with exposure to atrazine 

(hierarchal regression adjusted odds ratio (OR) 1.5 (95% confidence interval (95% CI), 

1.0 to 2.2)), adjusting for exposure to all other pesticides (47). A positive association 

between glyphosate and NHL was also observed (hierarchal regression adjusted OR 

1.6 (95% CI 0.9 to 2.8). Researchers reported approximately 2-fold increased odds of 

NHL for participants who reported using 5 or more pesticides, or 5 or more “potentially 

carcinogenic” pesticides. In a joint-effects model, those who used both atrazine and 

alachlor were reported to have a 60% increased odds of NHL in comparison to those 

who used neither of these 2 herbicides. 

EPA Review

Authors reported that the use of “adjusted priors” had little effect on point estimates, 

indicating the prior knowledge of general associations between these pesticides and 

NHL is limited. A main strength of the study is the analysis of atrazine -NHL risk while 

controlling for several other pesticide exposures over the lifetime (47 pesticide coadjusted in the analysis) using hierarchal regression techniques. Both the study design 

(pooled data analysis), and analysis (hierarchal regression) enhanced statistical power, 

and augmented the precision and accuracy (mutual adjustment) of the risk estimates. 

The selection of cases was clearly stated in the paper (and original papers), and the 

method of control selection likely allows for a reasonable and valid sample of the target 

population from which the cases arose. While selection of a control series that is 

representative of the source population from which the cases arose is often a challenge 

in population-based case-control studies, comparability of cases and controls across 

many demographic characteristics through use of matching in the study design, and the 

lack of strong statistical associations across the 47 pesticides, which would have been 

expected if an error in design had occurred, argue against a role of selection bias. 

Cases were either hospital-based or identified through state cancer registries, and case 

ascertainment during the time period of these three pooled studies was relatively high. 

In all instances, cases were pathologically confirmed, which enhances the validity of the 

outcome assessment. For both cases and controls, information concerning pesticide 

exposure and other relevant demographic information was similar, however it is noted 

that for the states NE, IA, and MN, specific pesticide prompts were provided (“did you 

ever use X?”) while in KA an open ended question was used. However, authors report 
56

that pesticide use was similar by state and case-control status (this argues against 

information bias). 

Limitations include the assessment of an ever-use pesticide exposure metric only, 

which disallows an assessment of exposure-response trends. However, the primary 

goal of the authors was to present multi-pesticide adjusted estimates of specific active 

ingredients linked with incident NHL across these studies. A validity study performed 

within one of the three pooled studies (pesticide sales records) indicated pesticide 

exposure was reported accurately by participants. Pesticide exposure assessment did 

reflect exposure over the lifetime, relevant to the etiology of NHL as cancers are 

expected to have a 5-20 year latency period between exposure and development 

(and/or diagnosis) of disease, however no information as to trend, range of exposure, or 

measurement of exposure during critical adult or even early life exposures is possible 

given the method of exposure assessment. 

Authors measured lifetime pesticide use, prior to cancer diagnosis, targeting an 

assessment of incident cancer in association with pesticide use. Relevant confounders 

including age, race, gender, other pesticide exposure (the primary goal of the analysis), 

education, were measured and considered for analysis. Only those variables that were 

shown to be confounders in this study were included in final models, enhancing the 

statistical power of the study. 

Overall, the pooled analysis performed by DeRoos et al. (2003) provided a weighted 

average of the individual risk estimates reported in the three population-based case 

control studies upon which the pooling was based; the use of prior distributions, albeit 

defined broadly, were not additionally informative in this analysis. While statistically 

significant results were observed for the association between NHL and atrazine, authors 

themselves cautioned against using specific pesticide-NHL estimates to make causal 

inference, given the exploratory nature of the underlying studies and multiple statistical 

tests performed within the pooled study. Therefore, while the pooled study reduces the 

influence of random variability through increasing sample size (pooling), and the 

hierarchal methods and parsimonious models selected further refine the estimate, 

results are only weakly suggestive of a possible link between atrazine and NHL.

MacElroy et al. 2007 “Risk of breast cancer for women living in rural areas from adult 

exposure to atrazine from well water in Wisconsin.”

Authors performed a population-based case-control study of atrazine exposure and 

breast cancer among 22,495 women residing in the state of Wisconsin. Women were 

eligible for inclusion in this study if the following criteria applied: English-speakers, 

residence in the study area, age 20-79, listed telephone number. Cases included 

women who were diagnosed with breast cancer between the years 1988 and 2001, and 

reported to the state tumor registry. Controls were randomly selected from state DMV 

(20-65 years) and Health Care Finance Administration (65-79 years) records to roughly 

approximate the age distribution of cases (10-year age categories), and for whom no 

previous breast cancer diagnosis was made. Eighty-three percent of eligible cases and 
57

controls were enrolled into this study. Investigators were interested in atrazine exposure 

from untreated well water used for drinking water. Therefore, authors restricted the 

study population to those who resided in a rural area for whom well-water would likely 

supply local drinking water defined as a region with no public water system. Upon 

applications of the eligibility and restriction criteria, 3,275 case and 3,669 controls were 

selected into this study.

Participants were first contacted through a mailing, followed by a 40-minute structured 

interview via telephone. The data collection period spanned 13 years, 1988-2001, and 

reflected three separate case-control studies over this time period. Researchers 

solicited information regarding basic demographics, breast cancer risk factors, and 

residential history. Data were requested for the reference year: the year of diagnosis for 

cases, and the year approximating a case diagnosis year for the controls. Interviewers 

were largely blinded to case-status; interviewers reported knowledge of case-status 

(obtained during the course of the interview process) in 12% of case interviews and 

21% of control interviews. 

Concentration of atrazine and atrazine metabolites in well water which provided the sole 

residential drinking water source for participants in this study was measured in a state 

survey of pesticide contamination during three survey years: 1994, 1996, and 2001. 

Using a stratified random sample approach, representative atrazine well water 

concentrations were measured in one well within each “civil section,” a sub-unit of the 

county defined in public land use surveys. Exposure assessment was pseudo-ecologic 

in nature in that the atrazine concentration in well water within the “civil section” was 

assumed to represent the well water (drinking water) concentration for individual 

participant residences within that “civil section.” Across the three sampling years, well 

water samples were taken during both an atrazine “high use” period (May-Oct.) and an 

atrazine “low use” period (Oct.-May). In addition, for a sub-set of the wells measured, 

repeated measures were taken between 2 sampling years. Investigators measured 

parent atrazine and chlorinated metabolites (deethylatrazine, deisoatrazine, 

diaminoatrazine). To estimate atrazine exposure between sampling years of 1994, 

1996, and 2001 to the entire study period of 1988-2001, authors utilized a “national 

neighborhood interpolation” method using geographic information system software 

(ArcGIS). Authors considered atrazine well water concentration within the entire state 

and within the highest agricultural area of the state separately, the south central WI 

region.

Authors estimated the association between atrazine concentration in well water and 

breast cancer risk using logistic regression, and modeling atrazine exposure as both a 

categorical (<0.15 ppb, 0.15-0.50 ppb, 0.50-1.0 ppb, 1.01-2.99 ppb, and greater than 3

ppb) using the lowest exposure group as referent, and as a continuous variable. In this 

study, approximately 20% of wells had measurable levels of atrazine, approximately 3% 

of the concentrations were greater than 3 ppb, the regulatory limit at the time of the 

study. In the agriculturally intensive south central region of the state, 34% of wells had 

measurable atrazine concentrations. Researchers report that atrazine concentrations 

were decreasing over the period of the study. 
58

Authors did not observe evidence of an association between atrazine concentration in 

well water and breast cancer. Comparing those in the moderately high category to the 

lowest exposure category, minimal increased odds of disease were reported (OR 1.10, 

95% CI 0.90, 1.40). Among participants in the highest atrazine exposure area, odds of 

breast cancer was non-statistically significantly elevated to 1.3 (95% CI 0.30, 5.0), 

however precision was low (n=3 atrazine exposed cases in the upper category). 

EPA Review

This study presents limited evidence of a role for atrazine drinking water exposure in 

relation to breast cancer. Authors utilized an available state survey of well water 

pesticide concentrations, including atrazine, geo-coded residential address, and 

advanced methods to interpolate between study years to assess atrazine exposure 

through untreated well-water supplied drinking water. There are several strengths to this 

method of exposure assessment. As compared to previous studies on this topic, which 

are largely ecologic study designs (with the exception of the AHS study of breast cancer 

among pesticide applicator’s spouses), these researchers were able to estimate 

atrazine drinking water concentrations in individual participants. They used a 

sophisticated method of interpolating aggregate data across study years, i.e., national 

neighborhood interpolation which uses a weighted average which can change over 

time. Restricting the sample to rural residents, using untreated well water as the 

drinking water source represented a highly exposed sample of the general population 

enhancing the possibility of noting an effect if one exists. Collection of extensive 

residential histories allowed authors to characterize the method of exposure 

assessment, i.e., how well current residential address approximate exposure during the 

critical exposure window during adulthood. In addition, authors collected wellcharacterized, high-quality information regarding established breast cancer risk factors 

on an individual level for use in the statistical analyses of these data.

However, using these exposure methods, there are numerous possibilities for exposure 

measurement error in this study, several are acknowledged by the authors. Matching 

geo-coded residence with concentration of atrazine in a well within the same “civil 

section,” authors assumed the atrazine concentration in one well would approximate all 

residential drinking water exposure supplied by wells. This is essentially a pseudoecologic method of exposure assessment, and likely resulted in a reasonable accurate 

ranking of atrazine exposure among the participants; however, some degree of 

exposure misclassification likely occurred. Authors summarized (averaged) atrazine well 

water concentration within study year, and then interpolated atrazine well water 

concentrations from the sampling sites to the entire state region. These modeling 

decisions likely resulted in a loss of precision, and represents lack of refinement in the 

exposure data, although the neighborhood interpolation method allows exposures to 

fluctuate over time. 

Authors discuss the role of residential mobility in relation to the method of exposure 

assessment, and conclude that because a majority of women resided in the current 
59

(reference year) residential address for more than 10 years, geo-coding current address 

to measure with atrazine well water in the area is a good measure of lifetime (or at least 

~20 year latency period of cancer) exposure. However, for a women diagnosed early in 

life, this exposure period may represent a lifetime (childhood home), and for women 

diagnosed later in life the exposure period may or may not reflect the relevant etiologic 

window for breast cancer. In addition, authors assumed untreated well water 

concentrations approximate drinking water concentrations, and acknowledge likely nondifferential measurement error in the lack of information regarding non-residential 

drinking water consumption (bottled water, workplace, and restaurant). In addition, the 

etiologic risk factors, including the role of inherited genes, for breast cancers diagnosed 

in the 3rd and 4th decades of life in contrast to later life diagnoses likely differ. This may 

have resulted in a heterogeneity in the breast cancer cases, and possibly reduced the 

ability to see an association. Stratification by age category would have been informative. 

Results may have been affected by potential exposure measurement error and outcome 

heterogeneity, or no true association exists. This study is insufficient to determine 

whether an association between atrazine and breast cancer exists, however the data to 

not support the assertion. 

Authors performed a hypothesis-testing, cohort study using ecologic exposure 

assessment methods to evaluate the association between atrazine exposure and breast 

cancer among Latinas diagnosed with breast cancer. Invasive breast cancer cases 

were identified from the California state cancer registry (CCR) between the years 1988 

and 1999. The CCR collected information regarding tumor characteristics, diagnosis 

date and treatments, relevant demographic and reproductive history information. 

Counties for which fewer than 10 breast cancer cases were diagnosed in the study 

period were excluded. Individual level breast cancer data were compared with county 

level pesticide exposure, and grouped demographic data. 

Mills and Yang 2006. “Regression Analysis of Pesticide Use and Breast Cancer 

Incidence in California Latinas”

Pesticide use information between the years 1970 and 1988 was obtained from the 

California state pesticide use registry (PUR). Pesticide applications must be reported to 

the state and are recorded in a database (1970-1988). The database includes 

information concerning application date, location, crop, number of acres applied, 

pounds active ingredient per acre, among other relevant information. Researchers 

examined associations for two time periods, by county and by pesticide type. Authors 

were interested in six pesticides, including atrazine and simazine.

Authors calculated standardized incidence ratios (SIR) using for 1988-1993 and then for 

1994-1999 to reflect secular changes in breast cancer trends (screening, diagnostic 

tools, knowledge in population), and to examine latency between exposure and 

diagnosis. Pesticide exposure was categorized into quartiles, and estimates were 

adjusted for age, socio-economic status (SES) and fertility. Co-variables were defined at 

the group level, i.e., average household income for county as a measure of SES.
60

There were 23,513 incident cases of breast cancer in this study diagnosed and 

recorded at the CCR between the years 1988 and 1999. Established breast cancer risk 

factors were significantly associated with the outcome in this study population, e.g., age 

at first birth, parity. Adjusting for age and other co-variables, authors reported no

association between atrazine exposure and breast cancer comparing the highest and 

lowest quartiles of exposure (1988-1993: OR 0.86 (95% CI 0.70, 1.05); 1994-1999 OR 

0.87 (95% CI 0.73, 1.04), p>0.05). Authors reported a slight elevated odds of breast 

cancer in association with simazine exposure; however, results were not statistically 

significant.

Authors performed a large, cohort study of pesticide exposure and breast cancer in a 

highly exposed group among CA Latinas. Using high quality cancer registry outcome 

ascertainment was high and data quality acceptable. Using state pesticide use records 

is an innovative method to assess exposure, and is novel in its use of available data 

sources to address a public health concern. In this study, established breast cancer risk 

factors were indeed significantly associated with breast cancer in this study. 

EPA Review

The major limitation of this study is the essentially ecologic nature of the exposure 

assessment. While useful in establishing support for novel hypotheses, these methods 

are limited utility in pesticide risk assessment. Authors assumed PUR reports for the 

county were a good approximation of pesticide exposure of women diagnosed with 

breast cancer. However, EPA notes the women may not have resided in the place of 

residence at the time of diagnosis for a 15-20 year period, an adequate latency period. 

Use of demographic data measured at the aggregate level in multi-variable regression 

analyses is questioned.

Overall, this study is supportive of the conclusion that atrazine exposure is not related to 

breast cancer risk. However, because of the lack of individual level exposure and 

confounder information, an association cannot be ruled out based upon this study. This 

study included a large sample size, with high quality outcome measurement, information 

on relevant confounding variables, and took place among a highly exposed population. 

However, the ecologic exposure methods limit use in risk assessment. It is not known 

with certainty whether the women with breast cancer had the levels of atrazine 

exposure assigned them in this study.

Muir et al. (2004) “Breast cancer incidence and its possible spatial association with 

pesticide application in two counties of England.”

Authors performed an ecologic analysis of the possible association between pesticide 

usage including atrazine and breast cancer rates in 2 counties in England, Lincolnshire 

and Leichestershire. Researchers included all cases of breast cancer diagnosed among 

women, ages 45 years and greater in these 2 counties between the years 1988 and 

1991. Cancer cases were ascertained through regional cancer registry (Trent Cancer 

Registry). Residential address at the time of diagnosis was coded into an electoral 

ward, and breast cancer incidence rates within each ward were calculated adjusting by 

age using the 1991 national census, and using the national population of England and 
61

Wales as the standard population (i.e., the number of breast cancer cases within each 

ward/the number of breast cancer cases in England/Wales, adjusting using age 

distribution recorded in 1991 national census). 

Pesticide exposure was measured at the group level. A pesticide usage survey for 1991 

was used to determined the total kg of active ingredient applied per kilometer by each 

ward within the 2 counties of England represented in the study. Pesticide level data 

were initially available at the “parish” level, and researchers calculated pesticide usage 

at the “ward” level using “proportional redistribution approach” which is essentially a

weighted average of kg applied by proportion of parish represented by the ward. 

Investigators included atrazine, aldicarb, lindane and cyanazine in the study as these 

were identified as potentially estrogenic substances by the study authors and 

hypothesized to play an etiologic role in breast cancer development.

Authors calculated the correlation between geographic areas (the wards) using 2 GISbased techniques, black-white join-count, and Moran I statistics. In addition, 

researchers performed regression analysis based using group-level breast cancer IRR 

as the dependent variable and pesticide usage by ward as independent variables. They 

did not adjust for other pesticides, or breast cancer risk factors. Authors stratified rural 

and urban wards in the analysis. Authors reported no significant correlations (“clusters”) 

of breast cancer by geographic area. Furthermore, authors observed no association 

between average pesticide usage by ward and breast cancer IRR in urban or rural 

areas of Lincolnshire, or urban areas of Leichershire. Authors did note a statistically 

significant (p<0.05) positive change in slope of breast cancer incidence rates and 1-unit 

change in kg of atrazine used per km2 (slope 0.17 (0.03, 0.31)). Authors observed 

similar result for aldicarb and lindane. 

EPA Review

Authors performed an ecologic analysis of breast cancer incidence in association with 

pesticide usage including atrazine. The researchers noted the inherent limitations of the 

study design, but suggest the results of this work supports excluding the possibility of a 

strong, positive association between atrazine usage and breast cancer among women 

diagnosed later in life (otherwise these study would have detected greater 

associations). Strengths of this ecologic study include use of sophisticated, GIS-based 

analytic techniques to discern correlations and associations using these aggregate data. 

Given that this study was performed during a time period in which the possibility of a 

“breast cancer cluster” was discussed in the media, the use of aggregate data, collected 

for a purpose other than epidemiologic investigation was likely a strength, as 

information bias due to differential pesticide recall is eliminated. However, the 

observation of associations between atrazine use in the ward and breast cancer 

incidence in only one of the two counties in the study weakens the argument of 

evidence of a true association. In addition to the well-known limitations of ecologic 

design, a number of additional design and measurement decisions may have weakened 

the strength of the associations including use of residential address at breast cancer 

diagnosis as a surrogate for lifetime residence and therefore pesticide exposure; the 
62

use of usage data as a surrogate for individual/group exposure; the use of 1991 usage 

data as representative of earlier, etiologically relevant time periods (1970s, 1980s for 

diagnoses 1988-1991); lack of confounder measurement and analytic adjustment. 

Overall, authors are likely correct in the assertion that there is not a true, strongly 

positive association between atrazine (or the other pesticides measured) and breast 

cancer, however this study design, given its known limitations, cannot persuasively 

argue in favor or in opposition to a true positive association.

Orsi et al. (2009). “Occupational exposure to pesticides and lymphoid neoplasms 

among men: results of a French case-control study.” [Occup Environ Med. 2009 May ; 

66(5): 291–298. ]

Researchers evaluated the association between farming and pesticide exposure 

specifically, and lymphoid neoplasms including non-Hodgkin’s lymphoma (NHL), 

multiple myeloma (MM), Hodgkin’s lymphoma (HL), and lymphoid proliferative 

syndrome (LPS) in a hospital-based case control study. This study took place in France, 

and recruitment occurred 2000 to 2004.

Cases and controls were recruited among 6 hospitals in France in the cities of Brest, 

Caen, Nantes, Lille, Toulouse and Bordeaux. Eligibility criteria included age range 20-75 

years, and residence within the respective hospital catchment areas. Cases eligibility 

included recent diagnosis (within 3 months; 18 months for LPS) [WHO ICD-0-3], and 

included both histopathological and cytological confirmation of neoplasm by a panel 

(size not stated) of pathologists and hematologists. Eligibility included no history of 

lymphoid neoplasms, residence in hospital catchment area, admission to hospital for 

conditions not likely related to either LN or pesticide exposure. For this study, females 

and persons with a history of immunosuppression or who reported use of 

immunosuppressive drugs were excluded. Application of eligibility criteria resulted in 

491 cases and 456 controls selected into the study. Controls were individually matched 

to cases on age, gender and center.

Two exposure questionnaires were administered to study participants: a selfadministered questionnaire and a structured in-person interview by trained interviewers 

and pesticide use expert. In addition to basic demographic, medical history, and 

residential and occupational history, a detailed job history including pesticide exposure 

was obtained from those who reported working in agriculture for at least 6 months. 

Regarding farm-related exposures, crop type, animal husbandry activities, pesticide 

use, and duration of pesticide use (months) information was obtained or derived from 

the obtained information. Industrial hygienists and professionals expert in assessing 

pesticide exposure re-interviewed those who provided insufficiently detailed information 

during the structured interview and pesticide exposure questions (77%). Upon 

completion of data collection, exposure experts matched participant responses with 

publicly available data sets to estimate pesticide exposure experienced (based on job 

history, crop and animals on farm, time period of employment, etc.) for missing 

responses. Authors modeled pesticide exposure as ever-use of any pesticide, any class 

of pesticide (e.g., herbicide, insecticide), and any sub-class (e.g., triazine). Based upon 
63

the total number of months/years in employment in agricultural job, authors modeled 

duration of pesticide exposure classified as none, less than the median number of 

months, and greater than or equal to the number of months. Trends were assessed 

using median of each category. Using publicly available pesticide usage databases, 

industrial hygienists assigned a probability of use of particular pesticide groups by 

respondents given the time period of employment, type of farm (mixed v. single), and 

crops or livestock on the farm, and classified the probability of particular pesticide 

exposure using this information (definite or probable). Pesticide exposure intensity was 

not modeled due to inadequate data. Interviewers were blinded as to case-status. All 

interviewers were performed with the same structured questionnaire and were 

performed in the same manner. 

Researchers utilized unconditional logistic regression to estimate the associations 

between pesticide use and LN, and LN subtypes. Authors report associations with 

employment in farming; corn farming in association with NHL, HL, MM, HCL; ever use 

of any pesticide in association with NHL, HL, and MM. For triazine specifically, 

associations were observed with HCL (OR 5.1, 95% CI 1.4-19.3). In addition, triazine 

use was associated with NHL (diffuse large cell lymphoma 8/20 OR 2.1 [95% CI 0.8–

5.0]) and follicular lymphoma 4/20, OR 2.3 [95% CI, 0.7–7.7]), but not with chronic 

lymphocytic leukemia 4/17 OR 0.9 [95% CI 0.3–3.0]. 

Sensitivity analyses using various lag times (10, 20, 30, 40 years), or consideration of 

only pesticide exposure which occurred in certain points in time (e.g., 30-40 years ago) 

did not change risk estimates. Use of conditional (individual matching) logistic 

regression, or collapsing of all possible pesticide exposures with the no exposed group 

in comparison with the definite exposed group did not change results. Adjustment for 

known LN risk factors, other co-variables, or iterative exclusion of certain admission 

reasons, and co-adjustment for other pesticide exposure did not appreciably change 

results.

EPA Review

Authors performed a hypothesis-generating study of the link between pesticide 

exposure and LN, and LN sub-types including NHL. Eligibility criteria and inclusion and 

exclusion factors were clearly delineated by authors. Use of hospital-based controls can 

be problematic in population-based studies due to the uncertainty as to whether the 

cases and controls were derived from the same source population. In this study, authors 

did not comment as to whether the cancer centers at the respective recruitment sites 

were reflective of primary or tertiary care facilities, and similarly whether the non-cancer 

departments (rheumatology, osteopathy) were reflective of the same level of care, i.e.,

whether the same types of patients would be present in each department/center. It is 

difficult to assess the possibility of selection bias in this study. In addition, after 

individual matching, authors reported significant differences by age and center, the 

matching variables, suggesting the matching process may not have been fully 

successful. Co-factors that are typically confounders in studies of LN were not 

confounders in this study. However comparison of the prevalence of smoking and 
64

alcohol use between controls and the general population were similar, and comparison 

of pesticide use between controls and regional agricultural population were also similar 

which argues against the role of selection bias if cases were a representative sample of 

all cases. It seems unlikely that pesticide use would influence case selection given the 

design of the study, but information to assess the possibility is not provided. In addition, 

the age range for HCL and other LN differed greatly; possibly two study samples ought 

to have been devised. 

Authors performed a reasonable measure of pesticide exposure, albeit only ever use of 

any pesticide, pesticide functional class, or sub-group (triazine) were measured. This 

study offers no additional information as to the association between atrazine use and 

LN. Authors used 2 questionnaires, a self-administered and a structured questionnaire 

by a trained interviewer; this is a superior method of exposure assessment as compared 

to self-report questionnaire only. Participants were re-contacted if additional information 

was needed, and the rate of re-interview was similar between cases and controls. 

Differential exposure misclassification was unlikely because cases and controls had a 

similar level of missingness in data (cases were not reporting differently than controls), 

and the re-interview rate was also similar between groups. In addition, as stated earlier, 

participants were blinded as to the study hypothesis. Non-differential misclassification 

may have occurred, although use of two questionnaires and trained interview likely 

lessened the effects of this bias. Similarly, cancer outcome was histologically and 

pathologically confirmed reducing potential information bias in outcome measurement. 

Authors achieved high participation rates which reduces the chance of selection bias. 

The interviewers were blinded as to case-status, reducing the potential for bias. Iterative 

removal of each of the six centers from the whole analysis in a sensitivity exercise did 

not result in differences in the risk estimates, arguing against a role for center effects in 

the overall results. Several sensitivity analyses suggest the results are not likely 

explained by other factors such as lag or latency of effect, use of hospital based 

controls from other departments that may also be related to the exposure, or coexposure to other pesticides. However, as pesticide exposure was only measured at the 

ever-use level, residual confounding may still have occurred, which would tend to 

reduce the size of the effect estimate. As reported by the authors, the study is underpowered to see results OR<1.7. Non-differential exposure misclassification may have 

additional reduced study power. Use of blinding/masking techniques to both the study 

hypothesis as well as case and control status by both lab technicians and trained 

interviewers enhanced the validity of results and reduced uncertainties such as recall 

bias and ascertainment bias. Survival bias is less likely as all cases were recruited 

within 3 months of diagnosis, 18 months with respect to LPS.

Authors suggest an association between triazine use and LN may be present, 

specifically with HCL, NHL and FL. Strengths of this study include the performance of 

several sensitivity analyses to reduce some sources of uncertainty, and use of 2 levels 

of pesticide exposure data collection by trained, blinded interviewers. However, the 

relatively low statistical power and relatively wide confidence bounds suggest lack of 

precision in the estimates and inability to exclude chance as an explanation for these 

findings. Given the lack of comparability between cases and controls and lack of 
65

information regarding control selection, selection bias may have been possible. 

Exposure assessment reflects ever-use over a lifetime and disallowed more refined 

analysis for risk assessment. While authors observed suggestive association between 

triazines and lymphoid neoplasms, limitations present reduce weight of the study for use 

in overall evidence base for atrazine carcinogenicity.

Rull et al. (2009). “Residential Proximity to Agricultural Pesticide Applications and 

Childhood Acute Lymphoblastic Leukemia.”

This study was performed within the Northern California Childhood Leukemia Study. 

Cases of pediatric acute lymphocytic leukemia (ALL) were selected in two different 

study phases (I and II) between 1995-2002 in 35 counties in the San Francisco Bay 

area, and the agriculturally intensive Central Valley. Cases were identified through rapid 

case ascertainment (RCA) within 72 hours of diagnosis. RCA aids epidemiologic 

evaluations through reduced recall problems (less time between diagnosis and recall 

period). Controls were individually matched to cases (1:1 or 1:2 in phases I and II, 

respectively) on the following factors: age, sex, maternal race, Hispanic ethnicity. 

Maternal county of residence at birth was used as a matching factor for phase I but not 

phase II of the study. Participants were eligible if the mothers resided in the study area, 

if the child was less than 15 years of age at diagnosis or referent year (controls), if ALL 

was first cancer ever diagnosed, and if family were either English or Spanish speaking. 

Eligible controls were identified using vital records.

Maternal residence at birth was compared with state pesticide use records (PUR) to 

estimate pesticide exposure. Participants provided extensive residential history 

information, in addition to demographic, health status, and other exposure information. 

Questionnaires were completed by participating mothers (self-report) initially, and an inperson follow-up interview was later scheduled. Because California state pesticide use 

reporting began only in 1990, all cases and controls for this analysis were restricted to 

those born after 1990. Among the 600 active ingredients with reported pesticide 

applications during the study period in proximity to participant homes, authors restricted 

the pesticide exposure analysis to 118 active ingredients for which there was some 

evidence of cancer, developmental or reproductive health effects, or evidence of 

endocrine disruption (adjudicated by authors); or, frequency of use was high. Authors 

summarized evidence to create six toxicity categories for grouped analysis. 

Authors considered participants who resided within 0.5 miles of pesticide applications to 

be exposed to pesticides. They defined the non-exposed referent group as those with 

less than 1 pound (lb) active ingredient (a.i.) applied per square mile. Using lb ai/mi2 as 

the exposure metric, investigators categorized cases and controls into a moderately 

exposed (1st to 49th percentile of exposure), and highly exposed (50th percentile and 

above) exposed categories. Where possible, quartiles of exposure using the same 

exposure metric were categorized. Authors evaluated pesticide exposure over the 

child’s lifetime as well as restricting to the first year of life.

Using conditional logistic regression (comparing exposure prevalence between 

discordant case-controls pairs), and additionally adjusting for household income in the 
66

analysis, authors reported borderline significant associations between those in the 

moderately exposed category of triazines (OR 1.9 (95% CI 1.0, 3.7), but not among 

those in the most highly exposed category. Adjusting for exposure to other classes of 

pesticides, the magnitude of the association in the moderately exposed category 

increased, however the precision decreased (OR 4.1, (95% CI 1.5, 11.1)). Authors did 

not observe evidence of an association with herbicide categories: OR 1.2 (95% CI 0.8, 

1.9), and highly exposed: OR 0.9 (95% CI 0.5, 1.5)) for exposure to herbicides. There 

was no association between pediatric triazine exposure during the first year of life and 

ALL risk in this study. Triazines to which this study population was exposed included 

atrazine, cyanazine, prometryn, pymetrozine, and simzine.

EPA Review

Authors performed a hypothesis-generating, population based case-control study of 

pediatric ALL in relation to pesticide exposure. Strengths of the study include 

identification of cases through rapid case ascertainment (RCA) within 72 hours of 

diagnosis, thus reducing the period of recall. In this study, pesticide exposure was 

estimated using residential history, so essentially participants were blinded to the study 

hypothesis reducing recall bias potential. The recruitment rate was high (84%), and the 

cases and controls were similar on several (matching) factors, reducing the potential for 

selection bias. Further, as 100% of cases were identified and recruited in the study 

period, the population based controls, matched on important risk factors for either 

exposure or disease, were likely a good approximation of the study population from 

which the pediatric cancers arose. 

While the authors utilized more sophisticated methods of exposure measurement than 

have been employed in other investigations of childhood cancers, limitations, of course, 

still exist. These include the lack of information on critical windows of exposure for 

development of a pediatric cancer, and lack of precision of estimation of specific active 

ingredients with ALL. Authors utilized extensive, self-reported residential histories over 

the time period of the child’s life provided by the mother (parent). Researchers then 

compared residential locations with publicly available pesticide use information to 

determine pesticide exposure status for each case and control. While studies have 

illustrated that residential proximity is a good surrogate for pesticide, authors 

acknowledge some degree of non-differential misclassification of exposure likely 

occurred in this study which would tend to under-estimate associations. In addition, as 

authors note, residential proximity alone was used to measure pesticide exposure, no 

attempt to modify the exposure estimate by weather conditions, temperature or other 

factors that may affect the potential for drift on the application day. In addition, through 

matching on county of maternal residence at the time of birth, authors may have 

inadvertently matched on the main exposure factors, i.e., pesticide exposure. In this 

case, reduced risk estimates would be anticipated. Given these factors, the significant 

associations observed for triazines in relation to ALL are potentially notable.
67

The non-monotonic risk pattern between the moderately exposed and highly exposed 

groups may be due to residual confounding, or sample size in each exposure category. 

Authors note that non-monotonic trends may be explained by biological processes in 

which greater risk would be anticipated in the moderate exposure group but not the high 

exposure group due to compensatory mechanisms. It is not evident in these data which 

explanation is more plausible, however a conclusion in support of the alternative 

hypothesis are weak. The grouping of triazines together, some of which have different 

modes of action, argue against a biological explanation in favor of methods related 

explanations, e.g., residual confounding, lack of precision in exposure estimation. 

Pesticide exposure measurement during gestation/pre-natal period would have 

enhanced the specificity of the exposure estimate during a potentially critical window of 

exposure, i.e., fetal development. This is in general a limitation of this study. However, it 

is notable that post-natal and early life exposures have been implicated in the etiology 

of childhood cancers, supporting a role for pesticide, possibly some triazine exposures 

in these observed risk estimates. However, more refinement of pesticide exposure and 

replication of results are needed before a causal association can be posited. 

Researchers with the Agricultural Health Study (AHS) examined the association 

between atrazine use and incident cancer among pesticide applicators enrolled in the 

AHS. This research extends the results of Alavanja et al. 2003 (a prostate cancer 

nested case control study).

Rusiecki et al. 2004 “Cancer Incidence among Pesticide Applicators exposed to atrazine in the 

Agricultural Health study (AHS)”

Cancer outcomes were ascertained through linkage with state cancer registries, and 

deaths were determined through linkage with the National Death Index (NDI). For the 

purposes of this investigation, participants end their time on study when one of the 

following events occurs: cancer diagnosis, death or loss to follow-up through geographic 

relocation or other reasons. Cancer outcomes were obtained for each participant from 

the time of enrollment (1993-1997) through December 31, 2001. Participants 

contributed an average of 6.5 years on study.

Lifetime pesticide exposure was obtained through self-administered questionnaire. 

Questionnaire information included not only pesticide exposure, but also use of 

personal protection equipment (PPE), application methods, repair status, smoking, 

alcohol and other lifestyle factors, in addition to basic demographic information. 

Participants provided information concerning ever-use of pesticides, number of days per 

year and number of years over the working lifetime. Compiling information from across 

the industrial hygiene and exposure assessment literature, AHS researchers modified 

lifetime days of exposure by intensity of exposure, using a validated intensity score. The 

intensity score reflects information concerning application method, PPE use, and 

percentage of time spent mixing and loading pesticides, and other factors. 

Researchers included only new cancer cases diagnosed since enrollment, and 

excluded participants who provided no information concerning atrazine use during a 

lifetime. Only anatomical cancer sites for which at least 20 exposed cases were 
68

diagnosed during the time period of follow-up were included in the analysis. Risk 

estimates were adjusted for age, sex, education, alcohol consumption, family history of 

specific cancers, state, and smoking status. In addition, final statistical models included 

the ten most highly correlated/associated pesticides to adjust for co-exposure to other 

pesticides (pesticide adjustment included: dicamba, cyanazine, alachlor, trifluralin, 2,4-

D, chlorimuron-ethyl, metribuzin, butylate, phorate and heptachlor). 

Among 53,943 AHS participants included in this study, 68% reported ever-using 

atrazine during their lifetime. Demographic and other characteristics were similar 

between the three exposure comparison groups. Overall, researchers reported no 

significant associations between lifetime atrazine use and all cancer sites combined, 

and several specific anatomical cancer sites. No associations between use of atrazine 

and prostate cancer were observed across the quartiles of either cumulative lifetime 

days or intensity-adjusted lifetime exposure days. However, the report suggested 

associations for non-Hodgkin lymphoma, multiple myeloma, lung cancer, and bladder 

cancer. Authors also evaluated atrazine use in relation to oral, colon, rectum, pancreas, 

kidney, melanoma, or leukemia cancer sites and observed no evidence of an 

association. Authors describe initial suggested associations with these anatomical 

cancer sites as preliminary in this study.

EPA Review

Authors performed a well-conducted, hypothesis-generating analysis of atrazine use in 

association with several anatomical cancer sites providing some preliminary evidence 

that atrazine exposure may be associated with lung, bladder, NHL and multiple 

myeloma (MM). However, as authors note, exposure-response trends are not 

monotonic and consistent; there are a small number of exposed cases for some of

these sites; and, there is a lack of other evidence to support the hypothesis that atrazine 

exposure could be causally associated with these cancer outcomes.

For this study of atrazine exposure and cancer outcomes nested within the larger AHS, 

authors excluded participants who already experienced a cancer diagnosis at 

enrollment (a prevalent cancer case), as well as participants who did not provide any 

information regarding atrazine use. Authors reported no significant differences in the 

demographic or exposure characteristics of those included and excluded from this 

study. Pesticide exposure was assessed at enrollment, independent of later cancer 

diagnosis; therefore, exposure and other relevant information was collected in a similar 

manner between those exposed and unexposed to atrazine, and there is no probability 

of a recall bias influencing the results.

The semi-quantitative exposure assessment method of AHS has been described and 

evaluated extensively in the literature. Essentially, self-reported information concerning 

lifetime pesticide use was obtained through written questionnaire. Authors examined 

lifetime exposure days (LTED), and LTED modified by use of personal protective 

equipment (PPE) and other factors known as intensity-weighted lifetime exposure days 

in their analysis. Recently, use of these literature-derived intensity scores has been 
69

shown to be a valid and reliable method of assessing lifetime pesticide exposure (See 

Blair et al. 2011; Thomas et al. 2010). Authors note, however, that use of this exposure 

metric does not allow extensive refinement of exposure, i.e., which decade of life did 

relevant exposure occur, and it only allows examination of pesticide exposure 

experienced as an adult. Similarly, the cancer diagnoses in this study were ascertained 

through linkage with state cancer registry; Iowa is a SEER state and North Carolina 

received a Silver rating from the National Association of Cancer Registries. All cancer 

diagnosis are pathology confirmed, including medical record review which reduces the 

chance of outcome measurement error and misclassification of disease.

Authors were able to effectively measure and control for potentially confounding 

variables including age, sex, education, alcohol use, family history of specific cancer 

(first degree), state and smoking status. For the assessment of lung cancer, authors 

were able to model smoking in several ways, a strength of this study. Criteria for 

inclusion of potentially confounding variables in the final model were conservative, i.e., a 

+/- 10% change in point estimate. In addition, authors were able to adjust for use of ten 

most highly correlated pesticides associated with atrazine use, reducing the uncertainty 

that other pesticide exposure may also play a role in specific cancer outcomes. 

However, it should be noted that while authors could adjust of use of more than one 

pesticide in the lifetime, the exposure data were not refined enough to estimate coexposure of multiple pesticides within a biologically relevant critical window of effect. 

However, use of both the no exposure and the low exposure groups as references (no 

exposure group not shown in paper), reduces the chance of residual confounding due to 

differences between the most highly exposed group and the referent.

The possibility of selection bias in this cohort study is low given less than 2% of the 

cohort has been lost to follow up at the time of this study. Exclusion of prevalent cases 

from the analysis reduces the chance of prevalence-incidence bias, however it is 

possible some non-cases are actually occult cancer cases. However, the AHS 

population is generally a healthy one. While it is difficult to recall exposures over a 

lifetime (recall), it is unlikely that cases and non-cases recall pesticide exposure 

information differently given the prospective design of the study. Although pesticide 

exposure may be misclassified in some instances, it is likely this misclassification is 

non-differential in nature leading to an attenuation of the risk estimate in most instances. 

With only 6.5 years on average on study at the time of this analysis, in many instances 

there were too few cancer cases to perform a robust statistical analysis. However, 

authors only presented risk estimates for cancer sites for which there were at least 20 

exposed cases, limiting the role of low statistical power as an explanation for the 

research findings. The use of Poisson regression techniques, however, is appropriate 

given the prospective cohort design. It is noted that for atrazine-prostate cancer

association which was previously postulated, study power was 89% to detect an 

association if an association truly existed. Sensitivity analyses including use of both the 

no exposed and low exposed groups as referent to note the differences in risk estimates 

and trends, in addition to the use of both primary and secondary incident cancer cases 

to increase the sample size resulted in few differences in the final estimates. Therefore, 
70

authors reduced the chance that residual confounding or low statistical power explains 

these findings. Lastly, authors acknowledge that the characteristics of this cohort limit 

generalizability of the results. AHS participants are predominately male, Caucasian, and 

atrazine users are largely residents of Iowa. 

Overall, authors performed a well-conducted, hypothesis-generating study of atrazine 

use in association with several anatomical cancer sites. Strengths of this study include 

large sample size; elimination of both recall and selection bias as an explanation for 

these findings through study design and high retention rates, respectively; lifetime 

pesticide exposure assessment, refined with intensity-weights, with high validity and 

reliability; high quality and complete outcome ascertainment through linkage with 

certified state cancer registries; and the ability to measure and adjust for most relevant 

confounding variables including other pesticide exposure. Limitations include the low 

number of exposed cases for some anatomical cancer sites evaluated, the result of 

exposure measurement error may have attenuated some of these risk estimates, lack of 

refined exposure in the relevant critical time windows possibly including early life 

exposure, and possibility of unmeasured confounding by other pesticides or 

environmental/occupational exposures. AHS researchers have recently updated and 

extended this work (See Beane-Freeman et al. 2011).

Thorpe et al. 2005 “Herbicides and Nitrates in Groundwater of Maryland and Childhood 

Cancers: A Geographic Information Systems Approach.”

Authors performed a GIS-enhanced, ecologic analysis of four specific types of pediatric 

cancers (leukemia, NHL, bone, and brain) and pesticide exposure (atrazine, simazine, 

alachlor, metolachlor) and nitrate exposure measured in well-water (drinking water 

surrogate) in the state of Maryland. Investigators identified pediatric (ages 0-17 years) 

cancers in the state between the years 1992 and 1998. Case locations were geo-coded 

using residential address at the time of diagnosis. Using the Census data, age-adjusted

pediatric cancer incidence rates were calculated by county and census-tract. 

Pesticide exposure was determined through USGS well water monitoring records, and 

state Department of Environment application records by county. There were 834 well 

sites for which pesticide/nitrate levels were measured. Detectable levels of atrazine 

were reported for 10% of the well-sites; none of the well sites reflected atrazine 

exposure greater than the MCL (3 ug/L). 

Using well-site locations, 2 buffers were created to reflect “exposed” areas. For 

pesticides, buffers reflecting concentrations both 0.15 ug/L to 0.50 ug/L, and greater 

than 0.50 ug/L were developed. Residences within the buffer were considered exposed. 

Population-based controls were selected from Census records to construct a 2x2 

unadjusted contingency table of the crude association between atrazine exposure and 

the four pediatric cancers of interest.

Authors reported 689 pediatric cancer cases reported to the state registry during the 

study time period of 1992-1998. Standardized incidence rates indicate the MD state 
71

rates were less than the national rates (8.5 v. 14.2/100,000 children less than 17 years. 

In GIS-enhanced cluster analysis, utilizing an NCI developed GIS-add on software tool 

called SaTScan, authors identified the state county of Worchester as a cluster for these 

pediatric cancers (significant correlations of cases in this area). Regarding atrazine 

exposure, authors report no association with all four pediatric cancers combined (OR 

1.1 (95% CI 0.78, 1.56), p=0.66). Positive associations with both bone cancer and 

leukemia were also observed, although non-statistically significant. A multiplicative joint 

effect was reported for exposure to atrazine, metolachlor and nitrate (OR 7.56 (95% CI 

4.16, 13.73), although the estimate lacks precision.

EPA Review

Limitations of the ecologic design are noted by the authors; they describe the research 

as hypothesis generating. There are few other studies investigating this specific 

association, and unfortunately this study in itself offers little evidence in support or in 

opposition to the notion that atrazine exposure through drinking water (well water) may 

be associated with these type of pediatric cancers. Authors selected these pesticides for 

study due mainly to the high prevalence of use and exposure in the state. The known 

residential mobility of new mothers (new families) indicates the residential address at 

childhood cancer diagnosis may not represent the area of MD, or of the U.S. in which 

possible in utero, early post-natal, or early life pesticide exposure may have occurred. In 

addition, it is not known whether well water pesticide concentration accurately reflects 

pesticide exposure, or exposure during critical windows of gestation or early life cancer. 

The role of genetic background in the etiology of these pediatric cancers in also 

unknown. The lack of a clear “cluster” or grouping of pediatric cancers by agricultural 

area argues against a true association. However, given the limitations of this study 

design, the study itself offers little evidence to inform the nature of the association 

between atrazine and childhood cancers. 

Authors performed a population based case control study of occupational and 

residential triazine exposure in association with epithelial ovarian cancer using 

state/regional cancer registries to identify ovarian cancer cases, and a combination of 

state level pesticide use reports and self-reported pesticide exposure questionnaire data 

to assess triazine exposure. The study population included women living in the Central 

Valley and working in the state (CA). Cases were eligible if living in the central valley 

during the 2000-01 study period, diagnosed with epithelial ovarian cancer, at least 18 

years old, and for whom a physician gave permission to contact (actively or passively). 

Controls were women who did not have an ovarian cancer diagnosis, who had at least 

one ovary (at risk of being a case), living in the same zip codes as cases (contacted 

through random digit dialing), at least 18 years of age. Cases and controls were 

frequency matched on 5-year age categories and race/ethnicity (non-Hispanic white, 

Hispanic/Latina, other). Study participants were contacted first by letter and then 

through telephone interview. Telephone interview included collection of demographic 

Young et al. 2005. “Triazine Herbicides and Epithelial Ovarian Cancer Risk in Central 

California.”
72

information, disease history, reproductive history, and employment history in agriculture. 

Variables such as location of employment, crops cultivated at farm of employment, job 

titles, and years of employment among other things were collected through the 

telephone interview from which occupational and residential pesticide usage was 

assessed using external data sources (aggregate level exposure assessment, pesticide 

usage at farm-site at time of employment used to assess individual exposure).

Authors utilized two databases available in the state of California to determine pesticide 

usage at the farm-level. Using these two databases together, authors were able to reconstruct historical pesticide usage at the farm level from the years 1974-1999. 

Pesticide exposure from occupation in agricultural setting reported by participants 

between 1950-1974 were set to missing, however authors did compare employment in 

agriculture pre- and post the 1950-1974 period in their analyses. Using location of farm, 

crop type and other information authors were able to access state pesticide use records 

to determine the amount of triazine applied to the crop (cumulative exposure), and 

summed across employment periods within each individual. Researchers developed a 

job exposure matrix (JEM) using job title, crop type, number acres treated and other 

information, and assigned each participant a weighted cumulative pesticide exposure 

value. To examine residential triazine exposure, researchers considered residential 

proximity to a triazine application. Authors used an ever/never, cumulative exposure, 

and JEM weighted cumulative exposure score in their analysis.

Authors initially identified 652 ovarian cancer cases reported to the state/regional 

registries between the years 2000 and 2001. Among these cases, only 256 were 

interviewed based upon lack of eligibility, lack of accurate contact information, or refusal 

to participate (40% response rate). Authors reported no differences in age or stage at 

diagnosis between cases included and excluded from study. Similarly, of 2,327 controls 

selected through random digit dialing, 1122 were interviewed (57% response rate). 

Authors evaluated total traizines (OR 1.34 (95% confidence interval (95% CI) 0.77, 

2.33), and independently atrazine (OR 0.76 (95% CI 0.16, 3.55)), simizine (OR 1.35, 

(95% CI 0.71, 2.39)) and cyanazine (OR 1.90 (95% CI 0.65, 5.56)) in association with 

ovarian cancer. Examining quintiles of total triazine exposure, no exposure-response 

trend was observed (p=0.22), and modeling triazine exposure as a continuous variable 

authors did not observe evidence of a positive slope. Authors modeled the JEM weights 

as the maxima (instead of average), or as zero and observed little difference. Authors 

reported no evidence of effect modification by several variables evaluated including 

age, race/ethnic, first or second degree family relative with either breast or ovarian 

cancer, or tumor type. 

EPA Review

Authors performed a hypothesis-testing evaluation of the relation between triazine, 

including atrazine, pesticide exposure and ovarian cancer. They reported evidence of 

an increased odds of ovarian cancer in association with total triazine use, simazine and 

cyanazine use, however the risks estimated for individual triazines lack precision due to 
73

the relatively low prevalence of use of triazines in this sample. Authors report no 

significant or positive association between atrazine exposure and ovarian cancer, 

although the prevalence of exposure to atrazine is low in this cohort, reducing the 

statistical power to see an effect for atrazine specifically. 

Authors included women, 18 years or older, who reported living in the 22 county area of 

the study who either had an ovarian cancer diagnosis or were at risk for the diagnosis 

(had at least one intact ovary). However, authors also used random digit dialing 

techniques to identify controls, and sent an introductory letter first to all participants. 

Therefore, participants must have had a telephone and accurate mailing address to 

participate in the study. Given the transient nature of some agricultural workforce 

members, these design decisions may have excluded women who had the greatest risk 

for pesticide exposure. The similarity in age and tumor type between the cases included 

and excluded from the study suggest comparability between included and excluded 

cases, authors did not have the data to compare occupational pesticide use between 

these two groups. In addition, the modest response rate (40% and 57%) in cases and 

controls, respectively, and differences between cases and controls in education level 

attained and percentage of foreign-born participants adds to the concern that the 

sample may not be a good representation of the target population of all females who 

may have had pesticide exposure in the workplace. In addition, authors excluded 

women who had died or were too ill to participate; authors did not obtain responses by 

proxy. While obtaining a proxy response required added resources, and is often fraught 

with other uncertainties, i.e., the accuracy of the proxy response, obtaining proxy 

response for a random subset of these excluded women may have been informative as 

to whether there were differences in reported pesticide use. If pesticide exposure is 

causally linked to ovarian cancer, those who died or were too ill to participate within a 2 

year period of diagnosis could also have been those most severely affected by the 

exposure, thus a bias could have been introduced. 

Strength of the study includes histopathological confirmation of tumors, reducing 

outcome measurement error. Authors designed the study to assure only incident 

cancers were identified by restricting the years of cancer diagnosis to a recent period (to 

the time period of study), and performing retrospective exposure analysis on the years 

prior. However, given the typically late stage of ovarian cancer development at 

diagnosis, lack of an ovarian cancer screening tool, and unfortunately short duration of 

the disease (rapid progress from diagnosis to death), and high case-fatality rate, 

authors could have increased their study power to look at incident and prevalent cases 

combined. 

Pesticide exposure was assessed through matching of both residence and workplace 

histories (farm site locations) with state pesticide use records from 1974-1999 which 

was obtained through self-report in the telephone interview. If pesticide exposure 

occurred in the distant past, recall may have been imperfect and non-differential 

exposure misclassification could have occurred. In addition, authors did not state 

whether participants or trained telephone interviewers were blinded to study hypothesis 

or to case-control status, respectively. Authors developed an ever/never, cumulative 
74

exposure (total pounds per acre per crop), and a JEM weighted cumulative exposure 

metric. These exposure metrics range from likely more accurate and less precise 

(ever/never), to less accurate and more precise (JEM weighted cumulative exposure). 

Authors modeled exposure as categorical or continuous variables, maximizing statistical 

power of the study data. No exposure-response trend was observed, however only 

quintiles of total triazine could be evaluated due to small sample size. Authors 

attempted to measure lifetime pesticide exposure in association with the cancer 

outcome, a strength of the study. It is possible that pesticide exposure decades prior to 

cancer diagnosis could be causally related to ovarian cancer. Authors could have 

evaluated latency by assuming certain lag-times in the data analysis, i.e., it is unlikely 

pesticide exposure a year prior to ovarian cancer diagnosis would be causally linked to 

the outcome. 

Given the strengths and limitations of the research, this study cannot persuasively 

support or reject the hypothesis that triazine exposure is linked to ovarian cancer.

Table B-5a: Summary of Study Results

Author Dat

e

Study 

Design

Cancer 

Endpoint

Location Sample 

Size

Exposure 

Assessment

Adjustment Risk Ratio

BeaneFreema

n

201

1

occupationa

l cohort

all cancers IA and NC 

private and 

commercial 

pesticide 

applicators

3,146 

incident 

cancers 

among 

53,663 

applicators

self-report 

atrazine use

age, race, 

gender, 

smoking, 

alcohol use, 

education, 

state of 

residence, 

family history 

of specific 

cancers, 

applicator 

type (private 

or 

commercial), 

and ever-use 

of other 

pesticides 

No 

association 

most cancer 

including: all 

cancers, 

prostate, 

breast, NHL. 

Thyroid: 1.0; 

q1 OR 4.55 

(95% 

CI,1.27,16.24)

; q2 OR 1.16 

(95% CI 

(0.23, 5.80); 

q3 OR 4.84 

(95% CI, 1.31, 

17.93)

Carreon 200

5

populationbased case 

control

glioma upper Midwest 

(IA, MN,MI,WI)

341 cases, 

528 controls

atrazine use 

by self-report 

questionnaire

age, 

education, 

other 

pesticide

OR 1.1 (95% 

CI 0.7-1.8) 

including 

proxy 

respondents 

DeRoos 200

3

pooled 

analysis (3 

nested 

casecontrol 

studies)

NHL IA and MN, 

NE, KA

650 

cases/1933 

controls

atrazine use 

by self-report 

questionnaire

; validated

age, study 

site, use of 47 

other 

pesticides

OR 1.6 (95% 

CI 1.1 to 2.5); 

Hierarchal 

regression 

result: OR 1.5 

(95% CI 1.0-

2.5)
75

Table B-5a: Summary of Study Results

Author Dat

e

Study 

Design

Cancer 

Endpoint

Location Sample 

Size

Exposure 

Assessment

Adjustment Risk Ratio

McElroy 200

7

population 

based case 

control

breast WI 3,275 

cases, 

3,669 

controls

Atrazine 

concentration 

in drinking 

water: <0.15 

ppb; 0.15-

0.50 ppb; 

0.50-1.0 ppb; 

1.01-2.99 

ppb; and 

greater than 

3 ppb

age, parity, 

phase of 

study, casecontrol status, 

age of 

menopause, 

body mass 

index, age at 

first full term 

pregnancy, 

menopausal 

status, age at 

menarche, 

recent alcohol 

consumption, 

education

OR: 1.0 (ref); 

1.1 (95% CI 

0.7–1.5); 0.9 

(95% CI 0.6–

1.3); 0.9 (95% 

CI 0.6–1.4); 

1.2 (95% CI 

0.3–5.8)

Mills 200

6

cohort breast CA 23,513 

cases

agricultural 

atrazine 

applications 

reported to 

state

Age at 

menarche, 

recent alcohol 

consumption, 

education.

IRR: 0.87 

(95% CI 0.73-

1.04);1988-

1993: OR 

0.86 (95% CI 

0.70, 1.05); 

1994-1999 

OR 0.87 (95% 

CI 0.73, 1.04), 

p>0.05

Muir 200

4

ecologic breast Lincolnshire, 

Leichestershire

, England

aggregated 

data; 49 

"wards" in 

Leichershire

, rural areas

atrazine use 

within ward

unadjusted, 

regression 

analysis with 

aggregate 

level data

Slope: 0.17 

(95% CI 0.03, 

0.31); no 

evidence 

correlation 

Orsi 200

9

hospitalbased case 

control 

lymphoma

s

France 491 cases, 

456 controls

self-reported 

triazine use

age, study 

center, socioeconomic 

status

NHL: OR 

1.9(95% CI 

0.9-3.8); HL: 

OR 3.2(95% 

CI 0.9-10.9); 

ABLN: OR 

1.8(95% CI 

1.0-3.3); HCL: 

5.1(95% CI 

1.4-19.3); FL: 

OR 2.30 (95% 

CI 0.7-7.7)

Rull 200

9

population 

based case 

control

pediatric 

acute 

lymphocyti

c leukemia 

(ALL)

CA 213 cases, 

268 

matched 

controls

proximity to 

triazine 

applications 

reported to 

state

income, other 

pest

OR 2.0 (95% 

CI 0.4-9.4)

Rusiecki 200

4

cohort all cancers IA and NC 

private and 

commercial 

pesticide 

applicators

1,361 

cancer 

cases 

among 

53,943 AHS 

applicators

self-report 

atrazine use

age, sex, 

alcohol, live 

on farm, 

smoking, 

education, 

family history, 

state, 10 

correlated 

pesticides

all: OR 1.0 

(95% CI 0.82-

1.26); lung: 

OR 1.9 (95% 

CI 0.93-3.94); 

bladder: OR 

3.06 (95% CI 

0.86-10.8); 

NHL: OR 1.6 

(95% CI 0.62-

4.16); MM: 
76

Table B-5a: Summary of Study Results

Author Dat

e

Study 

Design

Cancer 

Endpoint

Location Sample 

Size

Exposure 

Assessment

Adjustment Risk Ratio

OR 1.6 (95% 

CI 0.37-7.01)

Thorpe 200

5

ecologic pediatric 

cancers

Maryland 

counties 

689 

pediatric 

cancers, 

population 

based 

controls

atrazine 

concentration 

in drinking 

water

contingency 

table analysis

all pediatric 

cancers: OR 

1.1 (95% CI 

0.78, 1.56); 

bone: OR 

1.89 (95% CI 

0.76-4.70); 

leukemia: OR 

1.43 (95% CI 

0.89-2.30)

Young 200

5

population 

based case 

control

ovarian California 652 cases, 

1122 

controls

self-reported 

work, 

residential 

history and 

triazine use 

reports

age, 

race/ethnicity, 

ever 

pregnant, 

breastfeeding

, oral 

contraceptive

s use, family 

history, 

hormone 

replacement 

therapy

triazine: OR 

1.34 (95% CI 

0.77–2.30); 

atrazine: OR 

0.76 (95% CI 

0.16-3.55)