Search tips
Search criteria 


Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Am J Epidemiol. Author manuscript; available in PMC 2014 March 27.
Published in final edited form as:
PMCID: PMC3967588

Occupational Exposure to Pesticides and Risk of Adult Brain Tumors


The authors examined incident glioma and meningioma risk associated with occupational exposure to insecticides and herbicides in a hospital-based, case-control study of brain cancer. Cases were 462 glioma and 195 meningioma patients diagnosed between 1994 and 1998 in three US hospitals. Controls were 765 patients admitted to the same hospitals for nonmalignant conditions. Occupational histories were collected during personal interviews. Exposure to pesticides was estimated by use of a questionnaire, combined with pesticide measurement data abstracted from published sources. Using logistic regression models, the authors found no association between insecticide and herbicide exposures and risk for glioma and meningioma. There was no association between glioma and exposure to insecticides or herbicides, in men or women. Women who reported ever using herbicides had a significantly increased risk for meningioma compared with women who never used herbicides (odds ratio = 2.4, 95% confidence interval: 1.4, 4.3), and there were significant trends of increasing risk with increasing years of herbicide exposure (p = 0.01) and increasing cumulative exposure (p = 0.01). There was no association between meningioma and herbicide or insecticide exposure among men. These findings highlight the need to go beyond job title to elucidate potential carcinogenic exposures within different occupations.

Tumors of the brain, cranial nerves, and meninges account for 95 percent of tumors of the central nervous system (1) and include some of the most rapidly fatal types of cancer (2). An estimated 20,500 new cases of brain and other nervous system cancers were diagnosed during 2007 in the United States (3). The two most common histologic types of brain tumors are gliomas and meningiomas, and data suggest that gliomas are more common in men, while meningiomas occur more often in women (2).

The etiology of brain cancer is still poorly understood. Exposure to ionizing radiation and certain genetic abnormalities are the only established risk factors for brain tumors (2). Some studies suggest that hormonal factors are related to glioma and meningioma risk (47), and others indicate that brain tumors may be related to allergies or autoimmune disorders (810). Brain tumors have also been associated with several occupational and environmental exposures, including farming (1113) and pesticides (2, 1315). Some pesticides contain alkylureas or amines that metabolize to nitroso compounds, which have been associated with neurogenic tumors (15, 16).

Using data from a US hospital-based, case-control study of adult brain tumors conducted from 1994 to 1998, we examined risk of glioma and meningioma associated with occupational exposure to pesticides. Previous analyses of occupation and brain cancer risk in this study revealed a significant association between glioma and work as a general farmer or farmworker (odds ratio (OR) = 2.5, 95 percent confidence interval (CI): 1.4, 4.7) (11) and a nonstatistically significant association between meningioma and work as a general farmer or farmworker (OR = 2.0, 95 percent CI: 0.8, 5.3) (12). These analyses were based primarily on job title and did not include information about specific exposures. In the present study, we extend that work to examine associations between glioma and meningioma and occupational pesticide exposure using job-specific information.


This study has previously been described in detail (17). Participants were enrolled between 1994 and 1998 at one of three hospitals specializing in brain tumor treatment in Phoenix, Arizona; Boston, Massachusetts; and Pittsburgh, Pennsylvania. Eligible cases were patients 18 years or older who were newly diagnosed with intracranial glioma or other neuroepithelial neoplasms, meningioma, or acoustic neuroma (International Classification of Diseases for Oncology, Second Edition, codes 9380–9473, 9490–9506, 9530–9538, 9560) (18). This analysis focuses on glioma and meningioma. Controls were patients admitted to the same hospitals who were treated for various nonneoplastic conditions: injuries (25 percent), circulatory system disorders (22 percent), musculoskeletal disorders (22 percent), digestive disorders (12 percent), and other nonmalignant illnesses or conditions (19 percent). Study controls were frequency matched to the total case series on the basis of hospital, age (10–year intervals), sex, race/ethnicity, and distance of residence from the hospital. This study was approved by the institutional review boards of the National Cancer Institute and all participating hospitals.

Eligible cases and controls (or their next of kin) were contacted after permission was obtained from treating physicians, and written, informed consent was obtained from each participant. We interviewed 489 glioma patients (92 percent of those eligible), 197 meningioma patients (94 percent), and 799 control patients (86 percent). A structured interview was administered by a trained research nurse to all participants or their proxy respondents. The occupational section of the interview solicited information on each job held for 6 months or longer since the age of 16 years, including the name and location of each employer, type of product/service provided, job title, year started and stopped, full- or part-time work status, and principal activities. For 64 occupations of a priori interest, job-specific modules developed by an industrial hygienist were administered to elicit in-depth information on tasks and exposures for each job held for at least 2 years (19).

Exposure assessment

We collected information on 8,535 jobs. Each job was assessed for insecticides and herbicides. Of the 64 job modules, only those for general farmer, farmworker, gardener, and janitor contained specific questions about herbicides and insecticides. Information on the types of pesticides used was collected only for farmers. However, there were too few farmers to allow analysis of specific pesticide active ingredients. Exposure assessment for all jobs for which there were no job modules, or for which we did not ask questions about pesticide use, was based on a job exposure matrix (JEM). The JEM was developed by an industrial hygienist (P. A. S.) who reviewed more than 500 published papers on pesticides, of which more than 100 reported dermal measurements. Dermal exposure is thought to contribute 90–95 percent of total exposure (20), so respiratory exposure was not considered.

Dermal pesticide exposure measurements were summarized from the literature to estimate exposure levels for each job/type of crop/method of use or application/decade where available for grain, vegetable, orchard, and animal farmers; exterminators; gardeners; farmworkers; and greenhouse, lawn care, forestry, golf course, and pesticide manufacturing workers. The only measurements used were those taken on unexposed skin or typical clothing, defined as that worn most often by the monitored subjects for each job. Farmers and farmworkers were asked about their typical clothing, and adjustments to the estimates were made on the basis of published protective factors. Based on these measurements, JEMs were developed for insecticides and herbicides, incorporating estimates for exposure metrics of probability, frequency, and intensity, as well as a confidence assigned to each of these exposure variables. JEM metrics were modified on the basis of the questionnaire information.

Each job was assessed for these metrics for insecticides and herbicides. Probability was defined as the percentage of people with the same job and industry in the same decade who were likely to have exposure and, based on the JEM, it was assessed as follows: 0 (specifically reported no use, reported <10 hours/year of use of the pesticide class, or 0 percent probability based on the JEM); 1 (>0–33 percent probability); 2 (>33–66 percent probability); 3 (>66–89 percent probability); or 4 (self-reported use or ≥90 percent probability). Frequency of exposure was defined as the average number of hours exposed to a pesticide in 1 week (hours per year/52 weeks), and it was categorized as follows: 1 (<2 hours/week); 2 (2–10 hours/week); 3 (11–19 hours/week); or 4 (≥20 hours/week). Intensity was defined as the average expected amount of pesticide deposited on the clothing or exposed skin during use and categorized as follows: 1 (<1 mg/hour); 2 (1–9 mg/hour); 3 (10–99 mg/hour); or 4 (≥100 mg/hour). Table 1 summarizes the most frequently assigned values of probability, frequency, and intensity for the most commonly reported jobs (n > 100) and for general and livestock farmers, farmworkers, gardeners, and janitors. The top five most frequently reported jobs included waiter/waitress, sales clerk in grocery and drug stores, cashier in restaurants or food markets, teacher, and cook. About 25 percent of these jobs were categorized as exposed.

Most frequently assigned levels of exposure probability, frequency, and intensity for the most frequently reported jobs (n > 100) and general/livestock/dairy farmer, farmworker, gardener, and janitor, Phoenix, Arizona, Boston, Massachusetts, and ...

We assigned a confidence rating to each job and exposure metric (i.e., probability, frequency, intensity) as follows: 1 (the data were contradictory or no information was available); 2 (the value was based on the JEM); or 3 (the value was based on self-report or, for intensity, measurements were available). For farmworkers, we developed a matrix based upon the application method, the type of crop, and type of task, using the same JEM categories. Intensity for these jobs was modified according to the type of clothing reported as typically worn while working.

Statistical analysis

We used unconditional logistic regression to estimate odds ratios and calculate 95 percent confidence intervals to examine the association between exposure to insecticides and herbicides and glioma and, for meningioma risk, for men and women separately. We included the following in the analysis: ever versus never exposed, duration exposed (sum of total years exposed), cumulative exposure (exposure intensity × exposure frequency × total years worked, summed across all exposed jobs), cumulative exposure lagged by 10 years, average exposure (cumulative exposure/total years worked in exposed jobs), and total years worked at the job with the highest exposure. Continuous exposure variables were categorized into quartiles or cut at the median, depending upon the total numbers of exposed participants. Cutpoints were based upon the percentile distributions of exposed controls, were gender specific, and were determined for herbicides and insecticides separately.

The covariates in our models were age (18–29, 30–39, 40–49, 50–59, 60–69, 70–79, ≥80 years), education (less than high school, high school diploma, post-high school), race (White/non-White), marital status, hospital location (Phoenix, Arizona; Boston, Massachusetts; Pittsburgh, Pennsylvania), proxy interview (yes/no), distance lived from the hospital (0–5, >5–15, >15–30, >30–50, >50 miles; 1 mile = 1.61 km), and household income in $1,000s (<15.0, 15.0–24.9, 25.0–34.9, 35.0–49.9, 50.0–74.9, ≥75.0). We initially included smoking and history of cranial radiotherapy, but the addition of these variables had little impact on our estimates, so we excluded them. In addition, only 31 patients reported a history of cranial radiotherapy. We evaluated brain tumor risk using six baseline models to account for the combinations of gender, exposure (herbicides, insecticides), and outcome (glioma, meningioma). Tests for trend were computed using the Wald statistic, treating the exposure variable as continuous by entering the median value for each level of the categorical variable among controls. We performed all analyses a second time excluding proxy respondents. We examined risk stratified by age (≤50, >50 years) and, for gliomas, tumor grade (high, low). To evaluate potential bias due to hospital controls, we systematically excluded control subgroups from our analyses. p values were two sided, and statistical significance was set at p < 0.05.

We analyzed the data in three different ways to account for the varying levels of confidence associated with the exposure assessment. We initially considered all jobs with a probability of exposure of less than 2 as unexposed. This accounted for the uncertainty of our assigned exposures, but it did not account for the uncertainty of unexposed jobs. In a second analysis, we excluded all subjects who had at least one job, either exposed or unexposed, with low confidence (40 percent of cases; 40 percent of controls). Finally, we retained as many of the data as possible by using all jobs with an exposure probability of greater than 1, regardless of confidence level. Since the patterns of association were similar for all three methods, we report only the results using the full data set, regardless of confidence level.


We excluded 159 patients missing one or more exposure or sociodemographic variables. A total of 765 controls and 462 glioma and 195 meningioma patients were retained (table 2). Glioma and meningioma patients tended to be slightly older than controls. Glioma patients were predominantly male, and meningioma patients were predominantly female. Patients with tumors tended to be more educated than controls, and the majority of cases and controls were White/non-Hispanic. Approximately 50 percent of the cases and controls were from the Phoenix hospital. There were more proxy interviews (either full proxy or assisted) conducted for glioma patients than for meningioma patients or controls.

Characteristics of study controls and glioma and meningioma cases, Phoenix, Arizona, Boston, Massachusetts, and Pittsburgh, Pennsylvania, 1994–1998


There was no association between glioma and ever having been exposed to insecticides among men (OR = 1.0, 95 percent CI: 0.7, 1.5) or women (OR = 0.9, 95 percent CI: 0.6, 1.4) (table 3). For both genders, there was no significant association between glioma and total years of insecticide exposure or cumulative lifetime insecticide exposure. The results did not change appreciably when we lagged cumulative exposure by 10 years, and neither average lifetime exposure nor total years spent at the highest exposed job (data not shown) were associated with risk of glioma. For men, the results were similar for high- and low-grade glioma (table 4). There were too few glioma cases among exposed women to adequately examine risk by tumor grade. Our findings were similar for herbicides (table 3). There was no overall association between ever using herbicides and glioma risk in men (OR = 0.9, 95 percent CI: 0.6, 1.3) or women (OR = 1.3, 95 percent CI: 0.8, 2.0). We observed no association between glioma and total years of herbicide exposure or with cumulative lifetime herbicide exposure. The results did not change appreciably when we lagged cumulative exposure by 10 years, and neither average lifetime herbicide exposure nor total years spent at highest exposed job were associated with risk of glioma (data not shown).

Odds ratios and 95% confidence intervals for glioma and occupational exposure to insecticides and herbicides, Phoenix, Arizona, Boston, Massachusetts, and Pittsburgh, Pennsylvania, 1994–1998
Odds ratios and 95% confidence intervals for glioma and cumulative exposure to insecticides and herbicides, stratified by tumor grade (men only), Phoenix, Arizona, Boston, Massachusetts, and Pittsburgh, Pennsylvania, 1994–1998*


We observed no consistent association between meningioma and exposure to herbicides or insecticides among men (data not shown). Given that 77 percent of meningioma patients were female, there were only 16 insecticide- and eight herbicide-exposed male meningioma patients. Among women, there was no association between meningioma risk and insecticide exposure. Women who reported ever using herbicides had a significantly increased meningioma risk compared with women who never used herbicides (OR = 2.4, 95 percent CI: 1.4, 4.3) (table 5). We observed significant trends of increasing risk with increasing years of herbicide exposure (p = 0.01) and with increasing cumulative exposure (p = 0.01), which were somewhat stronger with 10-year lagging.

Odds ratios and 95% confidence intervals for meningioma and occupational exposure to insecticides and herbicides (women only), Phoenix, Arizona, Boston, Massachusetts, and Pittsburgh, Pennsylvania, 1994–1998*

There were no striking differences in risk by age at interview for men (table 6) for glioma or meningioma. For women, meningioma risks associated with herbicide exposure were higher for women more than 50 years of age. There was an inverse trend in glioma risk among women aged 50 years or less and exposed to insecticides, most pronounced above the median cumulative exposure level of greater than 19.8 mg/hour. The overall trends in risk observed between insecticides and herbicides and both tumor types, in both sexes, did not change when we excluded proxy respondents. Excluding major control subgroups did not change our results.

Odds ratios and 95% confidence intervals for glioma and meningioma and cumulative exposure to insecticides/herbicides, stratified by age (≤50 vs. >50 years), Phoenix, Arizona, Boston, Massachusetts, and Pittsburgh, Pennsylvania, 1994–1998 ...


In this large, multicenter, case-control study of brain tumors, we found no overall association between exposure to insecticides or herbicides and glioma risk in men or women. Likewise, we found no association between exposure to insecticides or herbicides and meningioma risk among men and no association between exposure to insecticides and meningioma among women. Women with occupational herbicide exposure, however, appeared to experience an increased risk for meningioma.

Several studies have examined pesticide exposure and brain tumors as a group, not glioma and meningioma separately. Therefore, there is little published information concerning the association of pesticide exposure and meningioma risk. Most studies of pesticide manufacturing workers have not shown excesses of mortality from brain cancer (2126), and some reported decreased risks for brain cancer (2729). Results from studies of licensed pesticide applicators and studies that have examined the association between pesticides and all brain cancers as a group have yielded mixed results, with many reporting excess risks (30, 31), some reporting no excess risks (32, 33), and others reporting reduced risks (34, 35).

Findings from a Swedish cohort study suggested positive associations between glioma and employment as a farm supervisor, forestry supervisor, or horticultural worker; however, occupational exposure to herbicides was not associated with glioma risk (36). Results from an Italian case-control study suggested a fourfold excess risk for glioma among farmers who used insecticides and fungicides and a threefold excess risk among herbicides users (15). A recent case-control study of pesticide use and glioma in Nebraska reported excess glioma risks for ever use of two herbicides and three insecticides, but these risks were attenuated after excluding proxy respondents (37). Findings from an international case-control study of occupation and glioma indicated no association between use of pesticides and either high- or low-grade glioma (38). In a US study, Ruder et al. (39) found no associations between glioma risk and 12 specific pesticides, but they found reduced risks for glioma incidence associated with insecticides, fumigants, and organochlorine insecticides. Provost et al. (40) reported a significantly increased risk for glioma, but not for meningioma, associated with the highest quartile of cumulative occupational exposure to pesticides. The authors reported risks for men and women combined and did not examine risk associated with different classes of pesticides.

In previous analyses of our data, work as a general farmer or farmworker was positively associated with glioma (11) and meningioma (12). These analyses based on job and industry titles assumed that all participants who held the same job in the same industry had similar exposures. Specific exposures underlying the excess risks noted among farmers and farmworkers, such as pesticides, could only be hypothesized. In the present study, only 13 of 81 farmer and 19 of 81 farmworker jobs were classified as exposed to insecticides or herbicides; either participants reported that they had never applied pesticides, or the detailed job information indicated no exposure. It is likely that our exposure assessment method reduced the potential misclassification of exposure status assumed from job titles (19, 41).

To our knowledge, there have been no studies investigating meningioma and pesticide-exposed women. Our finding that women exposed to herbicides experienced increased meningioma risk may be a chance finding, and our results should be interpreted cautiously. Women in the highest exposure category for herbicides (n = 17) were workers in eating places (eight jobs), grocery stores (seven jobs), and hardware stores (one job); a gardener; an apple farm laborer; a mobile home park manager; and a potato processor. Workers in eating places, grocery stores, and the potato processor were likely to have handled produce contaminated with herbicides, while the hardware cashier was likely to have handled contaminated herbicide spray cans.

It is unclear why we observed an inverse association between glioma and cumulative insecticide exposure among younger women; however, this pattern was not consistent across other insecticide exposure metrics. We know of no evidence that suggests that women's susceptibility to these compounds differs from that of men. Hormonal factors have also been associated with meningiomas and gliomas, but results have been inconsistent. In this population, we observed an excess glioma risk associated with older age at menarche (4). Others have also reported this association, while associations reported for hormone replacement therapy use and glioma have been inconsistent (6, 7). For meningioma, some have reported higher risk associated with use of hormone replacement therapy (5, 42), age at menarche and parity (5), and hormonal contraceptives (43) but reduced risk associated with menopause (44) and number of pregnancies (45). Others reported no association with parity and age at first birth (46), age at menarche (45), and oral contraceptive use (5, 42, 45).

Strengths of our study include a large number of histologically confirmed glioma and meningioma brain tumors, high participation rates, rapid identification of incident cancers, detailed exposure information for some jobs, and the extensive pesticide literature, which aided our exposure assessment. Our results may have been affected by differential recall between glioma and meningioma patients, as glioma patients may experience more impaired memory or cognition than do meningioma patients (17). It is unlikely that our results were markedly affected by differential recall between study participants and proxy respondents since our results did not change appreciably after excluding proxies from the analyses. Because we conducted the exposure assessment without knowledge of diagnoses, any potential exposure misclassification was likely to be nondifferential. We also attempted to minimize any referral bias by frequency matching cases and controls on distance between hospital and residence.

We cannot rule out the possibility of chance findings due to small numbers of pesticide-exposed individuals for certain analyses. Other farm exposures, such as zoonotic viruses, dusts, and solvents, may explain the previously reported associations between farming and brain cancers (11). Alternatively, excesses found in some studies may reflect the use of specific pesticides that were not used, or used rarely, by participants in our study. We were unable to examine the effects of individual pesticides because few participants recalled specific pesticide names. We had incomplete data concerning residential pesticide treatments. Levels of household application, however, tend to be substantially lower than what farmers experience during occupational application.

In this large, multicenter, case-control study of glioma and meningioma, we found that women occupationally exposed to herbicides were at increased risk for meningioma, which increased as exposure duration increased. Our examination of pesticide exposure was a follow-up analysis of occupation and brain cancer (11, 12), and we used detailed, job-specific exposure information collected through the administration of job-module questionnaires. Our findings highlight the need to go beyond job title in order to elucidate potential carcinogenic exposures within different occupations.


This research was supported by the Intramural Research Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health (National Cancer Institute contract N01-CP-15679-01 with Research Triangle Institute).

The authors thank Adam Risch from Information Management Services, Inc., Silver Spring, Maryland, for support with database development and data management.


Conflict of interest: none declared.


1. Preston-Martin S, Lewis S, Winkelmann R, et al. Descriptive epidemiology of primary cancer of the brain, cranial nerves, and cranial meninges in New Zealand, 1948–88. Cancer Causes Control. 1993;4:529–538. [PubMed]
2. Inskip PD, Linet MS, Heineman EF. Etiology of brain tumors in adults. Epidemiol Rev. 1995;17:382–414. [PubMed]
3. American Cancer Society. Cancer facts & figures 2007. Atlanta, GA: American Cancer Society, Inc; 2007. [Accessed January 27, 2007]. (
4. Hatch EE, Linet MS, Zhang J, et al. Reproductive and hormonal factors and risk of brain tumors in adult females. Int J Cancer. 2005;114:797–805. [PubMed]
5. Jhawar BS, Colditz G, Fuchs C, et al. Sex steroid hormone exposures and risk for meningiomas. J Neurosurg. 2003;99:848–853. [PubMed]
6. Huang K, Whelan EA, Ruder AM, et al. Reproductive factors and risk of glioma in women. Cancer Epidemiol Biomarkers Prev. 2004;13:1583–1588. [PubMed]
7. Navarro Silvera SA, Miller AB, Rohan TE. Hormonal and reproductive factors and risk of glioma: a prospective cohort study. Int J Cancer. 2005;118:1321–1324. [PubMed]
8. Brenner AV, Linet MS, Fine HA, et al. History of allergies and autoimmune disease and risk of brain tumors in adults. Int J Cancer. 2002;99:252–259. [PubMed]
9. Schlehofer B, Blettner M, Preston-Martin S, et al. Role of medical history in brain tumor development. Results from the international brain tumor study. Int J Cancer. 1999;82:155–160. [PubMed]
10. Wiemels JL, Wiencke JK, Sison JD, et al. History of allergies among adults with glioma and controls. Int J Cancer. 2002;98:609–615. [PubMed]
11. De Roos AJ, Stewart PA, Linet MS, et al. Occupation and the risk of adult glioma in the United States. Cancer Causes Control. 2003;14:139–150. [PubMed]
12. Rajaraman P, De Roos AJ, Stewart PA, et al. Occupation and risk of meningioma and acoustic neuroma in the United States. Am J Ind Med. 2004;45:395–407. [PubMed]
13. Khuder SA, Mutgi AB, Schaub EA. Meta-analyses of brain cancer and farming. Am J Ind Med. 1998;34:252–260. [PubMed]
14. Carreon T, Butler MA, Ruder AM, et al. Gliomas and farm pesticide exposure in women: the Upper Midwest Health Study. Environ Health Perspect. 2005;113:546–551. [PMC free article] [PubMed]
15. Musicco M, Sant M, Molinari S, et al. A case-control study of brain gliomas and occupational exposure to chemical carcinogens: the risk to farmers. Am J Epidemiol. 1988;128:778–785. [PubMed]
16. Preussmann R. N-Nitroso carcinogens in the environment. In: Searle CE, editor. Chemical carcinogens. Washington, DC: American Chemical Society; 1984. pp. 829–868.
17. Inskip PD, Tarone RE, Hatch EE, et al. Cellular telephone use and brain tumors. N Engl J Med. 2001;344:79–86. [PubMed]
18. Percy C, Van Holten V, Muir C, editors. International classification of diseases for oncology. 2nd ed. Geneva, Switzerland: World Health Organization; 1990.
19. Stewart PA, Stewart WF, Heineman EF, et al. A novel approach to data collection in a case-control study of cancer and occupational exposures. Int J Epidemiol. 1996;25:744–752. [PubMed]
20. Durham WF, Wolfe HR. Measurement of the exposure of workers to pesticides. Bull World Health Organ. 1962;26:75–91. [PubMed]
21. Coggon D, Pannett B, Winder PD, et al. Mortality of workers exposed to 2-methyl-4-chlorophenoxyacetic acid. Scand J Work Environ Health. 1986;12:448–454. [PubMed]
22. Bond GG, Wetterstroem NH, Roush GJ, et al. Cause-specific mortality among employees engaged in manufacture, formulation, or packaging of 2,4-dicholorphenoxyacetic acids and related salts. Br J Ind Med. 1988;45:98–105. [PMC free article] [PubMed]
23. Bloemen LJ, Mandel JS, Bond GG, et al. An update of mortality among chemical workers potentially exposed to the herbicide 2,4-dichlorophenoxyacetic acid and its derivatives. J Occup Med. 1993;35:1208–1212. [PubMed]
24. Shindell S, Ulrich S. Mortality of workers employed in the manufacture of chlordane: an update. J OccupMed. 1986;28:497–502. [PubMed]
25. Wong O, Brocker W, Davis HV, et al. Mortality of workers potentially exposed to organic and inorganic brominated chemicals, DBCP, TRIS, PBB, and DDT. Br J Ind Med. 1984;41:15–24. [PMC free article] [PubMed]
26. Wang HH, MacMahon B. Mortality of workers employed in the manufacture of chlordane and heptachlor. J Occup Med. 1979;21:745–748. [PubMed]
27. Lynge E. A follow-up study of cancer incidence among workers in manufacture of phenoxy herbicides in Denmark. Br J Cancer. 1985;52:259–270. [PMC free article] [PubMed]
28. Saracci R, Kogevinas M, Bertazzi PA, et al. Cancer mortality in workers exposed to chlorophenoxy herbicides and chlorophenols. Lancet. 1991;338:1027–1032. [PubMed]
29. Fingerhut MA, Halperin WE, Marlow DA, et al. Cancer mortality in workers exposed to 2,3,7,8-tetrachlorodibenzop- dioxin. N Eng J Med. 1991;324:212–218. [PubMed]
30. Figa-Talamanca I, Mearelli I, Valente P, et al. Cancer mortality in a cohort of rural licensed pesticide users in the province of Rome. Int J Epidemiol. 1993;22:579–583. [PubMed]
31. Swaen GMH, van Vliet C, Slangen JJM, et al. Cancer mortality among licensed herbicide applicators. Scand J Work Environ Health. 1992;18:201–204. [PubMed]
32. MacMahon B, Monson RR, Wang HH, et al. A second followup of mortality in a cohort of pesticide applicators. J Occup Med. 1988;30:429–432. [PubMed]
33. Morrison HI, Semenciw RM, Morison D, et al. Brain cancer and farming in western Canada. Neuroepidemiology. 1992;11:267–276. [PubMed]
34. Cantor KP, Booze CF. Mortality among aerial pesticide applicators and flight instructors: a reprint. Arch Environ Health. 1991;46:110–116. [PubMed]
35. Ronco G, Costa G, Lynge E. Cancer risk among Danish and Italian farmers. Br J Ind Med. 1992;49:220–225. [PMC free article] [PubMed]
36. Navas-Acien A, Pollan M, Gustavsson P, et al. Occupation, exposure to chemicals and risk of gliomas and meningiomas in Sweden. Am J Ind Med. 2002;42:214–227. [PubMed]
37. Lee WJ, Colt JS, Heineman EF, et al. Agricultural pesticide use and risk of glioma in Nebraska, United States. Occup Environ Med. 2005;62:786–792. [PMC free article] [PubMed]
38. Schlehofer B, Hettinger I, Ryan P, et al. Occupational risk factors for low grade and high grade glioma: results from an international case control study of adult brain tumors. Int J Cancer. 2005;113:116–125. [PubMed]
39. Ruder AM, Waters MA, Carreon T, et al. The Upper Midwest Health Study: a case-control study of primary intracranial gliomas in farm and rural residents. J Agric Saf Health. 2006;12:255–274. [PubMed]
40. Provost D, Gruber A, Lebailly P, et al. Brain tumors and exposure to pesticides: a case-control study in southwestern France. Occup Environ Med. 2007;64:509–514. [PMC free article] [PubMed]
41. Hepworth SJ, Bolton A, Parslow RC, et al. Assigning exposure to pesticides and solvents from self-reports collected by a computer assisted personal interview and expert assessment of job codes: the UK Adult Brain Tumour Study. Occup Environ Med. 2006;63:267–272. [PMC free article] [PubMed]
42. Claus EB, Black PM, Bondy ML, et al. Exogenous hormone use and meningioma risk: what do we tell our patients? Cancer. 2007;110:471–476. [PubMed]
43. Wigerts A, Lonn S, Mathiesen T, et al. Risk of brain tumors associated with exposure to exogenous female sex hormones. Am J Epidemiol. 2007;164:629–636. [PubMed]
44. Schlehofer B, Blettner M, Becker N, et al. Medical risk factors and the development of brain tumors. Cancer. 1992;69:2541–2547. [PubMed]
45. Lee E, Grutsch J, Persky V, et al. Association of meningioma with reproductive factors. Int J Cancer. 2006;119:1152–1157. [PubMed]
46. Lambe M, Coogan P, Baron J. Reproductive factors and the risk of brain tumors: a population-based study in Sweden. Int J Cancer. 1997;72:389–393. [PubMed]