Affiliations of authors: Occupational and Environmental Epidemiology Branch (WJL, AB, JAR, MD, MCRA), and Biostatistics Branch (JHL), Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Rockville, MD; Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC (JAH, DPS); Department of Preventive Medicine, College of Medicine, Korea University, Seoul, Korea (WJL).
Correspondence to: Michael C. R. Alavanja, DrPH, 6120 Executive Blvd., EPS 8000, Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD 20852 (e-mail: alavanjm{at}mail.nih.gov)
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ABSTRACT |
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INTRODUCTION |
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Chlorpyrifos is metabolized in the human liver to the active metabolite, chlorpyrifos oxon, which produces neurotoxicity by inhibiting esterases in the peripheral and central nervous system (6). There is little epidemiologic evidence of an association between chlorpyrifos exposure and human cancer, and most experimental studies have provided little or no evidence that chlorpyrifos has mutagenic or carcinogenic effects in humans (2). However, some experimental studies have detected chlorpyrifos-induced mutagenicity (7,8), sister-chromatid exchanges (9,10), and chromosomal loss (11). In rats, chlorpyrifos has been found to induce mitotic abnormalities and cytotoxicity (12); immunologic abnormalities, such as increased expression of the CD5 and CD8 surface markers (13); and generation of reactive oxygen species, DNA damage, and lactate acid dehydrogenase leakage (14). In humans exposed to chlorpyrifos, expression of CD26 and the frequency of autoantibodies both increased (15,16). In addition, chlorpyrifos modifies endogenous antioxidants (i.e., superoxide dismutase, glutathione peroxidase, and glutathione) in rats, possibly leading to the development of oxidative stress (17). A casecontrol study reported increased risk of non-Hodgkin lymphoma among male farmers exposed to chlorpyrifos in the United States, although that result was based on only seven cases (18).
The Agricultural Health Study is a prospective cohort study (19) that was designed to examine a wide variety of occupational exposures among farmers and commercial pesticide applicators and the risk of cancer and other chronic diseases. The overall approach is to evaluate risk factors for specific diseases of interest, once sufficient numbers of exposed cases have been observed in the cohort [e.g., prostate cancer (20)], and also to evaluate disease risks among selected groups with specific exposures (21). The extensive use of chlorpyrifos in agriculture and in households in the United States and worldwide, its possible genotoxicity, and the lack of adequate epidemiologic information on cancer in chlorpyrifos-exposed populations prompted us to investigate cancer incidence among pesticide applicators exposed to chlorpyrifos who were enrolled in the Agricultural Health Study (19).
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MATERIALS AND METHODS |
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The Agricultural Health Study is a prospective cohort study of certified pesticide applicators and their spouses in Iowa and North Carolina (19). Recruitment began in December 1993 and continued through December 1997. A total of 57 311 pesticide applicators (82.4% of eligible applicators in both states) enrolled in the study by completing an enrollment questionnaire when they sought a restricted-use pesticide license from the state Cooperative Extension Services or Departments of Agriculture. Cohort members are matched to cancer registry files in Iowa and North Carolina annually for case identification and to the state death registries and the National Death Index annually to ascertain vital status. For the current analysis, incident cancers were identified from the date of enrollment (i.e., 19931997) through December 31, 2001. Cancers were coded according to the International Classification of Diseases for Oncology, 2nd edition (ICD-O-2) (22). Cohort members who were alive at the end of follow-up but no longer residing in Iowa or North Carolina (n = 955) were identified through the current address records of the Internal Revenue Service, motor vehicle registration offices, and pesticide license registries of state agriculture departments and were censored in the year that they left the state. The average duration of follow-up was 6.4 years. All participants provided verbal informed consent, and institutional review boards of the National Cancer Institute, Battelle (the field station in North Carolina), the University of Iowa (the field station in Iowa), and Westat (coordinating center for the study) approved the protocol.
Exposure Assessment
The self-administered enrollment questionnaire collected comprehensive exposure data on 22 pesticides and ever/never use information on 28 additional pesticides, as well as information on use of personal protective equipment, pesticide application methods, pesticide mixing status, equipment repair methods, smoking history, alcohol consumption, history of cancer in first-degree relatives, and basic demographic data. All participants who completed the enrollment questionnaire were also given a self-administered take-home questionnaire that included more detailed questions about occupational history and questions on medical history and diet. Both questionnaires may be found at http://www.aghealth.org/questionnaires.html. A total of 24 671 pesticide applicators (43%) returned the take-home questionnaire. Participants who did and did not return the take-home questionnaire were similar with regard to farming practices, medical history including previous lung diseases, and demographic characteristics, except age distribution (23).
Data from the enrollment questionnaire and measurement data from the published pesticide exposure literature were used to estimate the intensity of exposure to individual pesticides using the following formula: intensity level = (mixing status + application method + equipment repair status) x personal protective equipment use, where the various levels of the four elements of the intensity score were weighted to reflect their importance to exposure (24). Mixing status was a three-level variable, based on never mixing, mixing less than 50% of the time, and mixing at least 50% of the time (values of 0, 3, and 9, respectively). Application method was a six-level variable, based on never applying, use of aerial-aircraft or distribution of tablets, application in furrow, use of boom on tractor, use of backpack, and use of hand spray (values of 0, 1, 2, 3, 8, and 9, respectively). Equipment repair status was a two-level variable, based on not repairing and repairing pesticide application equipment (0 and 2, respectively). Personal protective equipment use was coded as an eight-level variable based on the percentage of time that personal protective equipment was used while applying pesticides.
We constructed two lifetime chlorpyrifos exposure variables for this analysis, each categorized into quartiles based on the distribution of all cancer cases among chlorpyrifos-exposed applicators. The first, lifetime exposure-days, was obtained by multiplying the midpoints of the questionnaire categories of number of years an applicator personally applied or mixed chlorpyrifos by the number of days in an average year an applicator personally mixed or applied chlorpyrifos (i.e., years of use x days used per year, resulting in the following quartiles: 8.8, 8.924.5, 24.656.0,
56.1). The second lifetime chlorpyrifos exposure variable, intensity-weighted exposure-days, was obtained by multiplying the midpoint of lifetime exposure-days by the midpoint of intensity level (i.e., years of use x days used per year x intensity level, resulting in the following quartiles:
48.9, 49.0135.9, 136.0417.6,
417.7).
Statistical Analysis
Participants with prevalent cancer at enrollment (n = 1074) or who did not provide information on chlorpyrifos exposure (n = 1854) were excluded from this analysis, leaving 22 181 chlorpyrifos-exposed and 32 202 nonexposed applicators. Of those excluded, 44% were from Iowa and 56% were from North Carolina. Those excluded were older than the rest of the cohort and were more likely than the rest of the cohort to have some other missing data. However, they were similar to the rest of the cohort on smoking and overall pesticide use (data not shown).
We used Poisson regression in the Stata program (version 8.0) (25) to examine exposureresponse associations within the cohort and to explore the effect of potential confounding factors. Rate ratios (RRs) derived from the analysis were adjusted for age at enrollment (<40, 4049, 5059, 60 years), sex, educational level (high school graduate or less, beyond high school), smoking history (never/low/high, with smokers below the median value of 12 pack-years classified as low and smokers above the median classified as high), any alcohol consumption during the 12 months prior to enrollment (yes/no), history of cancer in a first-degree relative (yes/no), state of residence (Iowa/North Carolina), and year of enrollment. For pesticide categoryspecific rate ratios, we used applicators not exposed to chlorpyrifos as the reference category. Because of potential concomitant exposure to other pesticides, we adjusted rate ratios for exposure to the four pesticides (alachlor, carbofuran, fonofos, trifluralin) whose use was most highly correlated with intensity-weighted exposure-days to chlorpyrifos (Pearson correlation coefficient r
.4). The exposure levels of these four pesticides were categorized as never, low, and high; for each pesticide, the cut point between low and high exposure was set at the median of intensity-weighted exposure-days. We also added a variable for total years of pesticide application into the model as a surrogate measure of other potential farming exposure. We evaluated departures from a log linear model by adding a quadratic term for exposure-days and using a log likelihood test. We analyzed exposureresponse trends by including the categorical score (i.e., 0, 1, 2, 3) of each quartile as a continuous variable in the model and testing for the statistical significance of the slope. All tests of statistical significance were two-sided.
We conducted further analyses for lung cancer by stratifying on state of residence, histologic type, smoking history, and the first decade of chlorpyrifos use to investigate the consistency of associations observed. We also used data on the 24 671 participants who completed the self-administered take-home questionnaire to calculate rate ratios for lung cancer among chlorpyrifos-exposed applicators. These participants had additional information for other potential confounding factors, including previous lung diseases (yes/no), vegetable intake (low, medium, high), type of farm (e.g., corn or tobacco), and exposure to occupational factors such as asbestos, engine exhaust, silica, and welding fumes (yes/no). We also attempted to examine multiplicative interactions among chlorpyrifos exposure, other occupational factors, and risk of lung cancer. Our primary analysis focused on first primary lung cancers. We repeated the analysis including both first and second primary lung cancers; the results were essentially unchanged.
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RESULTS |
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DISCUSSION |
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Most previous studies have shown lower lung cancer rates for farmers than for the general population, which are probably due to a lower prevalence of smoking among farmers (27). Although several studies have reported increased lung cancer risk among pesticide-exposed populations, especially among those using DDT, diazinon, carbaryl, or propoxur (2830), the lack of information on tobacco use and on the details of specific pesticide use, limited causal interpretation. Overall, our cohort had a lower risk of lung cancer than the Iowa and North Carolina populations (31), but we did detect an exposureresponse pattern between chlorpyrifos exposure and lung cancer risk after controlling for other known cancer risk factors.
The mechanism by which chlorpyrifos increases lung cancer risk is not known. However, experimental studies suggest that chlorpyrifos may induce immune alteration (13,15,16) and oxidative stress (14,17) and may decrease the activity of glutathione S-transferase in animals and humans (32,33). Because glutathione conjugation represents the major pathway for elimination of benzopyrene epoxides in the lung, this pathway may offer an explanation for the possible co-carcinogenicity of chlorpyrifos in combination with polycyclic aromatic hydrocarbons from exposures such as cigarette smoking. Studies in the amphipod Hyalella azteca have shown that co-exposure to chlorpyrifos and methyl mercury increases toxicity additively by competition for glutathione, which would decrease the elimination of chlorpyrifos (32,34). Although this observation was made in an amphipod, it does provide a link to glutathione, which may be important biologically. These reported biologic activities of chlorpyrifos may explain the enhanced effects of chlorpyrifos in combination with other exposures and may also account for the observed lung cancer risk, despite the lack of consistent evidence for carcinogenicity in animal studies. A more complete analysis of lung cancer risk and the interaction of chlorpyrifos and other exposures will be possible as additional cases occur in the Agricultural Health Study; these analyses will also be important in helping to explain the mechanism by which chlorpyrifos is associated with increased lung cancer risk.
A limitation of this analysis as it relates to lung cancer is the possible confounding effect of smoking. Because of the small number of lung cancer patients who had been exposed to chlorpyrifos, we could not analyze data separately for women (n = 3) or for nonsmokers (n = 4). The lung cancer findings are unlikely to be due to smoking because other smoking-related cancers, such as those of the bladder, esophagus, and buccal cavity, showed no exposureresponse relationship with chlorpyrifos use after accounting for cigarette smoking, whether adjusted by pack-years, number of packs smoked per day, or years smoked (data not shown). Furthermore, neither index of chlorpyrifos exposure (lifetime exposure-days or intensity-weighted exposure-days) was correlated with pack-years smoked (r = .02 and .03, respectively), so confounding by smoking is not likely to be an important issue in our study.
Previous studies have reported an increased risk of rectal cancer among pesticide-exposed workers (35) and farmers (36,37). We found that the risk of rectal cancer increased with chlorpyrifos exposure; the trend was statistically significant for lifetime exposure-days but only approached statistical significance for intensity-weighted exposure-days. For both exposure measures, however, the positive trend was due to the elevated risk in the highest exposure category. The small numbers of cases and the non-monotonic shape of the exposureresponse curve therefore limit our conclusions about rectal cancer.
The etiology of brain cancer is poorly understood, but brain cancer has been linked to agricultural exposure, including exposure to pesticides (38). We found a statistically significantly increased risk of brain cancer with intensity-weighted exposure-days but not with lifetime exposure-days, although there were too few cases to produce a definitive answer. Because chlorpyrifos has neurotoxic effects in rat brains (39), the association of chlorpyrifos with brain cancer should be further studied in the cohort as additional cases occur.
We found a two-fold increased risk for lymphohematopoietic cancers in the highest category of intensity-weighted exposure-days but not in any other category of exposure. However, the lack of a corresponding increase with lifetime exposure-days is difficult to explain and weakens the argument for a causal relation.
The Agricultural Health Study has several important strengths. It is the largest epidemiologic study of pesticide applicators exposed to chlorpyrifos that has been conducted to date. Although the duration of cohort follow-up is still relatively short (6.4 years on average), as of December 2001, this analysis had 90% statistical power to detect a 1.5-fold increase in lung cancer incidence. All exposure information was collected before the diagnosis of cancer, which avoids caserecall bias. This study included comprehensive questionnaire data that were used to quantitatively estimate chlorpyrifos exposure levels and to control for potential confounding from lifestyle or other occupational exposures. The association between chlorpyrifos and lung cancer was observed whether low exposed or non-exposed persons were used as a referent group.
A limitation of this study and of almost all studies of pesticide users is that people who apply pesticides are seldom exposed to just a single agent. Coble et al. (40) evaluated the relationships among different agricultural exposures in this cohort and found that substantial bias due to unrecognized confounding from exposure to multiple agents was unlikely. To reduce the possibility of residual confounding, we adjusted the lung cancer risk estimates by including in our models the four pesticides whose use is most highly correlated with the use of chlorpyrifos. We further mitigated the possibility of uncontrolled confounding by using the pesticide applicators with the lowest exposure, instead of nonexposed applicators, as a reference group. Results were similar with both reference groups, suggesting that uncontrolled confounding was unlikely. Total years of pesticide application (of any pesticide) is a good measure of occupational exposure experienced by pesticide applicators, both farmers and commercial applicators, and therefore an excellent surrogate for many other factors. This variable was not statistically significant in the multivariable analysis, and it did not have a statistically significant effect on the risk estimates that were associated with chlorpyrifos exposure.
Another possible limitation is that the formulation, work practices, and application methods associated with chlorpyrifos use may have changed over the years. These changes may result in some exposure misclassification, particularly in studies in which exposure is based on subject's recall. However, recall of pesticide use by the Agricultural Health Study cohort has been shown to be as reliable as recall of other factors routinely evaluated by questionnaire in epidemiology studies, such as smoking and alcohol use, and to be better than recall of other factors, such as consumption of fruits and vegetables and physical activity (41). Hoppin et al. (42) also demonstrated that participants in our cohort provided plausible information regarding the duration of use of specific pesticides.
A potential limitation in chlorpyrifos exposure classification also should be considered. Among the chlorpyrifos-exposed applicators, most (93%) were farmers, and 7% were full-time applicators. The exposed group used chlorpyrifos for 6.6 years on average and for 9.4 days per year on average. Although the highest quartile of exposed applicators had more than 56 lifetime exposure-days, applicators in this quartile had much higher lifetime exposure-days on average (i.e., 224 mean lifetime exposure-days and 116 median lifetime exposure-days). We defined pesticide applicators who used chlorpyrifos for agricultural purposes as an exposed group and applicators who did not use chlorpyrifos as a nonexposed group. However, chlorpyrifos is a widely used insecticide for agricultural and nonagricultural purposes in the United States. Therefore, both groups may also be exposed to chlorpyrifos by nonoccupational routes to some extent, causing potential nondifferential misclassification of exposure.
Skin exposure is believed to be the main route of pesticide absorption into the body among applicators in agriculture (43). Therefore, the intensity level algorithm used to estimate pesticide exposure in this study emphasizes dermal absorption (24). However, for lung cancer, the respiratory route may be more important, and intensity-weighted exposure-days may be less appropriate than lifetime exposure-days. In this lung cancer analysis, however, results were similar with (intensity-weighted exposure-days) and without (lifetime exposure-days) taking into account factor weights associated with dermal exposure.
A total of 955 (less than 1%) of the cohort members left the states of Iowa and North Carolina during the period of the study (i.e., 19932001), and any incident cancers among this group are lost to the state cancer registries. This small portion of the total cohort is younger and more educated, smokes less, and has a slightly lower frequency of family history of cancer than the total cohort (data not shown) and is therefore likely to generate proportionally fewer cancers than the rest of the cohort. To assess the magnitude of the potential bias caused by including this group with a low cancer risk in the analysis, we recalculated the lung cancer risk estimates by adding all the lost person-years generated by this group to the denominator and assuming no cancer cases in the numerator. We observed only minimal changes in the risk estimates (data not shown), and these did not affect our conclusions.
In summary, our findings suggest an association between chlorpyrifos use and incidence of lung cancer among applicators in the Agricultural Health Study. The increased risk of lung cancer with increasing chlorpyrifos use was consistent after controlling for state of residence and for a variety of lifestyle factors, including smoking, other occupational exposures, previous lung diseases, type of farm, and vegetable intake. However, lung cancer was not an a priori hypothesized site linked to chlorpyrifos exposure, and thus our results must be interpreted cautiously, pending confirmatory studies in the Agricultural Health Study and elsewhere.
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NOTES |
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REFERENCES |
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1 Donaldson D, Kiely T, Grube A. Pesticide industry sales and usage: 1998 and 1999 market estimates, Washington (DC): Environmental Protection Agency; 2002. Available at: http://www.epa.gov/oppbead1/pestsales/99pestsales/market_estimates1999.pdf. [Last accessed: October 14, 2004.]
2 Smegal DC. Human health risk assessment-chlorpyrifos. Washington (DC): Environmental Protection Agency; 2002. Available at: http://www.epa.gov/oppsrrd1/op/chlorpyrifos/hedrra.pdf. [Last accessed: October 14, 2004.]
3 Environmental Protection Agency (EPA). Chlorpyrifos revised risk assessment and agreement with registrants. Washington (DC): EPA; 2000. Available at: http://www.epa.gov/pesticides/op/chlorpyrifos/agreement.pdf. [Last accessed: October 14, 2004.]
4 Centers for Disease Control and Prevention (CDC). Second national report on human exposure to environmental chemicalsorganophosphate pesticides: specific metabolites. p. 148. Atlanta (GA): CDC; 2003. Available at: http://www.cdc.gov/exposurereport/2nd/pdf/secondner.pdf. [Last accessed: October 14, 2004.]
5 Adgate JL, Barr DB, Clayton CA, Eberly LE, Freeman NC, Lioy PJ, et al. Measurement of children's exposure to pesticides: analysis of urinary metabolite levels in a probability-based sample. Environ Health Perspect 2001;109:58390.[ISI][Medline]
6 Richardson RJ. Assessment of the neurotoxic potential of chlorpyrifos relative to other organophosphorus compounds: a critical review of the literature. J Toxicol Environ Health 1995;44:135165.[ISI][Medline]
7 Waters MD, Simmon VF, Mitchell AD, Jorgenson TA, Valencia R. An overview of short-term tests for the mutagenic and carcinogenic potential of pesticides. J Environ Sci Health B 1980;15:867906.[ISI][Medline]
8 Patnaik KK, Tripathy NK. Farm-grade chlorpyrifos (Durmet) is genotoxic in somatic and germ-line cells of Drosophila. Mutat Res 1992;279:1520.[ISI][Medline]
9 Amer SM, Aly FA. Cytogenetic effects of pesticides. IV. Cytogenetic effects of the insecticides Gardona and Dursban. Mutat Res 1992;279:16570.
10 Sobti RC, Krishan A, Pfaffenberger CD. Cytokinetic and cytogenetic effects of some agricultural chemicals on human lymphoid cells in vitro: organophosphates. Mutat Res 1982;102:89102.[CrossRef][ISI][Medline]
11 Woodruff RC, Phillips JP, Irwin D. Pesticide-induced complete and partial chromosome loss in screens with repair-defective females of Drosophila melanogaster. Environ Mutagen 1983;5:83546.[ISI][Medline]
12 Roy TS, Andrews JE, Seidler FJ, Slotkin TA. Chlorpyrifos elicits mitotic abnormalities and apoptosis in neuroepithelium of cultured rat embryos. Teratology 1998;58:6268.[CrossRef][ISI][Medline]
13 Blakley BR, Yole MJ, Brousseau P, Boermans H, Fournier M. Effect of chlorpyrifos on immune function in rats. Vet Hum Toxicol 1999;41:1404.[ISI][Medline]
14 Bagchi D, Bagchi M, Hassoun EA, Stohs SJ. In vitro and in vivo generation of reactive oxygen species, DNA damage and lactate dehydrogenase leakage by selected pesticides. Toxicology 1995;104:12940.[CrossRef][ISI][Medline]
15 Thrasher JD, Heuser G, Broughton A. Immunological abnormalities in humans chronically exposed to chlorpyrifos. Arch Environ Health 2002;57:1817.[ISI][Medline]
16 Thrasher JD, Madison R, Broughton A. Immunologic abnormalities in humans exposed to chlorpyrifos: preliminary observations. Arch Environ Health 1993;48:8993.[ISI][Medline]
17 Bebe FN, Panemangalore M. Exposure to low doses of endosulfan and chlorpyrifos modifies endogenous antioxidants in tissues of rats. J Environ Sci Health B 2003;38:34963.[ISI][Medline]
18 Waddell BL, Zahm SH, Baris D, Weisenburger DD, Holmes F, Burmeister LF, et al. Agricultural use of organophosphate pesticides and the risk of non-Hodgkin's lymphoma among male farmers (United States). Cancer Causes Control 2001;12:50917.[CrossRef][ISI][Medline]
19 Alavanja MC, Sandler DP, McMaster SB, Zahm SH, McDonnell CJ, Lynch CF, et al. The Agricultural Health Study. Environ Health Perspect 1996;104:3629.[ISI][Medline]
20 Alavanja MC, Samanic C, Dosemeci M, Lubin J, Tarone R, Lynch CF, et al. Use of agricultural pesticides and prostate cancer risk in the agricultural health study cohort. Am J Epidemiol 2003;157:80014.
21 Lee WJ, Hoppin JA, Blair A, Lubin JH, Dosemeci M, Sandler DP, et al. Cancer incidence among pesticide applicators exposed to alachlor in the Agricultural Health Study. Am J Epidemiol 2004;159:37380.
22 Percy C, Van Holten V, Muir C. International classification of diseases for oncology. Geneva (Switzerland): World Health Organization; 1990. 2nd ed.
23 Tarone RE, Alavanja MC, Zahm SH, Lubin JH, Sandler DP, McMaster SB, et al. The Agricultural Health Study: factors affecting completion and return of self-administered questionnaires in a large prospective cohort study of pesticide applicators. Am J Ind Med 1997;31:23342.[CrossRef][ISI][Medline]
24 Dosemeci M, Alavanja MC, Rowland AS, Mage D, Zahm SH, Rothman N, et al. A quantitative approach for estimating exposure to pesticides in the Agricultural Health Study. Ann Occup Hyg 2002;46:24560.
25 StataCorp. Stata reference manual: release 8. College Station (TX): Stata Press, 2003.
26 Alavanja MC, Hoppin JA, Kamel F. Health effects of chronic pesticide exposure: cancer and neurotoxicity. Annu Rev Public Health 2004;25:155197.[CrossRef][ISI][Medline]
27 Blair A, Zahm SH. Cancer among farmers. Occup Med 1991;6:33554.[ISI][Medline]
28 Wesseling C, Antich D, Hogstedt C, Rodriguez AC, Ahlbom A. Geographical differences of cancer incidence in Costa Rica in relation to environmental and occupational pesticide exposure. Int J Epidemiol 1999;28:36574.[Abstract]
29 De Stefani E, Kogevinas M, Boffetta P, Ronco A, Mendilaharsu M. Occupation and the risk of lung cancer in Uruguay. Scand J Work Environ Health 1996;22:34652.[ISI][Medline]
30 Pesatori AC, Sontag JM, Lubin JH, Consonni D, Blair A. Cohort mortality and nested case-control study of lung cancer among structural pest control workers in Florida (United States). Cancer Causes Control 1994;5:3108.[ISI][Medline]
31 Alavanja MC, Lubin JH, Sandler DP, Hoppin JA, Thomas K, Tarone R, et al. Cancer incidence in the Agricultural Health Study. Scand J Work Environ Health. In press 2004.
32 Steevens JA, Benson WH. Toxicological interactions of chlorpyrifos and methyl mercury in the amphipod, Hyalella azteca. Toxicol Sci 1999;52:16877.[Abstract]
33 da Silva VI Jr, Torino LT, Michelon A, Sanchez Ferreira CA, Joaquim de Freitas DR, Termignoni C, et al. Effect of acaricides on the activity of a Boophilus microplus glutathione S-transferase. Vet Parasitol 2004;119:23745.[CrossRef][ISI][Medline]
34 Steevens JA, Benson WH. Toxicokinetic interactions and survival of Hyalella azteca exposed to binary mixtures of chlorpyrifos, dieldrin, and methyl mercury. Aquat Toxicol 2001;51:37788.[CrossRef][ISI][Medline]
35 Swaen GM, de Jong G, Slangen JJ, van Amelsvoort LG. Cancer mortality in workers exposed to dieldrin and aldrin: an update. Toxicol Ind Health 2002;18:6370.[CrossRef][ISI][Medline]
36 Zhong Y, Rafnsson V. Cancer incidence among Icelandic pesticide users. Int J Epidemiol 1996;25:111724.[Abstract]
37 Forastiere F, Quercia A, Miceli M, Settimi L, Terenzoni B, Rapiti E, et al. Cancer among farmers in central Italy. Scand J Work Environ Health 1993;19:3829.[ISI][Medline]
38 Khuder SA, Mutgi AB, Schaub EA. Meta-analyses of brain cancer and farming. Am J Ind Med 1998;34:25260.[CrossRef][ISI][Medline]
39 Slotkin TA. Cholinergic systems in brain development and disruption by neurotoxicants: nicotine, environmental tobacco smoke, organophosphates. Toxicol Appl Pharmacol 2004;198:13251.[CrossRef][ISI][Medline]
40 Coble J, Hoppin JA, Engel L, Elci OC, Dosemeci M, Lynch CF, et al. Prevalence of exposure to solvents, metals, grain dust, and other hazards among farmers in the Agricultural Health Study. J Expo Anal Environ Epidemiol 2002;12:41826.[CrossRef][ISI][Medline]
41 Blair A, Tarone R, Sandler DP, Lynch CF, Rowland A, Wintersteen W, et al. Reliability of reporting on life-style and agricultural factors by a sample of participants in the Agricultural Health Study from Iowa. Epidemiology 2002;13:949.[CrossRef][ISI][Medline]
42 Hoppin JA, Yucel F, Dosemeci M, Sandler DP. Accuracy of self-reported pesticide use duration information from licensed pesticide applicators in the Agricultural Health Study. J Expo Anal Environ Epidemiol 2002;12:3138.[CrossRef][ISI][Medline]
43 Maroni M, Colosio C, Ferioli A, Fait A. Biological monitoring of pesticide exposure: a review. Introduction. Toxicology 2000;143:1118.
Manuscript received April 15, 2004; revised September 24, 2004; accepted September 30, 2004.
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