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Cancer Epidemiology Biomarkers & Prevention Vol. 10, 1155-1163, November 2001
© 2001 American Association for Cancer Research
 

Non-Hodgkin’s Lymphoma and Specific Pesticide Exposures in Men

Cross-Canada Study of Pesticides and Health1

Helen H. McDuffie2, Punam Pahwa, John R. McLaughlin, John J. Spinelli, Shirley Fincham, James A. Dosman, Diane Robson, Leo F. Skinnider and Norman W. Choi3

Centre for Agricultural Medicine, University of Saskatchewan, Saskatoon, Saskatchewan, S7N 0W8 [H. H. M., P. P., J. A. D.]; National Cancer Institute of Canada, Epidemiology Unit, University of Toronto, Toronto, Ontario, M5S 1A8 [J. R. M.]; Centre for Health Evaluation and Outcome Sciences, St. Pauls Hospital, Vancouver, British Columbia, V6Z 1Y6 [J. S.]; Alberta Cancer Board, Division of Epidemiology, Prevention and Screening, Edmonton, Alberta, T6G 1Z2 [S. F.]; Saskatchewan Cancer Agency, Allan Blair Memorial Centre, Regina, Saskatchewan, S4T 7T1 [D. R.]; Department of Pathology, University of Saskatchewan, Saskatoon, Saskatchewan, S7N 0W8 [L. F. S.]; and Manitoba Cancer Treatment and Research Foundation, Winnipeg, Manitoba, R3E 0V9 [N. W. C.], Canada


 

   Abstract
Top
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 References
 
 
Our objective in the study was to investigate the putative associations of specific pesticides with non-Hodgkin’s Lymphoma [NHL; International Classification of Diseases, version 9 (ICD-9) 200, 202]. We conducted a Canadian multicenter population-based incident, case (n = 517)-control (n = 1506) study among men in a diversity of occupations using an initial postal questionnaire followed by a telephone interview for those reporting pesticide exposure of 10 h/year or more, and a 15% random sample of the remainder. Adjusted odds ratios (ORs) were computed using conditional logistic regression stratified by the matching variables of age and province of residence, and subsequently adjusted for statistically significant medical variables (history of measles, mumps, cancer, allergy desensitization treatment, and a positive history of cancer in first-degree relatives). We found that among major chemical classes of herbicides, the risk of NHL was statistically significantly increased by exposure to phenoxyherbicides [OR, 1.38; 95% confidence interval (CI), 1.06–1.81] and to dicamba (OR, 1.88; 95% CI, 1.32–2.68). Exposure to carbamate (OR, 1.92; 95% CI, 1.22–3.04) and to organophosphorus insecticides (OR, 1.73; 95% CI, 1.27–2.36), amide fungicides, and the fumigant carbon tetrachloride (OR, 2.42; 95% CI, 1.19–5.14) statistically significantly increased risk. Among individual compounds, in multivariate analyses, the risk of NHL was statistically significantly increased by exposure to the herbicides 2,4-dichlorophenoxyacetic acid (2,4-D; OR, 1.32; 95% CI, 1.01–1.73), mecoprop (OR, 2.33; 95% CI, 1.58–3.44), and dicamba (OR, 1.68; 95% CI, 1.00–2.81); to the insecticides malathion (OR, 1.83; 95% CI, 1.31–2.55), 1,1,1-trichloro-2,2-bis (4-chlorophenyl) ethane (DDT), carbaryl (OR, 2.11; 95% CI, 1.21–3.69), aldrin, and lindane; and to the fungicides captan and sulfur compounds. In additional multivariate models, which included exposure to other major chemical classes or individual pesticides, personal antecedent cancer, a history of cancer among first-degree relatives, and exposure to mixtures containing dicamba (OR, 1.96; 95% CI, 1.40–2.75) or to mecoprop (OR, 2.22; 95% CI, 1.49–3.29) and to aldrin (OR, 3.42; 95% CI, 1.18–9.95) were significant independent predictors of an increased risk for NHL, whereas a personal history of measles and of allergy desensitization treatments lowered the risk. We concluded that NHL was associated with specific pesticides after adjustment for other independent predictors.


 

   Introduction
Top
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 References
 
 
NHL4 has been epidemiologically associated with farming (1, 2, 3, 4, 5, 6, 7, 8) , with certain farm practices (9) , with pesticide exposure (10, 11, 12, 13) , and with certain other occupations (14, 15, 16, 17) . The term pesticide is used to denote a wide variety of chemicals used to destroy weeds (herbicides), insects (insecticides), and mold (fungicides). Such chemicals are widely used in agriculture, horticulture, and forestry, and in the secondary processing of the products of these primary industries. Many of the NHL and pesticide case-control or cohort studies focused either on a small geographical area (1 , 2 , 4) or on one occupational group (2 , 4 , 5 , 9) . Our study encompassed six provinces of Canada with diverse agricultural practices and a number of different types of occupational and nonoccupational exposures to pesticides. Non-Hodgkin’s lymphoma incidence rates have been increasing in Canada for the last 25 years reflecting a worldwide trend (18) that has not been explained by improved diagnostic (19) methods or record-keeping (20) .


 

   Materials and Methods
Top
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 References
 
 
Study Population.
We conducted a population-based case-control study among men resident in six Canadian provinces to test the pesticide-exposure hypothesis related to four rare tumors. Incident cases among men, ages 19 years or over, with a first diagnosis of STS, HD, NHL [International Classification of Diseases, version 9 (ICD-9), code 200 or 202], or MM diagnosed between September 1, 1991, and December 31, 1994, were eligible. To balance the number of cases by geographical regions, each province was assigned a target number of cases in each tumor category. Each province ceased to ascertain cases when their preassigned target was reached. This report is based solely on cases diagnosed with NHL. Cases were ascertained from provincial Cancer Registries except in Quebec, for which hospital ascertainment was used. The Cancer Registries and hospitals provided information, including pathology reports, to confirm the diagnosis. Pathological material was reviewed and classified according to the working formulation by the reference pathologist. Misclassified and ineligible (e.g., Kaposi’s sarcoma, known HIV-positive) cases were excluded. Subjects for whom pathological material was unavailable remained in the study. After physician consent was received, postal questionnaires and informed consent forms were mailed to potential cases. Surrogates for deceased cases were not contacted.

Men, ages 19 years and older, selected at random within age constraints from the provincial Health Insurance records (Alberta, Saskatchewan, Manitoba, Quebec), computerized telephone listings (Ontario), or voters’ lists (British Columbia) were potential controls. The random control subject selection was stratified by age ± 2 years to be comparable with the age distribution of the entire case group (STS, HD, NHL, and MM) within each province. Postal questionnaires and informed consent forms were mailed to potential controls. Surrogates for deceased persons were ineligible as controls. All of the participating control subjects were used in the statistical analyses of each cancer site.

Pilot Study.
We conducted a pilot study (21) in each provincial region to test study procedures and to determine an operational definition of pesticide exposure to distinguish between environmental (which includes bystander and incidental) and more intensive exposure. Nonoccupational use of pesticides (home, garden, hobby) was included. There were few individuals who were completely free of being exposed to pesticides. Therefore, we constructed graphs that demonstrated that the most efficient definition of pesticide exposure, which discriminated (a) between incidental, bystander, and environmental exposure as compared with more intensive exposure and (b) between cases and controls, was a cumulative total of 10 h per year to any combination of pesticides. The screening questions in the postal questionnaire were used to trigger telephone interviews among those with cumulative exposure of >=10 h/year to any combination of herbicides, insecticides, fungicides, fumigants, and/or algicides. The 68 cases and 103 controls who participated in the pilot study are not included in this report.

Pesticides.
Pesticide is a generic term describing a variety of compounds of diverse chemical structures and biological modes of action. In this study, the term pesticide refers primarily to herbicides, insecticides, fungicides, and fumigants.

We conducted a validation pilot study of the modified questionnaires (21) . Volunteer farmers (n = 27) completed the questionnaires and granted permission for us to access their records of purchases through their local agrochemical supplier. The concordance between the two sources was excellent and discordance was explainable by (a) the farmer paid in cash and the supplier discarded the record; (b) the farmer purchased the agrochemical in the United States, and, therefore, the local supplier did not have a record; (c) the farmer paid for professional ground or aerial spraying, and the account was listed in another name; or (d) the supplier had destroyed the records.

Questionnaires.
The questionnaires were modified versions of the telephone interview questionnaire that was used in studies of pesticide exposure and rare tumors in Kansas (11) and Nebraska (13) . With permission, we modified the questionnaire to create postal and telephone interview questionnaires. To control for the effects of other variables known or suspected to be associated with the development of NHL after conducting an extensive literature review, we used the postal questionnaire to capture demographic characteristics, antecedent medical history, family history of cancer, detailed lifetime job history, and occupational exposure history to selected substances, accidental pesticide spills, and use of protective equipment, as well as details of cigarette smoking history. The telephone questionnaire characterized exposure to individual pesticides. The pesticide data were collected at several levels beginning with the broadest categories (e.g., minimal exposure, occupations with potential pesticide exposure) and progressing sequentially to major classes (e.g., herbicides); to chemical groups (e.g., phenoxy herbicides); and finally to individual compounds (e.g., 2,4-D, MCPA, and 2,4,5-T).

In this report, we focus on lifetime exposure to individual pesticides classified by active ingredients and to major chemical classes of herbicides, insecticides, fungicides, and fumigants. We classified exposure by the number of herbicides, insecticides, fungicides, and fumigants reported by cases and controls as well as by the number of days per year of exposure to individual compounds.

Each subject who reported 10 h per year or more of exposure to pesticides (any combination of compounds) as defined by the screening questions, and a 15% random sample of the remainder was mailed a list of pesticides (both chemical and brand names) and an information letter. Each subject was subsequently telephoned to obtain details of pesticide use.

The listed pesticides were chosen for inclusion (22, 23, 24, 25) : (a) if the compound was ever registered for use in Canada and reviewed by the IARC; (b) if the pesticide was recently banned or restricted in Canada by the federal licensing agency; or (c) if the pesticide was commonly used in Canada for specific purposes.

To ensure consistency, we developed and distributed manuals for provincial study coordinators, interviewers, and data managers. Before commencing data collection, we held a 2-day workshop with provincial coordinators to review data collection procedures and policies, to practice interviewing skills, and to review SPSS-DE (Statistical Packages for the Social Sciences-Data Entry),5 the custom data entry program that we used. On receipt of a postal questionnaire, the provincial coordinator reviewed it for internal consistency and completeness. Data were computer-entered and verified in the province of origin, transported to the coordinating center, and rechecked for completeness, after which statistical analyses were performed.

Copies of the questionnaires and additional information on pesticides that were not included in this report are available from the corresponding author.

Pathology Review.
Pathologists in participating provinces were requested to send blocks or slides of tumor tissue removed at surgery to the reference pathologist. Ten subjects with Kaposi’s sarcoma were omitted on the basis of the etiological association with HIV infection. Any other known HIV-positive subjects had been previously excluded. Eighty-four % (436 of 517) of the NHL tumors were validated. Because of a change midstudy in some hospitals’ policies regarding supplying pathological material without charge, we were unable to obtain the remaining samples.

Statistical Analyses.
Data from the postal and telephone interviews were merged by using the identification number. Of the individuals selected randomly for a telephone interview, most had used one or no chemical pesticides. We reviewed these data and decided to include them in the statistical analyses because they might be informative with respect to low levels of exposure to pesticides and their inclusion maximized our sample size with respect to other known or suspected risk factors for NHL. We conducted descriptive analyses of each variable, which included, where applicable, frequencies, ranges, means ± SD, and median values for cases and controls separately.

To evaluate putative risk factors for NHL, conditional logistic regression was used to compute ORs and 95% CIs, stratifying by age groups and province of residence.6 ORs were calculated for categorical variables related to medical history that were selected based on previous studies (e.g., measles, mumps, previous cancer, allergy desensitization treatment, skin prick allergy test); pesticide exposure (<10 and >=10 h per year); and smoking history. Using conditional logistic regression, ORs were also calculated for (a) major chemical classes of herbicides, insecticides, fungicides, and fumigants; and (b) for individual active chemicals. The statistically significant (P < 0.05) medical variables were used to adjust the effect of exposure to pesticides classified by major chemical group and by individual active chemical. Given the study sample size and the case-control ratio, a priori power calculations indicated that we had sufficient statistical power to detect an OR of 2 when at least 1% of the controls was exposed to a specific pesticide or chemical class of pesticide. Conditional logistic analyses (26) were conducted that retained in the model, all covariates for which the P was <=.05. The criterion for entry into models was a P <= 0.20 in bivariate age and province stratified analyses.

We created dose-response levels based on days/year of personally mixing or applying selected herbicides, insecticides, fungicides, and fumigants. We reported ORs stratified by age and province of residence. We created exposure categories for exposures to multiple different herbicides, insecticides, fungicides, and fumigants. For these analyses, the unexposed category was specific to the class of pesticide. We also created exposure categories for exposures to combinations of herbicides, insecticides, fungicides, and fumigants for which the reference group did not report exposure to any of those classes of pesticides.

Ethics.
The protocol, letters of informed consent, questionnaires, and all other correspondence with potential subjects were approved by the relevant agencies in each province. All of the information that could be used to identify individuals remained within the province of origin under the control of the provincial principal investigators.


 

   Results
Top
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 References
 
 
Data from postal questionnaires based on responses from 517 NHL cases (67.1% of those contacted) and 1506 control subjects (48.0% of those contacted) were analyzed. Similar percentages of potential subjects resident in rural and urban areas responded. There were higher percentages of responders in the middle-age group than at either extreme among both cases and controls. Detailed information related to their pesticide exposure history was obtained by telephone interview from 119 NHL cases and 301 control subjects who indicated pesticide exposure of 10 h per year or more. A 15% random sample of cases and controls who indicated pesticide exposure of less than 10 h/year was also interviewed by telephone, resulting in detailed pesticide exposure information on 60 cases of NHL and on 155 controls. The total telephone interviewed sample consisted of 179 cases of NHL and 456 controls.

A summary of selected demographic, antecedent personal and familial medical history, general pesticide exposure as measured by the screening questions, and cigarette smoking history comparisons of NHL cases and population-based controls is shown in Table 1 . Because all of the controls (age-matched for STS, MM, HD, and NHL) were used in the analysis, cases were older than controls. Cases and controls were similar in their smoking patterns. Cases were less likely to have a history of measles or mumps and more likely to have a personal history of a previous primary cancer. Cases were more likely than controls to have a positive family history of cancer, whereas more controls had undergone allergy desensitization injections. A slightly higher proportion of cases than controls indicated cumulative exposure to pesticides of >=10 h per year.


 

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  		Table 1 Comparisons of demographic, antecedent personal medical, general pesticide exposures and cigarette smoking history between cases of NHL and control subjects based on the postal questionnaire

 
 
Table 2 summarizes reported exposure to herbicides classified by major chemical classes (phenoxy, phosphonic acid, thiocarbamates, phenols, dicamba, and dinitroaniline) and by individual compounds for which at least 1% of responders reported exposure. ORs are also shown after adjustment for the statistically significant (P < 0.05) variables reviewed in Table 1 , which included a history of measles, mumps, cancer, and allergy desensitization shots and a positive history of cancer in a first-degree relative. Cases experienced a significantly higher frequency of exposure to phenoxyherbicides, to dicamba or a mixture including dicamba, to 2,4-D, and to mecoprop.


 

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  		Table 2 Herbicides: frequency of exposure to herbicides classified into major chemical classes and as individual compounds

 
 
Table 3 summarizes the insecticide exposure data. Exposure to two major chemical classes, carbamates and organophosphates, was statistically significantly associated with NHL, whereas exposure to organochlorines as a group was not. Among individual carbamate compounds, exposure to carbaryl was statistically significantly associated with NHL. Among organochlorines, exposure to lindane, to aldrin, and to DDT was significantly associated with NHL. Malathion was the only individual organophosphate exposure statistically significantly associated with NHL.


 

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  		Table 3 Insecticides: frequency of exposure to insecticides classified into major chemical classes and as individual compounds

 
 
Exposure to fungicides is summarized in Table 4 . The fungicides with an amide group (ORadj, 1.70; 95% CI, 1.04–2.78) were associated with NHL, whereas aldehydes and those containing mercury were not. Among individual amidecontaining compounds, exposure to captan (ORadj, 2.51; 95% CI, 1.32–4.76) was associated with NHL.


 

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  		Table 4 Fungicides: frequency of exposure to fungicides classified into major chemical classes and as individual compounds

 
 
Malathion used as a fumigant was not associated with NHL (Table 5) . There were fewer users of malathion as a fumigant compared with its use on crops. Carbon tetrachloride fumigant exposure (ORadj, 2.42; 95% CI, 1.19–5.14) was associated with NHL.


 

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  		Table 5 Frequency of exposure to fumigants: individual compounds

 
 
Table 6 shows the results of a conditional logistic regression model that included major chemical classes of pesticides and all other covariates for which P < 0.05. The variables that remained statistically significantly associated with increased risk of NHL were a previous personal history of another malignancy, a history of cancer among first-degree relatives, and exposure to dicamba and mixtures containing dicamba. ORs for a personal history of measles or of allergy desensitization injections were significantly lower than those without this history. Table 7 summarizes a similar model that included individual pesticides and all of the other covariates for which P < 0.05 and in which mecoprop and aldrin exposure as well as the same covariates as in Table 6 were associated with NHL.


 

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  		Table 6 Most parsimonious model: conditional logistic regression analyses that contained major chemical classes of pesticides and important covariates (P < 0.05)

 
 

 
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  		Table 7 Most parsimonious model: conditional logistic regression analyses that contained individual chemical pesticides and important covariates (P < 0.05)

 
 
Table 8 shows the frequency of exposure to selected individual herbicides, insecticides, fungicides, and fumigants, stratified by the average number of days per year of exposure. In general, the results of these dose-response analyses are consistent with the exposed/nonexposed findings. Those compounds for which we found statistically significant case-control differences also have elevated ORs based on strata of the variable "days per year of exposure" (mecoprop, dicamba, malathion, DDT, captan, carbon tetrachloride, and sulfur). The exceptions were 2,4-D, for which there was no dose-response relationship, and glyphosate, which was not significant for exposure but for which we demonstrated a dose-response relationship.


 

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  		Table 8 Frequency of exposure to selected herbicides, insecticides, fungicides, and fumigants stratified by the number of days per year of exposure

 
 
Table 9 compares the frequencies of multiple herbicide, insecticide, fungicide, and fumigant use among cases and controls. Cases are significantly more likely to report exposure to between two and four herbicides or insecticides but not to five and more of either. An elevated OR was found for exposure to two or more fungicides. Table 9 also shows a dose-response relationship in comparisons of subjects who reported no pesticide exposure and those who reported using five or more pesticides.


 

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  		Table 9 Distribution of numbers of exposures to multiple types of pesticides among cases and controls

 
 

 
   Discussion
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
References
 
 
The hypothesis that farming (1, 2, 3, 4, 5, 6, 7, 8) , agricultural practices (9) , and pesticide exposure (10, 11, 12, 13 , 22, 23, 24, 25) are associated with NHL has been tested in a number of occupational studies. Not all of the studies confirm an association (27, 28, 29) . Pesticides have diverse chemistry and biological modes of action. In addition to the active ingredients, there are emulsifiers, carriers, dispersants, and a variety of agents used to formulate liquids, granular and mists. The major chemical classes of a priori interest based on epidemiological studies (10, 11, 12, 13 , 22, 23, 24, 25) were phenoxyherbicides, organophosphorus, organochlorines, aldehydes, and carbon tetrachloride. Occupational exposure to 2,4-D, 2,4,5-T, carbaryl, chlordane, DDT, diazinon, dichlorvos, lindane, malathion, nicotine, and toxaphene has been reported to be associated with NHL. In addition, our interest focused on pesticides classified as possibly or probably carcinogenic to humans based on evaluations by the IARC expert panels (Refs. 22, 23, 24, 25 ; phenoxyherbicides including 2,4-D, MCPA, and 2,4,5-T as a group, atrazine, chlordane, DDT, dichlorvos, heptachlor, and pentachlorophenol). Our bivariate results for exposure to groups of phenoxyherbicides or dicamba-containing herbicides, for carbamates and organophosphorus insecticides, and for amide fungicides and for carbon tetrachloride were not attenuated when simultaneously adjusted for the important medical covariates (history of measles, mumps, cancer, allergy desensitization shots, and a positive history of cancer in a first-degree relative).

Among individual compounds, our results that related to exposure to 2,4-D, mecoprop, dicamba, malathion, DDT, carbaryl, lindane, aldrin, captan, and sulfur compounds were not attenuated after simultaneous adjustment for the same medical covariates. Clearly, we had few exposed men whose exposure was limited to one pesticide or to one class of pesticides. Our results show elevated risk for exposure to multiple herbicides, insecticides, and fungicides.

The strength of our results is enhanced by their internal consistency as we applied the strategy of assessing risk by different analytic approaches progressing from exposure to: (a) major chemical classes of herbicides, insecticides, fungicides, and fumigants; (b) individual compounds within those major chemical classes; and (c) individual compounds stratified by days per year of exposure. We constructed models that included potential confounders (e.g., positive history of cancer in a first-degree relative). Generally, the same individual compounds or class of compounds was associated with case status. The risk estimates based on exposure to major chemical classes or to individual compounds tended to be precise, as indicated by the 95% CIs.

Our results confirm previously reported associations of NHL and a personal history of cancer (30 , 31) , of NHL and a history of cancer among first-degree relatives (32 , 33) , and of NHL and exposure to selected pesticides (1 , 3 , 5 , 9, 10, 11, 12, 13) . We were unable to find a previous report suggesting a protective effect of allergy desensitization shots. Koepsell et al. reported little association of the number of allergy desensitization shots and MM (34) . The relationship between allergy and cancer is complex with well-designed studies reporting opposite results (35, 36, 37, 38) . Cigarette smoking was not a risk factor overall, confirming one study (39) and contradicting others (40 , 41) , although certain subtypes (39 , 40) of NHL may be associated with cigarette smoking.

The limitations of this study relate to those inherent in the case-control design, specifically the potential for recall bias and for misclassification of pesticide exposure. Hoar et al. and Zahm et al. (11 , 13) , as well as others (27, 28, 29 , 42, 43, 44, 45) , have dealt extensively with these issues among farmers. We have included individuals in many different occupations as well as home and garden users. These are groups for whom we did not find extensive validation studies. Their inclusion may have biased our dose-response findings toward the null, although the yes/no responses to individual pesticides would be less affected. We reduced the number of surrogate responders by excluding deceased persons from our definition of eligible subjects. This strategy was useful in decreasing the potential for misclassification of exposure.

A second limitation is the less-than-optimal response rates. We continued to recruit subjects in each province until the target numbers were achieved. We compared respondents to nonrespondents using postal codes as an indicator of rural residence, and we did not find a rural bias among respondents.

We reported results for a number of chemical agents and exposures, not all of which were specified in the hypothesis. Therefore, the statistical analyses related to these unspecified agents should be considered exploratory. As a consequence of conducting multiple comparisons, a small number of statistically significant results may be attributable to chance.

The two-tiered study design permitted us to obtain detailed information related to factors other than pesticides that are known or suspected of being etiologically associated with NHL. The mailing of a list of pesticides with both trade and generic chemical names followed by a telephone interview allowed the collection of detailed information concerning pesticide exposure. The statistical power of our study was enhanced by the large number of cases and controls. In instances of rare exposures (<1% exposed), we had limited statistical power to detect associations. We restricted our analyses of individual pesticide compounds to those for which at least 1% of respondents indicated exposure.

The study was not restricted to pesticide exposure experienced by a specific occupational group. Occupational exposure was quite diverse; single versus multiple pesticides; indoor versus outdoor applications. For example, men who work in animal confinement buildings, grain elevators, and pesticide manufacturing have different exposure patterns in comparison with grain farmers and commercial applicators. Because this study encompassed a large geographical area of Canada, there was substantial diversity among agricultural enterprises and in the patterns and types of pesticide exposure.

Delineating the putative relationship between exposure to pesticides and NHL is complicated: (a) by the subject’s exposure to a variety of different pesticides many of which are not mutagenic, teratogenic, or carcinogenic when tested as a single compound; (b) by the complexity of formulations of pesticides, the details of which are privileged proprietary information; (c) by the diversity of routes of possible exposure, which include ingestion, dermal, inhalation, and ocular; (d) by unexpected interactions among seemingly unrelated exposures, such as the increased permeability of rubber gloves to 2,4-D when exposed simultaneously to the insect repellent DEET and sunlight (46) ; and (e) by the role of differential genetic susceptibility.

Garry et al. (47) describe a potential mechanism to explain the relationship between exposure to specific pesticides and an increased risk of developing NHL. They have demonstrated specific chromosomal alterations in the peripheral lymphocytes of pesticide applicators exposed to a variety of pesticide classes. A higher frequency of chromosomal breaks involving band 18q21 was found in men who applied only herbicides compared with nonoccupationally exposed controls. Higher frequencies of rearrangements and breaks involving band 14q32 were found among men who applied herbicides, insecticides, and fumigants compared with controls. Reciprocal translocations between chromosomes 14q32 and 18q21 are frequently found in NHL patients.

Our results support previous findings of an association between NHL and specific pesticide exposures. Our strategy of assessing risk by several different approaches, beginning with general categories (e.g., herbicides), proceeding through cumulative pesticide exposure to specific chemical classes, and proceeding further to specific chemicals, proved effective in delineating complex relationships. In our final models, NHL was associated with a personal history of cancer; a history of cancer in first-degree relatives; and exposure to dicamba-containing herbicides, to mecoprop, and to aldrin. A personal history of measles and of allergy desensitization treatments lowered risk.

 


 

   Acknowledgments
 
We are indebted to the members of the Advisory Committee for this project for the sharing of their experiences (Drs. G. B. Hill, A. Blair, L. Burmeister, H. Morrison, R. Gallagher, and D. White); to the provincial coordinators and data managers for their meticulous attention to detail (T. Switzer, M. Gantefor, J. Welyklolowa, J. Ediger, I. Fan, M. Ferron, E. Houle, S. de Freitas, K. Baerg, L. Lockinger, E. Hagel, P. Wang, and G. Dequiang), and to Dr. G. Theriault for supervising the collection of data in Quebec. We appreciate the care and dedication of S. de Freitas in preparation of the manuscript. The study participants gave freely of their time and shared personal details with us, and we sincerely thank each of them.


 

   Footnotes
 
The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

1 This research was funded by Health Canada Grant 6608-1258, the British Columbia Health Research Foundation, and the Centre for Agricultural Medicine, University of Saskatchewan.

2 To whom requests for reprints should addressed, at Centre for Agricultural Medicine, 103 Hospital Drive, P. O. Box 120, Royal University Hospital, Saskatoon, S. K., S7N 0W8, Canada. Phone: (306) 966-6154; Fax: (306) 966-8799; E-mail: mcduffie@sask.usask.ca.

3 Dr. Choi was a collaborator who is now deceased.

4 The abbreviations used are: NHL, non-Hodgkin’s lymphoma; DDT, 1,1,1-trichloro-2,2-bis (4-chlorophenyl) ethane; STS, soft tissue sarcoma; HD, Hodgkin’s disease; MM, multiple myeloma; 2,4-D, 2,4-dichlorophenoxyacetic acid; MCPA, 4-chloro-2-methylphenoxyacetic acid; 2,4,5-T, 2,4,5-trichlorophenoxyacetic acid; OR, odds ratio; ORadj, adjusted OR; 95% CI, 95% confidence interval.

5 SPSS-Data Entry II Statistical Package for the Social Sciences: Statistical Data Analysis. SPSS Inc., Chicago, Illinois, 1998.

6 EGRET Intuitive Software for DOS Micros Statistics and Epidemiology Research Corporation, 1993.

Received 12/20/00; revised 8/13/01; accepted 8/22/01.


 

   References
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 
 
 
  1. Cantor K. P., Blair A., Everett G., Gibson R., Burmeister L. F., Brown L. M., Schuman L., Dick F. R. Pesticides and other agricultural risk factors for non-Hodgkin’s lymphoma among men in Iowa, and Minnesota. Cancer Res., 52: 2447-2455, 1992.[Abstract]
  2. Saftlas A. F., Blair A., Cantor K. P., Hanrahan L., Anderson H. A. Cancer and other causes of death among Wisconsin farmers. Am. J. Ind. Med., 11: 119-129, 1987.[Medline]
  3. Pearce N. E., Smith A. H., Fisher D. O. Malignant lymphoma and multiple myeloma linked with agricultural occupation in a New Zealand cancer registration-based study. Am. J. Epidemiol., 121: 225-237, 1985.[Abstract]
  4. Burmeister L. F., Everett G. D., Van Lier S. F., Isacson P. Selected cancer mortality and farm practices in Iowa. Am. J. Epidemiol., 118: 72-77, 1983.[Abstract]
  5. Cantor K. P. Farming and mortality from non-Hodgkin’s lymphoma: a case-control study. Int. J. Cancer, 29: 239-247, 1982.[Medline]
  6. Delzell E., Grufferman S. Mortality among white and non-white farmers in North Carolina 1976–78. Am. J. Epidemiol., 121: 391-402, 1985.[Abstract]
  7. Buesching D. P., Wallstadt L. Cancer mortality among farmers. J. Natl. Cancer Inst. (Bethesda), 72: 503-504, 1984.[Medline]
  8. Schumacher M. C. Farming occupations and mortality from non-Hodgkin’s lymphoma in Utah: a case-control study. J. Occup. Med., 27: 580-584, 1985.[Medline]
  9. Wigle D. T., Semenciw R. M., Wilkins K., Riedel D., Ritter L., Morrison H., Mao Y. Mortality study of Canadian farm operators: non-Hodgkin’s lymphoma mortality and agricultural practices in Saskatchewan. J. Natl. Cancer Inst. (Bethesda), 82: 575-580, 1990.[Abstract]
  10. Hardell L., Eriksson M., Lenner P., Lundgren E. Malignant lymphoma and exposure to chemicals especially organic solvents, chlorophenols and phenoxy acids: a case-control study. Br. J. Cancer, 43: 169-176, 1981.[Medline]
  11. Hoar S. K., Blair A., Holmes F., Boysen C., Robel R. J., Hoover R., Fraumeni J. F. Agricultural herbicide use and risk of lymphoma and soft tissue sarcoma. J. Am. Med. Assn., 256: 1141-1147, 1986.[Abstract]
  12. Woods J. S., Polissar L., Severson R. K., Heuser L. S., Kulander E. G. Soft tissue sarcoma and non-Hodgkin’s lymphoma in relation to phenoxyherbicide and chlorinated phenol exposure. J. Natl. Cancer Inst., 78: 899-910, 1987.[Medline]
  13. Zahm S. H., Weisenburger D. D., Babbit P. A., Saal R. C., Vaught J. B., Cantor K. P., Blair A. A case control study of non-Hodgkin’s lymphoma and agricultural factors in Eastern Nebraska. Epidemiology, 1: 349-356, 1990.[Medline]
  14. Alavanja M. C. R., Blair A., Merkle S., Teske J., Eaton B., Reed B. Mortality among forest and soil conservationists. Arch. Environ. Health, 44: 94-101, 1989.[Medline]
  15. Gallagher R. P., Threlfall W. J., Band P. R., Spinelli J. J. Cancer mortality experience of woodworkers, loggers, fishermen, farmers and miners in British Columbia. Natl. Cancer Inst. Monogr., 69: 163-167, 1985.[Medline]
  16. Kross B. C., Burmeister L. F., Ogilvie L. K., Fuortes L. J., Fu C. M. Proportionate mortality study of golf course superintendents. Am. J. Ind. Med., 29: 501-506, 1996.[Medline]
  17. Scherr P. A., Hutchison G. B., Neiman R. S. Non-Hodgkin’s lymphoma and occupational exposure. Cancer Res., 52 (Suppl.): 5503s-5509s, 1992.[Abstract]
  18. Devesa S. S., Fears T. Non-Hodgkin’s lymphoma time trends: United States and international data. Cancer Res., 52 (Suppl.): 5432s-5440s, 1992.[Abstract]
  19. Banks P. M. Changes in diagnosis of non-Hodgkin’s lymphoma over time. Cancer Res., 52 (Suppl.): 5453s-5455s, 1992.[Abstract]
  20. Holford T. R., Zheng T., Magne S. T., McKay L. A. Time trends of non-Hodgkin’s lymphoma: are they real? what do they mean?. Cancer Res., 52 (Suppl.): 5443s-5446s, 1992.[Abstract]
  21. Dosman J. A., McDuffie H. H., Pahwa P., Fincham S., McLaughlin J. R., Robson D., Theriault G. . Pesticides, Soft Tissue Sarcoma, Lymphoma, and Multiple Myeloma. A Case Control Study in Three Regions of Canada. Report to Health and Welfare Canada on Project 6008-1223, University of Saskatchewan Saskatoon, Canada 1990.
  22. IARC Working Group. An evaluation of chemicals and industrial processes associated with cancer in humans based on human and animal data. Cancer Res., 40: 1-12, 1980.[Abstract]
  23. IARC. Some halogenated hydrocarbons and pesticide exposures. In: Monographs on the Evaluation of the Carcinogenic Risk of Chemicals to Humans, Vol. 41. Lyon, France: IARC, 1986.
  24. IARC. Overall Evaluation of Carcinogenicity: An Updating of IARC Monographs, Volumes 1–42, Suppl. 7. Lyon, France: IARC, 1987.
  25. IARC. Occupational exposures in insecticide application and some pesticides. In: Monographs on the Evaluation of Carcinogenic Risks to Humans, Vol. 53. Lyon, France: IARC, 1991.
  26. Breslow, N. E., and Day, N. E. The analysis of case-control studies. In: Statistical Methods in Cancer Research, Vol. 1, IARC Sci. Publ. 32. Lyon, France: IARC, 1980.
  27. Bond G. C., Bodner K. M., Cook R. R. Phenoxy herbicides and cancer: insufficient epidemiologic evidence for a causal relationship. Fundam. Appl. Toxicol., 12: 172-188, 1989.[Medline]
  28. Wiklund K., Dich J., Holm L-E. Risk of malignant lymphoma in Swedish pesticide appliers. Br. J. Cancer, 56: 505-508, 1987.[Medline]
  29. Wiklund K., Holm L-E. Trends in cancer risks among Swedish agricultural workers. J. Natl. Cancer Inst. (Bethesda), 77: 657-664, 1986.[Medline]
  30. Cerhan J. R., Wallace R. B., Folsom A. R., Potter J. D., Sellers T. A., Zheng W., Lutz C. T. Medical history risk factors for non-Hodgkin’s lymphoma in older women. J. Natl. Cancer Inst. (Bethesda), 89: 314-318, 1997.[Abstract]
  31. Berstein R., Ross R. K. Prior medication use and health history as risk factors for non-Hodgkin’s lymphoma: preliminary results from a case-control study in Los Angeles County. Cancer Res., 52 (Suppl.): 5510s-5515s, 1992.[Abstract]
  32. Linet M. S., Pottern L. M. Familial aggregation of hematopoietic malignancies and risk of non-Hodgkin’s lymphoma. Cancer Res., 52 (Suppl.): 5465s-5473s, 1992.[Abstract]
  33. Goldgar D. E., Easton D. F., Cannon-Allright L. A., Skolnick M. H. Systematic population-based assessment of cancer risk in first degree relatives of cancer probands. J Natl Cancer Inst. (Bethesda), 86: 1600-1608, 1994.[Abstract]
  34. Koepsell T. D., Daling J. R., Weiss N. S., Taylor S. W., Olshan A. F., Swanson G. M., Child M. Antigenic stimulation and the occurrence of multiple myeloma. Am. J. Epidemiol., 126: 1051-1062, 1987.[Abstract]
  35. Vena J. E., Bona J. R., Byers T. E., Middleton E., Swanson M. K., Graham S. Allergy-related diseases and cancer: an inverse association. Am. J. Epidemiol., 122: 66-74, 1985.[Abstract]
  36. Mills P. K., Beeson W. L., Fraser G. E., Phillips R. L. Allergy and cancer: organ site-specific results from the Adventist health study. Am. J. Epidemiol., 136: 287-295, 1992.[Abstract]
  37. Severson R. K., Davis S., Thomas D. B., Stevens R. G., Heuser L., Sever L. E. Acute myelocytic leukemia and prior allergies. J Clin. Epidemiol., 42: 995-1001, 1989.[Medline]
  38. McDuffie H. H., Cockcroft D. W., Talebi Z., Klaassen D. J., Dosman J. A. Lower prevalence of positive atopic skin tests in lung cancer patients. Chest, 93: 241-246, 1988.[Abstract]
  39. Herrinton L. J., Friedman G. D. Cigarette smoking and risk of non-Hodgkin’s lymphoma subtypes. Cancer Epidemiol. Biomark. Prev., 7: 25-28, 1998.[Abstract]
  40. Brown L. M., Everett G. D., Gibson R., Burmeister L. F., Schuman L. M., Blair A. Smoking and risk of non-Hodgkin’s lymphoma, and multiple myeloma. Cancer Causes Control, 3: 49-55, 1992.[Medline]
  41. Linet M. S., McLaughlin J. K., Hsing A. W., Wacholder S., CoChien H. T., Schuman L. M., Bjelke E., Blot W. J. Is cigarette smoking a risk factor for non-Hodgkin’s lymphoma? results from the Lutheran Brotherhood Cohort Study. Leuk. Res., 16: 621-624, 1992.[Medline]
  42. Blair A., Zahm S. H. Epidemiologic studies of cancer among agricultural populations McDuffie H. H. Dosman J. A. Semchuk K. M. Olenchock S. Senthilselvan A. eds. . Agricultural Health and Safety: Workplace, Environment, Sustainability, : 111-117, CRC Lewis Publishers Boca Raton, FL 1994.
  43. Brown L. M., Dosemeci M., Blair A., Burmeister L. Comparability of data obtained from farmers and surrogate respondents on use of agricultural pesticides. Am. J. Epidemiol., 134: 348-355, 1991.[Abstract]
  44. Blair A., Zahm S. H. Herbicides and cancer: a review and discussion of methodologic issues. Recent Results Cancer Res., 120: 132-145, 1990.[Medline]
  45. Blair A., Zahm S. H. Methodologic issues in exposure assessment for case-control studies of cancer and herbicides. Am. J. Ind. Med., 18: 285-293, 1990.[Medline]
  46. Moody R. P., Nadeau B. Effect of the mosquito repellent DEET and long-wave ultraviolet radiation on permeation of the herbicide 2,4-D and the insecticide DDT in natural rubber gloves. Am. Ind. Hyg. Assn. J., 53: 436-441, 1992.
  47. Garry V. F., Tarone R. E., Long L., Griffith J., Kelly J. T., Burroughs B. Pesticide appliers with mixed pesticide exposure: G-banded analysis and possible relationship to non-Hodgkin’s lymphoma. Cancer Epidemiol. Biomark. Prev., 5: 11-16, 1996.[Abstract]

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