Occupational Exposures and Hodgkin Lymphoma: Canadian Case ...

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Volume 51, Number 12, December 2009

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Occupational Exposures and Hodgkin Lymphoma: Canadian Case–Control Study Chandima P. Karunanayake, PhD Gayatri V. Singh, PhD John J. Spinelli, PhD John R. McLaughlin, PhD James A. Dosman, MD Helen H. McDuffie, PhD Punam Pahwa, PhD

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Objective: The objective was to study the association between Hodgkin Lymphoma (HL) and occupational exposures related to long-held occupation among males in Canada. Methods: A population-based case– control study of HL was conducted among males stratified by province of residence and age group. Conditional logistic regression was used to fit statistical models. Results: Several factors independently increased the risk of HL. Ever exposure to ionizing radiation from uranium showed a significant association with HL. Men who had smoked cigarettes for 25 years or more were the most likely to develop HL. Exposure to ultraviolet light and diagnosis with measles were negatively associated with HL, whereas diagnosis with shingles increased the risk of HL. Conclusions: The higher risk of developing HL may be associated with exposure to uranium ionizing radiation and years of cigarette smoking. (J Occup Environ Med. 2009;51:1447–1454) From the Canadian Centre for Health and Safety in Agriculture (Dr Karunanayake, Dr Singh, Dr Dosman, Dr Pahwa), College of Medicine, University of Saskatchewan, Saskatoon, Saskatchewan, Canada; Cancer Control Research (Dr Spinelli), British Columbia Cancer Agency, British Columbia, Canada; Population Studies & Surveillance (Dr McLaughlin), Cancer Care, Ontario, Canada, Dalla Lana School of Public Health, University of Toronto, Ontario, Canada, and Samuel Lunenfeld Research Institute, Toronto, Ontario, Canada; and Department of Community Health and Epidemiology (Dr Pahwa), University of Saskatchewan, Saskatoon, Saskatchewan, Canada. Dr McDuffie is deceased. The authors declare no competing financial interests. CPK made contributions to the statistical analysis and manuscript preparation. GVS made contribution to primary data analysis. JJS was the co-investigator and British Columbia representative who participated in the design of the study and who supervised data collection for the province of British Columbia. JRM was the co-investigator and Ontario representative who participated in the design of the study and who supervised data collection for the province of Ontario. JAD’s main contribution was grant writing and questionnaires development. HHM’s main contribution was grant writing, study design, questionnaires development, and study coordination. The concept of including family history variables in this study was HHM’s idea and she prepared the manuscript. JAD and HHM were co-principal investigators of the study. PP was the national coordinator and biostatistician for this study. PP was involved at the grant writing stage, participated in the design of the study, and questionnaires development. PP was the national coordinator and biostatistician for this study. PP trained data managers from the six provinces about data entry process, and supervised every stage of data cleaning. PP made significant contributions in the original statistical analysis required for the manuscript and preparation of the manuscript. All authors read and approved the final manuscript. Address correspondence to: Punam Pahwa, PhD, Canadian Centre for Health and Safety in Agriculture, University of Saskatchewan, Royal University Hospital, 103 Hospital Drive, Saskatoon, SK S7N 0W8, Canada; E-mail: [email protected]. Copyright © 2009 by American College of Occupational and Environmental Medicine DOI: 10.1097/JOM.0b013e3181be6bfe

odgkin lymphoma (HL) is one type of cancers that develops in the lymphatic system. HL constitutes approximately 12% of all lymphomas and the other 88% remaining is referred to as non-Hodgkin’s lymphoma (NHL).1 In Canada, mortality rates are low for HL and have decreased by 4.2% for men and 3.7% for women from 1995 to 2004.2 There is no single known cause for HL. Nevertheless, several factors appear to increase the risk of developing HL, including certain occupational and environmental exposures.3 On the basis of previous work, we categorize occupations into the three groups of 1) risk of developing HL in professions where there may be personal contact with persons,4 – 6 2) persons engaged in particular occupations,7–22 and 3) exposure or contact with particular chemical agents.23–29 The strongest association with HL and occupation was first found by Acheson,11 who reported an increased risk in woodworkers. Some studies demonstrated that farmers were at an elevated risk of mortality and developing HL.16,30,31 Epidemiological studies have reported positive associations between HL and exposure to uranium.29,32 Some studies demonstrated that there is a protective effect of ultraviolet (UV) radiation on lymphoma such as NHL and HL.33,34 Smoking has been reported as an important risk factor for HL.35 In this article, we examined the association between HL and 1) selected long-term occupations, and 2) occupational exposures based on an individual’s occu-

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pational history, and 3) smoking status and years of cigarette smoking.

Methods A summary of the study design and methodology have been reported previously.30,36,37 Briefly, the data were collected between September 1, 1991 and December 31, 1994 for this Canadian population-based case– control study in six provinces of men with an incident first diagnosis of HL. The control subjects were men, aged 18 years and older and frequency matched by age ⫾ 2 years to be comparable with the age distribution of the entire case group (soft tissue sarcoma, HL, NHL, and multiple myeloma) within each province of residence. The study had approximately five matched controls for each HL case. Subjects who were deceased were ineligible as either cases or controls. All participating control subjects were considered in the statistical analysis of each cancer site. Cases were selected from provincial cancer registries, except in the Province of Quebec where hospital records were used. Data were coded using International Classification of Diseases (ICD)-O 2nd edition, except Quebec where the ICD-O 1st edition38 was used. Malignant morphology codes 965–966 were included. A reference pathologist reviewed pathology reports and the tumour tissue slides for the 49% of the HL cases for which specimens could be obtained, and confirmed HL in all but 3.2% of cases. Cases not confirmed as HL were eliminated. Control subjects were selected through provincial health insurance records except in Ontario where telephone list and British Columbia where voter’s lists were used.30,36,37 There were two stages in this study. Stage 1 consisted of a selfadministered postal questionnaire. Stage 2 consisted detailed pesticide exposure information collected via telephone interview. With permission, we modified a pesticide exposure questionnaire developed by Hoar et al39 to create the study ques-

HL and Occupational Exposures

tionnaire. The stage 1 postal questionnaire was used for this article and detailed analysis of pesticide exposures will be in a separate article. We used the postal questionnaire to capture demographic details including smoking history, personal medical history, lifetime occupational history, and specific occupational exposures of interest. Detailed information about occupational history of all full time jobs held by the participant for at least 1 year were listed in the questionnaire. For each job held, the information on job titles and duration of employment were collected.40 A list of occupational exposures that had been linked to HL or to one of the other three types of cancers (NHL, soft tissue sarcoma, multiple myeloma) that we studied simultaneously was grouped into exposures from dusts, coal products, printing products, paints, metals, radiation, and miscellaneous. The question “Have you ever been exposed at work to any of the following exposures” was used to collect the information of exposures. Therefore, the responses for all of the exposures were “ever or never” exposed, which limited us to explore the dose– response relationships.

Statistical Analysis Data entry was performed using a custom designed SPSS-data entry program (SPSS Inc., Chicago, IL). Results were presented as frequencies for categorical variables and as mean and standard deviation (SD) for continuous variables for cases and controls. We obtained information about the duration of employment (measured in years) for each individual. The specific occupations were selected for analysis, if the occupant worked in a particular occupation at least for 1 year and if at least 2% of cases were reported for that occupational category. On the basis of that information, we derived a new variable that we called “longheld” occupations. Occupations were defined as “long-held” occupation if respondents worked for 10 years or

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more in that occupation. Years of cigarette smoking was defined as the total number of years smoked and ex-smokers and current smokers have greater than zero value for this variable. Others considered as nonexposed. Logistic regression was used to perform the case-only analysis to assess differences between subtypes of HL and various explanatory variables. Conditional logistic regression was used to compute adjusted odds ratios (OR) and 95% confidence intervals (95% CI) for the case– control analysis. Single variable conditional logistic regression was conducted to determine the association between each explanatory variable (ever or never exposed to that “specific” exposure) and the HL outcome. Also combined OR was calculated for major exposure groups from dusts, coal products, printing products, paints, metals, radiation, and miscellaneous if the person ever or never exposed to any of the exposures from that major group. Based on the model building procedure, explanatory variables that were significant (P ⱕ 0.20) from the single variable analysis were selected for the multivariate model. Statistically significant (P ⱕ 0.05) variables and important explanatory variables were considered for the final multivariate model, adjusting for age and Province of residence.

Ethical Approval The letters of informed consent, the questionnaires and other written material provided to potential subjects were submitted to and approved by each of the relevant agencies in each province. For Saskatchewan, the University of Saskatchewan Biomedical Research Ethics Board (#89- 12); for British Columbia, the University of British Columbia Behavioral Research Ethics Board (#B91- 185); for Quebec, the University of McGill Human Ethics. Board; for Alberta, the University of Alberta Health Research Ethics Board (Biomedical Panel); for Manitoba, the University of Manitoba

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Biomedical Research Ethics Board; and for Ontario, the University of Toronto Health Sciences Research Board approved the study protocol. All information that could be used to identify individual study participants remained within the province of origin under the control of each province’s principal investigator. After receiving permission to contact a potential case by the attending physician, a letter of informed consent and a questionnaire was mailed. Relatives of cases known to be deceased at ascertainment were not contacted because of the need to obtain detailed information concerning occupation and occupational exposures including a variety of types of pesticides. Control subjects were contacted directly by mail.

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Case–Control Analysis

investigate whether or not there was a dose–response relationship between duration of cigarette smoking and HL. A dose–response relationship between years of cigarette smoking and incidence of HL was observed. Those who smoked (ex or current smokers) for 25 or more years were 1.9 times more likely to be diagnosed with HL than nonsmokers (Table 1). Personal medical history of cases and populationbased controls are summarized and compared in Table 1. A previous diagnosis of shingles (OR [95% CI] ⫽ 2.16 [1.31 to 3.56]) was positively associated with risk of HL. A previous diagnosis of measles was negatively associated with risk of HL (OR [95% CI] ⫽ 0.76 [0.57 to 1.00]). A previous diagnosis of infectious mononucleosis statistically

The analysis included responses from 316 cases with HL and 1506 control subjects. The mean age ⫾ SD of cases was 40.2 ⫾ 15.9 years ranging from 18 to 88 years and of the controls, 54.1 ⫾ 16.4 years ranging from 18 to 92 years. Forty-four point (6%) of HL cases were younger than 35 years. Table 1 shows the characteristics of the study participants stratified by HL case– control status. There were no significant differences between HL cases and controls with respect to their smoking status: current smokers (OR [95% CI] ⫽ 1.28 [0.90 to 1.83]); ex-smokers (OR [95% CI] ⫽ 1.36 [0.97 to 1.90]). Years of cigarette smoking using four categories: no exposure, ⬍15 years, 15 to 24 years, and 25 or more years were used to

Results Case-Only Analysis Initially, we conducted a casesonly subtype analysis. Our data determined that the 316 HL cases consisted of 50.0% nodular sclerosis, 19.9% mixed cellularity, 21.2% miscellaneous HL, 6.7% lymphocytic predominance, and 1.9% lymphocytic depletion. We then divided the subtypes into two groups: 1) nodular sclerosis; and 2) others subtypes. For explanatory variables age, smoking status, years of smoking, diagnosed with shingles, diagnosed with measles, diagnosed with infectious mononucleosis, exposure to uranium, exposure to UV light and longheld occupations logistic regression analysis was performed to assess differences between the two groups. The dependent variable of this analysis was subtype group: nodular sclerosis and others subtypes. The results indicated that there was no significant difference exists between nodular sclerosis versus others subtypes (data not shown). Therefore, we considered HL subtypes as a whole, and further case– control analysis was conducted.

TABLE 1 Characterization of Study Participants Stratified by HL Case–Control Status: Demographics and Selected Medical History

Demographics Ever lived/worked on a farm, n (%) Yes No Smoking status, n (%)† Current smoker Ex-smoker Non-smoker Years of smoking No exposure ⬎15 15–24 ⱕ25 Medical history Previous diagnosis of cancer, n (%) Yes No Diagnosed with shingles, n (%) Yes No Diagnosed with measles, n (%) Yes No Diagnosed with infectious mononucleosis, n (%) Yes No

HL (N ⴝ 316)

Controls (N ⴝ 1506)

ORadj (95% CI)*

117 (37.0) 199 (63.0)

673 (44.7) 833 (55.3)

0.89 (0.67–1.18) 1.00

80 (25.8) 102 (32.9) 128 (41.3)

298 (20.2) 648 (44.0) 526 (35.7)

1.28 (0.90 –1.83) 1.36 (0.97–1.90) 1.00

139 (43.9) 57 (18.0) 51 (16.1) 69 (21.8)

598 (39.9) 198 (13.2) 211 (14.1) 490 (32.7)

1.00 0.99 (0.66 –1.46) 1.36 (0.90 –2.06) 1.86 (1.24–2.79)

10 (3.2) 306 (96.8)

87 (5.8) 1419 (94.2)

1.27 (0.62–2.60) 1.00

28 (8.9) 288 (91.1)

87 (5.8) 1419 (94.2)

2.16 (1.31–3.56) 1.00

153 (48.4) 163 (51.6)

888 (59.0) 618 (41.0)

0.76 (0.57–1.00) 1.00

23 (7.3) 293 (92.7)

48 (3.2) 1458 (96.8)

1.30 (0.74 –2.27) 1.00

*Adjusted for age (5 yr groups) and province. †40 missing. Statistically significant results are bold.

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TABLE 2 Adjusted OR and 95% CI for Various Long-Held Occupations (Job Titles) Job Title (Code) Accountant Clerk Driver Farmer Engineer Manager Salesman

HL Cases n (%)

Controls n (%)

ORadj* (95% CI)†

9 (2.8) 8 (2.5) 10 (3.2) 16 (5.1) 7 (2.2) 13 (4.1) 8 (2.5)

41 (2.7) 29 (1.9) 48 (3.2) 106 (7.0) 37 (2.5) 96 (6.4) 52 (3.4)

1.70 (0.77–3.72) 2.19 (0.94 –5.11) 1.35 (0.62–2.93) 0.95 (0.51–1.76) 1.34 (0.56 –3.24) 0.85 (0.45–1.60) 1.24 (0.56 –2.72)

*All ORs were adjusted for age and province of residence.

significantly was not associated with HL after adjusting for age and province of residence. Nevertheless, ␹2 test show a significant association (␹2 ⫽ 11.674, df ⫽ 1, P ⫽ 0.0006) between diagnosis of mononucleosis and incidence of HL. There was no significant association between HL cases and controls with respect to whether they ever lived or worked on a farm or with history of cancer.

Single Variable Conditional Logistic Regression Tables 2 and 3 show the single variable conditional logistic regression analyses results. Table 2 shows the distribution of “long-held” occupations during a lifetime stratified by case– control status. None of the long-held occupations was associated with risk of HL. The forty-five, specific occupational exposures reported were grouped into six classes: dusts; coal products; printing; paints; metals; and miscellaneous. Exposure to grain dust and a sour gas were associated with decreased risk of HL: OR (95% CI) ⫽ 0.67 (0.47 to 0.95) and OR (95% CI) ⫽ 0.47 (0.25 to 0.88), respectively (Table 3). Combined ORs for these six exposure classes were not significantly associated with HL. Ever exposed to radiation was further divided into two classes: nonionizing radiation and ionizing radiation. Ever exposed to ultra violet light, horticultural grow lights and unshielded microwaves were grouped into non-ionizing radiation, and ever exposed to radium and ex-

posed to uranium were grouped into ionizing radiation. There was a positive association between occupational exposure to uranium (ionizing radiation) and HL (OR [95% CI] ⫽ 2.58 [1.08 to 6.19]) and an inverse association between occupational exposure to UV light (OR [95% CI] ⫽ 0.62 [0.40 to 0.96]). Combined ORs for ionizing radiation (OR [95% CI] ⫽ 2.42 [1.12 to 5.24]) and non-ionizing radiation (OR [95% CI] ⫽ 0.62 [0.41 to 0.92]) showed a similar association to individual exposures (ultra violet light and uranium) and HL.

Multivariate Conditional Logistic Regression Table 4 shows the results of the multivariate conditional logistic regression model, adjusted for age and province of residence. The variables that remained statistically significantly associated with increased risk of HL were exposed to uranium (OR [95% CI] ⫽ 2.92 [1.19 to 7.18]), diagnosis with shingles (OR [95% CI] ⫽ 2.20 [1.33 to 3.62]), and 25 years or more of cigarette smoking (OR [95% CI] ⫽ 1.84 [1.22 to 2.78]). There was an inverse association with HL and exposure to ultraviolet light (OR [95% CI] ⫽ 0.61 [0.39, 0.94]) and diagnosis with measles (OR [95% CI] ⫽ 0.71 [0.53, 0.94]). A dose–response relationship between years of cigarette smoking and incidence of HL was observed.

Discussion We investigated several medical histories and the risk of HL. Several

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studies have reported an increased risk of HL after infectious mononucleosis.40 – 43 There was a 3-fold increased risk of HL43 to persons who had a history of infectious mononucleosis. Infectious mononucleosis is associated with exposure to EpsteinBarr virus. We could not verify this information, because we did not collect it. Nevertheless, diagnosis of infectious mononucleosis entered into the multivariable conditional logistic regression as a clinically important risk factor. Some studies have reported that diagnosis of shingles is usually a consequence of HL, because of their weakened immune system. Tavani et al44 reported that with a history of herpes zoster (commonly known as shingles), there was a 3-fold risk of having HL. Our study also confirms this result and showed a positive association with diagnosis of shingles and HL. Benharroch et al45 found an association between presence of measles virus antigens and occurrence of HL. In contrast to this, our study reported that diagnosed with measles negatively associated with HL. Therefore further investigations are needed to confirm our findings. Our study investigated the association between HL and several occupations, occupational exposures, and cigarette smoking. We did not observe any significant association with increased risk of developing HL and any long-held occupation. In contrast to other studies,10,21,22,46 no association was found here between exposure to wood dust or wood related occupations such as carpenter and HL. Several earlier studies4,5 reported that school teachers were at a high risk of HL, but we did not observe this association based on our data. Previous studies have also reported that farmers exposed to pesticides and animal-related activities might have a higher chance of developing HL.16,20,39,47 In contrast to these, other studies48 –50 reported a negative or no association between the occupation of farming or being a pesticides applicators and risk of de-

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TABLE 3 Adjusted OR and 95% CI for Various Occupational Exposures

Exposure Dusts Cement dust Fiberglass dust Coal dust Soil/field dust Whey dust Paper dust Wood dust Coke dust Stone dust Grain dust Sand Cardboard dust Metal dust Coal products Pitch Asphalt Crude petroleum Tar/tar products Printing Printing inks Printing fluid Paints Paints, dyes Metals Arsenic Nickel Cadmium Zinc Mercury Chromium Iron Lead Aluminum Miscellaneous Asbestos Used motor oil Diesel exhaust Cutting oils Cleaning fluids Preservatives Chlorine Hair permanent solutions Sour gas Wood smoke Lubricants Solvents Ether Moldy grain/forage Hair dyes Cyanide Non-ionizing radiation Ultra violet light Horticultural grow lights Unshielded microwaves Ionizing radiation Radium Uranium

HL Control Combined ORadj (N ⴝ 316) (N ⴝ 1506) N* (%) n* (%) ORadj (95% CI)† (95% CI)† 1.01 (0.76 –1.34) 107 (33.9) 89 (28.2) 19 (6.0) 78 (24.7) 7 (2.2) 64 (20.2) 114 (36.1) 15 (4.7) 43 (13.6) 56 (17.7) 78 (24.7) 51 (16.1) 94 (29.7)

432 (28.7) 319 (21.2) 149 (9.9) 375 (24.9) 38 (2.5) 180 (11.9) 445 (29.5) 58 (3.8) 173 (11.5) 347 (23.0) 303 (20.1) 170 (11.3) 368 (24.4)

1.01 (0.76 –1.34) 1.15 (0.85–1.57) 0.82 (0.48 –1.39) 0.78 (0.57–1.07) 0.82 (0.34 –1.97) 1.34 (0.95–1.90) 1.00 (0.76 –1.33) 1.30 (0.70 –2.43) 1.03 (0.70 –1.53) 0.67 (0.47–0.95) 1.04 (0.76 –1.42) 0.95 (0.65–1.38) 0.99 (0.74 –1.33)

11 (3.5) 37 (11.7) 16 (5.1) 42 (13.3)

38 (2.5) 142 (9.4) 84 (5.6) 143 (9.5)

2.01 (0.96 – 4.22) 1.17 (0.77–1.79) 0.82 (0.45–1.51) 1.18 (0.79 –1.77)

36 (11.4) 28 (8.9)

134 (8.9) 96 (6.4)

0.93 (0.61–1.44) 1.17 (0.72–1.89)

105 (33.2)

442 (29.3)

0.90 (0.68 –1.20)

9 (2.8) 19 (6.0) 11 (3.5) 19 (6.0) 15 (4.7) 13 (4.1) 25 (7.9) 32 (10.1) 59 (18.7)

28 (1.9) 85 (5.6) 55 (3.6) 103 (6.8) 63 (4.2) 58 (3.8) 100 (6.6) 182 (12.1) 220 (14.6)

1.48 (0.63–3.48) 0.89 (0.51–1.55) 0.74 (0.36 –1.50) 0.76 (0.44 –1.31) 1.06 (0.56 –2.00) 0.76 (0.39 –1.48) 0.97 (0.59 –1.58) 0.66 (0.43–1.02) 0.97 (0.68 –1.38)

52 (16.5) 99 (31.3) 118 (37.3) 61 (19.3) 100 (31.6) 7 (2.2) 36 (11.4) 11 (3.5) 14 (4.4) 71 (22.5) 116 (36.7) 129 (40.8) 44 (13.9) 32 (10.1) 7 (2.2) 5 (1.6)

237 (15.7) 400 (26.6) 464 (30.8) 277 (18.4) 419 (27.8) 21 (1.4) 202 (13.4) 33 (2.2) 92 (6.1) 371 (24.6) 477 (31.7) 516 (34.3) 170 (11.3) 176 (11.7) 33 (2.2) 36 (2.4)

0.98 (0.68 –1.40) 0.87 (0.65–1.17) 1.11 (0.83–1.47) 0.83 (0.59 –1.17) 0.81 (0.61–1.10) 1.83 (0.72– 4.69) 0.68 (0.45–1.03) 1.14 (0.53–2.46) 0.47 (0.25–0.88) 0.81 (0.59 –1.11) 0.94 (0.71–1.25) 0.93 (0.70 –1.23) 0.86 (0.57–1.28) 0.76 (0.48 –1.19) 1.00 (0.41–2.40) 0.62 (0.23–1.69)

35 (11.1) 9 (2.8) 4 (1.3)

151 (10.0) 39 (2.6) 25 (1.7)

0.62 (0.40–0.96) 0.83 (0.37–1.87) 0.48 (0.15–1.57)

4 (1.3) 10 (3.2)

12 (0.8) 18 (1.2)

2.24 (0.62– 8.08) 2.58 (1.08–6.19)

1.01 (0.73–1.42)

0.97 (0.64 –1.45)

0.90 (0.68 –1.20) 0.75 (0.55–1.02)

0.92 (0.69 –1.22)

0.62 (0.41–0.92)

2.42 (1.12–5.24)

*n and % are given for the “yes” responses. †All ORs were adjusted for age and province of residence. Statistically significant results are bold.

veloping HL. Our study did not confirm an association between farming and HL. The negative associations of exposure to grain dust and exposure to sour gas were not reported in literature. Therefore, these two associations should be viewed with caution. These negative associations could be due to immune stimulation or viral exposure and further investigation is needed to confirm these results. There have been reports of association between HL and ionizing radiation. Gilbert et al51 reported a positive association between low-dose exposure to ionizing radiation and risk of HL. In our study, participants reported any form of exposure to radium or exposure to uranium at work. In our study, we found that exposure to uranium (ionizing radiation) is significantly associated with increase risk of HL. This finding is in agreement with those of Pinkerton et al29 and Archer et al.52 Uranium exposure can be leads to potential chemical and radiological hazards. Poorly soluble uranium compounds are cleared slowly from the lungs and pose a potential internal radiation hazard.29 Therefore, it is important to look at the duration of exposure, because insoluble uranium compounds are accumulating in the lymph nodes. Lack of information on duration of exposure is one of the limitations of our study. UV radiation is a type of nonionizing radiation.53 Recent studies suggest that there is a protective or no effect between exposure to UV light and HL.33,34,54 Our study confirmed this association between exposure to UV light and HL. A European multicenter case– control study33 reported that the exposure to normal UV radiation at work was not associated with HL. Weihkopf et al54 reported that vacations in sunny climates were significantly negatively associated with HL. In Weihkopf et al’s54 article, the number of cumulative days exposed to sun at each location in the past was considered for analysis. In the same report, they

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TABLE 4 Multivariate Model of the Important Covariates Associated With HL Variable

OR (95% CI)*

Diagnosed with shingles (yes) Diagnosed with measles (yes) Diagnosed with infectious mononucleosis (yes) Ever exposed to uranium (ionizing radiation) (yes) Ever exposed to ultra violet light (non-ionizing radiation) (yes) Years of cigarette smoking (reference to no exposure) ⬎15 15–24 ⱕ25

2.20 (1.33–3.62) 0.71 (0.53–0.94) 1.44 (0.81–2.56) 2.92 (1.19–7.18) 0.61 (0.39–0.94) 0.98 (0.66 –1.46) 1.33 (0.87–2.02) 1.84 (1.22–2.78)

*All ORs were adjusted for age and province of residence. Statistically significant at 5% level results are bold.

mentioned that occupational sun light UV exposure was not significantly associated with HL. Therefore, UV light exposure should be viewed with caution until replicated with information on duration of exposure to UV light. Results from a large population-based case– control study from Denmark and Sweden34 observed that there is a negative association between sun light UV exposure and risk of HL and nonHL. Therefore, further confirmatory data from other epidemiological studies to confirm the negative association of UV light exposure and risk of HL are required. Previous studies of associations between smoking and HL are inconsistent. Briggs et al35 suggested that smoking is an important risk factor for HL. Other studies55–57 support the association, but there are frequently limitations of analysis, including absence of dose–response effects and small sample sizes. In our study, we looked at dose–response effects using years of cigarette smoking in relation to the risk of HL. Similar to Stagnano et al’s findings,55 our findings indicates that being an ever-smoker (ex and current smokers) who smoked 25 years placed more individuals at higher risk of developing HL compared with non smokers. A major strength of this study is the large number of cases and controls with approximately five controls per case from six Canadian

provinces. A complete occupational history and extensive list of potential occupational exposures were collected from the questionnaire. There are, however, several limitations in this study. One is the potential for recall bias and misclassification of occupational history. Also, occupational exposures in this study were self-reported, and thus might bias results. The duration of occupational exposures was not recorded. Therefore, it is difficulty to assess the dose–response relationship of occupational exposures and HL. Because of budget constraints, women were excluded from the study. The response rates are low; of 68.4% for cases and 48% for controls. There were several reasons not to participate in the study such as death, change of address, and refusal for both cases and controls. Because of the large number of jobs and exposures assessed there was a possibility of false-positive findings.

Conclusions Our results support previous findings of an association between HL and occupational exposures and environmental risk factors. In our analysis, an increased risk of developing HL is associated with exposure to uranium ionizing radiation and years of cigarette smoking. The risk of HL increased with the duration of smoking. Exposure to UV light at work showed a protective effect on developing HL.

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Acknowledgment We are grateful for the financial support of the National Health Research and Development Program of Health Canada, the British Columbia Health Research Foundation and the Canadian Centre for Health and Safety in Agriculture (formerly Centre for Agricultural Medicine), University of Saskatchewan. Special thanks go to the collaborators Drs. G. Theriault, D. Robson, S. Fincham, L. Skinnider, D. White, T. To and Late N.W. Choi. Also, the authors are indebted to the following members of the Advisory Committee: Drs. G.B. Hill, A. Blair, L. Burmeister, H. Morrison, R. Gallagher, and D. White. We are also grateful to the provincial coordinators, data managers and students (T. Switzer, M. Gantefor, J. Welykholowa, J. Ediger, I. Fan, M. Ferron, E. Houle, S. de Freitas, K. Baerg, L. Lockinger, E. Hagel, P. Wang, G. Dequiang, J. Hu C. Maguire, and J. Thiessen). We acknowledge the contributions of Dr. G. Theriault and Dr. N. Choi who supervised the collection of data in Quebec and Manitoba respectively. We extend our gratitude to Dr. L. Skinnider for reviewing the tumour tissues and to the hospitals that provided the tissues. The contribution of all the case and control volunteers who donated their time to this study and the organizations who permitted access to their records was invaluable.

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