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American Journal of Epidemiology logoLink to American Journal of Epidemiology
. 2008 Dec 4;169(2):176–185. doi: 10.1093/aje/kwn300

Occupational Exposure to Solvents and Risk of Non-Hodgkin Lymphoma in Connecticut Women

Rong Wang, Yawei Zhang, Qing Lan, Theodore R Holford, Brian Leaderer, Shelia Hoar Zahm, Peter Boyle, Mustafa Dosemeci, Nathaniel Rothman, Yong Zhu, Qin Qin, Tongzhang Zheng
PMCID: PMC2727253  PMID: 19056833

Abstract

A population-based case-control study involving 601 incident cases of non-Hodgkin lymphoma (NHL) and 717 controls was conducted in 1996–2000 among Connecticut women to examine associations with exposure to organic solvents. A job-exposure matrix was used to assess occupational exposures. Increased risk of NHL was associated with occupational exposure to chlorinated solvents (odds ratio (OR) = 1.4, 95% confidence interval (CI): 1.1, 1.8) and carbon tetrachloride (OR = 2.3, 95% CI: 1.3, 4.0). Those ever exposed to any organic solvent in work settings had a borderline increased risk of NHL (OR = 1.3, 95% CI: 1.0, 1.6); moreover, a significantly increased risk was observed for those with average probability of exposure to any organic solvent at medium-high level (OR = 1.5, 95% CI: 1.1, 1.9). A borderline increased risk was also found for ever exposure to formaldehyde (OR = 1.3, 95% CI: 1.0, 1.7) in work settings. Risk of NHL increased with increasing average intensity (P = 0.01), average probability (P < 0.01), cumulative intensity (P = 0.01), and cumulative probability (P < 0.01) level of organic solvent and with average probability level (P = 0.02) and cumulative intensity level of chlorinated solvent (P = 0.02). Analyses by NHL subtype showed a risk pattern for diffuse large B-cell lymphoma similar to that for overall NHL, with stronger evidence of an association with benzene exposure. Results suggest an increased risk of NHL associated with occupational exposure to organic solvents for women.

Keywords: case-control studies; lymphoma, non-Hodgkin; risk factors; solvents


Non-Hodgkin lymphoma (NHL) is the fifth most common cancer in the United States (1). It was estimated that more than 63,190 persons would be diagnosed with NHL and 18,680 would die from the disease in 2007 in the United States (2). From 1973 to the mid-1990s, the incidence of NHL steadily increased in the United States by 3%–4% annually (36). While NHL related to acquired immunodeficiency syndrome has declined sharply since the mid-1990s, NHL incidence not associated with acquired immunodeficiency syndrome has continued to increase (6), particularly for several major subtypes of NHL and in certain subpopulations (7). The risk of NHL has been associated with various inherited or acquired immunosuppressions; these severe deficiencies are relatively rare and cannot explain all of the increase in NHL incidence. Thus, the etiology of NHL is largely unknown.

Earlier epidemiologic studies have shown that occupational exposures may be associated with an increased risk of NHL. Increased risks of NHL were observed for workers in various industries and occupations, such as agriculture (812), metal production (10, 13), food (10, 14), pesticide applicators (15), painters and printers (13, 16), funeral directors and embalmers (13, 17), plumbers (13), dry cleaners (13), engineers, mechanics, and leather workers (10, 14). Occupational exposure to solvents has been suggested to be at least part of the reason for the observed increased risk; the data, however, linking solvent exposure to NHL risk have been inconsistent (13, 1821).

One reason for the inconsistent results could be misclassification of exposure in early epidemiologic studies. Job titles have been widely used as surrogate measurements for occupational exposure to solvents. Under the same job title, however, workers may have very different exposure experiences or exposure levels for various chemicals. Use of job titles as surrogates for specific occupational solvent exposures could result in at least nondifferential exposure misclassification and thus underestimate the underlying associations between occupational solvent exposure and NHL risk.

In this population-based case-control study of NHL in Connecticut women, we used a job-exposure matrix to assess solvent exposure instead of relying on only job titles as surrogate measurements for the exposures of interest. The job-exposure matrix developed by industrial hygienists at the National Cancer Institute allows for semiquantitative measurements of the association between occupational exposures and NHL risk.

MATERIALS AND METHODS

As described elsewhere (2226), participants in this population-based case-control study were women aged 21–84 years recruited in Connecticut from 1996 to 2000. Briefly, incident NHL cases were histologically confirmed, were diagnosed in Connecticut, and had no history of any type of cancer (except nonmelanoma skin cancer). A total of 601 of 832 identified incident NHL cases (72%) completed in-person interviews. Controls with Connecticut addresses were recruited by random digit dialing from among women aged less than 65 years or by random selection from Centers for Medicare and Medicaid Service files for women aged 65 years or older. The participation rate for controls identified via random digit dialing was 69%, and it was 47% for Health Care Financing Administration controls. In-person interviews were completed for 717 controls. Cases and controls were frequency matched within 5-year age groups. All procedures were performed in accordance with a protocol approved by the Human Investigations Committees at Yale University, the Connecticut Department of Public Health, and the National Cancer Institute.

A standardized, structured questionnaire was used to collect information on lifetime occupational history and other major suspected risk factors for NHL through in-person interviews. Participants were asked to report jobs held for a year or longer during their lifetime. For each reported job, detailed information was elicited on job title, activities or duties, company name, type of business, year begun, and year ended. All participants reported their lifetime job history. On average, both cases and controls held 3–4 jobs during their lifetime. The average numbers of years worked were 27.4 for cases and 27.0 for controls. Jobs were coded according to the 1980 Standard Occupational Classification Manual (27) and the 1987 Standard Industry Classification Manual (28) scheme.

Exposure to organic solvents and formaldehyde associated with each job was assessed by linking the coded occupational data with a job-exposure matrix updated by industrial hygienists at the National Cancer Institute (29, 30). We assessed exposure to any organic solvent and to benzene, any chlorinated solvent, and 7 specific chlorinated solvents—dichloroethylene, chloroform, dichloroethane, dichloromethane, methyl chloride, trichloroethylene, and carbon tetrachloride—individually.

The job-exposure matrix was applied as follows: first, every occupation and industry was assigned a semiquantitative estimate of intensity and probability according to a scale of 0–3 (0 = none, 1 = low, 2 = medium, and 3 = high exposure). Intensity was estimated on the basis of expected exposure level and frequency of the specific substance for a worker in that industry or occupation. Exposure probability is the likelihood that the specific substance is used by a worker in a given industry or occupation. Second, occupational and industrial exposure scores were combined by using the following algorithms (31): If the exposure depended on occupation only, then the exposure score for the occupation-industry combination was the square of occupational exposure estimation, that is, intensity = intensity2occupation, and probability = probability2occupation. If the exposure was dependent on occupation and industry, then the exposure score for the occupation-industry combination was the product of the occupational exposure estimation and the industrial exposure estimation, that is, intensity = intensityoccupation × intensityindustry, and probability = probabilityoccupation × probabilityindustry. Third, for each subject, this information was combined with duration data to estimate 1) ever exposure status, that is, whether the exposure estimate was ever greater than 0 during the subject's lifetime; 2) cumulative intensity of exposure, defined as the sum of (intensity index for each job × correspondent job duration); 3) cumulative probability of exposure, that is, the sum of (probability index for each job × correspondent job duration); 4) average intensity of exposure, defined as the sum of (intensity index for each job × correspondent job duration)/exposure duration; and 5) average probability of exposure, that is, the sum of (probability index for each job × correspondent job duration)/exposure duration. The final scores for average exposure intensity and probability were categorized as never exposed (0), low (<3), medium (35), and high intensity/probability (≥6). Exposure within 1 year before diagnosis/interview was excluded from the exposure assessment. During the exposure assignment process, the disease status of individuals was masked.

Odds ratios were used to estimate the associations between exposure to solvents and NHL risk. Unconditional logistic regression models, adjusted for age (continuous), family history of hematopoietic cancers (yes/no), alcohol consumption (ever/never), and race (white, black, other) were used to estimate odds ratios and their respective 95% confidence intervals. Adjustment for other variables, such as level of education, annual family income, tobacco smoking, and medical history of immune-related disease, did not result in material changes for the observed associations and thus were not included in the final method. Polytomous logistic regression was used to evaluate the association between histologic subtype of NHL and exposure (32). The cumulative exposure variables were divided into tertiles based on the distributions for controls and were analyzed as categorical variables. Whenever possible, we treated these exposures as continuous variables to test for linear trends. Heterogeneity in risk estimates between NHL subtypes was assessed by use of a Wald χ2 test with inclusion of an interaction term in the dichotomous and polytomous logistic regression models under the null hypothesis of no difference in risk estimates between subtypes. All tests of statistical significance were 2 sided, with an α level of 0.05. All statistical analyses were conducted by using SAS version 9.1 software (SAS Institute, Inc., Cary, North Carolina).

RESULTS

As shown in Table 1, ever exposure to chlorinated solvents increased the risk of NHL by 40% (95% confidence interval (CI): 1.1, 1.8). For specific chlorinated solvents, exposure to carbon tetrachloride was associated with a 2.3-fold increased risk of NHL (95% CI: 1.3, 4.0). Borderline significantly increased risks of NHL were found for those ever exposed to any organic solvent (odds ratio (OR) = 1.3, 95% CI: 1.0, 1.6) and formaldehyde (OR = 1.3, 95% CI: 1.0, 1.7). A nonsignificantly increased risk was linked to occupational exposure to benzene.

Table 1.

Solvent Exposure and Risk of Non-Hodgkin Lymphoma Among Connecticut Women, 1996–2000

Exposure No. of Controls No. of Cases ORa 95% CI
Any organic solvent
    Never 433 331
    Ever 284 270 1.3 1.0, 1.6
Benzene
    Never 589 481
    Ever 128 120 1.1 0.9, 1.5
Formaldehyde
    Never 516 398
    Ever 201 203 1.3 1.0, 1.7
Chlorinated solvents
    Never 530 405
    Ever 187 196 1.4 1.1, 1.8
Chloroform
    Never 670 566
    Ever 47 35 0.9 0.6, 1.5
Carbon tetrachloride
    Never 698 565
    Ever 19 36 2.3 1.3, 4.0
Dichloromethane
    Never 671 549
    Ever 46 52 1.5 1.0, 2.3
Dichloroethane
    Never 659 543
    Ever 58 58 1.3 0.9, 1.9
Methyl chloride
    Never 660 545
    Ever 57 56 1.2 0.8, 1.8
Trichloroethylene
    Never 638 524
    Ever 79 77 1.2 0.9, 1.8

Abbreviations: CI, confidence interval; OR, odds ratio.

a

Adjusted for age (continuous), family history of hematopoietic cancers (yes, no), alcohol consumption (yes, no), and race (white, black, other).

Table 2 presents the association between solvent exposure and the risk of NHL by average intensity and by average probability. A significantly increased risk of NHL was observed for those with average probability of exposure to any organic solvent at a medium-high level (OR = 1.5, 95% CI: 1.1, 1.9). Those exposed to chlorinated solvent with average intensity at a medium-high level had a significantly increased risk of NHL (OR = 1.5, 95% CI: 1.1, 2.1). We observed borderline increased risks of NHL for those with exposure to any organic solvent at a medium-high average intensity level, to formaldehyde at a low average intensity or probability level, to chlorinated solvent at a low average probability level, and to dichloromethane at a low average probability level. The risk of NHL increased with the average probability or average intensity level of any organic solvent and with average probability level of chlorinated solvent. A 2.3-fold significantly increased risk of NHL was observed for those exposed to carbon tetrachloride at a low average intensity (95% CI: 1.2, 4.5) or a low average probability level (95% CI: 1.3, 4.0); in addition, the risk of NHL increased with average probability level of carbon tetrachloride. However, no participant was exposed to carbon tetrachloride on average at a medium-high probability level.

Table 2.

Solvent Exposure and Risk of Non-Hodgkin Lymphoma by Average Exposure Intensity and Average Exposure Probability Among Connecticut Women, 1996–2000

Exposure Intensity
Probability
No. of Controls No. of Cases ORa 95% CI No. of Controls No. of Cases ORa 95% CI
Any organic solvent
    Never 433 331 433 331
    Low 190 169 1.2 0.9, 1.5 156 131 1.1 0.8, 1.5
    Medium-high 93 101 1.4 1.0, 2.0 127 139 1.5 1.1, 1.9
    P for trend 0.01 <0.01
Benzene
    Never 589 481 589 481
    Low 94 80 1.0 0.7, 1.4 53 40 0.9 0.6, 1.4
    Medium-high 34 40 1.5 0.9, 2.4 75 80 1.3 0.9, 1.8
    P for trend 0.05 0.05
Formaldehyde
    Never 516 398 516 398
    Low 120 129 1.4 1.0, 1.8 166 165 1.3 1.0, 1.7
    Medium-high 81 74 1.2 0.8, 1.7 35 38 1.4 0.9, 2.3
    P for trend 0.21 0.11
Chlorinated solvents
    Never 530 405 530 405
    Low 108 107 1.3 0.9, 1.7 145 152 1.4 1.0, 1.8
    Medium-high 79 89 1.5 1.1, 2.1 42 44 1.5 0.9, 2.3
    P for trend 0.02 0.21
Chloroform
    Never 670 566 670 566
    Low 28 21 0.9 0.5, 1.7 14 8 0.8 0.3, 1.8
    Medium-high 19 14 0.9 0.4, 1.8 33 27 1.0 0.6, 1.7
    P for trend 0.75 0.94
Carbon tetrachloride
    Never 698 565 698 565
    Low 13 26 2.3 1.2, 4.5 19 36 2.3 1.3, 4.0
    Medium-high 6 10 2.2 0.8, 6.3 0 0
    P for trend 0.05 0.01
Dichloromethane
    Never 671 549 671 549
    Low 33 37 1.5 0.9, 2.4 41 48 1.6 1.0, 2.4
    Medium-high 13 15 1.6 0.7, 3.3 5 4 1.2 0.3, 4.4
    P for trend 0.11 0.34
Dichloroethane
    Never 659 543 659 543
    Low 55 57 1.3 0.9, 1.9 51 50 1.2 0.8, 1.9
    Medium-high 3 1 0.4 0.0, 4.2 7 8 1.5 0.5, 4.1
    P for trend 0.42 0.33
Methyl chloride
    Never 660 545 660 545
    Low 51 52 1.3 0.8, 1.9 49 49 1.2 0.8, 1.9
    Medium-high 6 4 1.0 0.3, 3.4 8 7 1.2 0.4, 3.4
    P for trend 0.68 0.26
Trichloroethylene
    Never 638 524 638 524
    Low 71 64 1.1 0.8, 1.6 48 43 1.1 0.7, 1.8
    Medium-high 8 13 2.2 0.9, 5.4 31 34 1.4 0.9, 2.4
    P for trend 0.06 0.37

Abbreviations: CI, confidence interval; OR, odds ratio.

a

Adjusted for age (continuous), family history of hematopoietic cancers (yes, no), alcohol consumption (yes, no), and race (white, black, other).

Table 3 illustrates the results adjusted by both average exposure intensity and probability. Those women exposed to any organic solvent at both medium-high average intensity and medium-high average probability levels had a significantly increased risk (OR = 1.5, 95% CI: 1.1, 2.1). For those exposed to formaldehyde, a significantly elevated risk was observed at only a low average intensity and low average probability level (OR = 1.4, 95% CI: 1.1, 1.9). Low average probability of exposure to chlorinated solvent accompanied by medium-high average intensity also significantly increased the risk of NHL (OR = 1.7, 95% CI: 1.1, 2.4). A 2.3-fold increased risk of NHL was observed for those exposed to carbon tetrachloride at both a low average probability and a low average intensity level (95% CI: 1.2, 4.5).

Table 3.

Solvent Exposure and Risk of Non-Hodgkin Lymphoma by Both Average Exposure Intensity and Average Exposure Probability Among Connecticut Women, 1996–2000

Exposure Low Probability
Medium and High Probability
No. of Controls No. of Cases ORa 95% CI No. of Controls No. of Cases ORa 95% CI
Any organic solvent
    Low intensity 151 129 1.1 0.9, 1.5 39 40 1.4 0.9, 2.2
    Medium and high intensity 5 2 0.5 0.1, 2.7 88 99 1.5 1.1, 2.0
Benzene
    Low intensity 46 30 0.8 0.5, 1.3 48 50 1.2 0.8, 1.9
    Medium and high intensity 7 10 1.8 0.7, 4.8 27 30 1.4 0.8, 2.4
Formaldehyde
    Low intensity 104 115 1.4 1.1, 1.9 16 14 1.1 0.5, 2.4
    Medium and high intensity 62 50 1.0 0.7, 1.6 19 24 1.6 0.9, 3.1
Chlorinated solvents
    Low intensity 90 86 1.2 0.9, 1.7 18 21 1.6 0.8, 3.0
    Medium and high intensity 55 66 1.6 1.1, 2.3 24 23 1.4 0.8, 2.5
Chloroform
    Low intensity 12 8 0.9 0.4, 2.2 16 13 1.0 0.5, 2.1
    Medium and high intensity 2 0 17 14 1.0 0.5, 2.1
Carbon tetrachloride
    Low intensity 13 26 2.3 1.2, 4.5 0 0
    Medium and high intensity 6 10 2.2 0.8, 6.3 0 0
Dichloromethane
    Low intensity 33 36 1.5 0.9, 2.4 0 1
    Medium and high intensity 8 12 1.9 0.8, 4.8 5 3 0.9 0.2, 3.8
Dichloroethane
    Low intensity 48 50 1.3 0.9, 2.0 7 7 1.3 0.4, 3.7
    Medium and high intensity 3 0 0 1
Methyl chloride
    Low intensity 46 48 1.3 0.8, 2.0 5 4 1.0 0.3, 3.9
    Medium and high intensity 3 1 0.4 0.0, 4.2 3 3 1.5 0.3, 7.8
Trichloroethylene
    Low intensity 40 30 0.9 0.6, 1.5 31 34 1.4 0.9, 2.4
    Medium and high intensity 8 13 2.2 0.9, 5.4 0 0

Abbreviations: CI, confidence interval; OR, odds ratio.

a

Adjusted for age (continuous), family history of hematopoietic cancers (yes, no), alcohol consumption (yes, no), and race (white, black, other).

We also evaluated associations by cumulative intensity and probability (data not shown). About 50% increased risks of NHL were observed for those whose cumulative exposure intensity to any organic solvent was at least 36 indexes × year (95% CI: 1.1, 2.0) and those whose cumulative exposure probability to organic solvent was at least 29 indexes × year (95% CI: 1.1, 2.0). An odds ratio of 1.6 was observed for those whose cumulative exposure intensity to chlorinated solvent was more than 35 indexes × year (95% CI: 1.1, 2.3). For specific chlorinated solvents, a significantly increased risk was observed for those exposed to carbon tetrachloride at a cumulative exposure intensity of 3–18 indexes × year (OR = 4.3, 95% CI: 1.9, 10.2) and with a cumulative exposure probability of more than 35 indexes × year (OR = 5.2, 95% CI: 2.0, 13.9). Moreover, the risk of NHL increased with increasing cumulative intensity exposure levels of organic solvent (P = 0.01) and chlorinated solvents (P = 0.02). The risk of NHL also increased with cumulative exposure probability level of organic solvents (P < 0.01).

We further analyzed associations between occupational exposures and risks of major subtypes of NHL (Table 4). Analyses of risks of diffuse large B-cell lymphoma (DLBCL) showed the same patterns as the results for overall NHL. In addition, a significantly increased risk of DLBCL was observed for those exposed to benzene at an average medium-high probability level. Furthermore, risk of DLBCL increased with average intensity or probability level of benzene exposure. The effect of chlorinated solvent exposure on risk of NHL varied with major NHL subtypes at a high-medium average intensity level (χ2 = 7.24 (degrees of freedom = 2), P = 0.03), with a 2-fold increased risk of DLBCL (OR = 2.3, 95% CI: 1.5, 3.6). The risk of DLBCL also increased with average intensity level of any chlorinated solvent (P < 0.01).

Table 4.

Solvent Exposure and Risk of Major Subtypes of Non-Hodgkin Lymphoma by Average Exposure Intensity and Average Exposure Probability Among Connecticut Women, 1996–2000

Diffuse Large B-Cell Lymphoma
Follicular Lymphoma
Chronic Lymphocytic Leukemia/Small Lymphocytic Lymphoma
No. of Cases ORa 95% CI No. of Cases ORa 95% CI No. of Cases ORa 95% CI
Any organic solvent
    Never 93 77 40
    Ever 96 1.6 1.1, 2.2 59 1.2 0.8, 1.7 26 1.0 0.6, 1.7
    Average intensity
     Low 54 1.3 0.9, 1.9 38 1.1 0.7, 1.8 14 0.8 0.4, 1.6
     Medium-high 42 2.1 1.4, 3.3 21 1.3 0.7, 2.1 12 1.4 0.7, 2.7
     P for trend <0.01 0.21 0.22
    Average probability
     Low 40 1.2 0.8, 1.8 32 1.1 0.7, 1.8 10 0.7 0.4, 1.5
     Medium-high 56 2.1 1.4, 3.1 27 1.2 0.8, 2.0 16 1.3 0.7, 2.5
     P for trend <0.01 0.18 0.17
Benzene
    Never 149 107 54
    Ever 40 1.2 0.8, 1.8 29 1.3 0.8, 2.0 12 1.0 0.5, 2.0
    Average intensity
     Low 25 1.0 0.6, 1.7 18 1.1 0.6, 1.8 7 0.8 0.4, 1.9
     Medium-high 15 1.8 0.9, 3.4 11 1.8 0.9, 3.7 5 1.6 0.6, 4.3
     P for trend 0.04 0.18 0.08
    Average probability
     Low 11 0.8 0.4, 1.6 9 0.9 0.4, 2.0 3 0.7 0.2, 2.2
     Medium-high 29 1.5 1.0, 2.5 20 1.5 0.9, 2.5 9 1.3 0.6, 2.7
     P for trend 0.04 0.10 0.18
Formaldehyde
    Never 109 95 46
    Ever 80 1.9 1.3, 2.6 41 1.1 0.7, 1.6 20 1.2 0.7, 2.0
    Average intensity
     Low 54 2.1 1.4, 3.1 25 1.1 0.7, 1.8 12 1.2 0.6, 2.2
     Medium-high 26 1.5 0.9, 2.4 16 1.1 0.6, 1.9 8 1.2 0.5, 2.6
     P for trend 0.03 0.88 0.45
    Average probability
     Low 60 1.7 1.2, 2.4 35 1.1 0.7, 1.7 16 1.1 0.6, 2.0
     Medium-high 20 2.6 1.5, 4.7 6 0.9 0.4, 2.2 4 1.4 0.5, 4.3
     P for trend <0.01 0.81 0.52
Chlorinated solvent
    Never 120 91 53
    Ever 69 1.6 1.2, 2.3 45 1.4 0.9, 2.1 13 0.7 0.4, 1.3
    Average intensity
     Low 30 1.2 0.8, 1.9 29 1.5 1.0, 2.4 8 0.8 0.3, 1.6
     Medium-high 39 2.2 1.4, 3.4 16 1.2 0.7, 2.1 5 0.6 0.2, 1.7
     P for trend <0.01 0.39 0.68
    Average probability
     Low 49 1.5 1.0, 2.2 38 1.5 1.0, 2.3 11 0.7 0.4, 1.4
     Medium-high 20 2.1 1.2, 3.8 7 1.0 0.4, 2.3 2 0.6 0.1, 2.5
     P for trend 0.01 0.75 0.33

Abbreviations: CI, confidence interval; OR, odds ratio.

a

Adjusted for age (continuous), family history of hematopoietic cancers (yes, no), alcohol consumption (yes, no), and race (white, black, other).

DISCUSSION

The results from this population-based case-control study suggest that occupational exposure to organic solvents may increase NHL risk for women. In this study, we observed significantly increased risks of NHL with exposure to any organic solvent at medium-high average intensity and/or average probability levels. Moreover, significantly increased risks of NHL were observed for high cumulative intensity or probability groups. The risk of NHL increased with level of average and cumulative intensity or probability. Significantly increased risks of NHL for those exposed to organic solvents have also been reported in previous studies (18, 3335). Hardell et al. (34, 35) observed a 2-fold increased risk of NHL with exposure to organic solvents (OR = 2.4, 95% CI: 1.4, 3.9); moreover, an odds ratio of 3.5 (95% CI: 1.7, 7.1) was found for those exposed to high-grade organic solvents (34). Although Fritschi et al. (36) observed a marginally increased risk of NHL for only those exposed to any solvent (OR = 1.3, 95% CI: 1.0, 1.6), a significant dose-response effect by solvent exposure levels was also found. Olsson and Brandt (18) reported a 3-fold increased risk of NHL (OR = 3.3, 95% CI: 1.9, 5.8) for males exposed to organic solvents for at least 1 year. Dryver et al. (33) found a 60% increased risk for Swedish workers exposed to solvents for more than 5 years (OR = 1.6, 95% CI: 1.1, 2.3).

Our results also showed that the increased risk of NHL associated with exposure to solvents was seen mainly for those who reported exposure to chlorinated solvents. Chlorinated solvents have been widely used as extraction solvents, paint solvents, and coating solvents, as well as in cleaning and degreasing solvents. Seidler et al. (37) reported a significant association between malignant lymphoma risk and high exposure to chlorinated hydrocarbons (OR = 2.1, 95% CI: 1.1, 4.3). McDuffie et al. (38) observed a 2.4-fold increased risk of NHL for male Canadian pesticide workers who may have been exposed to carbon tetrachloride (95% CI: 1.2, 5.1). The lymphatic system has been regarded as a target for trichloroethylene toxicity (39). Results of 2 cohort studies of aircraft maintenance workers exposed to trichloroethylene or perchloroethylene suggested an increased NHL risk (40, 41). Note that only a relative small number of participants in our study were ever exposed to carbon tetrachloride; moreover, this exposure occurred for the most part at a low average probability exposure level. Thus, the significant finding between carbon tetrachloride and risk of NHL in this study might be due to chance.

A dose-dependent association between benzene exposure and risk of NHL was observed. A significantly increased risk of DLBCL for those exposed to benzene at a medium-high average probability level was found. A nonsignificantly but increased risk of NHL was also found for those who had an average medium-high intensity or probability level of exposure to benzene. Lymphocytes in peripheral blood are a hematologic cell type particularly sensitive to benzene toxicity (42, 43), and peripheral lymphatic cells are targeted by the genotoxic metabolites of benzene (44). Furthermore, benzene exposure has been linked to chromosomal aberrations found in NHL in cultured peripheral lymphocytes of exposed workers (45).

Thus, our results are consistent with an association between benzene exposure and risk of NHL. However, results regarding the association between benzene exposure and risk of NHL have been inconsistent in previous studies. A Chinese cohort study reported a 4-fold increased risk of NHL (risk ratio = 4.1, 95% CI: 1.2, 14.4) for workers employed before 1972, and the risk was strongly associated with cumulative exposure that occurred more than 10 years prior to diagnosis (P = 0.005). A case-control study from France also reported an almost 5-fold increased risk of NHL (OR = 4.6, 95% CI: 1.1, 19.2) for those who reported being exposed to benzene for more than 810 days (46). There are also studies that did not find any association between benzene exposure and risk of NHL among petroleum workers (47), which may have been due to the healthy-worker effect (48). As presented by Smith et al. (48), after adjusting for the healthy-worker effect, the observed standardized mortality ratio of lymphoreticulosarcoma in male refinery workers increased from 1.1 (95% CI: 0.6, 1.7) to 1.5 (95% CI: 1.2, 1.8). However, a recent meta-analysis found evidence of a significant association between occupational benzene exposure and NHL risk, particularly when restricted to studies with a higher-quality exposure assessment (49). Risk estimates for medium-high probability of exposure to benzene and NHL in the current study are consistent with the magnitude of effects reported in the meta-analysis.

Exposure to formaldehyde was found to be associated with an increased risk of NHL in our study, but the risk was mainly for those with a low exposure intensity or probability. Formaldehyde is used widely in manufacturing and chemical industries and also as a human tissue preservative. In experimental studies, formaldehyde is associated with increased frequencies of micronuclei, sister chromatid exchanges, chromosomal aberrations, and DNA-protein cross-links in peripheral lymphocytes of humans, as summarized by Hauptmann et al. (50). Two cohort studies have linked formaldehyde exposure to an increased risk of leukemia (50, 51). One epidemiologic study suggested that exposure to formaldehyde may be responsible for the observed increased risk of lymphoma for woodwork-related exposures (52); however, other studies have not found a positive association between formaldehyde exposure and NHL risk (13, 38, 53, 54).

Our results provide weak evidence that NHL risk may differ by subtypes. NHL comprises a heterogeneous group of lymphoid malignancies; it has been hypothesized that each subtype may have a distinct etiology (55). We observed that the effect of chlorinated solvent exposure on risk of NHL varied with major NHL subtypes at only a high-medium average intensity level. In this study, the sample size of a certain histologic subtype was relatively small, which limited our ability to detect the effect of solvent exposure on the risk of a certain NHL subtype. Few studies so far have evaluated the association between organic solvent exposures and risk of subtypes of NHL. Tatham et al. (53) found that exposure to solvents is associated with a significantly increased risk of small-cell diffuse lymphomas (OR = 1.6, 95% CI: 1.1, 2.2). Rego et al. (20) reported a 2-fold increased risk of diffuse NHL (OR = 2.0, 95% CI: 1.1, 3.7) for those whose first exposure to solvents occurred 6–25 years preceding diagnosis or interview. Fritschi et al. (36) reported an increased risk of B-cell NHL among workers ever exposed to solvents (OR = 1.3, 95% CI: 1.0, 1.7). Kato et al. (56) found an increased risk of B-cell NHL (OR = 1.5, 95% CI: 1.1, 2.1) for those with paint thinners/turpentine exposure.

This study is one of the few that has applied a job-exposure matrix to evaluate the association between solvents exposure and the risk of NHL in the United States. Most of the early epidemiologic studies used occupational titles or industry as surrogates to evaluate the association between occupational exposures and NHL risk. As pointed out by others, exposure and exposure intensity may vary by industries included in the same occupation title. Thus, use of job titles or industries separately as surrogates to study the exposure and disease relation may result in serious misclassification of exposure and intensity of exposure, which could bias the estimated association between the exposure and disease of interest (57). The advantages of using job-exposure matrixes to analyze occupational exposure and disease risk include that the job-exposure matrixes link information from both occupational titles and industry titles with specific exposures, therefore minimizing exposure misclassification, and allow for semiquantitative measurements of the occupational exposures and disease relation. Use of job-exposure matrixes in occupational epidemiologic studies could also significantly increase the statistical power compared with use of job or industrial titles (58).

Several potential limitations should be considered in interpreting our study results. One concern is misclassification of exposure. We assessed occupational exposure to specific solvents by linking the job-exposure matrixes with self-reported occupational histories, and some degree of exposure misclassification was unavoidable. In general, misclassification of exposure is unlikely to be differential. For multilevel exposure, nondifferential misclassification may bias relative risks away from the null in some categories (59, 60); however, it can bias the relative risk toward the null in the highest exposure category only (60). In this study, when exposure intensities and probabilities were categorized into more than 2 levels, significant associations were observed mainly at the highest exposure level.

Another potential limitation of the study is the relatively small sample size of certain subtypes and the low prevalence of occupational exposure to some organic solvents. A small sample size with low exposure prevalence not only reduces statistical power but also increases the possibility of false-positive associations. When we evaluated associations between occupational exposures and risks of major subtypes of NHL, significantly increased associations were observed for DLBCL patients only, the most common NHL subtypes in this study. Further studies with a larger sample size are needed to explore the associations between occupational solvents exposure and the risk of NHL by subtype.

In conclusion, in this population-based case-control study of Connecticut women, we found an increased risk of NHL from occupational exposure to any organic solvent, formaldehyde, chlorinated solvents, and carbon tetrachloride and some evidence of an association with benzene. These results support a potential association between occupational exposure to organic solvents and the risk of NHL among women. Future evaluation of the relation between solvent exposure and risk of NHL and its subtypes is warranted.

Acknowledgments

Author affiliations: Division of Environmental Health Sciences, Yale University School of Public Health, New Haven, Connecticut (Rong Wang, Yawei Zhang, Brian Leaderer, Yong Zhu, Tongzhang Zheng); Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland (Qing Lan, Shelia Hoar Zahm, Mustafa Dosemeci, Nathaniel Rothman); Division of Biostatistics, Yale University School of Public Health, New Haven, Connecticut (Theodore R. Holford); International Agency for Research on Cancer, Lyon, France (Peter Boyle); and Maine Center for Toxicology and Environmental Health, University of South Maine, Portland, Maine (Qin Qin).

This study was supported by grant CA62006 from the National Cancer Institute. Preparation of the manuscript for publication was partially supported by National Institutes of Health grant 5 D43 TW007864.

Certain data used in this study were obtained from the Connecticut Tumor Registry located in the Connecticut Department of Public Health. The authors assume full responsibility for analyses and interpretation of these data.

The authors thank the institutions that allowed access to diagnostic materials and pathology reports, including the following Connecticut hospitals: Charlotte Hungerford Hospital, Danbury Hospital, Greenwich Hospital, Griffin Hospital, Hartford Hospital, Johnson Memorial Hospital, Middlesex Hospital, Lawrence and Memorial Hospital, New Britain General Hospital, Bradley Memorial Hospital, Norwalk Hospital, St. Francis Hospital and Medical Center, St. Mary's Hospital, Hospital of St. Raphael, St. Vincent's Medical Center, Stamford Hospital, William W. Backus Hospital, Waterbury Hospital, Yale-New Haven Hospital, Manchester Memorial Hospital, Rockville General Hospital, Bridgeport Hospital, Windham Hospital, Sharon Hospital, Milford Hospital, New Milford Hospital, Bristol Hospital, MidState Medical Center, and Day-Kimball Hospital.

Conflict of interest: none declared.

Glossary

Abbreviations

CI

confidence interval

DLBCL

diffuse large B-cell lymphoma

NHL

non-Hodgkin lymphoma

OR

odds ratio

References

  • 1.Jemal A, Clegg LX, Ward E, et al. Annual report to the nation on the status of cancer, 1975–2001, with a special feature regarding survival. Cancer. 2004;101(1):3–27. doi: 10.1002/cncr.20288. [DOI] [PubMed] [Google Scholar]
  • 2.Jemal A, Siegel R, Ward E, et al. Cancer statistics. CA Cancer J Clin. 2007;57(1):43–66. doi: 10.3322/canjclin.57.1.43. [DOI] [PubMed] [Google Scholar]
  • 3.Fisher SG, Fisher RI. The epidemiology of non-Hodgkin's lymphoma. Oncogene. 2004;23(28):6524–6534. doi: 10.1038/sj.onc.1207843. [DOI] [PubMed] [Google Scholar]
  • 4.Clarke CA, Glaser SL. Changing incidence of non-Hodgkin lymphomas in the United States. Cancer. 2002;94(7):2015–2023. doi: 10.1002/cncr.10403. [DOI] [PubMed] [Google Scholar]
  • 5.Devesa SS, Fears T. Non-Hodgkin's lymphoma time trends: United States and international data. Cancer Res. 1992;52(19 suppl):5432s–5440s. [PubMed] [Google Scholar]
  • 6.Eltom MA, Jemal A, Mbulaiteye SM, et al. Trends in Kaposi's sarcoma and non-Hodgkin's lymphoma incidence in the United States from 1973 through 1998. J Natl Cancer Inst. 2002;94(16):1204–1210. doi: 10.1093/jnci/94.16.1204. [DOI] [PubMed] [Google Scholar]
  • 7.Morton LM, Wang SS, Devesa SS, et al. Lymphoma incidence patterns by WHO subtype in the United States, 1992–2001. Blood. 2006;107(1):265–276. doi: 10.1182/blood-2005-06-2508. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Khuder SA, Schaub EA, Keller-Byrne JE. Meta-analyses of non-Hodgkin's lymphoma and farming. Scand J Work Environ Health. 1998;24(4):255–261. doi: 10.5271/sjweh.318. [DOI] [PubMed] [Google Scholar]
  • 9.Kelleher C, Newell J, MacDonagh-White C, et al. Incidence and occupational pattern of leukaemias, lymphomas, and testicular tumours in western Ireland over an 11 year period. J Epidemiol Community Health. 1998;52(10):651–656. doi: 10.1136/jech.52.10.651. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Zheng T, Blair A, Zhang Y, et al. Occupation and risk of non-Hodgkin's lymphoma and chronic lymphocytic leukemia. J Occup Environ Med. 2002;44(5):469–474. doi: 10.1097/00043764-200205000-00015. [DOI] [PubMed] [Google Scholar]
  • 11.Keller-Byrne JE, Khuder SA, Schaub EA, et al. A meta-analysis of non-Hodgkin's lymphoma among farmers in the central United States. Am J Ind Med. 1997;31(4):442–444. doi: 10.1002/(sici)1097-0274(199704)31:4<442::aid-ajim10>3.0.co;2-#. [DOI] [PubMed] [Google Scholar]
  • 12.Blair A, Zahm SH. Cancer among farmers. Occup Med. 1991;6(3):335–354. [PubMed] [Google Scholar]
  • 13.Blair A, Linos A, Stewart PA, et al. Evaluation of risks for non-Hodgkin's lymphoma by occupation and industry exposures from a case-control study. Am J Ind Med. 1993;23(2):301–312. doi: 10.1002/ajim.4700230207. [DOI] [PubMed] [Google Scholar]
  • 14.Pearce N, Bethwaite P. Increasing incidence of non-Hodgkin's lymphoma: occupational and environmental factors. Cancer Res. 1992;52(19 suppl):5496s–5500s. [PubMed] [Google Scholar]
  • 15.Zahm SH. Mortality study of pesticide applicators and other employees of a lawn care service company. J Occup Environ Med. 1997;39(11):1055–1067. doi: 10.1097/00043764-199711000-00006. [DOI] [PubMed] [Google Scholar]
  • 16.Scherr PA, Hutchison GB, Neiman RS. Non-Hodgkin's lymphoma and occupational exposure. Cancer Res. 1992;52(19 suppl):5503s–5509s. [PubMed] [Google Scholar]
  • 17.Hayes RB, Blair A, Stewart PA, et al. Mortality of U.S. embalmers and funeral directors. Am J Ind Med. 1990;18(6):641–652. doi: 10.1002/ajim.4700180603. [DOI] [PubMed] [Google Scholar]
  • 18.Olsson H, Brandt L. Risk of non-Hodgkin's lymphoma among men occupationally exposed to organic solvents. Scand J Work Environ Health. 1988;14(4):246–251. doi: 10.5271/sjweh.1925. [DOI] [PubMed] [Google Scholar]
  • 19.Rego MA. Non-Hodgkin's lymphoma risk derived from exposure to organic solvents: a review of epidemiologic studies. Cad Saude Publica. 1998;14(suppl 3):41–66. doi: 10.1590/s0102-311x1998000700006. [DOI] [PubMed] [Google Scholar]
  • 20.Rego MA, Sousa CS, Kato M, et al. Non-Hodgkin's lymphomas and organic solvents. J Occup Environ Med. 2002;44(9):874–881. doi: 10.1097/00043764-200209000-00010. [DOI] [PubMed] [Google Scholar]
  • 21.Olsson H, Brandt L. Supradiaphragmatic presentation of non-Hodgkin's lymphoma in men occupationally exposed to organic solvents. Acta Med Scand. 1981;210(5):415–418. doi: 10.1111/j.0954-6820.1981.tb09841.x. [DOI] [PubMed] [Google Scholar]
  • 22.Zhang Y, Holford TR, Leaderer B, et al. Menstrual and reproductive factors and risk of non-Hodgkin's lymphoma among Connecticut women. Am J Epidemiol. 2004;160(8):766–773. doi: 10.1093/aje/kwh278. [DOI] [PubMed] [Google Scholar]
  • 23.Zhang Y, Holford TR, Leaderer B, et al. Blood transfusion and risk of non-Hodgkin's lymphoma in Connecticut women. Am J Epidemiol. 2004;160(4):325–330. doi: 10.1093/aje/kwh233. [DOI] [PubMed] [Google Scholar]
  • 24.Zheng T, Holford TR, Leaderer B, et al. Diet and nutrient intakes and risk of non-Hodgkin's lymphoma in Connecticut women. Am J Epidemiol. 2004;159(5):454–466. doi: 10.1093/aje/kwh067. [DOI] [PubMed] [Google Scholar]
  • 25.Zhang Y, Holford TR, Leaderer B, et al. Hair-coloring product use and risk of non-Hodgkin's lymphoma: a population-based case-control study in Connecticut. Am J Epidemiol. 2004;159(2):148–154. doi: 10.1093/aje/kwh033. [DOI] [PubMed] [Google Scholar]
  • 26.Morton LM, Holford TR, Leaderer B, et al. Alcohol use and risk of non-Hodgkin's lymphoma among Connecticut women (United States) Cancer Causes Control. 2003;14(7):687–694. doi: 10.1023/a:1025626208861. [DOI] [PubMed] [Google Scholar]
  • 27.US Department of Commerce. Standard Occupational Classification Manual. Washington, DC: US Government Printing Office; 1980. [Google Scholar]
  • 28.Office of Management and Budget. Standard Industrial Classification Manual. Washington, DC: US Government Printing Office; 1987. [Google Scholar]
  • 29.Dosemeci M, Cocco P, Gómez M, et al. Effects of three features of a job-exposure matrix on risk estimates. Epidemiology. 1994;5(1):124–127. doi: 10.1097/00001648-199401000-00019. [DOI] [PubMed] [Google Scholar]
  • 30.Gomez MR, Cocco P, Dosemeci M, et al. Occupational exposure to chlorinated aliphatic hydrocarbons: job exposure matrix. Am J Ind Med. 1994;26(2):171–183. doi: 10.1002/ajim.4700260204. [DOI] [PubMed] [Google Scholar]
  • 31.Dosemeci M, Stewart PA, Blair A. Evaluating occupation and industry separately to assess exposures in case-control studies. Appl Ind Hyg. 1989;4:256–259. [Google Scholar]
  • 32.SAS Institute, Inc. SAS OnlineDoc 9.1.3. Cary, NC: SAS Institute, Inc; p. 2005. [Google Scholar]
  • 33.Dryver E, Brandt L, Kauppinen T, et al. Occupational exposures and non-Hodgkin's lymphoma in Southern Sweden. Int J Occup Environ Health. 2004;10(1):13–21. doi: 10.1179/oeh.2004.10.1.13. [DOI] [PubMed] [Google Scholar]
  • 34.Hardell L, Eriksson M, Degerman A. Exposure to phenoxyacetic acids, chlorophenols, or organic solvents in relation to histopathology, stage, and anatomical localization of non-Hodgkin's lymphoma. Cancer Res. 1994;54(9):2386–2389. [PubMed] [Google Scholar]
  • 35.Hardell L, Eriksson M, Lenner P, et al. Malignant lymphoma and exposure to chemicals, especially organic solvents, chlorophenols and phenoxy acids: a case-control study. Br J Cancer. 1981;43(2):169–176. doi: 10.1038/bjc.1981.25. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Fritschi L, Benke G, Hughes AM, et al. Risk of non-Hodgkin lymphoma associated with occupational exposure to solvents, metals, organic dusts and PCBs (Australia) Cancer Causes Control. 2005;16(5):599–607. doi: 10.1007/s10552-004-7845-0. [DOI] [PubMed] [Google Scholar]
  • 37.Seidler A, Möhner M, Berger J, et al. Solvent exposure and malignant lymphoma: a population-based case-control study in Germany. J Occup Med Toxicol. 2007;2:2. doi: 10.1186/1745-6673-2-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.McDuffie HH, Pahwa P, McLaughlin JR, et al. Non-Hodgkin's lymphoma and specific pesticide exposures in men: cross-Canada study of pesticides and health. Cancer Epidemiol Biomarkers Prev. 2001;10(11):1155–1163. [PubMed] [Google Scholar]
  • 39.Dry Cleaning, Some Chlorinated Solvents and Other Industrial Chemicals. Lyon, France: International Agency for Research on Cancer; 1995. IARC Monographs on the Evaluation of Carcinogenic Risks to Humans; vol 63. [PMC free article] [PubMed] [Google Scholar]
  • 40.Spirtas R, Stewart PA, Lee JS, et al. Retrospective cohort mortality study of workers at an aircraft maintenance facility. I. Epidemiological results. Br J Ind Med. 1991;48(8):515–530. doi: 10.1136/oem.48.8.515. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Boice JD, Jr, Marano DE, Fryzek JP, et al. Mortality among aircraft manufacturing workers. Occup Environ Med. 1999;56(9):581–597. doi: 10.1136/oem.56.9.581. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Rothman N, Smith MT, Hayes RB, et al. An epidemiologic study of early biologic effects of benzene in Chinese workers. Environ Health Perspect. 1996;104(suppl 6):1365–1370. doi: 10.1289/ehp.961041365. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Lan Q, Zhang L, Li G, et al. Hematotoxicity in workers exposed to low levels of benzene. Science. 2004;306(5702):1774–1776. doi: 10.1126/science.1102443. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.US Environmental Protection Agency. Carcinogenic Effects of Benzene: An Update (Final). Washington, DC: US Environmental Protection Agency. 1998 (EPA/600/P-97/001F) [Google Scholar]
  • 45.Zhang L, Rothman N, Li G, et al. Aberrations in chromosomes associated with lymphoma and therapy-related leukemia in benzene-exposed workers. Environ Mol Mutagen. 2007;48(6):467–474. doi: 10.1002/em.20306. [DOI] [PubMed] [Google Scholar]
  • 46.Fabbro-Peray P, Daures JP, Rossi JF. Environmental risk factors for non-Hodgkin's lymphoma: a population-based case-control study in Languedoc-Roussillon, France. Cancer Causes Control. 2001;12(3):201–212. doi: 10.1023/a:1011274922701. [DOI] [PubMed] [Google Scholar]
  • 47.Wong O, Raabe GK. Non-Hodgkin's lymphoma and exposure to benzene in a multinational cohort of more than 308,000 petroleum workers, 1937 to 1996. J Occup Environ Med. 2000;42(5):554–568. doi: 10.1097/00043764-200005000-00016. [DOI] [PubMed] [Google Scholar]
  • 48.Smith MT, Jones RM, Smith AH. Benzene exposure and risk of non-Hodgkin lymphoma. Cancer Epidemiol Biomarkers Prev. 2007;16(3):385–391. doi: 10.1158/1055-9965.EPI-06-1057. [DOI] [PubMed] [Google Scholar]
  • 49.Steinmaus C, Smith AH, Jones RM, et al. Meta-analysis of benzene exposure and non-Hodgkin lymphoma: biases could mask an important association. Occup Environ Med. 2008;65(6):371–378. doi: 10.1136/oem.2007.036913. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50.Hauptmann M, Lubin JH, Stewart PA, et al. Mortality from lymphohematopoietic malignancies among workers in formaldehyde industries. J Natl Cancer Inst. 2003;95(21):1615–1623. doi: 10.1093/jnci/djg083. [DOI] [PubMed] [Google Scholar]
  • 51.Pinkerton LE, Hein MJ, Stayner LT. Mortality among a cohort of garment workers exposed to formaldehyde: an update. Occup Environ Med. 2004;61(3):193–200. doi: 10.1136/oem.2003.007476. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 52.Partanen T, Kauppinen T, Luukkonen R, et al. Malignant lymphomas and leukemias, and exposures in the wood industry: an industry-based case-referent study. Int Arch Occup Environ Health. 1993;64(8):593–596. doi: 10.1007/BF00517706. [DOI] [PubMed] [Google Scholar]
  • 53.Tatham L, Tolbert P, Kjeldsberg C. Occupational risk factors for subgroups of non-Hodgkin's lymphoma. Epidemiology. 1997;8(5):551–558. doi: 10.1097/00001648-199709000-00013. [DOI] [PubMed] [Google Scholar]
  • 54.Blair A, Stewart P, O'Berg M, et al. Mortality among industrial workers exposed to formaldehyde. J Natl Cancer Inst. 1986;76(6):1071–1084. [PubMed] [Google Scholar]
  • 55.Herrinton LJ. Epidemiology of the Revised European-American Lymphoma Classification subtypes. Epidemiol Rev. 1998;20(2):187–203. doi: 10.1093/oxfordjournals.epirev.a017980. [DOI] [PubMed] [Google Scholar]
  • 56.Kato I, Koenig KL, Watanabe-Meserve H, et al. Personal and occupational exposure to organic solvents and risk of non-Hodgkin's lymphoma (NHL) in women (United States) Cancer Causes Control. 2005;16(10):1215–1224. doi: 10.1007/s10552-005-0385-4. [DOI] [PubMed] [Google Scholar]
  • 57.Stewart PA, Herrick RF. Issues in performing retrospective exposure assessment. Appl Occup Environ Hyg. 1991;6:421–427. [Google Scholar]
  • 58.Siemiatycki J, Dewar R, Richardson L. Costs and statistical power associated with five methods of collecting occupation exposure information for population-based case-control studies. Am J Epidemiol. 1989;130(6):1236–1246. doi: 10.1093/oxfordjournals.aje.a115452. [DOI] [PubMed] [Google Scholar]
  • 59.Correa-Villaseñor A, Stewart WF, Franco-Marina F, et al. Bias from nondifferential misclassification in case-control studies with three exposure levels. Epidemiology. 1995;6(3):276–281. doi: 10.1097/00001648-199505000-00015. [DOI] [PubMed] [Google Scholar]
  • 60.Dosemeci M, Wacholder S, Lubin JH. Does nondifferential misclassification of exposure always bias a true effect toward the null value? Am J Epidemiol. 1990;132(4):746–748. doi: 10.1093/oxfordjournals.aje.a115716. [DOI] [PubMed] [Google Scholar]

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