Abstract
Objectives
Chlorinated solvents are classified as probable or possible carcinogens. It is unknown whether exposure to these agents increases the risk of malignant or benign brain tumors. Our objective was to evaluate associations of brain tumor risk with occupational exposure to six chlorinated solvents [i.e., dichloromethane, chloroform, carbon tetrachloride, 1,1,1-trichloroethane, trichloroethylene, and perchloroethylene].
Methods
489 glioma cases, 197 meningioma cases, and 799 controls were enrolled in a hospital-based case-control study conducted at three U.S. hospitals in Arizona, Massachusetts and Pennsylvania. Information about occupational history was obtained through a detailed in-person interview that included job-specific modules of questions such that the interview was tailored to each individual’s particular work history. An industrial hygienist assessed potential solvent exposure based on this information and an exhaustive review of the relevant industrial hygiene literature. Unconditional logistic regression models were used to calculate odds ratios (OR) and 95% confidence intervals (95%CI) for each solvent for ever/never, duration, cumulative, average weekly, and highest exposure.
Results
Overall, we found no consistent evidence of an increased risk of glioma or meningioma related to occupational exposure to the six chlorinated solvents evaluated. There was some suggestion of an association between carbon tetrachloride and glioma in analyses restricted to exposed subjects, with average weekly exposure above the median associated with increased risk compared to below-median exposure (OR=7.1, 95%CI: 1.1, 45.2).
Conclusions
We found no consistent evidence for increased brain tumor risk related to chlorinated solvents.
Keywords: epidemiology, cancer, solvents
INTRODUCTION
Chlorinated solvents are a class of hydrocarbon compounds containing chlorine and characterized by their volatile and lipophilic nature. Chlorinated solvents have been gaining international attention as probable or possible carcinogens, as classified by the International Agency for Research on Cancer.[1–4] These chemicals have been used widely in the United States, primarily as cleansers in a variety of applications including paint removal, degreasing and dry cleaning.[5] Some also have been used as solvents to decaffeinate coffee (e.g., methylene chloride and trichloroethylene),[6 7] and as anesthetics (e.g., chloroform, carbon tetrachloride and trichloroethylene).[6 8 9] Use of these chemicals began in the early 1900s and peaked in the 1970s and 1980s but has subsequently declined due to concerns about their effect on the environment and public health,[5] particularly regarding their possible carcinogenicity.[10] However, many of these chemicals continue to be used in the United States, including methylene chloride, 1,1,1-trichloroethane, chloroform, trichloroethylene, and tetrachloroethylene, and some of these are contained in household products, such as cleansers, adhesives and spot removers.[5]
Chlorinated solvents have been associated with increased risk of several cancers including leukemia, lymphoma, kidney and urinary tract cancer.[10–14] Elevated risk of brain tumors has been observed in occupations that may involve exposure to organic solvents (potentially including chlorinated hydrocarbons), such as painters, electricians and electrical workers, computer manufacturers, aircraft industry workers, metal industry workers, laboratory technicians, artists, and agricultural workers,[15–23] but the evidence is inconsistent, as some studies have reported no association.[24 25] Few studies have examined the relationship between exposure to specific chlorinated solvents and brain tumor risk. Those studies that do exist are mortality studies with limited occupational exposure information that was collected from next of kin or death certificates. Nonetheless, these studies have found suggestive associations of an increased risk.[18 26 27]
Given that chlorinated solvents can cross the blood-brain barrier due to their relatively small size, non-polarity, and lipid solubility, they have the potential to interact with and damage the central nervous system. In fact, some chlorinated solvents previously were used as anesthetics,[6 8 9] and epidemiologic studies have shown that long-term exposure to chlorinated solvents is associated with pathologies of the nervous system, including dementia, cerebral atrophy, and Parkinson disease.[28 29]
Here, we report findings from an analysis within a large, hospital-based case-control study investigating whether occupational exposure to six chlorinated solvents is associated with risks of glioma and meningioma. Exposure assessment was assessed by an expert industrial hygienist after review of participants’ occupational histories and their answers to job-specific interview modules designed to obtain detailed information regarding potential solvent exposure in the workplace.
MATERIALS AND METHODS
Study population
Details of the study design and population have been described previously.[30–32] In brief, subjects were recruited and enrolled in a hospital-based case-control study of brain tumors between 1994 and 1998 in Boston, MA (Brigham and Women’s Hospital), Pittsburgh, PA (Western Pennsylvania Hospital), and Phoenix, AZ (St. Joseph’s Hospital and Medical Center). All three hospitals were regional referral centers for brain tumors.
Eligible cases included patients diagnosed with a first primary glioma or other neuroepitheliomatous neoplasm (codes 9380–9473 and 9490–9506 of the International Classification of Diseases for Oncology, 2nd edition [ICD-O-2]), meningioma (ICD-O-2 codes 9530–9538), or acoustic neuroma (ICD-O-2 code 9560) within the eight weeks during or preceding hospitalization. For this analysis, only glioma (n=489) and meningioma (n=197) cases were included. Participation rates were 92% and 94% for glioma and meningioma cases, respectively. All participating case diagnoses were confirmed by microscopy. The majority of cases (80%) were enrolled and interviewed within three weeks after diagnosis.
Controls for this study (n=799) were patients admitted to the same hospitals for non-malignant conditions, including injuries (25%), circulatory system disorders (22%), musculoskeletal disorders (22%), digestive disorders (12%), and other conditions (19%) and were frequency-matched to cases (1:1) by sex, age at interview (18–29, 30–39, 40–49, 50–59, 60–69, 70–79, 80–99 years), race/ethnicity (non-Hispanic white, Hispanic white, African-American, other), hospital (Boston, Pittsburgh, Phoenix), and proximity to the hospital (0–4, 5–14, 15–29, 30–49, 50+ miles). The participation rate among controls was 86%.
This study was reviewed and approved by the institutional review boards of each participating institution, and written informed consent was obtained from all study participants or their proxies.
Exposure assessment
Patients were interviewed in person by a trained research nurse who administered a computer-based questionnaire to collect information on lifetime occupational histories as well as other potential risk factors for brain tumors, including demographic variables (education, household income, marital status, religion) and history of radiotherapy to the head. For patients who were too ill to respond, functionally impaired or had died, interviews were conducted with a proxy, usually the spouse. Proxy interviews were conducted for 16% (n=78) of glioma cases, 8% (n=15) of meningioma cases, and 3% (n=23) of controls.
Information on occupational histories was collected for all jobs held for at least six months since the age of 16 years and included the name of the employer, dates of employment, job title, amount of time worked (full versus part time), type of business or service, tasks conducted, and materials and equipment used. For jobs with expected potential for exposure to specific chemicals, additional occupational information was collected through industry- and job-specific interview modules of questions.[33] Sixty-four modules were developed to elicit detailed information on workplace determinants of exposure to a variety of agents, including chlorinated solvents. The information collected in the modules included the average frequency of various solvent-related tasks (converted to times per week), the average length of time it took to perform given solvent-related tasks (converted to hours per instance), sensory descriptions, dermal exposure, work practices, engineering controls, and personal protective equipment use.[33] Electronic versions of the occupational history data were sent to an expert industrial hygienist (PAS) within two weeks of the interview and reviewed for completeness and consistency. Up to ten supplemental questions were developed to resolve missing or ambiguous information, and brief telephone re-interviews were conducted within six weeks of the initial interview. Thirty-six subjects did not complete the occupational histories. Of these, 29 (including 9 glioma cases, 5 meningioma cases, and 15 controls) never worked outside of the home and were considered unexposed. The remaining seven patients (5 glioma cases and 2 controls) were excluded from our analyses.
Based on the occupational histories and the industrial hygiene literature, the industrial hygienist assessed levels of exposure to six chlorinated solvents distinguished by the numbers of carbon atoms (1 or 2) and covalently bound chlorine atoms (2, 3 or 4): dichloromethane (DCM) (synonymous with methylene chloride), trichloromethane (chloroform), tetrachloromethane (carbon tetrachloride), 1,1,1-trichloroethane (TCA), trichloroethylene (TCE), and tetrachloroethylene [perchloroethylene (PERC)]. We did not include singly chlorinated methane or ethane, as these agents have different properties and, thus, different uses, namely, as refrigerants and gasoline additives rather than as industrial cleansers.
The exposure assessment for the six solvents was conducted after an extensive review of the occupational health literature. Approximately 350 papers, reports and documents on these solvents were reviewed. Values representing more than 5000 measurement results were abstracted and compiled,[34 35] and determinants of exposure [mechanism of release (e.g., evaporation), process condition (i.e., open or closed), temperature, usage rate (quantity used), type of ventilation, location (indoors or out of doors), work in a confined space, and proximity to the source] associated with the measurements were identified. If the exposure determinants listed above were not identified, rules were developed for assigning the determinant values by decade. For example, if a study measured exposure to a chemist but did not indicate the determinants of exposure such as the type of location where the subject worked, the measurements were assigned the “indoor” location. Confidence ratings for the determinants values were assigned on a scale of 1 (low) to 4 (high).
From this information, over 20 task exposure matrices were developed for common tasks associated with the solvents (e.g., degreasing, dry cleaning, lab work, hospital care, plastic manufacture, etc.) that assigned probability and frequency of exposure by decade (1930s–1990s). For intensity, the measurement data abstracted from the literature were modeled from their exposure determinants using maximum likelihood methods to estimate the arithmetic mean exposure level in parts per million (ppm) for each unique combination of exposure determinants and year.[36]
Probability, frequency, and intensity of exposure to each solvent were assessed for each job according to decade after review of all the available information using the task exposure matrices but modifying them based on the subject-specific reported information. The probability that the subject was likely exposed given the available information was categorized as 0%, 1–10%, 10–49%, 50–89%, or ≥90%. For all subjects with a probability >0%, a frequency was assigned as ≤1 hr/wk, 2–10, >10–20, or >20. Lastly, the industrial hygienist assigned a confidence score, which reflected the quality of the background information on which the probability and frequency estimates were made, using a four-point scale ranging from 1 (low) to 4 (high).
To estimate intensity, each job with a probability >0% was evaluated for the same determinants of exposure following the same rules as for the measurement data. A model for each solvent was then used to assign the estimated exposure level to each of the six solvents to each job based on its assigned determinants. The intensity level was estimated on a continuous scale in parts per million.
For each of the six solvents, subjects were categorized as unexposed if the probability of exposure to a given solvent was 0% in all of their jobs. Subjects were categorized as possibly exposed if the maximum probability of exposure among all jobs held was > 0% and ≤ 49%. Subjects were categorized as probably exposed if there was at least a 50% probability of exposure in any of the jobs held; thus, the categories to which subjects were assigned as unexposed, possibly exposed and probably exposed were mutually exclusive for a given solvent. Additional exposure metrics for probably exposed subjects included: duration of exposure (years of employment in jobs with exposure probability ≥ 50%), cumulative exposure (estimated as ppm-hours (intensity*frequency*years) summed across all jobs with exposure probability ≥ 50%), average weekly exposure (estimated as ppm-hours per week using cumulative exposure divided by years exposed), and highest exposure (estimated as ppm, the highest intensity achieved in any job) for each of the six solvents.
Possibly exposed subjects were included in initial analyses in which exposure was assessed as unexposed versus possibly exposed, but they were excluded from all subsequent analyses. This was due to the likely poor specificity of exposure classification for this group, as indicated by the unrealistically high prevalence of exposure (24–33% possibly exposed) among controls. Given the importance of using high specificity exposure metrics when evaluating risks related to rare exposures,[37] we restricted analyses for more detailed exposure metrics to unexposed and probably exposed subjects only.
Statistical analysis
Unconditional logistic regression models were used to calculate odds ratios (OR) and 95% confidence intervals (95% CI) for risk of glioma or meningioma. Models were adjusted for age at diagnosis, sex, race/ethnicity, hospital site, and residential zone defined by proximity to the hospital. Additional adjustment for cigarette smoking and education was made, but point estimates did not change materially, and, thus, we present results from the more parsimonious models adjusted only for the matching factors described above. Additionally, we adjusted for estimated cumulative occupational exposures to lead, magnetic fields, herbicides and insecticides, each of which has been implicated, to some degree, in previous studies of brain tumor risk.[31 32 38] Separate models were fitted for each of the six solvents for each exposure metric. For ever/never analyses for particular solvents, we additionally included all other solvents in the model to account for possible confounding by other solvent exposures. We also evaluated risks related to exposure to any solvent, in which subjects were classified as exposed if they were probably exposed to any of the six solvents and unexposed if they were not exposed to any of the six solvents. To explore possible effect modification, we stratified ever/never analyses of glioma risk by gender. Too few cases of meningioma were exposed to have the power to conduct stratified analyses or analyses of more detailed exposure metrics (i.e., duration of exposure, cumulative exposure, average weekly exposure, and highest exposure).
For analyses of risk of glioma related to the more detailed exposure metrics, we used the median level of duration, cumulative, average weekly and highest exposure among controls as a cut-point to classify all probably exposed subjects as low versus highly exposed for each exposure metric for a given solvent. We conducted analyses using unexposed subjects as the referent group as well as using the low exposed subjects as the referent group. The latter analyses accounted for the possibility that unexposed persons may be substantially different from exposed persons in ways that cannot be adjusted for in our analysis. Thus, comparing highly exposed subjects with those who had lower exposure levels may be a more accurate comparison for evaluating risks, assuming that a dose-response relationship exists. We also conducted analyses exploring the potential effects of a 10-year exposure latency period by adjusting the exposure metrics excluding any work performed within 10 years of diagnosis (interview).
For sensitivity analyses, we reran all the models excluding subjects categorized as probably exposed if their confidence was one. Four subjects (two controls, one glioma case and one meningioma case) were dropped. To account for possible selection bias, we also reran our analyses systematically excluding each major subgroup of controls, as defined above. All models also were reanalyzed excluding subjects for whom information was collected from a proxy respondent (n=117). All analyses were performed using Stata version 11.0 (College Station, TX).
RESULTS
Table 1 shows selected characteristics of the study participants by case-control status. Study subjects were predominantly (~90%) white, non-Hispanic. The mean age (and standard deviation) at hospital admission was 49.6 (16.5) years for controls, 51.5 (16.9) years for glioma patients and 55.2 (14.3) years for meningioma patients. The majority of glioma patients were male, whereas the majority of meningioma cases were female. About 50% of controls and cases were diagnosed at St. Joseph’s Hospital and Medical Center in Phoenix. Regardless of case status, the majority of subjects received some post-high school education, but, of these, the majority did not complete a four-year college degree. Most had a history of cigarette smoking. Very few subjects (<3%) reported ever having received radiation therapy to the head.
Table 1.
Selected characteristics of participants in the National Cancer Institute (NCI) Brain Tumor Case-control study, 1994–1998
| Characteristics | Controls (n=797) a n (%) |
Glioma (n = 484) a n (%) |
Meningioma (n = 197) n (%) |
|---|---|---|---|
| Age at interview (years) | |||
| 18–29 | 101 (12.7) | 58 (12.0) | 4 (2.0) |
| 30–49 | 310 (38.9) | 173 (35.7) | 71 (36.0) |
| 50–69 | 276 (34.6) | 166 (34.3) | 85 (43.1) |
| 70–90 | 110 (13.8) | 87 (18.0) | 37 (18.8) |
| Sex | |||
| Female | 434 (54.5) | 211 (43.6) | 151 (76.6) |
| Male | 363 (45.5) | 273 (56.4) | 46 (23.4) |
| Race/ethnicity | |||
| White, non-Hispanic | 713 (89.5) | 439 (90.7) | 163 (82.7) |
| White, Hispanic | 54 (6.8) | 26 (5.4) | 14 (7.1) |
| African American | 19 (2.4) | 10 (2.1) | 9 (4.6) |
| Other | 11 (1.4) | 9 (1.9) | 11 (5.6) |
| Hospital site | |||
| Phoenix, AZ | 405 (50.8) | 243 (50.2) | 99 (50.3) |
| Boston, MA | 220 (27.6) | 150 (31) | 79 (40.1) |
| Pittsburgh, PA | 172 (21.6) | 91 (18.8) | 19 (9.6) |
| Proximity of residence to the hospital (miles) | |||
| 0–4 | 262 (32.9) | 124 (25.6) | 59 (29.9) |
| 5–14 | 227 (28.5) | 152 (31.4) | 56 (28.4) |
| 15–29 | 163 (20.5) | 115 (23.8) | 43 (21.8) |
| 30–49 | 59 (7.4) | 42 (8.7) | 17 (8.6) |
| 50+ | 86 (10.8) | 51 (10.5) | 22 (11.2) |
| Educational level | |||
| < High school | 105 (13.2) | 63 (13.0) | 24 (12.2) |
| High school or GED | 232 (29.1) | 121 (25.0) | 57 (28.9) |
| 1–3 years college/technical school | 245 (30.7) | 130 (26.9) | 68 (34.5) |
| 4-year college | 105 (13.2) | 87 (18.0) | 23 (11.7) |
| Graduate/professional school | 89 (11.2) | 67 (13.8) | 24 (12.2) |
| Unknown | 21 (2.6) | 16 (3.3) | 1 (0.5) |
| Cigarette smoker | |||
| Never | 292 (36.6) | 215 (44.4) | 81 (41.1) |
| Ever | 488 (61.2) | 256 (52.9) | 111 (56.3) |
| Unknown | 17 (2.1) | 13 (2.7) | 5 (2.5) |
| Radiation therapy to head | |||
| No | 775 (97.2) | 476 (98.3) | 189 (95.9) |
| Yes | 22 (2.8) | 8 (1.7) | 8 (4.1) |
Two controls and five glioma cases were missing occupational exposure data.
Risk of glioma associated with exposure to chlorinated solvents
Table 2 presents results from models describing the risk of glioma related to ever having been exposed to any chlorinated solvent or to a specific solvent. Sixteen percent (n=89) of controls and 14.4% (n=51) of cases were evaluated as having ever been exposed to any chlorinated solvent with a probability of at least 50%. The jobs accounting for most of the ever exposed subjects included chemists, various types of mechanics, painters, lab technicians, electricians, dry cleaning workers, surgeons (chloroform only), and farmers (DCM only). Overall risk of glioma was not significantly associated with exposure to any chlorinated solvent (OR=0.9, 95% CI: 0.6, 1.3), with some suggestion of an inverse association in men (OR=0.6, 95% CI: 0.4, 1.0) but not in women (OR=1.1, 95% CI: 0.5, 2.3). For any given solvent, less than 5% of cases [n ranging from 9 to 21 (mean 14)], mostly male, were rated as probably exposed. The most common exposure was DCM, and the least common exposures were TCA and PERC. Observed associations were consistent with the null hypothesis for each solvent, with the exceptions of DCM and TCE, which showed inverse associations among males (but not females). Additional adjustment for occupational exposure to lead, magnetic fields, herbicides or insecticides, either individually or jointly, had no meaningful effect on odds ratio estimates (data not shown).
Table 2.
Odds ratios a for risk of glioma associated with estimated occupational exposure to chlorinated solvents, stratified by gender (NCI Brain Tumor Case-control Study, 1994–1998)
| Chlorinated Solvent | Exposure status | All | Males | Females | ||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Controls n (%) | Cases n (%) | OR (95% CI) | Controls n | Cases n | OR (95% CI) | Controls n | Cases n | OR (95% CI) | ||
| Any solvent | Unexposed | 466 (84.0) | 302 (85.6) | 1.0 | 163 | 151 | 1.0 | 303 | 151 | 1.0 |
| Exposed | 89 (16.0) | 51 (14.4) | 0.9 (0.6, 1.3) | 65 | 38 | 0.6 (0.4, 1.0) | 24 | 13 | 1.1 (0.5, 2.3) | |
| Methylene chloride (DCM) | Unexposed | 534 (67.0) | 337 (69.6) | 1.0 | 183 | 167 | 1.0 | 351 | 170 | 1.0 |
| Possible | 210 (26.4) | 126 (26.0) | 0.8 (0.6, 1.1) | 139 | 90 | 0.7 (0.5, 1.0) | 71 | 36 | 1.1 (0.7, 1.7) | |
| Probable | 53 (6.6) | 21 (4.3) | 0.5 (0.3, 0.9) | 41 | 16 | 0.4 (0.2, 0.8) | 12 | 5 | 1.0 (0.3, 2.9) | |
| Chloroform | Unexposed | 551 (69.1) | 347 (71.7) | 1.0 | 211 | 180 | 1.0 | 340 | 167 | 1.0 |
| Possible | 225 (28.2) | 119 (24.6) | 0.8 (0.6, 1.0) | 140 | 82 | 0.7 (0.5, 1.0) | 85 | 37 | 0.9 (0.6, 1.4) | |
| Probable | 21 (2.6) | 18 (3.7) | 1.3 (0.7, 2.4) | 12 | 11 | 1.1 (0.5, 2.6) | 9 | 7 | 1.5 (0.5, 4.1) | |
| Carbon tetrachloride | Unexposed | 576 (72.3) | 367 (75.8) | 1.0 | 213 | 182 | 1.0 | 363 | 185 | 1.0 |
| Possible | 192 (24.1) | 102 (21.1) | 0.7 (0.5, 0.9) | 127 | 79 | 0.7 (0.5, 1.0) | 65 | 23 | 0.7 (0.4, 1.1) | |
| Probable | 29 (3.6) | 15 (3.1) | 0.6 (0.3, 1.2) | 23 | 12 | 0.6 (0.3, 1.2) | 6 | 3 | 1.1 (0.3, 4.5) | |
| 1,1,1-Trichloroethane (TCA) | Unexposed | 525 (65.9) | 334 (69.0) | 1.0 | 190 | 171 | 1.0 | 335 | 163 | 1.0 |
| Possible | 260 (32.6) | 140 (28.9) | 0.8 (0.6, 1.0) | 164 | 92 | 0.6 (0.5, 0.9) | 96 | 48 | 1.1 (0.7, 1.7) | |
| Probable | 12 (1.5) | 10 (2.1) | 1.0 (0.4, 2.4) | 9 | 10 | 1.2 (0.5, 3.1) | 3 | 0 | - | |
| Trichloroethylene (TCE) | Unexposed | 528 (66.3) | 334 (69.0) | 1.0 | 193 | 166 | 1.0 | 335 | 168 | 1.0 |
| Possible | 242 (30.4) | 139 (28.7) | 0.8 (0.6, 1.1) | 148 | 99 | 0.8 (0.6, 1.1) | 94 | 40 | 0.9 (0.6, 1.3) | |
| Probable | 27 (3.4) | 11 (2.3) | 0.5 (0.3, 1.1) | 22 | 8 | 0.4 (0.2, 1.0) | 5 | 3 | 1.0 (0.2, 4.3) | |
| Perchloroethylene (PERC) | Unexposed | 522 (65.5) | 339 (70.0) | 1.0 | 191 | 165 | 1.0 | 331 | 174 | 1.0 |
| Possible | 255 (32.0) | 136 (28.1) | 0.7 (0.5, 0.9) | 166 | 102 | 0.7 (0.5, 1.0) | 89 | 34 | 0.7 (0.5, 1.1) | |
| Probable | 20 (2.5) | 9 (1.9) | 0.7 (0.3, 1.6) | 6 | 6 | 1.2 (0.4, 3.8) | 14 | 3 | 0.5 (0.1, 1.7) | |
Odds ratios computed using unconditional logistic regression adjusting for age group (<30, 30–49, 50–69, 70+), race (white vs. non-white), sex, hospital site and proximity of residence to the hospital.
Table 3 presents results for glioma risk in relation to duration of exposure, cumulative exposure, average weekly exposure, and highest exposure for each individual solvent. None of the six chlorinated solvents was consistently associated with glioma risk by these four exposure metrics at a significance level of α = 0.05. Average weekly exposure to DCM was inversely associated with glioma risk in an exposure-response relationship, but other exposure metrics for DCM did not demonstrate a decreasing risk gradient among exposed subjects. In fact, when comparing workers with exposure levels above the median to those with exposure levels below the median, risk of glioma was elevated with increasing duration of exposure to DCM, although the association was not statistically significant. Average weekly exposure to carbon tetrachloride was significantly associated with an increased risk of glioma when comparing workers with exposure levels above the median versus those with exposure levels below the median. Similarly, risks were elevated for subjects with levels above the median for cumulative exposure, highest exposure and duration of exposure to carbon tetrachloride, but they were not statistically significant. However, glioma risk was significantly elevated with increasing cumulative and average weekly exposure to carbon tetrachloride after adjusting for occupational exposures to lead and magnetic fields (OR=56.4, 95% CI: 1.9, 1686.2 for cumulative; OR=60.2, 95% CI: 2.4, 1533.8 for average weekly), based on 11 highly exposed cases and 14 highly exposed controls.
Table 3.
Odds ratios for risk of glioma associated with estimated occupational exposure to chlorinated solvents according to four exposure metrics with exposure levels categorized as below (=low) or above (=high) the median level in controls (NCI Brain Tumor Case-control Study, 1994–1998)
| Exposure metric/level | Controls n (%) | Cases n (%) | ORa (95% CI) | Ptrendb | ORc (95% CI) | Pvalue |
|---|---|---|---|---|---|---|
| Methylene chloride (DCM) | ||||||
|
| ||||||
| Years exposed | ||||||
| Unexposed | 534 (91.0) | 337 (94.1) | 1.0 | |||
| Low | 31 (5.3) | 9 (2.5) | 0.4 (0.2, 0.8) | 1.0 | ||
| High | 22 (3.8) | 12 (3.4) | 0.7 (0.3, 1.4) | 0.04 | 2.1 (0.6, 6.7) | 0.22 |
| Cumulative exposure | ||||||
| Unexposed | 534 (91.0) | 337 (94.1) | 1.0 | |||
| Low | 27 (4.6) | 11 (3.1) | 0.5 (0.2, 1.0) | 1.0 | ||
| High | 26 (4.4) | 10 (2.8) | 0.5 (0.2, 1.1) | 0.02 | 0.6 (0.2, 2.0) | 0.37 |
| Average weekly exposure | ||||||
| Unexposed | 534 (91.0) | 337 (94.1) | 1.0 | |||
| Low | 27 (4.6) | 15 (4.2) | 0.7 (0.3, 1.3) | 1.0 | ||
| High | 26 (4.4) | 6 (1.7) | 0.3 (0.1, 0.8) | 0.01 | 0.2 (0.0, 0.8) | 0.02 |
| Highest exposure | ||||||
| Unexposed | 534 (91.0) | 337 (94.1) | 1.0 | |||
| Low | 27 (4.6) | 12 (3.4) | 0.5 (0.3, 1.1) | 1.0 | ||
| High | 26 (4.4) | 9 (2.5) | 0.5 (0.2, 1.0) | 0.02 | 0.8 (0.2, 2.6) | 0.66 |
|
| ||||||
| Chloroform | ||||||
|
| ||||||
| Years exposed | ||||||
| Unexposed | 551 (96.3) | 347 (95.1) | 1.0 | |||
| Low | 12 (2.1) | 9 (2.5) | 1.2 (0.5, 2.9) | 1.0 | ||
| High | 9 (1.6) | 9 (2.5) | 1.3 (0.5, 3.4) | 0.51 | 2.3 (0.4, 14.6) | 0.39 |
| Cumulative exposure | ||||||
| Unexposed | 551 (96.3) | 347 (95.1) | 1.0 | |||
| Low | 11 (1.9) | 11 (3.0) | 1.5 (0.6, 3.6) | 1.0 | ||
| High | 10 (1.8) | 7 (1.9) | 1.0 (0.4, 2.6) | 0.71 | 1.4 (0.3, 7.0) | 0.68 |
| Average weekly exposure | ||||||
| Unexposed | 551 (96.3) | 347 (95.1) | 1.0 | |||
| Low | 16 (2.8) | 14 (3.8) | 1.3 (0.6, 2.7) | 1.0 | ||
| High | 5 (0.9) | 4 (1.1) | 1.1 (0.3, 4.3) | 0.59 | 2.2 (0.2, 24.5) | 0.52 |
| Highest exposure | ||||||
| Unexposed | 551 (96.3) | 347 (95.1) | 1.0 | |||
| Low | 12 (2.1) | 8 (2.2) | 0.9 (0.4, 2.4) | 1.0 | ||
| High | 9 (1.6) | 10 (2.7) | 1.6 (0.7, 4.2) | 0.38 | 4.0 (0.7, 24.3) | 0.13 |
|
| ||||||
| Carbon tetrachloride | ||||||
|
| ||||||
| Years exposed | ||||||
| Unexposed | 576 (95.2) | 367 (96.1) | 1.0 | |||
| Low | 18 (3.0) | 7 (1.8) | 0.5 (0.2, 1.2) | 1.0 | ||
| High | 11 (1.8) | 8 (2.1) | 0.9 (0.3, 2.2) | 0.31 | 1.6 (0.4, 7.5) | 0.55 |
| Cumulative exposure | ||||||
| Unexposed | 576 (95.2) | 367 (96.1) | 1.0 | |||
| Low | 15 (2.5) | 5 (1.3) | 0.4 (0.1, 1.1) | 1.0 | ||
| High | 14 (2.3) | 10 (2.6) | 0.9 (0.4, 2.0) | 0.34 | 2.8 (0.6, 14.4) | 0.21 |
| Average weekly exposure | ||||||
| Unexposed | 576 (95.2) | 367 (96.1) | 1.0 | |||
| Low | 15 (2.5) | 4 (1.1) | 0.3 (0.1, 0.9) | 1.0 | ||
| High | 14 (2.3) | 11 (2.9) | 1.1 (0.5, 2.4) | 0.45 | 7.1 (1.1, 45.2) | 0.04 |
| Highest exposure | ||||||
| Unexposed | 576 (95.2) | 367 (96.1) | 1.0 | |||
| Low | 15 (2.5) | 4 (1.1) | 0.3 (0.1, 1.0) | 1.0 | ||
| High | 14 (2.3) | 11 (2.9) | 1.0 (0.4, 2.2) | 0.39 | 3.2 (0.6, 17.2) | 0.18 |
|
| ||||||
| 1,1,1-Trichloroethane (TCA) | ||||||
|
| ||||||
| Years exposed | ||||||
| Unexposed | 525 (97.8) | 334 (97.1) | 1.0 | |||
| Low | 6 (1.1) | 5 (1.5) | 1.0 (0.3, 3.4) | 1.0 | ||
| High | 6 (1.1) | 5 (1.5) | 0.8 (0.2, 2.7) | 0.76 | - | |
| Cumulative exposure | ||||||
| Unexposed | 525 (97.8) | 334 (97.1) | 1.0 | |||
| Low | 6 (1.1) | 6 (1.7) | 1.1 (0.3, 3.5) | 1.0 | ||
| High | 6 (1.1) | 4 (1.2) | 0.7 (0.2, 2.6) | 0.70 | - | |
| Average weekly exposure | ||||||
| Unexposed | 525 (97.8) | 334 (97.1) | 1.0 | |||
| Low | 6 (1.1) | 6 (1.7) | 1.0 (0.3, 3.3) | 1.0 | ||
| High | 6 (1.1) | 4 (1.2) | 0.8 (0.2, 2.8) | 0.76 | - | |
| Highest exposure | ||||||
| Unexposed | 525 (97.8) | 334 (97.1) | 1.0 | |||
| Low | 6 (1.1) | 5 (1.5) | 0.9 (0.3, 3.1) | 1.0 | ||
| High | 6 (1.1) | 5 (1.5) | 0.9 (0.3, 3.0) | 0.80 | - | |
|
| ||||||
| Trichloroethylene (TCE) | ||||||
|
| ||||||
| Years exposed | ||||||
| Unexposed | 528 (95.1) | 334 (96.8) | 1.0 | |||
| Low | 16 (2.9) | 3 (0.9) | 0.3 (0.1, 0.9) | 1.0 | ||
| High | 11 (2.0) | 8 (2.3) | 1.0 (0.4, 2.6) | 0.32 | 4.6 (0.5, 39.7) | 0.16 |
| Cumulative exposure | ||||||
| Unexposed | 528 (95.1) | 334 (96.8) | 1.0 | |||
| Low | 14 (2.5) | 4 (1.2) | 0.4 (0.1, 1.2) | 1.0 | ||
| High | 13 (2.3) | 7 (2.0) | 0.7 (0.3, 1.8) | 0.19 | 0.7 (0.1, 4.8) | 0.68 |
| Average weekly exposure | ||||||
| Unexposed | 528 (95.1) | 334 (96.8) | 1.0 | |||
| Low | 14 (2.5) | 8 (2.3) | 0.7 (0.3, 1.7) | 1.0 | ||
| High | 13 (2.3) | 3 (0.9) | 0.4 (0.1, 1.2) | 0.07 | 0.1 (0.0, 1.7) | 0.11 |
| Highest exposure | ||||||
| Unexposed | 528 (95.1) | 334 (96.8) | 1.0 | |||
| Low | 14 (2.5) | 6 (1.7) | 0.6 (0.2, 1.6) | 1.0 | ||
| High | 13 (2.3) | 5 (1.5) | 0.5 (0.2, 1.5) | 0.11 | 0.1 (0.0, 1.8) | 0.13 |
|
| ||||||
| Perchloroethylene (PERC) | ||||||
|
| ||||||
| Years exposed | ||||||
| Unexposed | 522 (96.3) | 339 (97.4) | 1.0 | |||
| Low | 13 (2.4) | 6 (1.7) | 0.8 (0.3, 2.0) | 1.0 | ||
| High | 7 (1.3) | 3 (0.9) | 0.7 (0.2, 2.7) | 0.44 | - | |
| Cumulative exposure | ||||||
| Unexposed | 522 (96.3) | 339 (97.4) | 1.0 | |||
| Low | 10 (1.9) | 6 (1.7) | 0.9 (0.3, 2.6) | 1.0 | ||
| High | 10 (1.9) | 3 (0.9) | 0.5 (0.1, 1.9) | 0.35 | - | |
| Average weekly exposure | ||||||
| Unexposed | 522 (96.3) | 339 (97.4) | 1.0 | |||
| Low | 10 (1.9) | 5 (1.4) | 0.7 (0.2, 2.2) | 1.0 | ||
| High | 10 (1.9) | 4 (1.2) | 0.7 (0.2, 2.3) | 0.46 | - | |
| Highest exposure | ||||||
| Unexposed | 522 (96.3) | 339 (97.4) | 1.0 | |||
| Low | 12 (2.2) | 4 (1.2) | 0.5 (0.2, 1.7) | 1.0 | ||
| High | 8 (1.5) | 5 (1.4) | 1.0 (0.3, 3.3) | 0.63 | - | |
ORs computed using unconditional logistic regression adjusting for age group, race, sex, hospital and proximity of residence to the hospital, and excluding possibly exposed individuals.
Ptrend was calculated using the exposure metric as a 3-level ordinal variable (0=unexposed, 1=below median level, 2=above median level), and, thus, does not necessarily indicate a risk gradient among the exposed.
ORs computed using unconditional logistic regression adjusting for age group, race, sex, hospital and proximity of residence to the hospital, and excluding unexposed and possibly exposed individuals.
In general, including a 10-year lag did not substantially change our findings, but point estimates for chloroform and DCM moved towards the null (data not shown). Excluding subjects for whom proxy respondents provided the information or subjects with a confidence level of one (low confidence), or excluding any of the major control subgroups, also did not meaningfully change point estimates (data not shown).
Risk of meningioma associated with chlorinated solvents
Only 16 (11%) of meningioma cases had ever been exposed to any chlorinated solvent, and fewer than 10 cases (with n ranging from 3 to 8) were classified as having a probability ≥50% of ever having been exposed to any particular chlorinated solvent (Table 4). The most common exposures were DCM and chloroform, and the least common was PERC. Overall risk of meningioma was not associated with exposure to any of the chlorinated solvents, although non-significant elevated risks were observed for exposure to TCA (OR=2.3, 95% CI: 0.7, 7.2), which was more pronounced in the model including all six chlorinated solvents (OR=4.1, 95% CI: 0.6, 28.6) (Table 4). Chloroform and TCE also had non-significantly elevated risks that were more pronounced in the models adjusting for all other solvents. Additional adjustment for occupational exposures to lead, magnetic fields, herbicides or insecticides had no material effect individually or jointly on odds ratio estimates (data not shown). Point estimates did not change appreciably in sensitivity analyses; this includes dropping subjects with a confidence level of one, excluding subjects for whom a proxy respondent provided the information collected, excluding any of the control series diagnostic subgroups, or accounting for a 10-year minimum latency (data not shown).
Table 4.
Odds ratios for risk of meningioma associated with estimated occupational exposure to chlorinated solvents (National Cancer Institute Brain Tumor Case-control Study, 1994–1998)
| Chlorinated Solvent | Exposure status | Controls n (%) | Cases n (%) | ORa (95% CI) | ORb (95% CI) |
|---|---|---|---|---|---|
| Any solvent | Unexposed | 466 (84.0) | 131 (89.1) | 1.0 | |
| Exposed | 89 (16.0) | 16 (10.9) | 0.8 (0.4, 1.4) | ||
| Methylene chloride (DCM) | Unexposed | 534 (67.0) | 147 (74.6) | 1.0 | 1.0 |
| Possible | 210 (26.4) | 42 (21.3) | 0.9 (0.6, 1.3) | 1.6 (0.7, 3.5) | |
| Probable | 53 (6.6) | 8 (4.1) | 0.8 (0.4, 1.8) | 0.8 (0.2, 3.0) | |
| Chloroform | Unexposed | 551 (69.1) | 150 (76.1) | 1.0 | 1.0 |
| Possible | 225 (28.2) | 39 (19.8) | 0.7 (0.5, 1.1) | 0.9 (0.4, 1.9) | |
| Probable | 21 (2.6) | 8 (4.1) | 1.3 (0.5, 3.1) | 1.9 (0.6, 5.9) | |
| Carbon tetrachloride | Unexposed | 576 (72.3) | 158 (80.2) | 1.0 | 1.0 |
| Possible | 192 (24.1) | 32 (16.2) | 0.6 (0.4, 1.0) | 0.5 (0.2, 1.1) | |
| Probable | 29 (3.6) | 7 (3.6) | 1.2 (0.5, 3.0) | 0.6 (0.1, 2.9) | |
| 1,1,1-Trichloroethane (TCA) | Unexposed | 525 (65.9) | 146 (74.1) | 1.0 | 1.0 |
| Possible | 260 (32.6) | 46 (23.4) | 0.8 (0.5, 1.2) | 0.9 (0.4, 2.1) | |
| Probable | 12 (1.5) | 5 (2.5) | 2.3 (0.7, 7.2) | 4.1 (0.6, 28.6) | |
| Trichloroethylene (TCE) | Unexposed | 528 (66.3) | 145 (73.6) | 1.0 | 1.0 |
| Possible | 242 (30.4) | 46 (23.4) | 0.8 (0.5, 1.2) | 1.0 (0.4, 2.2) | |
| Probable | 27 (3.4) | 6 (3.0) | 1.2 (0.5, 3.2) | 1.5 (0.4, 6.3) | |
| Perchloroethylene (PERC) | Unexposed | 522 (65.5) | 142 (72.1) | 1.0 | 1.0 |
| Possible | 255 (32.0) | 52 (26.4) | 0.9 (0.6, 1.3) | 1.0 (0.5, 2.2) | |
| Probable | 20 (2.5) | 3 (1.5) | 0.5 (0.1, 1.7) | 0.3 (0.1, 1.7) |
Odds ratios computed using unconditional logistic regression adjusting for age group (<30, 30–49, 50–69, 70+), race (white vs. non-white), sex, hospital and proximity of residence to the hospital.
Odds ratios computed as above, and additionally adjusting for all other solvents.
DISCUSSION
In this large hospital-based case-control study, using state-of-the-art exposure assessment with job-specific interview modules, we found no consistent evidence of an increased risk of glioma or meningioma related to occupational exposures to any of the six chlorinated solvents evaluated. There was some suggestion of a positive association between carbon tetrachloride and glioma risk, although the confidence intervals were wide. TCA was also non-significantly associated with elevated risk of meningioma. We observed an inverse association between average weekly exposure to DCM and glioma risk among highly exposed subjects (exposure > median), but not for duration of exposure, cumulative exposure or highest exposure.
Several studies have found an association between risk of brain tumors and occupations involving potential for exposure to chlorinated solvents;[15–18 23] however, these studies did not identify specific etiologic agents or disentangle the effects of potentially correlated occupational exposures, such as non-ionizing electromagnetic radiation, lead and other chemical agents. Our results raise questions as to whether exposure to chlorinated solvents is the relevant hazard underlying the reported increased risk of glioma among electrical and electronics workers.[18]
Few studies have investigated the association between occupational exposures to specific chlorinated solvents and risk of brain tumors.[26 27] In general, these were mortality studies in which exposure was assessed through job-exposure matrices using information collected either from next of kin[26] or from death certificates.[27] Thus, they did not have available the detailed occupational information from the subject that we had. Moreover, cases were ascertained in the late 1970s[26] or 1980s,[27] so their work experience may have occurred prior to peak use of chlorinated solvents in the United States. Unlike our study, Heineman and colleagues found some evidence for an increased risk of astrocytic brain tumors related to occupational exposure to DCM, and weak or no evidence for the other five solvents evaluated, although they did observe some elevated ORs for carbon tetrachloride and trichloroethane. Similarly, Cocco and colleagues found some evidence for an increased risk in women of CNS tumors, in general, related to DCM, but no clear pattern by probability or intensity of exposure; they did not examine risks in men. Cocco and colleagues did not assess exposure to specific chlorinated solvents other than DCM, although they did evaluate chlorinated aliphatic hydrocarbons as a group, nor did they specifically evaluate risks of glioma or benign meningioma. Given the absence of a priori evidence supporting a protective effect of DCM, and the fact that the association was limited to only one exposure metric, it is doubtful that this association is causal.
Our study has several important strengths. A hospital-based design was used to allow for the rapid ascertainment of newly diagnosed cases, high participation rates and interview of cases and controls under similar conditions. We used a robust exposure assessment method based on detailed occupational histories and job-specific interview modules designed to elicit information on exposure to six widely used chlorinated solvents, rather than relying only on a job-exposure matrix. We conducted an extensive literature review and developed probability and frequency task matrices to follow when subject-specific information was missing. We used a rigorous method to estimate intensity.[36] Moreover, we also had relatively detailed information on cumulative occupational exposures to other agents possibly associated with brain tumors, including lead, magnetic fields and pesticides, which allowed us to address potential confounding.
Our study also has several limitations. We had limited power to evaluate exposure-response relationships given the small numbers of subjects estimated to be highly exposed to any particular chlorinated solvent. We cannot rule out the possible importance of exposure misclassification, even though our exposure assessment was based on more detailed information than that in previously published studies. Misclassification may be due, in part, to the complexity of use of these solvents which have been used interchangeably and at times together, making the evaluation of specific exposures difficult. It is unlikely that misclassification would differ between controls and cases; thus, this could bias our estimates of association towards the null, so our findings may be false negatives and should be interpreted with caution. Another potential limitation of this study is the possibility that impaired cognition or memory might limit the ability of glioma patients to recall past exposures. In principal, this could lead to under- or over-reporting but would be expected to bias odds ratio estimates towards the null. Nevertheless, information collected directly from study participants rather than a proxy respondent is generally a more reliable source of information for job histories. The possibility of reporting bias was lessened by the highly structured and controlled nature of the computer-assisted personal interview. Thus, any bias of this kind is likely to be random, resulting in bias towards the null.
In summary, this large U.S. hospital-based case-control study of incident glioma and meningioma, using the most detailed exposure assessment method to date, does not show clear evidence for an association with occupational exposures to six chlorinated solvents.
What this paper adds.
Chlorinated solvents are classified as probable or possible carcinogens and have been associated with increased risk of several cancers, including leukemia, lymphoma and urinary tract cancer, but it is unknown whether exposure to such solvents increases risk of brain tumors.
Three case-control studies have reported increased risk of brain tumors associated with occupational exposure to chlorinated solvents, but these studies had limited exposure information collected from next-of-kin.
Our study coupled direct interview of rapidly ascertained brain tumors cases and controls with the most detailed exposure assessment method to date to evaluate a possible relationship between exposure to chlorinated solvents and brain tumor risk.
We found no consistent evidence of an increased risk of glioma or meningioma related to occupational exposures to any of six chlorinated solvents, though there was limited evidence of a positive association between carbon tetrachloride and glioma.
Acknowledgments
Funding
This research was supported, in part, by the Intramural Research Program of the Division of Cancer Epidemiology and Genetics, National Cancer Institute at the National Institutes of Health.
Abbreviations
- CI
confidence interval
- CNS
central nervous system
- DCM
dichloromethane
- NCI
National Cancer Institute
- OR
odds ratio
- PERC
perchloroethylene
- ppm
parts per million
- TCA
trichloroethane
- TCE
trichloroethylene
Footnotes
Competing interests
None
Ethical approval
This study was approved by the Institutional Review Boards of each participating institution, and written informed consent was obtained from all study participants or their proxies.
Disclaimer
The findings and conclusions in this report are those of the authors and do not necessarily represent the views of the National Institute for Occupational Safety and Health.
Licence statement: The Corresponding Author has the right to grant on behalf of all authors and does grant on behalf of all authors, an exclusive licence (or non-exclusive for government employees) on a worldwide basis to the BMJ Publishing Group Ltd and its Licensees to permit this article (if accepted) to be published in Occupational and Environmental Medicine and any other BMJPGL products to exploit all subsidiary rights, as set out in our licence (http://group.bmj.com/products/journals/instructions-for-authors/licence-forms) and the Corresponding Author accepts and understands that any supply made under these terms is made by BMJPGL to the Corresponding Author.
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