Krishnan, Geetha MPH; Felini, Martha MPH; Carozza, Susan E. PhD; Miike, Rei MPH; Chew, Terri MPH; Wrensch, Margaret PhD
The etiology of gliomas, the most common type of primary malignant brain tumor, is not well understood. Because most patients with gliomas have very poor prognosis, with an average 5-year survival rate of 29.5%, 1 there is a compelling need to better understand causes of glioma in hopes of discovering factors that might be modified to prevent this deadly disease. Many epidemiologic studies have examined the relationship between brain tumors and occupational exposures. Industries associated with increased brain tumor risk have included rubber manufacturing, petrochemical refineries, polyvinyl chloride production, chemical plants, and nuclear plants. 2 Specific occupations associated with elevated risks of brain tumors have included health care professionals (physicians, nurses, dentists), 3–5 electrical workers, 6–8 and agricultural workers. 9
In this population-based study, we present case–control comparisons of job histories. Previous studies have relied heavily on data from death certificates and cancer registries, which give limited information on an individual’s job history. A unique feature of our study is the detailed life job histories collected for all participants. To further increase validity of diagnosed cases, a pathologist conducted an independent histological review of the cases’ tumor samples. Combined, these features enabled us to get a clearer picture of the relationship between occupation and the various types of malignant glioma.
We ascertained all adults newly diagnosed with glioma (International Classification of Disease for Oncology, morphology codes 9380–9481) in six San Francisco Bay Area counties (Alameda, Contra Costa, Marin, San Mateo, San Francisco, and Santa Clara) from August 1991 to April 1994 (series I) and from May 1997 to August 1999 (series II). Cases were ascertained within 2 to 8 weeks of diagnosis using Northern California Cancer Center’s rapid case ascertainment program as previously described. 10,11 Controls ascertained through random digit dialing using methods previously described 10 were frequency matched to cases by age, race, and gender.
The study participant’s lifetime job histories were elicited from a personal interview. In series I we asked about any jobs that lasted 3 months or more whereas in series II we asked about jobs that lasted at least 1 year. Jobs of similar duties in similar industries were combined to meet a minimum criterion of 1 year of employment, even if the jobs were not with the same employer. Participants were asked for job and industry titles, a description of the job activity, starting year and ending year, total months/years worked, and the number of hours per week worked. The job titles and industry titles were coded into standard occupational classification (SOC) and standard industrial classification (SIC) codes and then further coded into one of 56 occupational groups based on the method of Schnitzer et al 12 Some occupational groups were more defined by occupation (SOC codes) and others were more defined by industry (SIC codes) depending on an industrial hygienist’s assessment of which was more influential with regard to exposure. Of the 8913 jobs reported by study participants, 142 did not fit into the 56 occupational categories.
Odds ratios were initially estimated comparing cases’ and controls’ longest-held occupation. The longest-held occupation was that occupational category in which the subject had accumulated the most hours worked in their lifetime. The number of hours worked was calculated by multiplying the number of years worked at a particular job by the number of hours worked per week times 50 weeks. Assuming that a full time job is 40 hours per week for 50 weeks a year, the equivalent of a full time year is 2000 hours. Those participants who did not specify the number of hours per week were assumed to have a full time job for the time specified. If a participant had multiple longest held occupations of the same duration, then one was picked at random for the analysis; only 28 of the 1716 participants had more than one longest held occupation. Those in the referent group were people who did not have the given occupational group as their longest held, including those who were never employed. These analyses were further subdivided by gender and histological type (astrocytic, non-astrocytic gliomas). Odds ratios also were estimated for those “ever” employed in the job category for one year or more versus those never employed or employed less than one year in the occupational group. All odds ratios were adjusted for age, ethnicity (white, non-white), and gender, except gender specific odds ratios that were adjusted for age and ethnicity.
Other types of analyses examined those employed 10 years or more in a given occupation with and without a 10-year latency period, “ever employed” split by series I and II, self- and proxy-reported cases separately versus controls, gender, and histological type of cases. Occupational groups with fewer than three cases were not included in analyses stratified by gender or tumor type.
SAS software was used for data management and PROC LOGISTIC was used to calculate odds ratios and 95% confidence intervals. In the results, ‘elevated’ refers to odds ratios greater than or equal to 2 and ‘lowered’ refers to odds ratios less than or equal to 0.50. In addition, the term ‘significant’ refers to odds ratios whose lower confidence limit is greater than 1.00 or whose upper limit is less than 1.00.
Cases and Controls
Combining both series I and series II, there were a total of 1129 eligible cases. Of those cases, full interview was obtained for 81% (n = 896) of cases and 2% (n = 23) completed only a telephone interview. Only 11% (n = 128) refused to enter the study, 1% (n = 22) were too ill or had a language problem, 4% (n = 47) couldn’t be located and 1% (n = 13) did not get a doctor’s consent to contact. Of those cases who completed an interview, 2% (n = 17) had to be dropped from the study because a neuropathology review indicated that the subject either did not have glioma or medulloblastoma (n = 4), permission for review was not obtained (n = 4), tumor specimens were unavailable (n = 4), or tumor specimens were insufficient for diagnosis (n = 5). Therefore, 879 cases were available for analysis from series I and II.
Of the 15,894 phone numbers in both series contacted through random digit dialing, 8% (n = 1316) yielded eligible controls. Of the total phone numbers contacted, 19% (n = 3086) were not in service, 14% (n = 2242) were businesses, 7% (n = 1047) were faxes or modems, 12% (n = 1964) had no response after 10 calls, 12% (n = 1824) were refusals, 5% (n = 827) had language or health problems, 20% (n = 3158) were eligible but the quota for their age/race/gender had been filled, and finally 3% (n = 430) were either too young, had multiple lines, lived out of the area, or were closed out. Of the eligible controls, 66% (n = 864) completed a full interview, 13% (n = 169) completed an abbreviated telephone interview only, 14% (n = 184) refused to enter the study, 1% (n = 17) either had a language problem or were too ill to interview, 3% (n = 43) were not located, 3% (n = 39) were either related to cases, out of the area, good matches but the study closed, or otherwise couldn’t be used. The total number of controls for both series I and II was 864.
Comparison of Series I and II
In series I, there were 476 cases and 462 controls. In series II there were 403 cases and 402 controls. We recently published a paper on the findings in series I and occupational groups. 13 For the current work, we combined the new series II data with the data for series I after preliminary analysis showed no important differences in case–control comparisons of job histories. Table 1 lists demographic information about both studies. There were some differences between the studies to be considered when combining them. The percentage of ethnicities categorized as “other,” which consists of all ethnicities other than White or African American, increased from 11 to 15% of study participants. Series II participants were on average, slightly older than series I. The mean age for series I cases was 54 years and for series II, 56 years. These changes may reflect the changing demographics of the Bay Area over the period of five years between the studies. Series II participants also tended to be more educated than series I. The histological distributions of cases in the two series were similar, except that series II had a higher percentage of cases with oligodendroglioma and lower percentage with oligoastrocytoma. Overall, there were a lower percentage of proxies and a higher percentage of self-reporting cases in series II than series I.
The histological distribution of cases is shown in Table 1. A majority of the cases (76%) were astrocytic, that is glioblastomas, anaplastic astrocytomas, and astrocytomas. Other histologies considered were mixed (6%), oligodendrogliomas (10%), ependymomas (1%), and otherwise classified (6%).
For the longest-held occupations, the mean number of years per study participant was the full time equivalent of 19.3 years for cases and 19.6 years for controls. Controls had an average number of 5.7 jobs in 2.8 occupational categories during their lifetime. Cases reported or were reported by their proxy to have an average of 4.6 jobs in 2.5 occupational categories. For proxy reported cases, the mean number of years for the longest held occupation was the full time equivalent of 22.2 years, and for self-reported cases, 17.5 years. Proxy reported cases held an average 4.2 jobs and 2.4 occupations, whereas self-reported cases held on average 4.9 jobs and 2.6 occupations. In interpreting these findings, it is important to remember that self-reporting cases are 15 years younger on average than proxy reported cases.
Table 2 lists numbers of cases and controls and odds ratios for longest held occupations, sorted from highest to lowest odds ratio. Occupational groups with elevated odds ratios for longest held occupations include firefighters, physicians, welders, material moving equipment operators, janitors, artists, and foundry or smelter workers. A nearly significant odds ratio of 3.0 (95% CI = 0.97–9.4) was observed for physicians. Additionally, cases were significantly more likely than controls to have a longest held occupation as food service workers. [odds ratio:1.8 (95% CI = 1.0–3.2)].
Among men (Table 3), elevated odds ratios for longest held occupation were observed for firefighters, physicians, material moving equipment operators, janitors (P < 0.05), motor vehicle operators (P < 0.05), and personal service workers. Among women, occupational groups with elevated odds ratios for longest held occupation were messengers, legal and social service workers, electronic equipment operators, painters, and food processors.
Among cases with astrocytic tumors (Table 4), elevated odds ratios for longest held occupation were found for firefighters, physicians (P < 0.05), material moving equipment operators, and janitors. For nonastrocytic cases, elevated odds ratios for longest held occupation were observed for firefighters, material moving equipment operators, janitors (P < 0.05), textile workers (P < 0.05), aircraft operators, food service workers, and construction workers.
In the ‘ever-employed’ category (Table 2), firefighters, physicians, foundry-smelter workers, textile workers, and water transport all had not significant elevated odds ratios. Among ever-employed nonastrocytic cases, foundry and smelter workers had an elevated odds ratio of 7.6 (95% CI = 1.5–38.3) and textile workers had an odds ratio of 4.7 (95% CI = 1.6–13.8).
For longest-held occupational categories, lowered but not significant odds ratios were found for writers and journalists, biological scientists, paper workers, mechanics, chemists, and photographers/photoprocessors. Lowered but not significant odds ratios were observed for ever employment as stone, glass, concrete workers, photographers, and geologists/surveyors. Significant lowered odds ratios in the ever employed category were observed among farm managers/workers, managers, administrators, clerks, and vehicle mechanics. When examining controls versus self-reporting cases, only clerks had a significantly reduced odds ratio.
Our study reproduced findings of many other studies but failed to confirm other findings. In this study, most white-collar occupations, with the exception of physicians and legal and social service workers, had non-significant close to null odds ratios. Blue-collar workers who are likely to have chemical exposures, such as firefighters, welders, janitors, and textile workers showed elevated odds ratios. Furthermore, in this study elevated odds ratios were observed for men with longest held occupations in material moving equipment and motor vehicle operators, possibly suggesting a role of fuel exhaust exposures in brain tumor risk.
Deleterious associations of brain tumors with health care workers, including physicians, nurses, and dental professionals have been observed in previous studies. 3–5 Cases defined as ever employed physicians in this study included two orthopedic surgeons, a spinal cord injury physician, an ophthalmologist, two psychiatrists, a neurologist, a surgeon, and a family physician. Among the controls there was a clinical psychiatrist, an anesthesiologist, a neurologist, and a clinical researcher. Upon closer inspection, most of the cases were practicing physicians or surgeons who worked primarily with patients whereas most of the controls seemed to have a research background. A possible explanation for the elevated odds ratio could be that practicing physicians might be unavailable to participate in our study as controls and perhaps only those that had an interest in research may have elected to participate. Alternatively, there may be some exposure among physicians working with patients that increases the risk of brain tumors. Possible exposures could include infectious agents, radiation exposures, cleaning agents or chemicals. 3 Odds ratios for dentists and dental technicians, who have many similar exposures to physicians, were slightly elevated in this study (ranging from 1.2 among all subjects for longest held occupation to 1.4 among men and among those with astrocytic tumors). However, odds ratios for nurses and health technicians who may also share similar exposures were very close to 1.0 overall, but were slightly elevated among men (1.3).
Among women, elevated odds ratios for glioma were observed for the white-collar occupational group of legal and social service workers. When examined closely, six of the 15 female cases were in the legal profession, and the rest were social workers. All the controls were social workers except one minister. A previous study found an increased brain tumor risk among teachers and counselors. 3 Social service workers, counselors, teachers, and lawyers come into close contact with a wide variety of people. Therefore, similarly to the case of the physician, they may have a higher likelihood of coming into contact with an infectious agent. In experimental animal studies, anaplastic astrocytomas and glioblastoma multiforme have been induced with oncogenic RNA viruses such as the avian, murine, and sarcoma viruses. 14 However, there have been few epidemiological studies that examine the role of viruses or other infectious agents in causing brain tumors. This finding suggests future investigation into the relationship between glioma risk and the frequency of contact with a variety of people.
The rest of the occupations with elevated odds ratios fall under the category of ‘blue-collar’ jobs. An occupation that has been consistently associated with risk of brain tumor in previous studies is textile workers. 4,5,15–17 Our study found an almost 6-fold elevated risk of brain tumors for longest held occupation among nonastrocytic cases. However, this finding was based on only three cases whose brain tumor classifications were oligodendroglioma, oligoastrocytoma, and other. For those ‘ever employed’ as textile workers, there was a not significant 2-fold risk of a brain tumor for women. The category of textile worker includes seamstresses, dressmakers, garment factory workers, and clothing alterers. Textile workers may come into contact with many chemicals additives, such as dyes, formaldehyde, and other compounds, used in fabric production. 18 Exposure to formaldehyde has been linked in previous studies to increased risk of brain tumors, 2,19 but the results have been inconclusive.
Associations between janitors and cleaning service workers and brain tumors have been found in several studies. 5,6,16,20 In this study, male janitors had a significant 9-fold risk of brain tumors, about double the risk found in a recent Iowa case-control study for men who worked in the industry 10 or more years. 16 Maids and janitors could be exposed to numerous solvents and other chemicals found in cleaning agents. It is also possible that their work schedules might make it more difficult to be contacted or to participate as controls.
Male motor vehicle operators, which include truck, bus, and taxi drivers, had a 2-fold risk of brain cancer. Many previous studies have suggested an association between vehicle drivers, mechanics, transportation workers, and other occupations that have exposures to petroleum waste or diesel exhaust. 5,7,17,20,21 Prior to the late 1970s, these drivers may have had a higher exposure to lead from gasoline exhaust, which may be linked to an increased risk of brain cancer. 22
Food service workers, such as waiters, cooks, caterers, and restaurant managers showed a significant elevated risk for brain cancer. A recent study found elevated odds ratios among women who were waitresses. 16 Possible exposures could include infectious agents among people or food products.
Participants who were ever employed as a foundry or smelter worker, among non-astrocytic cases, showed a 7-fold elevated risk of glioma. This finding was based on four cases with three oligodendrogliomas and one juvenile pilocytic astrocytoma. Most of the cases and controls worked in an iron or steel foundry. Foundry workers are exposed to polycyclic aromatic hydrocarbons, which are believed to be carcinogenic, and have been linked to other cancer sites, especially the lung, skin, and bladder. 23 To date there have not been any other epidemiological studies that have found an association between foundry work and gliomas.
Our study found several not significant positive associations with occupations that other studies have linked to brain cancer, including firefighters, 24,25 aircraft operators, 20,26 welders and cutters, 4,8,27 construction workers, 4,17 material moving equipment operators, 16 and food processors. 4 Possible carcinogenic exposures of firefighters include benzene, asbestos, polycyclic aromatic hydrocarbons, formaldehyde, diesel exhaust, and other chemical agents. 24 Welders and cutters are often exposed to both magnetic fields and various metal compounds. 8 Aircraft operators may be exposed to a number of factors including cosmic radiation and ozone exposures. 26 In this study, the aircraft operators were predominantly pilots and flight attendants.
Our study did not find any association with those in the farming profession, electronics, or engineering professions as reported in other studies. 9,15,16,20,28 However, there was a slightly elevated not significant risk among women whose longest held occupations were electronic equipment operators. These professions, especially farming and engineering, tend to involve extremely heterogeneous job duties; studies of specific worker cohorts might be more likely to detect associations than the general categories used in this case-control study.
There were several significantly reduced odds ratios found for those ever employed as vehicle mechanics, clerks, farm managers & workers, salesmen, and electronic equipment operators. A possible explanation for these findings is inaccurate recall by proxies of jobs done for shorter periods of time. For example, proxies might be less likely than the cases themselves to know about a brief job the case may have undertaken as a clerk, salesmen, or farmworker. The only significantly reduced odds ratio among controls and self-reporting cases was forever employment as clerks. We found odds ratios of 0.50 or less for longest held job in six occupational categories. Because these six occupational groups do not have an obvious connection, an explanation could be that controls with certain occupations might be more likely to be reached by random digit dialing or be more willing to participate. Another explanation for the findings is chance, given that the results were not statistically significant.
Because 40% of our case participants were reported by proxy, there are some limitations in the accuracy of our study’s findings. Proxies tend to underreport the number of jobs a case may have held, especially those of short duration or those in the distant past. This might explain the lower mean number of jobs reported by proxy-reported cases as compared to self-reported cases. This may also explain the higher number of jobs reported by controls as compared to cases. Since most of our results rely on longest held occupations, both of these factors are unlikely to affect the risk estimates found in this study.
Although longest-held occupations can give a meaningful picture of an individual’s lifetime occupational exposure, the time-span worked within an occupational group can vary greatly from one individual to another. One disadvantage of this method is the inability to assess a specific relationship between glioma risk and the amount of time in a given occupation. Furthermore, relative or actual intensity of exposures is not captured through examination of longest held-occupations.
Participation biases may have played a role in some of our findings. Whether controls elect to participate in our study could depend on their occupation. Those employed in occupations with hectic or odd schedules (eg, physicians, janitors, firefighters) may be less likely to be contacted through random digit dialing or less likely to agree to participate than those with standard hours. This type of selection bias may bias the results toward an elevated odds ratio (ie, proportionately more cases than controls in these occupations may have participated). Odds ratios also might have been affected by the fact that most controls were relatively healthy people. However, using longest held occupation for comparisons might minimize this latter problem since the focus is not on current occupation.
Although associations with job exposures to specific agents might be more useful than associations with job titles, such exposures probably will vary by calendar year and vocation. Nevertheless, we plan in the future to link our more detailed work history information to exposure matrices being developed at the National Cancer Institute.
Because of the large sample size, this study is one of the few studies that was able to stratify results by gender and histology. Similar exposures from various occupations were combined in order to increase the validity of the results. Nevertheless, some findings were still based on very small numbers. In addition, due to the large number of occupations examined there may have been some significant results produced by chance. Despite these and other limitations, this study’s results clearly support the need for future investigation of the risks of occupational exposures with glioma, particularly among those in reportedly higher risk occupations and industries in this and other studies.
Funding for this study was provided by grant RO152689 from the National Cancer Institute.
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