Introduction
Evidence to date reveals an inconsistent association between parental and subject occupation and brain tumors (1-4). Paternal exposures in hydrocarbon-associated occupations, the petroleum industries, and paint exposures have been associated with brain cancer (5). Maternal exposures have received less attention, but some studies have yielded suggestive results linking occupational exposures to pesticides and solvents to childhood brain tumors (6, 7).
We previously reported an association between maternal employment in electronic parts manufacturing and textile industries and brain tumor from a population-based case-control study from 74 cases and 170 controls (7). In this report, we present the results from the larger, completed case-control study to assess the association between parental and subject occupation and brain tumor risk.
Materials and Methods
Study Design
Details regarding the design of our study (202 cases and 501 controls) have been previously described (7-9). Briefly, this is a population-based case-control study conducted in the metropolitan area of Kaohsiung, an industrialized city in southern Taiwan with a large petroleum industry. Subjects were recruited between November 1997 and December 2005. Incident cases were identified and recruited through (a) a rapid case ascertainment system set up in three large referral hospitals in Kaohsiung and (b) screening the Cancer Registry File from the Taiwan Department of Health. All cases were reviewed by a pathologist in Kaohsiung Medical University Hospital. Eligible cases included all pathologically confirmed incident primary brain cases (benign and malignant: International Classification of Diseases-9 codes 191-192, 194.3-194.4, and 225), ages 0 to 29 years, and currently residing in the study area. Eighty-four percent of brain tumor cases initially reviewed were enrolled in the study. Controls were cancer-free residents of the study area, selected randomly from the population registry data based on the personal identification number system of the Taiwanese government. Each case was matched with three controls on age (±1 year) and sex. Of those initially contacted, 61% of prospective controls agreed to participate in the study. In-person interviews were conducted with the parents and/or subjects to collect information regarding the descriptive characteristics, medical history, as well as environmental, occupational, and behavioral factors. The histology and location of the brain tumors in our cases are presented in Table 1. Demographic information on the study population is displayed in Table 2.
Histology and location of 202 brain tumor cases in subjects 0 to 29 y in Kaohsiung, Taiwan (1997-2005)
Characteristic . | No. of cases (%) . | |
---|---|---|
Histology of tumor (%) | ||
Glioma | 75 (37) | |
Pilocytic astrocytoma | 10 | |
Astrocytoma, nonpilocytic | 48 | |
Oligodendroglioma | 9 | |
Ependymoma | 8 | |
Medulloblastoma | 20 (10) | |
Adenoma | 52 (26) | |
Craniopharyngioma | 10 (5) | |
Nerve sheath tumor | 7 (3) | |
Meningioma | 9 (4) | |
Germ cell tumor or teratoma | 15 (8) | |
Other | 8 (4) | |
Missing histology | 6 (3) | |
Location of tumor | ||
Cerebrum | 72 (36) | |
Posterior fossa | 31 (15) | |
Sella turcica | 71 (35) | |
Meninges | 24 (12) | |
Cranial nerve | 4 (2) |
Characteristic . | No. of cases (%) . | |
---|---|---|
Histology of tumor (%) | ||
Glioma | 75 (37) | |
Pilocytic astrocytoma | 10 | |
Astrocytoma, nonpilocytic | 48 | |
Oligodendroglioma | 9 | |
Ependymoma | 8 | |
Medulloblastoma | 20 (10) | |
Adenoma | 52 (26) | |
Craniopharyngioma | 10 (5) | |
Nerve sheath tumor | 7 (3) | |
Meningioma | 9 (4) | |
Germ cell tumor or teratoma | 15 (8) | |
Other | 8 (4) | |
Missing histology | 6 (3) | |
Location of tumor | ||
Cerebrum | 72 (36) | |
Posterior fossa | 31 (15) | |
Sella turcica | 71 (35) | |
Meninges | 24 (12) | |
Cranial nerve | 4 (2) |
Characteristics of cases and controls
Characteristic . | Cases (n = 202) . | Controls (n = 501) . | ||
---|---|---|---|---|
Sex (%) | ||||
Male | 105 (52) | 260 (52) | ||
Female | 97 (48) | 241 (48) | ||
Age (%) | ||||
Under 5 y | 32 (16) | 80 (16) | ||
5 to 9 | 25 (12) | 59 (12) | ||
10 to 14 | 22 (11) | 62 (12) | ||
15 to 19 | 34 (17) | 88 (18) | ||
20 and over | 89 (44) | 212 (42) | ||
History of smoking (%) | ||||
Ever | 29 (14) | 48 (10) | ||
Never | 172 (86) | 452 (90) | ||
Smoker in household (%) | ||||
Yes | 126 (62) | 292 (58) | ||
No | 76 (38) | 209 (42) | ||
X-ray (%) | ||||
Yes | 44 (22) | 103 (21) | ||
No | 158 (78) | 398 (79) | ||
Petroleum/petrochemical plant within 1 km of home (%) | ||||
Yes | 19 (9) | 51 (10) | ||
No | 183 (91) | 450 (90) | ||
Parental occupational history available | 127 (63) | 309 (62) |
Characteristic . | Cases (n = 202) . | Controls (n = 501) . | ||
---|---|---|---|---|
Sex (%) | ||||
Male | 105 (52) | 260 (52) | ||
Female | 97 (48) | 241 (48) | ||
Age (%) | ||||
Under 5 y | 32 (16) | 80 (16) | ||
5 to 9 | 25 (12) | 59 (12) | ||
10 to 14 | 22 (11) | 62 (12) | ||
15 to 19 | 34 (17) | 88 (18) | ||
20 and over | 89 (44) | 212 (42) | ||
History of smoking (%) | ||||
Ever | 29 (14) | 48 (10) | ||
Never | 172 (86) | 452 (90) | ||
Smoker in household (%) | ||||
Yes | 126 (62) | 292 (58) | ||
No | 76 (38) | 209 (42) | ||
X-ray (%) | ||||
Yes | 44 (22) | 103 (21) | ||
No | 158 (78) | 398 (79) | ||
Petroleum/petrochemical plant within 1 km of home (%) | ||||
Yes | 19 (9) | 51 (10) | ||
No | 183 (91) | 450 (90) | ||
Parental occupational history available | 127 (63) | 309 (62) |
Job Title Classification
Details of the job title classification system have been previously described (7). Each job was assigned two four-digit codes, one for occupation and one for industry, by project staff in Taiwan familiar with the Taiwanese occupational and industrial coding system. Codes followed the Taiwanese government's standardized classification system for occupations and industries, which is adapted from the systems used by the International Labor Organization (10). The classification system groups occupations and industries by a four-digit code, the first digit designating the broadest group and additional digits representing progressively more specific categories. Odds ratios were calculated for each occupation or industry group, first using one-digit codes, and then subsequently using two-, three-, and four-digit codes to investigate more specific classifications. We list the major (one-digit) occupation and industry categories of our study population in Table 3.
Selected industrial and occupational categories of study population
Person . | Industry or occupation . | Cases, controls with job . |
---|---|---|
Subject | Agriculture, forestry, fishing and animal husbandry | 17, 69 |
Electricity, gas and water | 20, 42 | |
Trade and eating-drinking places | 15, 40 | |
Social, personal and related community services | 28, 51 | |
Professional | 12, 24 | |
Technicians and associate professionals | 17, 44 | |
Clerks | 14, 33 | |
Craft and related trades workers | 20, 23 | |
Mother | Electricity, gas and water | 48, 139 |
Trade and eating-drinking places | 24, 60 | |
Social, personal and related community services | 40, 63 | |
Professionals | 11, 29 | |
Technicians and associate professionals | 20, 54 | |
Clerks | 18, 53 | |
Service workers and shop and market sales workers | 32, 61 | |
Craft and related trades workers | 22, 49 | |
Plant and machine operators and assemblers | 18, 44 | |
Father | Agriculture, forestry, fishing and animal husbandry | 74, 200 |
Electricity, gas and water | 21, 55 | |
Construction | 10, 14 | |
Trade and eating-drinking places | 12, 28 | |
Finance, insurance, and real estate | 11, 8 | |
Servicemen | 55, 139 | |
Technicians and associate professionals | 12, 25 | |
Service workers and shop and market sales workers | 14, 26 | |
Craft and related trades workers | 22, 66 | |
Plant and machine operators and assemblers | 11, 24 |
Person . | Industry or occupation . | Cases, controls with job . |
---|---|---|
Subject | Agriculture, forestry, fishing and animal husbandry | 17, 69 |
Electricity, gas and water | 20, 42 | |
Trade and eating-drinking places | 15, 40 | |
Social, personal and related community services | 28, 51 | |
Professional | 12, 24 | |
Technicians and associate professionals | 17, 44 | |
Clerks | 14, 33 | |
Craft and related trades workers | 20, 23 | |
Mother | Electricity, gas and water | 48, 139 |
Trade and eating-drinking places | 24, 60 | |
Social, personal and related community services | 40, 63 | |
Professionals | 11, 29 | |
Technicians and associate professionals | 20, 54 | |
Clerks | 18, 53 | |
Service workers and shop and market sales workers | 32, 61 | |
Craft and related trades workers | 22, 49 | |
Plant and machine operators and assemblers | 18, 44 | |
Father | Agriculture, forestry, fishing and animal husbandry | 74, 200 |
Electricity, gas and water | 21, 55 | |
Construction | 10, 14 | |
Trade and eating-drinking places | 12, 28 | |
Finance, insurance, and real estate | 11, 8 | |
Servicemen | 55, 139 | |
Technicians and associate professionals | 12, 25 | |
Service workers and shop and market sales workers | 14, 26 | |
Craft and related trades workers | 22, 66 | |
Plant and machine operators and assemblers | 11, 24 |
In our analysis, all persons in the subgroup who held jobs, but did not have the occupation or industry title in question, were used as the referent groups. Paternal, maternal, and subject data were analyzed separately. Odds ratios were adjusted using conditional logistic regression for subject smoking (ever smoked or not), parental smoking (either parent ever smoked or not), and exposure to medical radiation (ever exposed or not). These covariates were chosen to form a parsimonious analysis and to provide comparability with our previously published analysis.
Results
No association was seen between parental or subjects' occupation or industry classification and brain tumor. Age-adjusted analyses did not change our results. Subgroup analysis of glioma, the predominant histologic type, did not reveal significant associations between brain tumor and either occupation or industry classification. Because of the location of our study (in a city with a large petrochemical processing industry), we also examined (as a group) those parental and subject occupations and industries that were likely to involve exposures to petrochemicals. For these jobs considered as a group, we found no significant association with brain tumors.
Discussion
We did not detect any association between parental or subjects' occupational history and the risk of brain tumors in our population-based case-control study which used questionnaires to determine occupational and industrial classifications. The question of whether parents' exposure to carcinogens in the workplace could increase the risk of brain cancer in the children is yet unresolved. Recent reviews of the studies concerning the relation of parents' occupations and brain tumors have suggested that there are elevated risks of brain tumors in children for fathers who work in industries involving paper and pulp, pesticide solvents, painting, printing, and graphic arts, and for mothers with exposure to fertilizers and pesticides during pregnancy (2, 4, 5). Our study, set in an industrial city with a large petrochemical and petroleum industry, was not able to show an association.
Our study has several major strengths including (a) the choice of controls from a population registry, (b) high participation rate of cases and controls, and (c) tumor pathology confirmed by a pathologist.
The limitations of our study include recall bias—differential recall on exposure among cases and controls (11). Our ability to obtain occupational histories, however, did not vary by disease status, and it is possible that parents are more likely to accurately remember jobs than exposures of possibly shorter duration such as dietary intake or alcohol use.
Several factors may have contributed to the null association found in this study. Brain tumor is a broad term describing diverse histologic types and each of them could have different etiologic factors contributing to development. Our sample size was not large enough to assess all subtypes separately, but we were able to examine the largest subtype, glioma, independently.
Disclosure of Potential Conflicts of Interest
No potential conflicts of interest were disclosed.
Grant support: T32 MH073122 (M. Mazumdar), ES09723 and ES00002 (D.C. Christiani), and the Brain Tumor Society (D.C. Christiani).
Acknowledgments
The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
We thank Chu-Ling Yu and Robbie Ali for their assistance and Janna Frelich for data management.