Environment and Breast Cancer: Science Review
About
Breast cancer risk in relation to occupations with exposure to carcinogens and endocrine disruptors: a Canadian case-control study
Brophy, J. T., Keith, M. M., Watterson, A., Park, R., Gilbertson, M., Maticka-Tyndale, E., Beck, M., Abu-Zahra, H., Schneider, K., Reinhartz, A., Dematteo, R., Luginaah, I. Environ Health. 2012. 11:1, 87.
Topic area
Environmental pollutant - Occupation
Environmental pollutant - Occupation
Study design
Population based case-control
Population based case-control
Funding agency
Health Canada - Women's Health Contribution Progra
Health Canada - Women's Health Contribution Progra
Study Participants
Number of Cases
1006
1006
Menopausal Status
The menopausal status of women included in this study is listed here.
Stratified analyses by menopausal status
Number of Controls
Controls: 1146
Controls: 1146
Participant selection: Inclusion and exclusion criteria
Criteria used to select participants in the study.
Cases were recruited from 2002 to 2008 with a) new diagnosis of histologically confirmed breast cancers b) current residence in Essex or Kent counties c) agreement to participate in a 1-2 hour interview in English. Controls were recruited in the same geographic area from 2003 to 2007 by randomly generating telephone numbers linked to mailing addresses. Only one control per household was allowed to participate, and controls did not have prior history of breast or ovarian cancer. Cases and controls were matched on 3 year intervals.
Comment about participation selection
Researchers attempted to reduce recruitment bias by disclosing the study's goal to understand the causes of cancer, without emphasizing occupation or environment.
Researchers attempted to reduce recruitment bias by disclosing the study's goal to understand the causes of cancer, without emphasizing occupation or environment.
Exposure Investigated
Exposures investigated
Jobs were coded using the North American Industry Classification System (NAICS) and National Occupational Classification (NOC). 32 minor sectors of work and 8 major sectors of work were coded to consider potential exposures to mammary carcinogens. Minor
Jobs were coded using the North American Industry Classification System (NAICS) and National Occupational Classification (NOC). 32 minor sectors of work and 8 major sectors of work were coded to consider potential exposures to mammary carcinogens. Minor
How exposure was measured
Job history
Job history
Exposure assessment comment
This is a thorough examination of occupations, which includes major sectors and minor sectors, and previous agricultural work, which may predispose women to higher breast cancer risk following subsequent occupational exposures.
This is a thorough examination of occupations, which includes major sectors and minor sectors, and previous agricultural work, which may predispose women to higher breast cancer risk following subsequent occupational exposures.
Early life exposures considered
Yes, menarche through first pregnancy.
Yes, menarche through first pregnancy.
Breast cancer outcome investigated
Primary incident breast cancer
Primary incident breast cancer
Confounders considered
Other breast cancer risk factors, such as family history, age at first birth, and hormone replacement therapy use, that were taken into account in the study.
Smoking, education, family income, employment duration, age, parity, number of pregnancies, duration fecundity, total time breastfeeding
Genetic characterization included
If the study analyzed relationships between environmental factors and inherited genetic variations, this field will be marked “Yes.” “No”, if not.
No
Strength of associations reported
Compared to restaurant sector jobs, 5-year lag:
Food manufacturing: aOR 2.25 (95% CI 0.97-5.26)
Plastics manufacturing (auto): aOR 3.12 (95% CI 1.29-7.55)
Cumulative exposure, 5-year lag:
10 years in a high-exposed job (0,1,2 weight scale): aOR 1.29 (95% CI 1.10-1.51)
10 years in a high-exposed job (0,1,10 weight scale): aOR 1.42 (95% CI 1.18-1.73)
Farming (0,1,10 weight scale): aOR 1.35 (95% CI 1.00-1.82)
Plastics (auto) (0,1,10 weight scale): aOR 2.41 (95% CI 1.31-4.44)
Metalworking (0,1,10 weight scale): aOR 1.71 (95% CI 0.99-2.95)]
Analyses of major sectors with cumulative exposure (0,1,10 scale) showed significantly elevated OR for: farming: OR 1.34 (95% CI 1.03-1.74)
plastics: OR 2.43 (95% CI 1.39-4.22)
metalworking: OR 1.73 (95% CI 1.02-2.92).
Cumulative exposure in major sectors and tumor receptor status showed:
farming: OR of ER- tumors: 1.71 (95% CI 1.12-2.62)
metalworking: OR of ER+/PR+ tumors: 2.03 (95% CI 1.11-3.71)
auto industry plastics: OR of ER+/PR+ tumors: 3.63 (95% CI 1.90-6.94)
canning: OR of ER+/PR- tumors: 4.01 (95% CI 1.37-11.8) and of ER- tumors: 3.19 (95% CI 1.16-8.75).
Analyses by major sectors, premenopausal status:
auto plastics: OR 5.10 (95% CI 1.68-15.5)
canning: OR 5.20 (95% CI 0.95-28.5)
Analyses by major sectors, postmenopausal status:
auto plastics: OR 2.29 (95% CI 1.12-4.67)
Compared to restaurant sector jobs, 5-year lag:
Food manufacturing: aOR 2.25 (95% CI 0.97-5.26)
Plastics manufacturing (auto): aOR 3.12 (95% CI 1.29-7.55)
Cumulative exposure, 5-year lag:
10 years in a high-exposed job (0,1,2 weight scale): aOR 1.29 (95% CI 1.10-1.51)
10 years in a high-exposed job (0,1,10 weight scale): aOR 1.42 (95% CI 1.18-1.73)
Farming (0,1,10 weight scale): aOR 1.35 (95% CI 1.00-1.82)
Plastics (auto) (0,1,10 weight scale): aOR 2.41 (95% CI 1.31-4.44)
Metalworking (0,1,10 weight scale): aOR 1.71 (95% CI 0.99-2.95)]
Analyses of major sectors with cumulative exposure (0,1,10 scale) showed significantly elevated OR for: farming: OR 1.34 (95% CI 1.03-1.74)
plastics: OR 2.43 (95% CI 1.39-4.22)
metalworking: OR 1.73 (95% CI 1.02-2.92).
Cumulative exposure in major sectors and tumor receptor status showed:
farming: OR of ER- tumors: 1.71 (95% CI 1.12-2.62)
metalworking: OR of ER+/PR+ tumors: 2.03 (95% CI 1.11-3.71)
auto industry plastics: OR of ER+/PR+ tumors: 3.63 (95% CI 1.90-6.94)
canning: OR of ER+/PR- tumors: 4.01 (95% CI 1.37-11.8) and of ER- tumors: 3.19 (95% CI 1.16-8.75).
Analyses by major sectors, premenopausal status:
auto plastics: OR 5.10 (95% CI 1.68-15.5)
canning: OR 5.20 (95% CI 0.95-28.5)
Analyses by major sectors, postmenopausal status:
auto plastics: OR 2.29 (95% CI 1.12-4.67)
Results Comments
Cumulative work in plastics, metalworking, and canning between menarche and first pregnancy was more strongly associated with breast cancer risk than in subsequent time periods, though OR during this period was only significant for plastics workers. This study considered many additional job titles. We focus on (1) significant positive associations (2) if a particular job or sector was significantly associated with breast cancer in at least one study, we report results from all other studies that considered that sector, regardless of significance. It is important to note that job coding criteria generally differed across studies.
Cumulative work in plastics, metalworking, and canning between menarche and first pregnancy was more strongly associated with breast cancer risk than in subsequent time periods, though OR during this period was only significant for plastics workers. This study considered many additional job titles. We focus on (1) significant positive associations (2) if a particular job or sector was significantly associated with breast cancer in at least one study, we report results from all other studies that considered that sector, regardless of significance. It is important to note that job coding criteria generally differed across studies.
Reviewers Comments
The analyses were divided into critical time windows that represent distinct stages of breast development that could affect risk. However, these time periods may also reflect employment patterns. Although higher income and education have generally been associated with higher breast cancer risk, this study found an elevated risk in women with lower SES, which may have resulted from higher exposure to EDCs and carcinogens in lower income manufacturing and agricultural industries of the study area.
The analyses were divided into critical time windows that represent distinct stages of breast development that could affect risk. However, these time periods may also reflect employment patterns. Although higher income and education have generally been associated with higher breast cancer risk, this study found an elevated risk in women with lower SES, which may have resulted from higher exposure to EDCs and carcinogens in lower income manufacturing and agricultural industries of the study area.