Journal Article
Research Support, Non-U.S. Gov't
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Occupation, industry, and the risk of prostate cancer: a case-control study in Montréal, Canada.

Environmental Health 2016 October 22
BACKGROUND: Age, family history and ancestry are the only recognized risk factors for prostate cancer (PCa) but a role for environmental factors is suspected. Due to the lack of knowledge on the etiological factors for PCa, studies that are both hypothesis-generating and confirmatory are still needed. This study explores relationships between employment, by occupation and industry, and PCa risk.

METHODS: Cases were 1937 men aged ≤75 years with incident PCa diagnosed across Montreal French hospitals in 2005-2009. Controls were 1994 men recruited concurrently from electoral lists of French-speaking Montreal residents, frequency-matched to cases by age. In-person interviews elicited occupational histories. Unconditional logistic regression estimated odds ratios (OR) and 95 % confidence intervals (CI) for the association between employment across 696 occupations and 613 industries and PCa risk, adjusting for potential confounders. Multinomial logistic models assessed risks by PCa grade. Semi-Bayes (SB) adjustment accounted for the large number of associations evaluated.

RESULTS: Consistently positive associations-and generally robust to SB adjustment-were found for occupations in forestry and logging (OR 1.9, 95 % CI: 1.2-3.0), social sciences (OR 1.6, 95 % CI: 1.1-2.2) and for police officers and detectives (OR: 1.8, 95 % CI 1.1-2.9). Occupations where elevated risk of high grade PCa was found included gasoline station attendants (OR 4.3, 95 % CI 1.8-10.4) and textile processing occupations (OR 1.8, 95 % CI 1.1-3.2). Aside from logging, industries with elevated PCa risk included provincial government and financial institutions. Occupations with reduced risk included farmers (OR 0.6, 95 % CI 0.4-1.0) and aircraft maintenance workers (OR 0.1, 95 % CI 0.0-0.7).

CONCLUSIONS: Excess PCa risks were observed across several occupations, including predominantly white collar workers. Further analyses will focus on specific occupational exposures.

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