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Am J Respir Crit Care Med. 2011 Apr 1;183(7):941-8. doi: 10.1164/rccm.201006-0940OC. Epub 2010 Oct 29.

Exposure to diesel motor exhaust and lung cancer risk in a pooled analysis from case-control studies in Europe and Canada.

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  • 1International Agency for Research on Cancer, Lyon, France.

Abstract

RATIONALE:

Diesel motor exhaust is classified by the International Agency for Research on Cancer as probably carcinogenic to humans. The epidemiologic evidence is evaluated as limited because most studies lack adequate control for potential confounders and only a few studies have reported on exposure-response relationships.

OBJECTIVES:

Investigate lung cancer risk associated with occupational exposure to diesel motor exhaust, while controlling for potential confounders.

METHODS:

The SYNERGY project pooled information on lifetime work histories and tobacco smoking from 13,304 cases and 16,282 controls from 11 case-control studies conducted in Europe and Canada. A general population job exposure matrix based on ISCO-68 occupational codes, assigning no, low, or high exposure to diesel motor exhaust, was applied to determine level of exposure.

MEASUREMENTS AND MAIN RESULTS:

Odds ratios of lung cancer and 95% confidence intervals were estimated by unconditional logistic regression, adjusted for age, sex, study, ever-employment in an occupation with established lung cancer risk, cigarette pack-years, and time-since-quitting smoking. Cumulative diesel exposure was associated with an increased lung cancer risk highest quartile versus unexposed (odds ratio 1.31; 95% confidence interval, 1.19-1.43), and a significant exposure-response relationship (P value < 0.01). Corresponding effect estimates were similar in workers never employed in occupations with established lung cancer risk, and in women and never-smokers, although not statistically significant.

CONCLUSIONS:

Our results show a consistent association between occupational exposure to diesel motor exhaust and increased risk of lung cancer. This association is unlikely explained by bias or confounding, which we addressed by adjusted models and subgroup analyses.

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PMID:
21037020
[PubMed - indexed for MEDLINE]
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