Occupational exposure to lead and lung cancer: results from two case-control studies in Montreal, Canada
Bibliographic record
Abstract
OBJECTIVES: We investigated the association between workplace lead exposure and lung cancer risk, separately for organic lead and for inorganic lead, from either engine emissions or from other sources. METHODS: Two population-based case-control studies were carried out in Montreal (1979-1986 and 1996-2002) to investigate occupational factors in relation to lung cancer among 1593 men with histologically confirmed incident lung cancer, and 1426 controls from the general population. Interviews elicited information on sociodemographic characteristics, lifetime smoking and occupational history. Chemists translated each job into potential chemical exposures. Cumulative indices of exposure were derived and classified into non-substantial and substantial exposure. ORs adjusted for several potential confounders including smoking, and 95% CIs were estimated by logistic regression. RESULTS: Lifetime prevalences of exposure in Study I were 3% for organic lead, 40% for inorganic lead from engine emissions and 17% for inorganic lead from other sources; corresponding prevalences in Study II were 4%, 19% and 16%, respectively. No associations were observed when comparing ever to never exposed subjects in pooled analyses (organic lead, OR=1.39, 95% CI 0.77 to 2.52; inorganic lead from engine emissions: OR=0.89, 95% CI 0.72 to 1.09; inorganic lead from other sources: OR=0.99, 95% CI 0.76 to 1.29). Nor were these exposures associated with lung cancer in subjects with substantial cumulative exposure. CONCLUSIONS: In this large study, using a blinded expert-based assessment of lifetime occupational exposure and adjustment for several potential confounders, we observed no increased risk of lung cancer with exposure to lead compounds.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".