Occupational exposure to organic dust increases lung cancer risk in the general population
Bibliographic record
Abstract
BACKGROUND: Organic dust is a complex mixture of particulate matter from microbial, plant or animal origin. Occupations with exposure to animal products have been associated with an increased lung cancer risk, while exposure to microbial components (eg, endotoxin) has been associated with a decreased risk. To date there has not been a comprehensive evaluation of the possible association between occupational organic dust exposure (and its specific constituents) and lung cancer risk in the general population. METHODS: The SYNERGY project has pooled information on lifetime working and smoking from 13 300 lung cancer cases and 16 273 controls from 11 case-control studies conducted in Europe and Canada. A newly developed general population job-exposure matrix (assigning no, low or high exposure to organic dust, endotoxin, and contact with animals or fresh animal products) was applied to determine level of exposure. ORs for lung cancer were estimated by logistic regression, adjusted for age, sex, study, cigarette pack-years, time since quitting smoking, and ever employment in occupations with established lung cancer risk. RESULTS: Occupational organic dust exposure was associated with increased lung cancer risk. The second to the fourth quartile of cumulative exposure showed significant risk estimates ranging from 1.12 to 1.24 in a dose-dependent manner (p<0.001). This association remained in the highest quartile after restricting analyses to subjects without chronic obstructive pulmonary disease or asthma. No association was observed between lung cancer and exposure to endotoxin or contact with animals or animal products. CONCLUSION: Occupational exposure to organic dust was associated with increased lung cancer risk in this large pooled case-control study.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".