304 Lung cancer risk among hairdressers - a pooled analysis of case-control studies conducted between 1985 and 2010
Bibliographic record
Abstract
Objectives Increased risk of lung cancer has been observed among hairdressers mostly in studies that did not adjust for smoking as a confounder; the objective of the present study was to evaluate this in the SYNERGY project while adjusting for smoking. Methods SYNERGY consists of 16 pooled case-control studies conducted in Europe, Canada, China and New Zealand between 1985 and 2010. Lifetime occupational and smoking information was collected through interviews from 19,369 cases of lung cancer and 23,674 matched populations or hospital controls. Hairdressers were identified using the ISCO codes 5–70.20 (women’s hairdresser) and 5–70.30 (men’s hairdresser/barber). Odds ratios (ORs) and 95% confidence intervals (95% CI) of lung cancer risk were estimated using unconditional logistic regression. Results Overall, 170 cases and 167 controls ever worked as hairdresser or barber. The ORs for lung cancer in male hairdressers/barbers were 1.04 (95% CI: 0.79, 1.37) before adjustment for smoking and 0.91 (95% CI: 0.66, 1.25) after, and did not change markedly with regard to the time of employment. The ORs in women were 1.65 (95% CI: 1.16, 2.35) before adjustment for smoking and 1.12 (95% CI: 0.75, 1.68) after; although women employed before 1954 experienced an increased lung cancer risk also after adjustment for smoking (OR 2.66, 95% CI: 1.09, 6.47). Smoking habits differed in female hairdressers vs. non-hairdressers, while there was no significant difference in smoking habits between male hairdressers/barbers and non-hairdressers/barbers. Conclusion Our results suggest that most findings of increased lung cancer risk among hairdressers are likely due to smoking behaviour among this occupational group and not directly related to occupational exposure.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.013 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 source (direct Gemma or distilled Codex), 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".