Indoor air pollution from solid fuel use, chronic lung diseases and lung cancer in Harbin, Northeast China
Bibliographic record
Abstract
In some areas of China, indoor air pollution (IAP) originating principally from the combustion of solid fuels has a relevant role in lung cancer. Most previous studies focused on the female population and only a few on both the sexes. We analyzed the relationship between IAP from solid fuel use and selected chronic lung diseases and lung cancer risk in Harbin, Northeast China, an area with a very high base line risk of lung cancer for both the sexes. We used data from a case-control study conducted between 1987 and 1990, including 218 patients with incident, histologically confirmed lung cancer and 436 controls admitted to the same hospitals as cases. We calculated an index of IAP from solid fuel use exposure using data on heating type, cooking fuel used, and house measurements. Cases reported more frequently than controls an exposure to coal fuel for house heating and/or cooking, and the odds ratio (OR) for ever versus never exposed was 2.19 [95% confidence interval (CI): 1.08-4.46]. The ORs of lung cancer according to subsequent tertiles of IAP exposure index were 1.82 (95% CI: 1.14-2.89) and 1.99 (95% CI: 1.26-3.15) as compared with the lowest tertile. The ORs of lung cancer for participants with a history of chronic bronchitis and tuberculosis were 3.79 (95% CI: 2.38-6.02) and 3.82 (95% CI: 1.97-7.41), respectively. This study gives further support and quantification of the positive association between IAP, history of selected nonmalignant lung diseases, and lung cancer risk for both the sexes.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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 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".