Airflow Obstruction and Use of Solid Fuels for Cooking or Heating. BOLD (Burden of Obstructive Lung Disease) Results
Bibliographic record
Abstract
RATIONALE: Evidence supporting the association of COPD or airflow obstruction with use of solid fuels is conflicting and inconsistent. OBJECTIVE: To assess the association of airflow obstruction with self-reported use of solid fuels for cooking or heating. METHODS: We analysed 18,554 adults from the BOLD study, who had provided acceptable post-bronchodilator spirometry measurements and information on use of solid fuels. The association of airflow obstruction with use of solid fuels for cooking or heating was assessed by sex, within each site, using regression analysis. Estimates were stratified by national income and meta-analysed. We carried out similar analyses for spirometric restriction, chronic cough and chronic phlegm. MEASUREMENTS AND MAIN RESULTS: We found no association between airflow obstruction and use of solid fuels for cooking or heating (ORmen=1.20, 95%CI 0.94-1.53; ORwomen=0.88, 95%CI 0.67-1.15). This was true for low/middle and high income sites. Among never smokers there was also no evidence of an association of airflow obstruction with use of solid fuels (ORmen=1.00, 95%CI 0.57-1.76; ORwomen=1.00, 95%CI 0.76-1.32). Overall, we found no association of spirometric restriction, chronic cough or chronic phlegm with the use of solid fuels. However, we found that chronic phlegm was more likely to be reported among female never smokers and those who had been exposed for ≥20 years. CONCLUSION: Airflow obstruction assessed from post-bronchodilator spirometry was not associated with use of solid fuels for cooking or heating.
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.005 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".