Association between exposure to ambient particulate matter and chronic obstructive pulmonary disease: results from a cross-sectional study in China
Bibliographic record
Abstract
Objective The association between exposure to ambient particles with a median aerodynamic diameter less than 10/2.5 µm (particulate matter, PM10/2.5) and COPD remains unclear. Our study objective was to examine the association between ambient PM10/2.5 concentrations and lung functions in adults. Methods A cross-sectional study was conducted in southern China. Seven clusters were randomly selected from four cities across Guangdong province. Residents aged ≥20 years in the participating clusters were randomly recruited; all eligible participants were examined with a standardised questionnaire and spirometry. COPD was defined as a post-bronchodilator FEV1/FVC less than 70%. Atmosphere PM sampling was conducted across the clusters along with our survey. Results Of the subjects initially recruited, 84.4% (n=5993) were included for analysis. COPD prevalence and atmosphere PM concentration varied significantly among the seven clusters. COPD prevalence was significantly associated with elevated PM concentration levels: adjusted OR 2.416 (95% CI 1.417 to 4.118) for >35 and ≤75 µg/m3 and 2.530 (1.280 to 5.001) for >75 µg/m3 compared with the level of ≤35 µg/m3 for PM2.5; adjusted OR 2.442 (95% CI 1.449 to 4.117) for >50 and ≤150 µg/m3 compared with the level of ≤50 µg/m3 for PM1. A 10 µg/m3 increase in PM2.5 concentrations was associated with a 26 mL (95% CI −43 to −9) decrease in FEV1, a 28 mL (−49 to −8) decrease in FVC and a 0.09% decrease (−0.170 to −0.010) in FEV1/FVC ratio. The associations of COPD with PM10 were consistent with PM2.5 but slightly weaker. Conclusions Exposure to higher PM concentrations was strongly associated with increased COPD prevalence and declined respiratory function. Trial registration number ChiCTR-OO-14004264; Post-results.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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".