Air pollution and emergency department visits for respiratory diseases: A multi-city case crossover study
Bibliographic record
Abstract
Increasing evidence suggests that ambient air pollution is a major risk factor for both acute and chronic respiratory disease exacerbations and emergencies. The objective of this study was to determine the association between ambient air pollutants and emergency department (ED) visits for respiratory conditions in nine districts across the province of Ontario in Canada. Health, air pollutant (PM2.5, NO2, O3, and SO2), and meteorological data were retrieved from April 2004 to December 2011. Respiratory diseases were categorized as: chronic obstructive pulmonary disease (COPD, including bronchiectasis) and acute upper respiratory diseases. A case-crossover design was used to test the associations between ED visits and ambient air pollutants, stratified by sex and season. For COPD among males, positive results were observed for NO2 with lags of 3–6 days, for PM2.5 with lags 1–8, and for SO2 with lags of 4–8 days. For COPD among females, positive results were observed for O3 with lags 2–4 days, and for SO2 among lags of 3–6 days. For upper respiratory disease emergencies among males, positive results were observed for NO2 (lags 5–8 days), for O3, (lags 0–6 days), PM2.5 (all lags), and SO2 (lag 8), and among females, positive results were observed for NO2 for lag 8 days, for O3, PM2.5 among all lags. Our study provides evidence of the associations between short-term exposure to air pollution and increased risk of ED visits for upper and lower respiratory diseases in an environment where air pollutant concentrations are relatively low.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".