Associations of Ambient Air Pollution with Chronic Obstructive Pulmonary Disease Hospitalization and Mortality
Bibliographic record
Abstract
RATIONALE: Ambient air pollution has been suggested as a risk factor for chronic obstructive pulmonary disease (COPD). However, there is a lack of longitudinal studies to support this assertion. OBJECTIVES: To investigate the associations of long-term exposure to elevated traffic-related air pollution and woodsmoke pollution with the risk of COPD hospitalization and mortality. METHODS: This population-based cohort study included a 5-year exposure period and a 4-year follow-up period. All residents aged 45-85 years who resided in Metropolitan Vancouver, Canada, during the exposure period and did not have known COPD at baseline were included in this study (n = 467,994). Residential exposures to traffic-related air pollutants (black carbon, particulate matter <2.5 μm in aerodynamic diameter, nitrogen dioxide, and nitric oxide) and woodsmoke were estimated using land-use regression models and integrating changes in residences during the exposure period. COPD hospitalizations and deaths during the follow-up period were identified from provincial hospitalization and death registration databases. MEASUREMENTS AND MAIN RESULTS: An interquartile range elevation in black carbon concentrations (0.97 × 10(-5)/m, equivalent to 0.78 μg/m(3) elemental carbon) was associated with a 6% (95% confidence interval, 2-10%) increase in COPD hospitalizations and a 7% (0-13%) increase in COPD mortality after adjustment for covariates. Exposure to higher levels of woodsmoke pollution (tertile 3 vs. tertile 1) was associated with a 15% (2-29%) increase in COPD hospitalizations. There were positive exposure-response trends for these observed associations. CONCLUSIONS: Ambient air pollution, including traffic-related fine particulate pollution and woodsmoke pollution, is associated with an increased risk of COPD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".