Exposure to low ambient concentrations of criteria air pollutants in Ontario, Canada, and the incidence of acute myocardial infraction and congestive heart failure, 1996-2012
Bibliographic record
Abstract
Background: Exposure to ambient air pollution, even at relatively low concentrations, has been linked to increased cardiovascular deaths. Less is known about the impact of low-level air pollution on the incidence of major cardiovascular outcomes such as acute myocardial infarction (AMI) and congestive heart failure (CHF). We conducted a population-based cohort study in Ontario, Canada, where the concentrations of pollutants are among the lowest in the world, to assess whether air pollution exposure is associated with incident AMI and CHF. Methods: We assembled a cohort of 50,464 adults from Ontario who responded to one of five population-based health surveys between 1996 and 2008 and had no prior history of cardiovascular disease. Follow-up extended until 31 December 2012. First-time incident AMI and CHF (nonfatal and fatal) were ascertained from the Ontario Myocardial Infarction Database and the Ontario Congestive Heart Failure Databases, two validated databases in Ontario, as well as the vital statistics database. We derived 2-year running average concentrations of PM2.5, NO2, and O3 at the subjects’ residences before events from satellite observations, land-use regression models, and an optimal interpolation method, respectively. We used Cox proportional hazards models, adjusting for various individual and contextual risk factors from the surveys such as smoking, body mass index, and neighborhood income. The association was estimated for each pair of outcomes and air pollutants. We conducted various sensitivity analyses including further control for access to family physicians. Results: For each interquartile range increase of PM2.5 (3.5μg/m3), the adjusted hazard ratio was 1.08 (95% CI: 1.01-1.14) for AMI and 1.04 (95% CI: 0.99-1.09) for CHF. No consistent evidence of association was observed for NO2 and O3. Our risk estimates were robust to sensitivity analyses. Conclusions: Exposure to PM2.5, even at low levels, may contribute to the incidence of AMI and CHF.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".