Urban Air Pollution and Emergency Department Visits for Cardiac and Respiratory Diseases
Bibliographic record
Abstract
Air pollution affects various aspects of human health. Here, the associations between the number of emergency department visits for circulatory and respiratory problems and ambient air pollution in Toronto, Canada, in the period between April 2004 and December 2015 were studied. The health data were linked with urban air pollution data and weather factors. The conditional Poisson regression models were built for 18 strata (sex, age group, season), 8 exposure factors (air pollutants, indexes), and their 15 lags (0-14 days). Circulatory problems: the associations were intensified in the cold period (October - March) and were associated with the air quality health index (AQHI). The estimated relative risks for all patients in the cold period, for an increase of the AQHI by 1, at lags 0, 1, and 2 were 1.017 and 95% confidence interval (1.010, 1.024), 1.014 (1.007, 1.021), and 1.009 (1.002, 1.016). Respiratory problems: the analogous results for ozone and its increase by 12.8 ppb at lags 3, 4, and 5 were 1.052 (1.033, 1.161), 1.039 (1.020, 1.121), and 1.027 (1.008, 1.082). It was observed that exposure to certain air pollutants (nitrogen dioxide, ozone, and the AQHI index) are associated with increased emergency department visits in both cardiac and respiratory health problems.
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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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".