Interactive Effects of Air Pollution and Air Temperature on Preterm Delivery in 24 Major Cities across Canada
Bibliographic record
Abstract
Background: Epidemiological studies have reported associations between preterm birth and short-term exposure to ambient air pollution and air temperature. However, it remains uncertain whether there are interactive effects of air pollution and temperature on risk of preterm birth. We investigated whether short-term associations of ambient air pollution were modified by air temperature and whether air pollution levels affected the temperature-preterm birth associations in 24 major cities across Canada.Methods: We first analyzed air temperature-stratified associations between air pollution and preterm birth as well as air pollution-stratified temperature-preterm birth associations using city-specific Cox proportional hazards models with a distributed lag nonlinear temperature term in each city. All models were adjusted for individual-level confounders. City-specific effect estimates were then pooled using random-effects meta-analysis.Results: Pooled associations between air pollutants and risk of preterm delivery were overall positive and generally stronger at high relatively compared to low air temperatures. For example, on lag-0 (i.e. same day of preterm delivery) with high air temperatures (>75th percentile), an increase of 7.4 μg/m3 in PM2.5 corresponded to a 2.51% (95% CI: 0.39%, 4.67%) increase in preterm delivery, which was significantly higher than that on days with low air temperatures (<25th percentile) [-0.18% (95%CI: -0.97%, 0.62%)]. On days with high air pollution (>50th percentile), both heat- and cold-related preterm delivery risks increased.Conclusion: Our findings showed that the association between preterm delivery and air pollution was modified by air temperature and vice versa. Our findings point to the importance of understanding the combined health effects of ambient air pollution and air temperature.
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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 | 0.000 |
| 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".