Coarse Particulate Matter and Hospitalization for Respiratory Infections in Children Younger Than 15 Years in Toronto: A Case-Crossover Analysis
Bibliographic record
Abstract
OBJECTIVES: The purpose of this study was to examine the association between ambient air pollution and hospitalization for respiratory infections among children who were younger than 15 years in Toronto during a 4-year period (1998-2001). METHODS: Exposures averaged during periods that varied from 1 to 7 days were used to assess the effects of air pollutants, including thoracic particulate matter (PM10), fine (PM2.5) and coarse (PM10-2.5) particulate matter, carbon monoxide (CO), sulfur dioxide (SO2), nitrogen dioxide (NO2), and ozone (O3), on hospitalization for respiratory infections. A case-crossover design was used to calculate odds ratios for the hospitalization adjusted for daily weather conditions with an incremented exposure corresponding to the interquartile range in air pollution exposures. RESULTS: When particulate matter and gaseous pollutants were mutually taken into account, the effect remained pronounced for PM10-2.5 in both boys and girls. The adjusted odds ratio for 6-day average exposure to PM10-2.5 with an increment of 6.5 microg/m3 was 1.15 (95% confidence interval: 1.02-1.30) for boys and 1.18 (95% confidence interval: 1.01-1.36) for girls. The effect also remained for PM10 in boys and for NO2 in girls. PM2.5, CO, SO2, and O3 showed no significant effects on hospitalization for respiratory infection in both genders when other pollutants were taken into consideration. CONCLUSION: Our study suggested a detrimental effect of relatively low levels of ambient particulate matter and gaseous pollutants, especially coarse particulate matter and NO2, on hospitalization for respiratory infections in children.
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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".