Ambient air pollution and children's health: A systematic review of Canadian epidemiological studies
Bibliographic record
Abstract
BACKGROUND: There is growing concern about the health effects of ambient air pollution (AP) in children. The present article summarizes and compares local information regarding the adverse effects of AP on the health of Canadian children with reports from elsewhere. METHODS: PUBMED, MEDLINE and EMBASE databases were searched for epidemiological studies, published between January 1989 and December 2004, on the adverse health effects of criteria air pollutants among Canadian children. RESULTS: Eleven studies investigated the association between AP and various respiratory health outcomes, while one study assessed the effect of AP on sudden infant death syndrome. Another study examined the effects of AP on pregnancy outcomes. Most of the available information was from Ontario and British Columbia. Despite inconsistencies among study results and data from elsewhere, evidence from Canadian studies suggest that AP may cause adverse respiratory health effects in children and adverse pregnancy outcomes, and may contribute to infant mortality in Canada. INTERPRETATION: AP has detrimental health effects among Canadian children. Paediatricians and other health care workers with an interest in child health should encourage parents and children to adhere to smog (AP) advisories. Existing regulatory practices should be reviewed to reduce current levels of ambient air pollutants in Canada.
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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 | 0.007 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.017 | 0.035 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".