Regional Variations in Risk Factors for Asthma in School Children
Bibliographic record
Abstract
BACKGROUND: The authors have previously reported an increased prevalence of asthma in Estevan, Saskatchewan (21.4%) compared with Swift Current, Saskatchewan (16.2%). OBJECTIVE: To determine the association between asthma and personal and indoor environmental risk factors in these communities. METHODS: A population-based cross-sectional study was conducted in January 2000. A questionnaire was distributed to school children in grades 1 to 6 for completion by a parent. Multivariate logistic regression was used to examine associations between various risk factors and physician-diagnosed asthma. RESULTS: Asthma was associated with respiratory allergy (adjusted OR [adjOR]=8.85, 95% CI 6.79 to 11.54), early respiratory illness (adjOR=2.81, 95% CI 1.96 to 4.03) and family history of asthma (adjOR=2.37, 95% CI 1.67 to 3.36). Several environmental factors varied with asthma by town. In Estevan, asthma was associated with home mould or dampness (adjOR=1.82, 95% CI 1.23 to 2.69) and was inversely associated with air conditioning (adjOR=0.56, 95% CI 0.37 to 0.85). The risk of asthma was increased if the child had previous exposure to environmental tobacco smoke from the mother in both communities (Swift Current: OR=1.87, 95% CI 1.06 to 3.30; Estevan: OR=2.00, 95% CI 1.17 to 3.43), and there was an inverse association with current exposure to environmental tobacco smoke from the mother in Estevan (OR=0.64, 95% CI 0.40 to 1.00). When multivariate analyses were stratified by sex, the relationship between home mould or dampness and asthma was most prominent in girls in Estevan. CONCLUSIONS: Despite a similar regional location, different risk factors for asthma were identified in each community. Local environmental factors are important to consider when interpreting findings and planning asthma care.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".