Asthma incidence in a national sample of Canadian adolescents
Bibliographic record
Abstract
Background: Estimates of asthma incidence and its determinants have rarely been obtained from rural regions, especially in adolescent populations. Objective: To compare the incidence of asthma among Canadian adolescents in rural and urban regions and to examine the determinants of asthma incidence. Methods: We used data from the National Population Health Survey (NPHS), a nationally representative longitudinal survey of Canadians. The NPHS uses a complex survey design with data collected every 2 years since 1994/95. The NPHS collects information on socio-demographics and some health behaviours. All persons aged 12-18 years without asthma in Cycle 1 were followed until a reported diagnosis of asthma or censoring up to Cycle 7. Rural residence was defined by living in an area of <1000 people and >400 people/km 2 . Incidence and Cox regression analyses were population weighted and bootstrapping procedures were used to estimate variances. Results: This sample represented 2,482,610 adolescents of whom 293,445 developed asthma. Approximately 19% of the cohort was rural living at baseline. The incidence of asthma was approximately 10.2 per 1000 person-years and was higher in urban dwellers than rural dwellers (10.9 vs. 7.7 per 1000 person-years). In adjusted analysis, rural residence was not associated with asthma development [Hazard ratio (HR)=0.58, 95%CI=0.25-1.32, p=0.19]. Being female and being exposed to passive smoking were both associated with the development of asthma (p<0.01). Conclusions: Unlike results from younger children, a rural dwelling was not protective of developing asthma among adolescents, despite showing a trend. Asthma prevention initiatives for adolescents should target girls and focus on smoking exposure.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".