Article Component of Statistics Canada Catalogue no. 82-003-X Health Reports Changes in the prevalence of asthma among Canadian children
Bibliographic record
Abstract
Asthma is one of the most common chronic conditions in childhood, and its prevalence is increasing in many countries, including Canada.1-4 This article picks up where previous examinations of childhood asthma have left off.4,5 Based on data from the National Longitudinal Survey of Children and Youth (NLSCY), changes in prevalence rates among children aged 0 through 11 are examined from 1994/1995 through 2000/2001, by asthma severity, and by child and family socio-demographic factors. Prevalence increasing In 1994/1995, 11 % of Canadian children aged 0 to 11 (nearly 520,000) had been diagnosed with asthma. By 2000/2001, the rate had risen to more than 13% (Table 1), a statistically significant increase of nearly 70,000 children. Among children with asthma, the proportion with high-severity symptoms dropped from 41 % in 1994/1995 to 36 % in 2000/2001. This is similar to a British study that found a significant increase in the prevalence of asthma diagnosis, but only for children with mild symptoms.6 Asthma attacks less common Despite the increase in childhood asthma, the prevalence of asthma attacks decreased. In 1994/ 1995, about half (51%) of 0- to 11-year-olds with asthma were reported to have had an attack in the previous year; by 2000/2001, this proportion had dropped to 39 % (Table 1). Changes in the prevalence of asthma among Canadian children by Rochelle Garner and Dafna Kohen
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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 | 0.003 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.020 | 0.051 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.257 | 0.132 |
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".