Asthma and Allergic Disease Prevalence in a Diverse Sample of Toronto School Children: Results from the Toronto Child Health Evaluation Questionnaire (T‐CHEQ) Study
Bibliographic record
Abstract
BACKGROUND: Asthma is the most common chronic disease in children. OBJECTIVES: To describe the prevalence of asthma and allergic disease in a multiethnic, population-based sample of Toronto (Ontario) school children attending grades 1 and 2. METHODS: In 2006, the Toronto Child Health Evaluation Questionnaire (T-CHEQ) used the International Study of Asthma and Allergies in Childhood survey methodology to administer questionnaires to 23,379 Toronto school children attending grades 1 and 2. Modifications were made to the methodology to conform with current privacy legislation and capture the ethnic diversity of the population. Lifetime asthma, wheeze, hay fever and eczema prevalence were defined by parental report. Asthma was considered to be current if the child also reported wheeze or asthma medication use in the previous 12 months. RESULTS: A total of 5619 children from 283 randomly sampled public schools participated. Children were five to nine years of age, with a mean age of 6.7 years. The overall prevalence of lifetime asthma was 16.1%, while only 11.3% had current asthma. The reported prevalence of lifetime wheeze was 29.2%, while 14.2% reported wheeze in the past 12 months. Sociodemographic and major health determinant characteristics of the T-CHEQ population were similar to 2001 census data, suggesting a diverse sample that was representative of the urban childhood population. CONCLUSIONS: Asthma continues to be a highly prevalent chronic disease in Canadian children. A large proportion of children with reported lifetime asthma, who were five to nine years of age, did not report current asthma symptomatology or medication use.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".