The burden of asthma in Canadian children and adolescents of South Asian descent
Bibliographic record
Abstract
The prevalence of asthma and wheezing symptoms vary greatly geographically and between different ethnic groups. We aim to compare asthma prevalence in South Asian Canadians (SAC), the general Canadian population (GCP) and a population in South Asia (SA). We hypothesize the prevalence of asthma in SAC group to be smaller than the prevalence in the GCP group, but greater than the prevalence in the SA group. Data from the International Study for Asthma and Allergies in Childhood (ISAAC) were analyzed from 5 centers in Canada. A validated surname algorithm based on 200 known South Asian surnames was used to determine ethnicity. We then compared the prevalence of asthma and wheezing ever and exercise induced wheezing in the last 12 months among the South Asians to the prevalence in the general population, and the published prevalence of asthma from the ISAAC survey conducted in SA. The prevalence of South Asian children was 0.59 and 1.39% respectively among children (6-7 years) and adolescents (13-14 years). For school children the prevalence of asthma, and wheezing was similar in the SAC group (22%) compared to the GCP group (18.6%), and much higher than that observed for the ISAAC survey conducted in SA (3.7%). For adolescents we observed similar results (17.2%, 22.6%, 4.5%). This study shows no differences in asthma prevalence between South Asians and the general Canadian population. However, the proportion of South Asian children and adolescents in the Canadian ISAAC study is smaller than the proportion in the Canadian population. Nonetheless, the prevalence of asthma in South Asians living in Canada was more than double that observed using the same survey in South Asia.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".