Fifty years of pediatric asthma in developed countries: How reliable are the basic data sources?
Bibliographic record
Abstract
Given the difficulties in diagnosing, or even defining, asthma in children, claims of a pediatric asthma epidemic in Canada and other developed countries are accepted with surprisingly little critical examination. We reviewed a broad range of data sources to understand how the epidemic evolved during the last 50 years and also to assess the reliability of the conclusions drawn from that data. We obtained Canadian National and Provincial data from Statistics Canada National Population Health Survey, and the British Columbia Ministry of Health respiratory database. International data were obtained by extensive review of pediatric asthma epidemiological surveys published during the last 50 years. In many developed countries, there have been three separate epidemics involving different aspects of pediatric asthma during the last 50 years: a double peaked mortality epidemic (1960s and 1980s), a hospital admission epidemic (peaked around 1990) and a steadily growing epidemic of children who report asthmatic symptoms on questionnaires. Canadian pediatric rates for asthma mortality (1-2/million/year) and hospital admission (1-2/thousand/year) are low and have fallen for the last 20 years. Rates based on questionnaire studies are high (10-15/hundred) and rose steadily over the same period. Objective reductions in asthma deaths and hospital admission likely reflect improved education and treatment programmes. Current claims of an epidemic based largely on subjective self-reported symptoms require more careful analysis. The possibility that symptom misperception, disease fashions, and poor recall, may be part of the explanation for the current high levels of self-reported symptoms deserves more attention.
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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 | 0.190 | 0.394 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.023 | 0.043 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.010 | 0.015 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".