Opposing Trends in the Prevalence of Health Professional‐Diagnosed Asthma by Sex: A Canadian National Population Health Survey Study
Bibliographic record
Abstract
BACKGROUND: The prevalence of asthma is on the rise worldwide, with large variations in prevalence existing between and within countries. Little is known regarding the variation in asthma prevalence in adults living in rural and urban settings. OBJECTIVES: Using questionnaire data from the Canadian National Population Health Survey, the prevalence of asthma at four time periods (1994/1995 [cycle 1], 1996/1997 [cycle 2], 1998/1999 [cycle 3] and 2000/2001 [cycle 4]) was compared between rural and urban populations stratified by sex, smoking status and age group. Asthma was defined as a positive response to the question: "Do you have asthma diagnosed by a health professional?" METHODS: To account for the complexity of the survey design, the bootstrap method was used to calculate prevalences and 95% CIs. RESULTS: Overall, the prevalence of asthma increased from 7.3% (cycle 1) to 7.5% (cycle 4). After stratifying by sex, the asthma prevalence decreased among men, but in women, there was a steady increase. Asthma prevalence increased for both the rural population and the urban population. After stratifying each cycle by sex and location (rural or urban), both rural and urban men showed a decrease in asthma prevalence. On dividing according to age groups (0 to 14 years, 15 to 34 years, 35 to 64 years, and 65 years and older), the prevalence of asthma was greatest in the 15- to 34-year age group of urban and rural women. CONCLUSIONS: Asthma prevalence increased among rural and urban women. The prevalence of asthma was highest among female smokers and male nonsmokers when stratified by smoking status. Based on these findings, the rate of increase in asthma prevalence is different for men and women.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".