Asthma and Chronic Obstructive Pulmonary Disease (COPD) Prevalence and Health Services Use in Ontario Métis: A Population-Based Cohort Study
Bibliographic record
Abstract
INTRODUCTION: Chronic respiratory diseases cause a significant health and economic burden around the world. In Canada, Aboriginal populations are at increased risk of asthma and chronic obstructive pulmonary disease (COPD). There is little known, however, about these diseases in the Canadian Métis population, who have mixed Aboriginal and European ancestry. A population-based study was conducted to quantify asthma and COPD prevalence and health services use in the Métis population of Ontario, Canada's largest province. METHODS: The Métis Nation of Ontario Citizenship Registry was linked to provincial health administrative databases to measure and compare burden of asthma and COPD between the Métis and non-Métis populations of Ontario between 2009 and 2012. Asthma and COPD prevalence, health services use (general physician and specialist visits, emergency department visits, hospitalizations), and mortality were measured. RESULTS: Prevalences of asthma and COPD were 30% and 70% higher, respectively, in the Métis compared to the general Ontario population (p<0.001). General physician and specialist visits were significantly lower in Métis with asthma, while general physician visits for COPD were significantly higher. Emergency department visits and hospitalizations were generally higher for Métis compared to non-Métis with either disease. All-cause mortality in Métis with COPD was 1.3 times higher compared to non-Métis with COPD (p = 0.01). CONCLUSION: There is a high burden of asthma and COPD in Ontario Métis, with significant prevalence and acute health services use related to these diseases. Lower rates of physician visits suggest barriers in access to primary care services.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".