Prevalence of and Risk Factors for Self‐Reported Chronic Bronchitis in a Canadian Population: The Canadian Community Health Survey, 2007 To 2008
Bibliographic record
Abstract
BACKGROUND: Chronic bronchitis (CB) represents one of the respiratory disease phenotypes that affect the Canadian health care system significantly. Presently, almost 6.5% of total health care costs are related to respiratory diseases. OBJECTIVE: To determine the prevalence of self-reported CB and associated risk factors in the Canadian general population. METHODS: Data regarding individuals ≥12 years of age from the Canadian Community Health Survey, 2007 to 2008, were analyzed. CB was determined through self-reported health professional diagnosis. Information regarding covariates of importance, such as demographics, lifestyle variables and socioeconomic status, was obtained. A weighted logistic regression analysis was performed with appropriate technique for clustering effects. RESULTS: The prevalence of self-reported CB was 2.5%. A greater prevalence of self-reported CB associated with older age, female sex and white ethnic group was found. There were differences in the prevalence of self-reported CB among regions of Canada for household income, educational attainment and smoking status. CONCLUSION: The results suggest an association between ethnicity and the prevalence of CB. The associations between self-reported CB prevalence and household income, educational attainment and smoking status varied according to region of Canada.
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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 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".