Prevalence, incidence and characteristics of chronic cough among adults from the Canadian Longitudinal Study on Aging
Bibliographic record
Abstract
The objective of this study was to investigate the prevalence and incidence of chronic cough in a sample of Canadian adults, and how these are influenced by age, sex, smoking, respiratory symptoms, medical comorbidities and lung function. Participants with chronic cough were identified from the Canadian Longitudinal Study on Aging (CLSA) based on self-reported daily cough in the past 12 months. This is a prospective, nationally generalisable, stratified random sample of adults aged 45-85 years at baseline recruited between 2011 and 2015, and followed-up 3 years later. The prevalence and incidence per 100 person-years are described, with adjustments for age, sex and smoking. Of the 30 097 participants, 29 972 completed the chronic cough question at baseline and 26 701 did so at follow-up. The prevalence of chronic cough was 15.8% at baseline and 17.6% at follow-up with 10.4-17.1% variation across seven provinces included in the CLSA comprehensive sample. Prevalence increased with age and current smoking, and was higher in males (15.2%), Caucasians (14%) and those born in North America, Europe or Oceania (14%). The incidence of chronic cough adjusted for age, sex and smoking was higher in males and in underweight and obese subjects. Subjects with respiratory symptoms, airway diseases, lower forced expiratory volume in 1 s (% predicted), cardiovascular diseases, psychological disorders, diabetes and chronic pain had a higher incidence of chronic cough. The prevalence and incidence of chronic cough is high in the CLSA sample with geographic, ethnic and gender differences, influenced by a number of medical comorbidities.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".