The Association between Risk Factors and Chronic Obstructive Pulmonary Disease in Canada: A Cross-sectional Study Using the 2014 Canadian Community Health Survey
Bibliographic record
Abstract
BACKGROUND: The global prevalence of chronic obstructive pulmonary disease (COPD) is expected to increase and the disease is projected to be the third leading cause of death by the year 2020. The purpose of this study was to measure the prevalence and determine the risk factors for COPD in Canada. METHODS: This is a cross-sectional study that uses data from a nationally generalizable survey, the Canadian Community Health Survey, 2014. There were 46,924 respondents aged 35 years or older. Uni- and multi-variate logistic regression analyses were conducted to determine the risk factors associated with COPD. RESULTS: The overall prevalence of COPD in the surveyed population was 5.69%. Results from multivariate logistic regression showed that COPD was significantly higher among individuals who were 65 years or older (odds ratio [OR] =4.43; 95% confidence interval [CI]: 3.69-5.33), current smokers (OR = 5.13; 95% CI: 4.43-5.95), underweight or obese by body mass index ([OR = 1.81; 95% CI: 1.38-2.38] and [OR = 1.58; 95% CI: 1.41-1.77], respectively), with a total personal income of <$20,000 (OR = 3.67; 95% CI: 2.95-4.57,), and some postsecondary education (OR = 1.42; 95% CI: 1.14-1.76). Immigrants were less likely to have COPD compared to Canadian-born respondents (OR = 0.67; 95% CI: 0.57-0.79). CONCLUSIONS: COPD is a growing and serious public health issue in Canada. The risk factors identified in this study provide useful targets to health promotion and education initiatives, health-care providers, and public health organizations to decrease the prevalence of COPD.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.004 | 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) | 0.002 | 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".