Prevalence and associated factors of COPD among Aboriginal peoples in Canada: a cross-sectional study
Bibliographic record
Abstract
BACKGROUND: COPD among Aboriginal peoples in Canada is a major public health concern. This study was conducted in order to determine the prevalence and association between certain risk factors and COPD among the 35-year-old or older Aboriginal peoples in Canada. METHODS: This is a cross-sectional study. It uses data from Statistics Canada's Aboriginal Peoples Survey (APS), 2012. It consists of 8,117 self-identified Aboriginal peoples, aged 35 years old or older from all Canadian provinces and territories. The study outcomes centered on evaluating the prevalence and associated factors of COPD. RESULTS: This study found that 6.80% of the participants self-reported having COPD. Results of the logistic regression analysis show that COPD was significantly higher among daily smokers (odds ratio [OR], 2.28; 95% confidence interval [95% CI], 1.65-3.14), aged 55 years or older (OR, 3.04; 95% CI, 2.14-4.30), who earned $5,000-$9,999 per annum (OR, 4.21; 95% CI, 2.39-7.41) and needed health care over the past 12 months and did not receive it (OR, 1.83; 95% CI, 1.27-2.65). CONCLUSION: The findings of our study show that COPD is strongly associated with Aboriginal peoples, who are older, smoke, have a low socioeconomic status (SES) and do not have access to health care when needed. Clinicians, health care professionals, medical/public health organizations, researchers and patients will greatly benefit from additional research in this common, serious and often overlooked disease among Aboriginal peoples in Canada.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 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".