Second‐Hand Smoke Exposure in Canada: Prevalence, Risk Factors, and Association with Respiratory And Cardiovascular Diseases
Bibliographic record
Abstract
OBJECTIVES: The aims of the present study were to estimate the prevalence of second-hand smoke exposure in Canada, to identify sociodemographic risk factors for second-hand smoke exposure, and to examine the relationship between second-hand smoke exposure and respiratory and cardiovascular diseases. METHODS: Data from the 2000/2001 Statistics Canada Canadian Community Health Survey (n=130,880, aged 12 years or older) were analyzed. Second-hand smoke exposure was based on self-report within the past month. The presence of chronic health conditions was also based on self-report. Because ex-smokers would be expected a priori to have poorer health than never-smokers, the analysis was stratified by previous smoking status. RESULTS: Approximately 25% of never-smokers and 30% of ex-smokers self-reported recent second-hand smoke exposure. The following factors were identified as risk factors for second-hand smoke exposure: men; residences in Quebec, Atlantic Canada and the Territories; younger ages; nonimmigrant status; low education and income levels; social assistance receipt; and households without children younger than 12 years of age. After controlling for potential confounders, both never- and ex-smokers exposed to second-hand smoke had significantly higher odds of self-reporting asthma (20% to 30%) and chronic bronchitis (50%) than those not exposed to second-hand smoke. Among ex-smokers, those exposed to second-hand smoke also had significantly higher odds of self-reporting hypertension (20%) than those not exposed to second-hand smoke. No associations were observed between second-hand smoke exposure and emphysema or heart disease. CONCLUSIONS: Self-reported recent second-hand smoke exposure in Canada in 2000/2001 was high, and was associated with asthma, chronic bronchitis and hypertension in never- and ex-smokers. Potential causal associations and public health implications warrant additional research.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".