Gender Differences in Smoking and Self Reported Indicators of Health
Bibliographic record
Abstract
HEALTH ISSUE: Smoking among Canadian women is a serious public health issue. Using the 1998-99 National Population Health Survey, this study examined underlying factors contributing to differences in prevalence of smoking among subgroups of women and men, and its effects on self-reported indicators of health. KEY FINDINGS: In Canada, 26.4% of women and 29.2% of men were classified as current smokers. Higher levels of education and income were associated with decreased odds of current smoking. Adjusting for all other factors, being an ethnic minority decreased the odds of current smoking for both men and women (OR:0.35, 99%CI:0.23-0.54; OR:0.13, 99%CI: 0.09-0.20 respectively). Single mothers had the highest odds of smoking (OR: 2.12, 99%CI: 1.28-3.51) when compared to married mothers with children under 25 years of age. Current women smokers and current and former men smokers were less likely to report very good or excellent health compared with never smokers (OR: 0.83, 99%CI: 0.70-0.98; OR: 0.49, 99%CI: 0.41-0.60; OR: 0.75, 99%CI: 0.63-0.90 respectively). Women who were current smokers had increased odds of needing health care and not receiving it (OR: 1.50, 99%CI: 1.10-2.05). DATA GAPS AND RECOMMENDATIONS: Key issues for Canadian women include an increased prevalence of smoking among young girls and the strong association between smoking and social and economic disadvantage. Tobacco control policies and programs must target high-risk groups more effectively. Of particular importance is the development of programs and policies that do not serve to reinforce existing inequities, but rather, contribute to their amelioration.
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 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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".