Sociodemographic characteristic of changes in smoking patterns in rural and urban population of PURE Poland study: findings from 6-year follow up
Bibliographic record
Abstract
BACKGROUND: Tobacco smoking is one of the most serious modern civilization threats. According to WHO identifying patterns of tobacco use is essential for implementing effective preventive policies. The aim of the paper was to assess changes in smoking patterns among the PURE study population over 6 years. METHODS: The study sample comprised of 1784 adult participants from PURE Poland study, who were assessed at baseline (2007-2010) and then at 6-year follow-up. Participants were classified into current smokers, ex-smokers and never smokers. Smoking patterns were analyzed according to sex, age/birth cohort, place of residence (urban vs rural setting), and education level. RESULTS: Overall, a significant decrease of 3.1% in current smokers was observed (from 20.0% in baseline to 16.9 at follow-up). However, 0.8% of never smokers and 6.2% of ex-smokers at baseline were classified as current smokers at 6-year follow-up. Despite overall decrease in percentage of current smokers in both rural and urban area, in fact significantly more ex-smokers from rural area became current smokers after 6 years. Living in the rural area was associated with nearly two-fold increase in current smoking, and almost two-fold decline in chances to quit smoking. The highest percentage of current smokers was observed in birth year cohort 1961-1979. CONCLUSION: Despite a small but significant decline in overall smoking rates, important differences in smoking and quitting patterns emerged between rural and urban areas, as well as sexes. A less favorable smoking patterns were observed among women, and rural populations, suggesting that these are important targets of future tobacco control interventions in Poland.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".