Secondhand smoke presence in outdoor areas in 12 European countries
Bibliographic record
Abstract
INTRODUCTION: Secondhand smoke (SHS) causes morbidity and mortality among non-smokers. OBJECTIVES: To investigate SHS presence in outdoor areas from 12 European countries and its association with country-level characteristics. METHODS: Cross-sectional study performed in 2017-2018 within the TackSHS project. We conducted a face-to-face survey on a representative sample of the population aged 15 years and older from 12 European countries: Bulgaria, England, France, Germany, Greece, Ireland, Italy, Latvia, Poland, Portugal, Romania, and Spain. Out of 11,902 participants, 8,562 were non-smokers. SHS presence was assessed in selected outdoor areas and defined as respondents viewing someone smoking the last time they visited each setting within the last 6 months. A ranking score for outdoor SHS presence was assigned to each country based on the SHS presence in each setting. We used Spearman's correlation (r) and the Chi-squared tests to assess the relationship between SHS presence and country-level characteristics. RESULTS: Except for children's playgrounds (39.5%; 95% confidence interval, CI: 37.6%-41.3%), more than half of non-smokers reported SHS presence in outdoor areas: schools (52.0%; 95%CI: 50.2%-53.7%), stadia (57.4%; 95%CI: 55.4%-59.4%), parks (67.3%; 95%CI: 66.0%-68.5%), hospitals (67.3%; 95%CI: 65.8%-68.7%), public transport stops (69.9%; 95%CI: 68.6%-71.2%), bar/restaurant terraces (71.4%; 95%CI: 70.2%-72.6%), and beaches (72.8%; 95%CI: 71.4%-74.1%). Residents in Latvia showed the highest overall outdoor SHS presence rank, followed by Greece, and Portugal. Outdoor SHS presence was directly correlated to the country's smoking prevalence (r = 0.64), and inversely correlated to the Tobacco Control Scale 2016 overall score (r = -0.62), the socio-demographic index 2017 (r = -0.56), and Gross Domestic Product per capita 2018 (r = -0.47) (p < 0.001). CONCLUSIONS: SHS presence is high in most outdoor areas in Europe, especially in countries with higher smoking prevalence and lower tobacco control performance. To address outdoor SHS exposure, our findings require considering smoking bans along with other strategies to reduce smoking prevalence.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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 teacher head, 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".