Secondhand Smoke Exposure and Other Signs of Tobacco Consumption at Outdoor Entrances of Primary Schools in Eleven European Countries
Bibliographic record
Abstract
Introduction: Although smoking restrictions at child-related settings are progressively being adopted, school out-door entrances are neglected in most smoke-free policies across Europe. Objectives:To describe secondhand smoke (SHS) exposure and tobacco-related signs in outdoor entrances of primary schools in Europe according to area-level socioeconomic status (SES), smoke-free policy, national smoking prevalence, and geographical region. Methods:In this cross-sectional study we monitored vapor-phase nicotine concentrations at 220 school outdoor entrances in 11 European countries (March 2017–October 2018). To account for nicotine presence, we used the laboratory's limit of quantification of 0.06μg/m3as point threshold. We also recorded the presence of smell of smoke, people smoking, cigarette butts, and ashtrays. Half of the schools were in deprived areas. We grouped countries according to their Tobacco Control Scale (TCS) score, smoking prevalence (2017–2018), and United Na-tions M49 geographical region. Results:There were detectable levels of nicotine in 45.9% of the outdoor entrances, in 29.1% smell of smoke, in43.2% people smoking, in 75.0% discarded butts, and in 14.6% ashtrays. Median nicotine concentration was below the laboratory's limit of quantificationb0.06μg/m3(Interquartile range:b0.06–0.119). We found higher SHS levels in countries with lower TCS scores, higher national smoking prevalence, and in the Southern and East-ern European regions. People smoking were more common in schools from lower area-level SES and in countries with lower TCS scores (pb0.05). Conclusions: Smoking at school outdoor entrances is a source of SHS exposure in Europe. These findings support the extension of smoking bans with a clear perimeter to the outdoor entrances of schools.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".