Measurement of airborne nicotine, as a marker of secondhand smoke exposure, in homes with residents who smoke in 9 European countries
Bibliographic record
Abstract
Smoke-free policies are effective in preventing secondhand smoke (SHS) exposure, but their adoption at home remains largely voluntary. This study aimed to quantify SHS exposure in homes with residents who smoke in Europe according to households’ characteristics, tobacco consumption habits, and national contextual factors. Cross-sectional study (March 2017–September 2018) based on measurements of air nicotine inside 162 homes with residents who smoke from nine European countries. We installed passive samplers for seven consecutive days to monitor nicotine concentrations. Through self-administered questionnaires, we collected sociodemographic information and the number of individuals who smoke, smoking rules, frequency, location, and quantity of tobacco use in households. Country-level factors included the overall score in the Tobacco Control Scale 2016, the smoking prevalence, and self-reported SHS exposure prevalence. Nicotine concentrations were analyzed as continuous and dichotomous variables, categorized based on the limit of quantification of 0.02 μg/m3. Overall, median nicotine concentration was 0.85 μg/m3 (interquartile range (IQR):0.15–4.42), and there was nicotine presence in 93% of homes. Participants reported that smoking was not permitted in approximately 20% of households, 40% had two or more residents who smoked, and in 79% residents had smoked inside during the week of sampling. We found higher nicotine concentrations in homes: with smell of tobacco smoke inside (1.45 μg/m3 IQR: 0.32–6.34), where smoking was allowed (1.60 μg/m3 IQR: 0.68–7.63), with two or more residents who smoked (2.42 μg/m3 IQR: 0.58–11.0), with more than 40 cigarettes smoked (2.92 μg/m3 IQR: 0.97–10.61), and where two or more residents smoked inside (4.02 μg/m3 IQR: 1.58–11.74). Household nicotine concentrations were significantly higher in countries with higher national smoking prevalence and self-reported SHS exposure prevalence (p < 0.05). SHS concentrations in homes with individuals who smoke were approximately twenty times higher in homes that allowed smoking compared to those reporting smoke-free household rules. Evidence-based interventions promoting smoke-free homes should be implemented in combination with strengthening other MPOWER measures.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".