Exposure to Second-Hand Tobacco Smoke in Portugal After the Implementation of the Smoking Ban: A Systematic Review
Bibliographic record
Abstract
INTRODUCTION: Estimating the prevalence of second-hand tobacco smoke exposure is a public health priority while evaluating the population-attributable disease burden and impact of smoking bans. We conducted a systematic review to analyze how secondhand tobacco smoke exposure has been assessed, and how its prevalence has been estimated among the Portuguese population since the implementation of the partial smoking ban in 2008. METHODS: A literature search was conducted in the Web of Science, MEDLINE and Embase databases until November 2022, applying a pre-designed search strategy and following the PRISMA 2020 guidelines. The search was not restricted by study period, study design, sample size or language, and was complemented by a manual literature search. A modified Newcastle-Ottawa scale was used to assess the quality of the studies. RESULTS: Thirteen cross-sectional studies were included. The prevalence of second-hand tobacco smoke exposure among the three European studies ranged from 8.2% (adult population exposed at home in 2010) to 93.3% (adolescent/adult population exposed in bar/restaurant terraces in 2016). Three nationwide studies estimated children's exposure at home: ranging from 32.6% in 2010 - 2011 to 14.4% in 2016. According to the most recent studies, 49.8% of women living in Porto were exposed during the third trimester of pregnancy in 2010 - 2011; 32.6% and 38.4% of children were exposed at home, respectively in Lisbon and the Azores. CONCLUSION: A significant proportion of the Portuguese population, especially children and pregnant women, remain exposed to secondhand tobacco smoke. A comprehensive smoke-free policy is needed, not only in outdoor public places, but also in indoor private settings.
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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 | 0.007 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".