The Impact of Ontario Smoke-Free Legislation on Secondhand Smoke in Enclosed Public Places
Bibliographic record
Abstract
Many studies have evaluated the impact of indoor smoking bans on secondhand smoke (SHS) exposure. No studies have assessed the impact of a smoking ban on SHS in enclosed areas outside separately ventilated, designated smoking rooms (DSRs). This study evaluated the overall impact of the Smoke-Free Ontario Act implemented May 31, 2006, on SHS in bars and coffee shops and the impact of banning DSRs on SHS outside DSRs. Air particulate matter (PM) and carcinogenic particulate polycyclic aromatic hydrocarbons (PPAH) were measured in May 2006 before the ban inside and outside DSRs in Toronto venues (13 coffee shops and 14 bars) that allowed smoking only in DSRs, and in Windsor venues (10 coffee shops and 10 bars) where smoking was allowed in shared spaces. Measurements were repeated 2 months post-ban. Air quality index values (AQIs) were calculated. Mixed model analysis was applied, taking into account measurement errors for repeated measures. Post ban, mean PM and PPAH levels were reduced by 87% (from 494 to 67 mm(2)/m(3)) and 94% (from 196 to 11 ng/m(3)), respectively, inside Toronto DSRs. Mean PM and PPAH levels were reduced by 10% (from 124 to 111 mm(2)/m(3)) and 46% (from 45 to 24 ng/m(3)), respectively, outside Toronto DSRs. In all Windsor venues, mean PM and PPAH levels were reduced by 83% (from 488 to 81 mm(2)/m(3)) and 90% (from 107 to 10 ng/m(3)), respectively. All reductions were statistically significant (p < 0.0001). In Toronto venues, the AQI was reduced from the "very unhealthy" range inside DSRs and the "moderate" range outside Toronto DSRs to the "good" range, and in Windsor venues from the "unhealthy for sensitive groups" range to the "good" range post-ban. Pre-ban PPAH levels including those outside Toronto DSRs may be associated with cardiovascular injury. DSRs did not provide adequate protection from SHS. The Smoke-Free Ontario Act produced a significant and firm reduction in SHS exposure in venues both with and without DSRs.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".