Impact of Canada’s menthol cigarette ban on quitting among menthol smokers: pooled analysis of pre–post evaluation from the ITC Project and the Ontario Menthol Ban Study and projections of impact in the USA
Bibliographic record
Abstract
INTRODUCTION: Between 2015 and 2018, Canada banned menthol cigarettes. This study pooled data from two pre-post cohort studies (the Ontario Menthol Ban Study, and the International Tobacco Control Policy Evaluation (ITC) Canada Survey, conducted in seven provinces) to derive more precise estimates of the impact of Canada's menthol ban on quitting and to apply these estimates to project the impact of a menthol ban in the USA. METHODS: Weighted multivariable logistic analyses compared post-ban quit success of menthol smokers with non-menthol smokers (for daily smokers and for all (daily + non-daily) smokers), controlling for sex, age, ethnicity, education, baseline smoking status, baseline cigarettes per day and study regions. Projections to the USA were created by multiplying the effect size of the Canadian menthol ban on quitting (percentage of increased quitting among menthol smokers) by the number of menthol smokers overall and among African Americans, from the 2019 National Survey on Drug Use and Health. RESULTS: After the menthol cigarette ban, menthol smokers were more likely than non-menthol smokers to have quit smoking among daily smokers (difference=8.0%; 95% CI: 2.4% to 13.7%,p=0.005) and all (daily+non-daily) smokers (difference=7.3%; 95% CI: 2.1% to 12.5%,p=0.006). The projected number of smokers who would quit after a US menthol ban would be 789 724 daily smokers (including 199 732 African Americans) and 1 337 988 daily+non-daily smokers (including 381 272 African Americans). CONCLUSIONS: This pooled analysis of Canada's menthol cigarette ban provides the foundation for estimating the impact of menthol bans in the USA and other countries. Projections suggest that a US menthol cigarette ban would have a substantial impact on increasing quitting.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".