Use of electronic cigarettes across 13 ITC countries with different regulatory environments
Bibliographic record
Abstract
Background Electronic cigarettes have become an international phenomenon, although few studies have compared e-cigarette use across countries. This paper presents prevalence estimates of self-reported e-cigarette awareness, trial (ever-tried), current use (daily/weekly/monthly), and daily use from 13 countries that vary on the strictness of e-cigarette policies/regulations. Methods Cross-sectional analyses of representative samples of adult (≥18-years) current and former smokers participating in International Tobacco Control Project (ITC) surveys in 13 countries from the most recent ITC survey wave (2013-2017). Countries were categorized into those with no e-cigarette policies (NP), less restrictive policies (LRP), or more restrictive policies (MRP). Results Weighted prevalence estimates of four key measures were computed: 1. Awareness: for NP countries: Zambia (2014): 3%, Bangladesh (2014/15): 7%, China (2013/15): 59%; LRP countries: Netherlands (2017): 92%, Republic of Korea (2016): 94%, United States (US) and England (2016): 99%; MRP countries: Uruguay (2014): 52%, Mexico (2014/15): 61%, Brazil (2016): 73%, Malaysia (2013/2014): 86%, Australia and Canada (2016): 99%. 2. Trial: for NP countries: Zambia (0%), Bangladesh (1%), China (11%); LRP countries: Netherlands (39%), Korea (44%), England (52%). US (58%); MRP countries: Uruguay (7%), Mexico (10%), Malaysia (38%), Australia (45%), Canada (49%). 3. Daily/weekly/monthly use: for NP countries: Zambia and Bangladesh (< 1%); China (1%); LRP countries: Korea (6%), Netherlands, US, England (7%); MRP countries: Uruguay (0%), Brazil (1%), Mexico (2%), Australia and Canada (6%), Malaysia (12%). 4. Daily use: for NP countries: Zambia, Bangladesh, China (all 0%); LRP countries: Korea (3%), Netherlands (3%), US (3%), England (4%); MRP countries: Uruguay and Brazil (0%), Mexico (1%), Canada (2%), Australia (3%), Malaysia (4%). [E-cigarette Trial, Current Use, and Daily Use] Conclusions With minor exceptions (e.g. Australia), awareness, trial, and use of e-cigarettes across the 13 countries generally reflected the de facto environment rather than the statutory environment implied by the law(s). Country income classification and survey year also appear to be strongly associated with use.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".