Patterns of Non-Cigarette Tobacco and Nicotine Use Among Current Cigarette Smokers and Recent Quitters: Findings From the 2020 ITC Four Country Smoking and Vaping Survey
Bibliographic record
Abstract
INTRODUCTION: This study explores patterns of use of non-cigarette tobacco and nicotine products among adult cigarette smokers and recent ex-smokers. Along with cigarette smoking status we explore differences as a function of countries with different product regulations, gender, and age. METHODS: Data came from the ITC Four Country Smoking and Vaping Wave 3 Survey conducted between February-June 2020. The analytic sample consisted of 9112 current cigarette smokers (at least monthly) and 1184 recent ex-smokers (quit cigarettes ≤ 2 years) from Australia, Canada, England, and the United States. Respondents were asked about their cigarette smoking and current use of the following non-cigarette products: combustible tobacco (cigars, cigarillos, pipe, waterpipe); noncombustible tobacco (smokeless tobacco, and heated tobacco products [HTPs]); and non-tobacco nicotine products (nicotine vaping products [NVPs], nicotine replacement therapy [NRT], and nicotine pouches). RESULTS: Overall, NVPs (13.7%) and NRT (10.9%) were the most reported nicotine products used, followed by cigars (5.3%), cigarillos (4.2%), and HTPs (3.5%). More than 21% current and recent ex-smokers of cigarettes reported using a non-tobacco nicotine product and noncombustible product, with respondents in England reporting the highest levels of use (>26%). Males, younger respondents, and current non-daily cigarette smokers were more likely to use non-cigarette nicotine products. Notably, 11.6% of ex-cigarette smokers were using other combustible tobacco. CONCLUSION: Considerable percentages of current cigarette smokers and ex-smokers use non-cigarette nicotine products, and there are unexpectedly high levels of use of other combustible products by those recent ex-smokers of cigarettes which is concerning and has important implications for definitions of smoking cessation. IMPLICATIONS: The tobacco product market has evolved to include new products which add to existing non-cigarette tobacco products creating a much more diverse nicotine market. This brief report provides a snapshot of use of various combustible and noncombustible nicotine-containing products among current cigarette smokers and recent ex-smokers in four western countries. Our results indicate that use of non-cigarette tobacco and nicotine products among these cigarette smokers and recent ex-smokers is not low, particularly among males, younger and non-daily cigarette smokers. Use of other combustible tobacco among respondents that recently quit cigarette smoking is concerning and has important implications for definitions of smoking cessation. Increased emphasis on researching non-cigarette nicotine product use is warranted in tobacco control generally and smoking cessation in particular.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".