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Record W3134833123 · doi:10.1093/ntr/ntab040

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

2021· article· en· W3134833123 on OpenAlexafffundabout
Lin Li, Ron Borland, K. Michael Cummings, Shannon Gravely, Anne C K Quah, Geoffrey T. Fong, Connor R. Miller, Maciej Ł. Goniewicz, Michael Le Grande, Ann McNeill

Bibliographic record

VenueNicotine & Tobacco Research · 2021
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsOntario Institute for Cancer ResearchUniversity of Waterloo
FundersNational Institute for Health and Care ResearchCanadian Institutes of Health ResearchNational Cancer InstituteOntario Institute for Cancer ResearchNational Institutes of HealthCanadian Cancer Society
KeywordsNicotineSmokeless tobaccoMedicineTobacco productCigarette smokingEnvironmental healthNicotine replacement therapyTobacco useInternal medicinePopulation

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.109
GPT teacher head0.364
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations40
Published2021
Admission routes3
Has abstractyes

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