Tobacco-Free Oral Nicotine Product Use Among Youth in the U.S., 2019–2021
Bibliographic record
Abstract
Introduction: Novel tobacco-free oral nicotine products are not combusted, easy to conceal, available in flavors, and do not contain tobacco leaf. Since 2016, oral nicotine product sales have increased and may be gaining popularity among youth. This study aims to examine the trends in the prevalence and correlates of oral nicotine product use among U.S. youth. Methods: Data from participants aged 16-19 years in the U.S. International Tobacco Control Policy Evaluation Project Youth Tobacco and Vaping Survey were analyzed cross-sectionally from August 2019, February 2020, August 2020, February 2021, and August 2021. Weighted descriptive statistics and logistic regressions were used to describe the use and correlates of oral nicotine products. Results: Oral nicotine product use significantly increased from 3.5% in August 2019 to 4.1% in August 2021. Oral nicotine product use was most prevalent among those aged 18 years, male, and non-Hispanic White. Those who used cigarettes (AOR=2.18, 95% CI=19.37, 40.88), nicotine vaping products (AOR=4.27, 95% CI=3.02, 6.04), and smokeless tobacco (AOR=28.14, 95% CI=19.37, 40.88) in the past 30 days were more likely to report recent use of oral nicotine products. Conclusions: Although oral nicotine products are less popular among U.S. youth than cigarettes, nicotine vaping products, and smokeless tobacco, their prevalence of use significantly increased. Oral nicotine product users are more likely to use other nicotine products, but the availability of flavors and easy-to-conceal design may be appealing to those who may not use nicotine products. Researchers should continue to observe the behaviors associated with oral nicotine product use to inform the need for future regulatory efforts.
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 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 | 0.001 | 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) | 0.001 | 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".