How Widespread is the Use of E-Cigarettes Among Adults in the United States Who Have Never Smoked? A Tale of Three Studies
Bibliographic record
Abstract
Background Whilst e-cigarettes are a less harmful means of consuming nicotine than combustible cigarettes, concerns have been expressed about their use by adults who have never smoked (ANS). It is important to quantify the prevalence of e-cigarette use and to understand patterns of use among ANS to effectively guide public health policy and regulatory decisions.Methods The prevalence and patterns of e-cigarette use among ANS were estimated drawing upon data from three national studies in the United States; Population Assessment of Tobacco and Health Study (n = 29,780); the Tobacco Product Prevalence Study (n = 6,428); and the National Health Interview Survey (n = 27,651).Results An estimated 5.0 million (5.5%) to 18.6 million (11.1%) ANS have tried e-cigarettes and most of this use is experimental. An estimated 1.5 million (1.6%) to 4.8 million (2.9%) ANS currently use e-cigarettes, and current use is primarily infrequent. However, an estimated 0.5 million (0.5%) to 2.2 million (1.3%) ANS use e-cigarettes frequently. Prevalence of e-cigarette use is highest among younger (18–24 years) ANS.Conclusions E-cigarettes are intended to be used by adults who are currently smoking combustible cigarettes as a means of quitting combustible cigarette use or substantially reducing the number of cigarettes smoked.Therefore ANS are an unintended user population. The public health impact associated with e-cigarette use by ANS depends on whether these adults are using e-cigarettes to displace combustible cigarette use (harm avoidance) or whether they would otherwise not have initiated nicotine use if e-cigarettes were not available (harm exposure).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".