Changes in cigarette smoking initiation, cessation, and relapse among U.S. adults: a comparison of two longitudinal samples
Bibliographic record
Abstract
BACKGROUND: The tobacco epidemic in the U.S. has matured in the past decade. However, due to rapidly changing social policy and commercial environments, tailored prevention and interventions are needed to support further reduction in smoking. METHODS: Using Tobacco Use Supplement to the Current Population Survey (TUS-CPS) 2002-2003 and 2010-2011 longitudinal cohorts, five smoking states are defined including daily-heavy, daily-light, non-daily, former and non-smoker. We quantified the changes between smoking states for the two longitudinal cohorts, and used a series of multivariable logistic regression models to examine the association of socio-demographic attributes and initial smoking states on smoking initiation, cessation, and relapse between waves within each cohort. RESULTS: The prevalence of adult heavy smoking decreased from 9.9% (95% CI: 9.6%, 10.2%) in 2002 to 7.1% (95% CI: 6.9%, 7.4%) in 2010. Non-daily smokers were less likely to quit in the 2010-2011 cohort than the 2002-2003 cohort (37.0% vs. 44.9%). Gender, age group, smoker type, race and marital status exhibit similar patterns in terms of their association to the odds of initiation, cessation and relapse between the two cohorts, while education groups showed some inconsistent results between the two cohorts regarding the odds of cessation. CONCLUSIONS: Transitions between smoking states are complex and increasingly unstable, requiring a holistic, population-based perspective to understand the stocks and flows that ultimately dictate the public health impact of cigarette smoking behavior. This knowledge helps to identify groups in need of increased tobacco control prevention and intervention efforts.
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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 | 0.000 |
| 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".