Cigarette Prices and Disparities in Smoking Cessation in the United States
Bibliographic record
Abstract
INTRODUCTION: Achieving cessation in people with established smoking patterns remains a challenge. Increasing cigarette prices has been one of the most successful strategies for lowering smoking rates. The extent to which it has remained effective in encouraging cessation among adults in recent years and how the effectiveness has varied by sociodemographic characteristics is unclear. AIMS AND METHODS: Using repeated cross-sectional data collected by the Tobacco Use Supplement of the Current Population Survey, we investigate the relationship between cigarette prices and cessation from 2003 to 2019 in adults at least 25 years old. We examine the associations between price and cessation in the population overall and by sex, race and ethnicity, and socioeconomic status. RESULTS: We found mixed support for associations between greater local prices and cessation. Unadjusted models showed that greater local prices were associated with greater odds of cessation, but the associations did not persist after controlling for sociodemographic characteristics. The associations did not significantly differ by respondent characteristics. Sensitivity analysis using alternative specifications and retail state price as the main predictor showed similar results. Sensitivity analysis with controls for e-cigarette use in the 2014-2019 period showed that greater local price was associated with cessation among adults with less than a high school degree. When stratified by year of data collection, results show that greater local prices were associated with cessation after 2009. CONCLUSIONS: Overall, the study adds to the conflicting evidence on the effectiveness of increasing prices on smoking cessation among adults with established smoking patterns. IMPLICATIONS: Higher cigarette prices have been one of the most successful tools for lowering smoking prevalence. It remains unclear how effective they have been in recent years in encouraging adults with established smoking patterns to quit. The study's results show that greater local prices were associated with higher odds of cessation, but the association did not persist after sociodemographic adjustment. In a sensitivity analysis, greater local price was associated with cessation among people with less than a high school degree in models controlling for e-cigarette use. We also found evidence that greater local price was associated with cessation after 2009. More comprehensive smoke-free coverage was also associated with greater odds of cessation. The study's results highlight that encouraging cessation among adults with an established smoking pattern remains a challenging policy problem even when cigarette prices rise.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".