Do tobacco regulatory and economic factors influence smoking cessation outcomes? A post-hoc analysis of the multinational EAGLES randomised controlled trial
Bibliographic record
Abstract
INTRODUCTION: We previously reported global regional differences in smoking cessation outcomes, with smokers of US origin having lower quit rates than smokers from some other countries. This post-hoc analysis examined global regional differences in individual-level and country-level epidemiological, economic and tobacco regulatory factors that may affect cessation outcomes. METHODS: EAGLES (Evaluating Adverse Events in a Global Smoking Cessation Study) was a randomised controlled trial that evaluated first-line cessation medications and placebo in 8144 smokers with and without psychiatric disorders from 16 countries across seven regions. Generalised linear and stepwise logistic regression models that considered pharmacotherapy treatment, psychiatric diagnoses, traditional individual-level predictors (eg, demographic and smoking characteristics) and country-specific smoking prevalence rates, gross domestic product (GDP) per capita, relative cigarette cost and WHO-derived MPOWER scores were used to predict 7-day point prevalence abstinence at the end of treatment. RESULTS: In addition to several traditional predictors, three of four country-level variables predicted short-term abstinence: GDP (0.54 (95% CI 0.47, 0.63)), cigarette relative income price (0.62 (95% CI 0.53, 0.72)) and MPOWER score (1.03 (95% CI 1.01, 1.06)). Quit rates varied across regions (22.0% in Australasia to 55.9% in Mexico). With northern North America (USA and Canada) as the referent, the likelihood of achieving short-term abstinence was significantly higher in Western Europe (OR 1.4 (95% CI 1.14, 1.61)), but significantly lower in Eastern Europe (0.39 (95% CI 0.22, 0.69)) and South America (0.17 (95% CI 0.08, 0.35)). CONCLUSIONS: Increased tobacco regulation was associated with enhanced quitting among participants in the EAGLES trial. Paradoxically, lower GDP, and more affordable cigarette pricing relative to a country's GDP, were also associated with higher odds of quitting. Geographical region was also a significant independent predictor. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov, NCT01456936.
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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 | 0.046 | 0.041 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.013 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".