Cross-border Purchasing of Cigarettes among Smokers in Six European Countries: Findings from the EUREST-PLUS ITC Europe Surveys
Bibliographic record
Abstract
Introduction The availability of lower-cost cigarettes provides price-sensitive smokers with incentives to purchase cheaper cigarettes in order to minimize their financial costs of continuing to smoke. This study estimates the prevalence of and factors associated with cross-border purchasing of cheaper cigarettes among nationally representative samples of smokers from Germany, Greece, Hungary, Poland, Romania, and Spain (n = 6,011). Material and Methods The primary outcome was purchasing cheaper out-of-country cigarettes in the last six months. The prevalence of cross-border purchasing was estimated by country and residential location, defined as (a) living in regions bordering a country where the cost of the most popular price category brand of cigarettes was at least €1/pack lower than in smokers' home countries, (b) living in regions bordering a country with similar cigarette prices, and (c) living in regions not bordering other countries. Weighted multivariable logistic regression tested differences in purchasing cheaper out-of-country cigarettes by country and residential location. Results Residential location was associated with purchasing cheaper out-of-country cigarettes in Germany and Poland (p < 0.05): 31% of German and 11% of Polish smokers living in regions bordering lower-price countries made such purchases in the last six months. Across all countries, smokers living in areas bordering lower-price countries had 4.21 times greater odds of purchasing cheaper out-of-country cigarettes compared to smokers living in non-border areas (95% CI: 2.39-7.42). Conclusions Tax harmonization policies that minimize cross-border price differentials can eliminate lower-priced alternatives for price-sensitive smokers.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".