Trends in the use of premium and discount cigarette brands: findings from the ITC US Surveys (2002–2011)
Bibliographic record
Abstract
OBJECTIVE: The purpose of this paper was to examine trends in the use of premium and discount cigarette brands and determine correlates of type of brand used and brand switching. METHODS: Data from the International Tobacco Control (ITC) US adult smoker cohort survey were analysed. The total study sample included 6669 adult cigarette smokers recruited and followed from 2002 to 2011 over eight different survey waves. Each survey wave included an average of 1700 smokers per survey with replenishment of those lost to follow-up. RESULTS: Over the eight survey waves, a total of 260 different cigarette brands were reported by smokers, of which 17% were classified as premium and 83% as discount brands. Marlboro, Newport, and Camel were the most popular premium brands reported by smokers in our sample over all eight survey waves. The percentage of smokers using discount brands increased between 2002 and 2011, with a marked increase in brand switching from premium to discount cigarettes observed after 2009 corresponding to the $0.61 increase in the federal excise tax on cigarettes. Cigarette brand preferences varied by age group and income levels with younger, higher income smokers more likely to report smoking premium brand cigarettes, while older, middle and lower income, heavier smokers were more likely to report using discount brands. CONCLUSIONS: Our data suggest that demographic and smoking trends favour the continued growth of low priced cigarette brands. From a tobacco control perspective, the findings from this study suggest that governments should consider enacting stronger minimum pricing laws in order to keep the base price of cigarettes high, since aggressive price marketing will likely continue to be used by manufacturers to compete for the shrinking pool of remaining smokers in the population.
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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 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".