Area-level differences in the prices of tobacco and electronic nicotine delivery systems — A systematic review
Bibliographic record
Abstract
OBJECTIVE: To examine associations between area-level characteristics (socioeconomic status, racial or ethnic characteristics, age, and any other characteristics that may be associated with vulnerability) and the prices of tobacco products and electronic nicotine delivery systems (ENDS). DATA SOURCES: We searched MEDLINE, EconLit and Scopus, unpublished and grey literature, hand-searched four specialty journals, examined references of relevant studies, and contacted key informants. STUDY SELECTION: We considered all studies that quantitatively examined area-level variations in the prices of tobacco products and ENDS. We included all studies that examined any area-level measures regardless of the geographic location, language or time of publication. At least two reviewers independently screened the articles. We identified 20 studies. DATA EXTRACTION: At least two reviewers independently extracted the characteristics, methods, and main results and assessed the quality of each included study. DATA SYNTHESIS: Overall, cigarette prices were found to be lower in lower socioeconomic status neighbourhoods, and in neighbourhoods with a higher percentage of youth, and Blacks or African Americans. We identified too few studies that examined price differences for cigarillos, chewing tobacco, roll-your-own, and ENDS to reach any conclusions. CONCLUSIONS: Our findings are in keeping with tobacco industry documents that detailed how manufacturers used race, class, and geography to target vulnerable populations and suggest that regulations that can limit industry price manipulation such as minimum, maximum, and uniform prices, and high specific excise taxes should be considered. More frequent and systematic monitoring of tobacco prices and ENDS is warranted.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".