The associations between prices and taxes and the use of tobacco products in Latin America and the Caribbean: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Although taxes that raise retail tobacco prices and industry-initiated price increases have been shown to decrease tobacco consumption, the scarcity of studies in Latin America and the Caribbean using household- or individual-level data in existing reviews limits their policy relevance. OBJECTIVE: To conduct a systematic review and meta-analysis to assess the association between prices and taxes and the use of tobacco products in Latin America and the Caribbean. METHODS: We searched six electronic bibliographic databases, two online search engines, two working paper repositories, and hand-searched seven journals. We included all quantitative studies that used any measures of individual or household tobacco use as an outcome, written in English, Portuguese or Spanish. We used random-effects meta-analyses to pool results across studies. RESULTS: We found consistent evidence that in Latin American countries, higher cigarette prices were associated with lower cigarette smoking participation, consumption and initiation and that effect sizes were large enough to be policy meaningful. Pooled own-price elasticities indicate that higher prices were associated with a less than proportional decrease in tobacco use (pooled own-price elasticities, participation: 0.14 [95% CI -0.22, -0.06]; consumption: 0.54 [95% CI -0.75, -0.34]; total: 0.75 [95% CI -1.14, -0.36]). We found no consistent evidence that socioeconomic status, age, sex, rurality, or geographic regions affected price responsiveness. CONCLUSIONS: Our review confirms that taxes that raise tobacco prices can effectively lower tobacco use. Moreover, raising tobacco prices through increased taxes is anticipated to boost tax revenue due to the inelastic nature of the demand for tobacco.
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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 | 0.020 | 0.056 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.036 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".