Fewer Cancer Cases in 4 Countries of the WHO European Region in 2018 through Increased Alcohol Excise Taxation: A Modelling Study
Why this work is in the frame
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Bibliographic record
Abstract
INTRODUCTION: Prevention of cancer has been identified as a major public health priority for Europe, and alcohol is a leading risk factor for various types of cancer. This contribution estimates the number of cancer cases that could have potentially been averted in 2018 in 4 European countries if an increase in alcohol excise taxation had been applied. METHODS: Current country and beverage-specific excise taxation of 4 member states of the WHO European Region (Germany, Italy, Kazakhstan, and Sweden) was used as a baseline, and the potential impacts of increases of 20, 50, and 100% to current excise duties were modelled. A sensitivity analysis was performed, replacing the current tax rates in the 4 countries by those levied in Finland. The resulting increase in tax was assumed to be fully incorporated into the consumer price, and beverage-specific price elasticities of demand were obtained from meta-analyses, assuming less elasticity for heavy drinkers. Model estimates were applied to cancer incidence rates for the year 2018. RESULTS: In the 4 countries, >35,000 cancer cases in 2018 were caused by alcohol consumption, with the highest rate of alcohol-attributable cancers recorded in Germany and the lowest in Sweden. An increase in excise duties on alcohol would have significantly reduced these numbers, with between 3 and 7% of all alcohol-attributable cancer cases being averted if taxation had been increased by 100%. If the 4 countries were to adopt an excise taxation level equivalent to the one currently imposed in Finland, an even higher proportion of alcohol-attributable cancers could be avoided, with Germany alone experiencing 1,600 fewer cancer cases in 1 year. DISCUSSION/CONCLUSION: Increasing excise duties can markedly reduce cancer incidence in European countries.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 it