Estimating the impact of availability restrictions and taxation increases on alcohol consumption, 100% alcohol-attributable and all-cause mortality in the Baltic countries and Poland 2001-2020
Bibliographic record
Abstract
Introduction:Major alcohol control policy measures in the Baltic countries and Poland have been shown to reduce alcohol per capita consumption (APC), 100% alcohol-attributable and all-cause mortality.This publication aims to estimate the effects of taxation increases and availability restrictions separately.Material and methods: Data were obtained from the statistical offices of the countries included except for alcohol consumption data, which were taken from the WHO for comparability reasons.Various types of regression analyses were conducted on time-series data using generalized additive mixed models.Results: On average, taxation increases were associated with decreases in APC (-0.89 litres (l); 95% CI: -1.35 l, -0.43 l) and all-cause mortality (-1.3%; 95% CI: -2.4%, -0.17%) among males.Given the average number of deaths in the four countries, the 1.3% reduction in the male mortality rate corresponds to 93 deaths postponed in Estonia, 166 in Latvia, 239 in Lithuania, and 2,606 in Poland, using the 2019 populations of the respective countries as the reference points.For 100% alcohol-attributable mortality, there were significant associations with availability restrictions for males (-12.1%;95% CI: -17.8%, -6.4%) and females (-8.5%; 95% CI: -16.3%, -0.7%), as well as with taxation for females (-9.06%; 95% CI: -14.02%, -3.83%).All other associations were in the hypothesized direction but did not reach statistical significance.Conclusions: Different effects were found for taxation increases and availability restrictions.The former works via reducing the level of consumption, and thereby reduces all-cause mortality, while the latter seems to work more specifically on reducing heavy drinking occasions and consequently in particular on decreasing 100% alcohol-attributable mortality.Both alcohol control policies important to reduce consumption and alcohol-attributable mortality.However, they produce partly different outcomes, and thus should be implemented depending on the epidemiological profile and the desired effects.
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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 | 0.011 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".