The economic costs of alcohol consumption in Lithuania, 2015–20
Bibliographic record
Abstract
Alcohol per capita consumption in Lithuania among the population 15 years of age and older has been among the highest globally in recent decades. Long-term alcohol consumption trends and drinking patterns signal a significant public health problem, as well as social and economic losses. This study aimed to estimate the economic burden associated with alcohol consumption in Lithuania from 2015 to 2020. We used a cost-of-illness methodology with the human capital approach to estimate the economic burden and applied a prevalence-based approach. Using multiyear data, we estimated both, direct and indirect costs. Direct costs included healthcare and childcare, law enforcement, and justice system costs. Indirect costs included costs of productivity loss due to premature mortality. The total economic cost of alcohol consumption in Lithuania between 2015 and 2020 was estimated at an annual average of €542.958 million (in 2020 Euros) or about 1.18% of the Lithuanian total Gross Domestic Product. The highest proportion (65%) of the estimated costs was associated with productivity losses due to premature mortality. Alcohol use places a considerable burden on Lithuanian society in terms of illness, injury, death, and economic costs. Alcohol control policies, in particular excise taxation increases and availability restrictions have been shown to decrease this burden.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".