Non‐alcoholic beer in the European Union and <scp>UK</scp>: Availability and apparent consumption
Bibliographic record
Abstract
INTRODUCTION: Market research indicates an increasing interest in low- and no-alcohol drinks in Europe, but there is no systematic overview of their availability and consumption. In this article, we present data on the availability and apparent consumption of non-alcoholic beer in the European Union and the UK. METHODS: We use Sold production, exports and imports by PRODCOM list (NACE Rev. 2) dataset, available in Eurostat, to extract the available data on sold production, exports and imports of non-alcoholic beer in the EU-27 (total and country-level) and the UK between 2013 and 2019, and additionally calculate the apparent consumption. RESULTS: Between 2013 and 2019, the sold production volume in the EU increased from 0.59 to 1.38 billion litres, the value from 0.42 to 1.28 billion EUR and value per litre from 0.72 to 0.93 EUR/L. In 2019, the share of non-alcoholic beer represented 3.8% of all beer volume and 4.1% of all beer value produced. Five countries accounted for 80.8% of sold production volume: Germany, the Netherlands, Spain, Poland and Czechia. The Netherlands and Germany were the largest exporters, while importing was distributed more equally. Per capita, average apparent consumption (2017-2019) was highest in Czechia, followed by the Netherlands, Spain, Luxembourg and Germany. DISCUSSION AND CONCLUSIONS: Our results show the increasing availability of non-alcoholic beer in the EU-27, although overall changes seem to be driven by a small number of countries. More research is needed at the country-level on no- and low-alcohol consumption trends and drivers, and their impact on alcohol-related harm reduction.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".