The nutritional content of supermarket beverages: a cross-sectional analysis of New Zealand, Australia, Canada and the UK
Bibliographic record
Abstract
OBJECTIVE: To compare the nutritional content, serving size and taxation potential of supermarket beverages from four different Western countries. DESIGN: Cross-sectional analysis. Multivariate regression analysis and χ 2 comparisons were used to detect differences between countries. SETTING: Supermarkets in New Zealand (NZ), Australia, Canada and the UK. SUBJECTS: Supermarket beverages in the following categories: fruit juices, fruit-based drinks, carbonated soda, waters and sports/energy drinks. RESULTS: A total of 4157 products were analysed, including 749 from NZ, 1738 from Australia, 740 from Canada and 930 from the UK. NZ had the highest percentage of beverages with sugar added to them (52 %), while the UK had the lowest (39 %, P<0.001). CONCLUSIONS: There is substantial difference between countries in the mean energy, serving size and proportion of products eligible for fiscal sugar taxation. Current self-regulatory approaches used in these countries may not be effective to reduce the availability, marketing and consumption of sugar-sweetened beverages and subsequent intake of free sugars.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".