The nutritional content of supermarket beverages: a cross-sectional analysis of New Zealand, Australia, Canada and the UK
Bibliographic record
Abstract
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 (9 %, P <0·001). Differences in energy, carbohydrate and sugar content were observed between countries and within categories, with UK products generally having the lowest energy and sugar content. Up to half of all products across categories/countries exceeded the US Food and Drug Administration’s reference single serving sizes, with fruit juices contributing the greatest number. Between 47 and 83 % of beverages in the different countries were eligible for sugar taxation, the UK having the lowest proportion of products in both the low tax (5–8 % sugar) and high tax (>8 % sugar) categories. 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 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 | 0.001 | 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".