Nutrition labelling, marketing techniques, nutrition claims and health claims on chip and biscuit packages from sixteen countries
Bibliographic record
Abstract
OBJECTIVE: Food packages were objectively assessed to explore differences in nutrition labelling, selected promotional marketing techniques and health and nutrition claims between countries, in comparison to national regulations. DESIGN: Cross-sectional. SETTING: Chip and sweet biscuit packages were collected from sixteen countries at different levels of economic development in the EPOCH (Environmental Profile of a Community's Health) study between 2008 and 2010. SUBJECTS: Seven hundred and thirty-seven food packages were systematically evaluated for nutrition labelling, selected promotional marketing techniques relevant to nutrition and health, and health and nutrition claims. We compared pack labelling in countries with labelling regulations, with voluntary regulations and no regulations. RESULTS: Overall 86 % of the packages had nutrition labels, 30 % had health or nutrition claims and 87 % displayed selected marketing techniques. On average, each package displayed two marketing techniques and one health or nutrition claim. In countries with mandatory nutrition labelling a greater proportion of packages displayed nutrition labels, had more of the seven required nutrients present, more total nutrients listed and higher readability compared with those with voluntary or no regulations. Countries with no health or nutrition claim regulations had fewer claims per package compared with countries with regulations. CONCLUSIONS: Nutrition label regulations were associated with increased prevalence and quality of nutrition labels. Health and nutrition claim regulations were unexpectedly associated with increased use of claims, suggesting that current regulations may not have the desired effect of protecting consumers. Of concern, lack of regulation was associated with increased promotional marketing techniques directed at children and misleadingly promoting broad concepts of health.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".