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Record W2130718671 · doi:10.1017/s1368980013002498

Nutritional quality of food items on fast-food ‘kids’ menus’: comparisons across countries and companies

2013· article· en· W2130718671 on OpenAlexafffundabout
Erin Hobin, Christine A. White, Ye Li, Maria Chiu, Mary O'Brien, David Hammond

Bibliographic record

VenuePublic Health Nutrition · 2013
Typearticle
Languageen
FieldMedicine
TopicConsumer Attitudes and Food Labeling
Canadian institutionsImpactUniversity of TorontoPublic Health OntarioUniversity of Waterloo
FundersCanadian Cancer Society Research InstituteCanadian Institutes of Health ResearchUniversity of Waterloo
KeywordsCalorieBusinessMultinational corporationQuality (philosophy)PopulationAdvertisingSaturated fatFood scienceMarketingEnvironmental healthMedicineBiology

Abstract

fetched live from OpenAlex

OBJECTIVE: To compare energy (calories), total and saturated fats, and Na levels for 'kids' menu' food items offered by four leading multinational fast-food chains across five countries. DESIGN: A content analysis was used to create a profile of the nutritional content of food items on kids' menus available for lunch and dinner in four leading fast-food chains in Australia, Canada, New Zealand, the UK and the USA. SETTING: Food items from kids' menus were included from four fast-food companies: Burger King, Kentucky Fried Chicken (KFC), McDonald's and Subway. These fast-food chains were selected because they are among the top ten largest multinational fast-food chains for sales in 2010, operate in high-income English-speaking countries, and have a specific section of their restaurant menus labelled 'kids' menus'. RESULTS: The results by country indicate that kids' menu foods contain less energy (fewer calories) in restaurants in the USA and lower Na in restaurants in the UK. The results across companies suggest that kids' menu foods offered at Subway restaurants are lower in total fat than food items offered at Burger King and KFC, and food items offered at KFC are lower in saturated fat than items offered at Burger King. CONCLUSIONS: Although the reasons for the variation in the nutritional quality of foods on kids' menus are not clear, it is likely that fast-food companies could substantially improve the nutritional quality of their kids' menu food products, translating to large gains for population health.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.368
Threshold uncertainty score0.751

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.110
GPT teacher head0.376
Teacher spread0.266 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations29
Published2013
Admission routes3
Has abstractyes

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