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Record W2981773172 · doi:10.1186/s12966-019-0854-x

Evaluation of a voluntary nutritional information program versus calorie labelling on menus in Canadian restaurants: a quasi-experimental study design

2019· article· en· W2981773172 on OpenAlexaffabout
Lana Vanderlee, Christine M. White, David Hammond

Bibliographic record

VenueInternational Journal of Behavioral Nutrition and Physical Activity · 2019
Typearticle
Languageen
FieldMedicine
TopicConsumer Attitudes and Food Labeling
Canadian institutionsUniversity of Waterloo
FundersNational Cancer InstituteNational Institutes of Health
KeywordsCalorieNoticeClinical nutritionNutrition informationNutritional informationNutrition EducationNutrition LabelingServing sizeEnvironmental healthMedicineTurnoverSupplemental Nutrition Assistance ProgramNutrition facts labelLabellingGerontologyPsychologyFood scienceGeographyAgricultureFood securityFood insecurity

Abstract

fetched live from OpenAlex

BACKGROUND: A significant proportion of the Canadian diet comes from foods purchased in restaurant settings. In an effort to promote healthy eating, the province of British Columbia (BC) implemented the Informed Dining Program (IDP), a voluntary, industry supported information program in 2012, while the province of Ontario implemented mandatory calorie labelling on menus in 2017. The study examined differences in awareness and the self-reported influence of nutrition information on food choices in restaurants with voluntary nutrition information, calorie labelling on menus, and no nutrition information program. METHODS: Exit surveys were conducted outside of nine chain restaurants in Toronto, Ontario and Vancouver, British Columbia (Canada) in 2012, 2015, and 2017 with varying nutrition information programs implemented. Logistic regression analyses compared self-reported noticing and influence of nutrition information in restaurants with: 1) the IDP which provided nutrition information upon request, 2) calorie labelling on menus, and 3) control restaurants with no specific nutrition information program in place, adjusted for year, city and socio-demographic characteristics. Awareness and knowledge of the IDP were also examined. RESULTS: There were no significant differences in noticing and self-reported influence of nutrition information on food choices between restaurants with the IDP and restaurants with no program. Participants were more likely to notice nutrition information in restaurants when calorie information was provided on menus (57%) compared to in restaurants with the IDP (22%, AOR = 6.20, 95%CI 3.51-10.94, p < 0.001) or restaurants with no nutrition information program (20%, AOR = 7.44, 95%CI 4.21-13.13, p < 0.001). Participants in restaurants with menu labelling were also more likely to report that nutrition information influenced their food purchase (38%) compared to restaurants with the IDP (12%, AOR = 4.43, 95%CI 2.36-8.30, p < 0.001) and restaurants with no nutrition information program (12%, AOR = 5.29, 95%CI 2.81-9.95, p < 0.001). Fewer than 1 in 5 participants who visited an IDP restaurant had heard of the IDP across all data collection years in both cities. CONCLUSIONS: There was no evidence that voluntary programs which provide nutrition information upon request were effective. Providing calorie information on menus increased the likelihood that consumers noticed and that their food choices were influenced by nutrition information in restaurant settings.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: Non-randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.603
Threshold uncertainty score0.790

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.001
Science and technology studies0.0050.003
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.085
GPT teacher head0.409
Teacher spread0.324 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
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

Citations13
Published2019
Admission routes2
Has abstractyes

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