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Record W2946168817 · doi:10.1186/s12966-019-0799-0

Taxes and front-of-package labels improve the healthiness of beverage and snack purchases: a randomized experimental marketplace

2019· article· en· W2946168817 on OpenAlex
Rachel B. Acton, Amanda Jones, Sharon I. Kirkpatrick, Christina A. Roberto, David Hammond

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInternational Journal of Behavioral Nutrition and Physical Activity · 2019
Typearticle
Languageen
FieldMedicine
TopicConsumer Attitudes and Food Labeling
Canadian institutionsUniversity of Waterloo
FundersOntario Ministry of Research and InnovationCanadian Institutes of Health ResearchUniversity of WaterlooPublic Health AgencyPublic Health Agency of Canada
KeywordsNutrition facts labelPurchasingCalorieSugarSnack foodLabellingAdvertisingAdded sugarFood scienceEnvironmental healthMedicineBusinessMarketingPsychology

Abstract

fetched live from OpenAlex

BACKGROUND: Sugar taxes and front-of-package (FOP) nutrition labelling systems are strategies to address diet-related non-communicable diseases. However, there is relatively little experimental data on how these strategies influence consumer behavior and how they may interact. This study examined the relative impact of different sugar taxes and FOP labelling systems on beverage and snack food purchases. METHODS: A total of 3584 Canadians 13 years and older participated in an experimental marketplace study using a 5 (FOP label condition) × 8 (tax condition) between-within group experiment. Participants received $5 and were presented with images of 20 beverages and 20 snack foods available for purchase. Participants were randomized to one of five FOP label conditions (no label; 'high in' warning; multiple traffic light; health star rating; nutrition grade) and completed eight within-subject purchasing tasks with different taxation conditions (beverages: no tax, 20% tax on sugar-sweetened beverages (SSBs), 20% tax on sugary drinks, tiered tax on SSBs, tiered tax on sugary drinks; snack foods: no tax, 20% tax on high-sugar foods, tiered tax on high-sugar foods). Upon conclusion, one of eight selections was randomly chosen for purchase, and participants received the product and any change. RESULTS: Compared to those who saw no FOP label, participants who viewed the 'high in' symbol purchased less sugar (- 2.5 g), saturated fat (- 0.09 g), and calories (- 12.6 kcal) in the beverage purchasing tasks, and less sodium (- 13.5 mg) and calories (- 8.9 kcal) in the food tasks. All taxes resulted in substantial reductions in mean sugars (- 1.4 to - 4.7 g) and calories (- 5.3 to - 19.8 kcal) purchased, and in some cases, reductions in sodium (- 2.5 to - 6.6 mg) and saturated fat (- 0.03 to - 0.08 g). Taxes that included 100% fruit juice ('sugary drink' taxes) produced greater reductions in sugars and calories than those that did not. CONCLUSIONS: This study expands the evidence indicating the effectiveness of sugar taxation and FOP labelling strategies in promoting healthy food and beverage choices. The results emphasize the importance of applying taxes to 100% fruit juice to maximize policy impact, and suggest that nutrient-specific FOP 'high in' labels may be more effective than other common labelling systems at reducing consumption of targeted nutrients.

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.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.407
Threshold uncertainty score0.241

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.019
GPT teacher head0.345
Teacher spread0.325 · 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