Consumers’ Response to an On‐Shelf Nutrition Labelling System in Supermarkets: Evidence to Inform Policy and Practice
Bibliographic record
Abstract
Policy Points: On-shelf nutrition labelling systems in supermarkets, such as the Guiding Stars system, are intended to provide consumers with simple, standardized nutrition information to support more informed and healthier food choices. Policies that support the provision of simplified nutrition labelling systems may encourage consumers to make positive shifts in food-purchasing behaviors. The shifts in consumer food-purchasing patterns observed in our study after the introduction of the Guiding Stars system in supermarkets translated into measurable nutritional benefits, including more items purchased with slightly less trans fat and sugar and more fiber and omega-3 fatty acids. This study is one of the first to report the positive impact of an on-shelf nutrition labelling system on supermarket sales and revenues-key information that was specifically requested by the US National Academies, as such labelling interventions may be more sustainable if they lead to higher revenues. CONTEXT: Providing a nutrition rating system on the front of food packages or on retail shelf tags has been proposed as a policy strategy for supporting healthier food choices. Guiding Stars is an on-shelf nutrition labelling system that scores foods in a supermarket based on nutritional quality; scores are then translated into ratings of 0 to 3 stars. It is consistent with evidence-informed recommendations for well-designed labels, except for not labelling 0-star products. The largest supermarket retailer in Canada rolled out the Guiding Stars system in supermarkets across Ontario, Canada. The aim of our study was to examine the extent to which consumers respond to an on-shelf nutrition labelling system in supermarkets to inform current and future nutrition labelling policies and practices. METHODS: Capitalizing on a natural experiment, we conducted a quasi-experimental study across 3 supermarket banners (or "chains") in Ontario, one of which implemented the Guiding Stars system in 2012. We used aggregated supermarket transaction data to test the effect of Guiding Stars on the nutritional quality of food purchases in intervention supermarkets relative to control supermarkets. We also conducted exit surveys among 783 randomly selected shoppers from intervention and control supermarkets to assess consumer awareness, understanding, trust, and self-reported use of the labelling system. FINDINGS: Relative to control supermarkets, shoppers in intervention supermarkets made small but significant shifts toward purchasing foods with higher nutritional ratings; however, shifts varied in direction and magnitude across food categories. These shifts translated into foods being purchased with slightly less trans fat and sugar and more fiber and omega-3 fatty acids. We also found increases in the number of products per transaction, price per product purchased, and total revenues. Results of the exit surveys indicate a modest proportion of consumers were aware of, understood, and trusted Guiding Stars in intervention supermarkets, and a small proportion of consumers reported using this system when making purchasing decisions. However, 47% of shoppers exposed to Guiding Stars were confused when asked to interpret the meaning of a 0-star product that does not display a rating on the shelf tag. CONCLUSIONS: This study demonstrates support for policies promoting on-shelf nutrition labels designed according to evidence-informed principles, but policymakers should move forward with caution when investing in such systems until research has confirmed optimal label design, clarified the mechanisms through which dietary intake is improved, and assessed associations with nutrition-related health outcomes.
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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 | 0.040 | 0.163 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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".