The impact of shelf tags with Nutri-Score on consumer purchases: a difference-in-difference analysis of a natural experiment in supermarkets of a major retailer in Belgium
Abstract Background Delhaize, a major Belgian retailer, started implementing electronic shelf labels (ESL) with Nutri-Score since May 2019. Nutri-Score rates the healthfulness of packaged foods with five colours/letters from red/E (least healthy) to green/A (most healthy). This study evaluated the i...
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oai:doaj.org-article:50d39d5d09f549788a4f765a03fc875c2021-11-21T12:42:47ZThe impact of shelf tags with Nutri-Score on consumer purchases: a difference-in-difference analysis of a natural experiment in supermarkets of a major retailer in Belgium10.1186/s12966-021-01207-71479-5868https://doaj.org/article/50d39d5d09f549788a4f765a03fc875c2021-11-01T00:00:00Zhttps://doi.org/10.1186/s12966-021-01207-7https://doaj.org/toc/1479-5868Abstract Background Delhaize, a major Belgian retailer, started implementing electronic shelf labels (ESL) with Nutri-Score since May 2019. Nutri-Score rates the healthfulness of packaged foods with five colours/letters from red/E (least healthy) to green/A (most healthy). This study evaluated the impact of ESL on consumer purchases, overall, and by food category. Methods For 43 intervention stores (implementing ESL in the period 27 May 2019–19 June 2019), a control store, from the same province and retailer-assigned cluster was matched. There were 14 unique control stores. By store, weekly non-food and food sales for 2018 and 2019 were received by Nutri-Score (A/B/C/D/E) and food category according to a retailer-assigned classification system. The primary outcomes were the proportion of food sales for Nutri-Score A,B,C,D,E. Difference-in-differences regression analysis was conducted to estimate the effect of the ESL intervention on proportion of overall food and food category sales for Nutri-Score A,B,C,D,E, using linear mixed models to account for clustering at store-level. We controlled for store characteristics (region, cluster, non-food sales) and week of the year. Analyses were weighted to re-balance discrepancy between the number of intervention and control stores. To account for multiple testing, a Bonferroni adjustment was applied. Results Comparing pre- and post-intervention periods, difference-in-differences for the proportion of Nutri-Score B and C product sales were more favourable in intervention than control stores (0.11 ± 0.04%, p = 0.007 and − 0.06 ± 0.03%, p = 0.026 respectively), while difference-in-differences for the proportion of Nutri-Score D product sales were less favourable in intervention than control stores (0.12 ± 0.04%, p = 0.002). For 17/58 food categories (representing 29% of total food sales) a positive impact [increase in healthier (Nutri-Score A, B) and/or decrease in less healthy (Nutri-Score D, E) food sales], and for 16/58 categories (representing 24% of total food sales) a negative impact was found. Positive impacts were found for vegetable, fruit and dairy products and confectionery. Negative impacts were found for bread and bakery products. Conclusion The impact of ESL on consumer purchases was mixed. Favourable difference-in-differences were found for Nutri-Score B and C products and unfavourable difference-in-differences for Nutri-Score D products. Shelf labeling on its own is unlikely to significantly influence consumer behaviours.Stefanie VandevijvereNicolas BergerBMCarticleFront-of-pack labelingElectronic shelf labelingNutri-scoreSupermarketsBelgiumNutritional diseases. Deficiency diseasesRC620-627Public aspects of medicineRA1-1270ENInternational Journal of Behavioral Nutrition and Physical Activity, Vol 18, Iss 1, Pp 1-20 (2021) |
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Front-of-pack labeling Electronic shelf labeling Nutri-score Supermarkets Belgium Nutritional diseases. Deficiency diseases RC620-627 Public aspects of medicine RA1-1270 |
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Front-of-pack labeling Electronic shelf labeling Nutri-score Supermarkets Belgium Nutritional diseases. Deficiency diseases RC620-627 Public aspects of medicine RA1-1270 Stefanie Vandevijvere Nicolas Berger The impact of shelf tags with Nutri-Score on consumer purchases: a difference-in-difference analysis of a natural experiment in supermarkets of a major retailer in Belgium |
description |
Abstract Background Delhaize, a major Belgian retailer, started implementing electronic shelf labels (ESL) with Nutri-Score since May 2019. Nutri-Score rates the healthfulness of packaged foods with five colours/letters from red/E (least healthy) to green/A (most healthy). This study evaluated the impact of ESL on consumer purchases, overall, and by food category. Methods For 43 intervention stores (implementing ESL in the period 27 May 2019–19 June 2019), a control store, from the same province and retailer-assigned cluster was matched. There were 14 unique control stores. By store, weekly non-food and food sales for 2018 and 2019 were received by Nutri-Score (A/B/C/D/E) and food category according to a retailer-assigned classification system. The primary outcomes were the proportion of food sales for Nutri-Score A,B,C,D,E. Difference-in-differences regression analysis was conducted to estimate the effect of the ESL intervention on proportion of overall food and food category sales for Nutri-Score A,B,C,D,E, using linear mixed models to account for clustering at store-level. We controlled for store characteristics (region, cluster, non-food sales) and week of the year. Analyses were weighted to re-balance discrepancy between the number of intervention and control stores. To account for multiple testing, a Bonferroni adjustment was applied. Results Comparing pre- and post-intervention periods, difference-in-differences for the proportion of Nutri-Score B and C product sales were more favourable in intervention than control stores (0.11 ± 0.04%, p = 0.007 and − 0.06 ± 0.03%, p = 0.026 respectively), while difference-in-differences for the proportion of Nutri-Score D product sales were less favourable in intervention than control stores (0.12 ± 0.04%, p = 0.002). For 17/58 food categories (representing 29% of total food sales) a positive impact [increase in healthier (Nutri-Score A, B) and/or decrease in less healthy (Nutri-Score D, E) food sales], and for 16/58 categories (representing 24% of total food sales) a negative impact was found. Positive impacts were found for vegetable, fruit and dairy products and confectionery. Negative impacts were found for bread and bakery products. Conclusion The impact of ESL on consumer purchases was mixed. Favourable difference-in-differences were found for Nutri-Score B and C products and unfavourable difference-in-differences for Nutri-Score D products. Shelf labeling on its own is unlikely to significantly influence consumer behaviours. |
format |
article |
author |
Stefanie Vandevijvere Nicolas Berger |
author_facet |
Stefanie Vandevijvere Nicolas Berger |
author_sort |
Stefanie Vandevijvere |
title |
The impact of shelf tags with Nutri-Score on consumer purchases: a difference-in-difference analysis of a natural experiment in supermarkets of a major retailer in Belgium |
title_short |
The impact of shelf tags with Nutri-Score on consumer purchases: a difference-in-difference analysis of a natural experiment in supermarkets of a major retailer in Belgium |
title_full |
The impact of shelf tags with Nutri-Score on consumer purchases: a difference-in-difference analysis of a natural experiment in supermarkets of a major retailer in Belgium |
title_fullStr |
The impact of shelf tags with Nutri-Score on consumer purchases: a difference-in-difference analysis of a natural experiment in supermarkets of a major retailer in Belgium |
title_full_unstemmed |
The impact of shelf tags with Nutri-Score on consumer purchases: a difference-in-difference analysis of a natural experiment in supermarkets of a major retailer in Belgium |
title_sort |
impact of shelf tags with nutri-score on consumer purchases: a difference-in-difference analysis of a natural experiment in supermarkets of a major retailer in belgium |
publisher |
BMC |
publishDate |
2021 |
url |
https://doaj.org/article/50d39d5d09f549788a4f765a03fc875c |
work_keys_str_mv |
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