Can an On-Shelf Nutrition Labelling System Improve the Nutritional Quality of Food Purchases in Supermarkets?

The U.S. food system is rapidly changing, including the growth of mass merchandisers and dollar stores, which may impact the quality of packaged food purchases (PFPs). Furthermore, diet-related disparities exist by socioeconomic status (SES) and rural residence. We use data from the 2010–2018 Nielsen Homescan Panel to describe the nutritional profiles of PFPs by store type and to assess whether these vary by household urbanicity and SES. Store types include grocery stores, mass merchandisers, club stores, online shopping, dollar stores, and convenience/drug stores. Food and beverage groups contributing the most calories at each store type are estimated using survey-weighted means, while the associations of urbanicity and SES with nutritional quality are estimated using multivariate regression. We find that households that are customers at particular store types purchase the same quality of food regardless of urbanicity or SES. However, we find differences in the quality of foods between store types and that the quantity of calories purchased at each store type varies according to household urbanicity and SES. Rural shoppers tend to shop more at mass merchandisers and dollar stores with less healthful PFPs. We discuss implications for the types of store interventions most relevant for improving the quality of PFPs.

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Objective understanding of the front-of-pack nutrition label Nutri-Score by European consumers

European Journal of Public Health ◽

10.1093/eurpub/ckaa165.902 ◽

2020 ◽

Vol 30 (Supplement_5) ◽

Author(s):

M Egnell ◽

Z Talati ◽

P Galan ◽

V Andreeva ◽

S Vandevijvere ◽

...

Keyword(s):

Nutritional Quality ◽

Food Choices ◽

Nutrition Labels ◽

Logistic Regression Models ◽

Traffic Lights ◽

Nutrition Labelling ◽

Food Packages ◽

Objective Understanding ◽

Quality Of Food

Abstract Background The effectiveness of Front-of-Pack nutrition Labels (FoPL) may be influenced by national context. In light of the ongoing efforts to harmonize nutrition labelling across Europe, the study aimed to compare the effectiveness of five FoPLs (Health Star Rating system [HSR], Multiple Traffic Lights [MTL], Nutri-Score, Reference Intakes [RIs], Warning symbol) in 12 European consumers. Methods In 2018-2019, for three food categories, approximately 1,000 participants per country were asked to select which food they would prefer to purchase between three products with distinct nutritional quality, and then to rank the products nutritional quality. Participants completed these tasks first with no FoPL and then, after randomization to one of the five FoPLs, with a FoPL on food packages. Associations between FoPLs and change in (i) nutritional quality of food choices, and (ii) ability to correctly rank the products nutritional quality were assessed with multivariable logistic regression models. Results Compared with the RIs, the Nutri-Score (OR = 3·23[2·75-3·81]; p < 0.0001), followed by the MTL (OR = 1·68[1·42-1·98]; p < 0.0001), was the most effective FoPL in helping participants identify the foods nutritional quality, overall and in each of the 12 countries. Differences between FoPLs regarding food choice modifications were smaller, but the effect of the Nutri-Score was slightly higher in eliciting healthier food choices overall compared with the RIs, followed by the Warning symbol, MTL and HSR. Conclusions These findings from an online experiment provide insights on the Nutri-Score's effectiveness in multiple European countries in the context of FoPL harmonization in Europe. Key messages The comparison of the effectiveness of front-of-pack labels highlighted the relative performance of various types of labels, the Nutri-Score showing a higher performance than other schemes. The higher performance of the Nutri-Score was identified for objective understanding and to a lesser extent food choices.

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Corrigendum for Perignon et al. Co-construction and evaluation of a prevention program for improving the nutritional quality of food purchases at no additional cost in a socio-economically disadvantaged population. Curr Dev Nutr 2017;1: e001107

Current Developments in Nutrition ◽

10.1093/cdn/nzy023 ◽

2018 ◽

Vol 2 (7) ◽

Keyword(s):

Prevention Program ◽

Economically Disadvantaged ◽

Nutritional Quality ◽

Additional Cost ◽

Food Purchases ◽

Disadvantaged Population ◽

Quality Of Food

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Household food security: Perceptions, behavior and nutritional quality of food purchases

Journal of Economic Psychology ◽

10.1016/j.joep.2016.05.003 ◽

2016 ◽

Vol 55 ◽

pp. 139-148 ◽

Cited By ~ 2

Author(s):

Andrés Silva ◽

Juan Carlos Caro ◽

David Magaña-Lemus

Keyword(s):

Food Security ◽

Nutritional Quality ◽

Household Food Security ◽

Food Purchases ◽

Household Food ◽

Quality Of Food

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Nutritional quality of retail food purchases is not associated with participation in the Supplemental Nutrition Assistance Program for nutrition-oriented households

PLoS ONE ◽

10.1371/journal.pone.0240263 ◽

2020 ◽

Vol 15 (12) ◽

pp. e0240263

Author(s):

Yu Chen ◽

Biing‐Hwan Lin ◽

Lisa Mancino ◽

Michele Ver Ploeg ◽

Chen Zhen

Keyword(s):

Low Income ◽

Nutritional Quality ◽

Supplemental Nutrition Assistance Program ◽

Healthy Foods ◽

Supplemental Nutrition ◽

Assistance Program ◽

Food Purchases ◽

Quality Of Food ◽

Nutrition Assistance

The Supplemental Nutrition Assistance Program (SNAP) provides millions of low-income Americans food benefits and other forms of nutrition assistance. Evidence indicates that SNAP reduces food insecurity. However, there is a concern that the food benefit may increase the demand for less healthy foods more than healthier foods, thereby reducing the overall nutritional quality of the participant’s food basket. This paper aims to examine the association of SNAP participation with the nutritional quality of food-at-home purchases of low-income households and to investigate the potential heterogeneity among consumers with different levels of nutrition attitude. This analysis used food purchase data from the USDA National Household Food Acquisition and Purchase Survey (FoodAPS). Our study sample included 2,218 low-income households, of which 1,184 are SNAP participants, and 1,034 are income-eligible nonparticipants. Multivariate regressions were performed to explore the SNAP-nutritional quality association. A household’s nutrition attitude was measured using its response to a question on whether the household searched for nutrition information online in the last 2 months. Households that affirmed they had an online nutrition search were treated as nutrition-oriented households (21.2% of the low-income sample), and households that did not were considered less nutrition-oriented households (78.8%). For robustness, we also created an alternative nutrition attitude measure based on reported use of the nutrition facts label. We found that among less nutrition-oriented households, SNAP participants had a statistically significant 0.097 points (p = 0.018) lower Guiding Stars rating than low-income nonparticipants. However, there was no significant SNAP-nutritional quality association among nutrition-oriented households. In conclusion, SNAP participation was associated with lower nutritional quality of food purchases among less nutrition-oriented households, but not among nutrition-oriented households. The results suggest that the intended nutritional benefits of restrictions on purchases of healthy foods may not reach the subgroup of nutrition-oriented SNAP participants.

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