Can nutritional information modify purchase of ultra-processed products? Results from a simulated online shopping experiment

Leandro Machín, Alejandra Arrúa, Ana Giménez, María Rosa Curutchet, Joseline Martínez, Gastón Ares, Leandro Machín, Alejandra Arrúa, Ana Giménez, María Rosa Curutchet, Joseline Martínez, Gastón Ares

Abstract

Objective: The aim of the present work was to evaluate the influence of two front-of-pack nutrition information schemes (traffic-light system and Chilean warning system) on consumer purchase of ultra-processed foods in a simulated online grocery store.

Design: Following a between-subjects design, participants completed a simulated weekly food purchase in an online grocery store under one of three experimental conditions: (i) a control condition with no nutrition information, (ii) a traffic-light system and (iii) the Chilean warning system. Information about energy (calories), sugar, saturated fats and salt content was included in the nutrition information schemes.

Setting: Participants were recruited from a consumer database and a Facebook advertisement.

Subjects: People from Montevideo (Uruguay), aged 18-77 years (n 437; 75 % female), participated in the study. All participants were in charge of food purchase in the household, at least occasionally.

Results: No significant differences between experimental conditions were found in the mean share of ultra-processed foods purchased by participants, both in terms of number of products and expenditure, or in the mean energy, sugar, saturated fat and salt content of the purchased items. However, the Chilean warning system decreased intended purchase of sweets and desserts.

Conclusions: Results from this online simulation provided little evidence to suggest that the traffic-light system or the Chilean warning system in isolation could be effective in reducing purchase of ultra-processed foods or improving the nutritional composition of the purchased products.

Keywords: Nutritional information; Traffic-light system; Ultra-processed foods; Warning system.

Figures

Fig. 1
Fig. 1
Screenshot of the online grocery store used in the simulated shopping experiment, showing examples of products as seen by the participants who completed the task without nutrition information. Food categories are shown on the left and some of the products included in one of the categories (‘Frozen foods/ready-to-eat meals’) are shown on the right using the name of the product, a picture and its price
Fig. 2
Fig. 2
Example of how nutrition information was presented on the products using the traffic-light system (a) and the Chilean warning system (b)
Fig. 3
Fig. 3
Mean percentage of products high in key target nutrients (, high in energy (calories); , high in sugar; , high in saturated fat; , high in salt) for participants who completed the task in the control condition (without nutrition information) and with two front-of-pack nutrition information schemes (traffic-light system and Chilean warning system). Vertical bars correspond to Tukey’s honestly significant differences (P=0·05)

References

    1. World Health Organization (2014) Global Status on Non-Communicable Diseases 2014. Geneva: World Health Organization.
    1. Story M, Kaphingst KM, Robinson-O’Brien R et al.. (2008) Creating healthy food and eating environments: policy and environmental approaches. Annu Rev Public Health 29, 253–272.
    1. Zobel EH, Wansen TW, Rossing P et al.. (2016) Global changes in food supply and the obesity epidemic. Curr Obes Rep 5, 449–455.
    1. Popkin BM, Adair LS & Ng SW (2012) Global nutrition transition and the pandemic of obesity in developing countries. Nutr Rev 70, 3–21.
    1. Juul F & Hemmingsson E (2015) Trends in consumption of ultra-processed foods and obesity in Sweden between 1960 and 2010. Public Health Nutr 18, 3096–3107.
    1. Rauber F, Campagnolo PD, Hoffman DJ et al.. (2015) Consumption of ultraprocessed food products and its effects on children’s lipid profiles: a longitudinal study. Nutr Metab Cardiovasc Dis 25, 116–122.
    1. Moubarac J-C, Martins AP, Claro RM et al.. (2013) Consumption of ultra-processed foods and likely impact on human health. Evidence from Canada. Public Health Nutr 16, 2240–2248.
    1. Louzada ML, Baraldi LG, Steele EM et al.. (2015) Consumption of ultra-processed foods and obesity in Brazilian adolescents and adults. Prev Med 81, 9–15.
    1. Tavares LF, Fonseca SC, Garcia Rosa ML et al.. (2012) Relationship between ultra-processed foods and metabolic syndrome in adolescents from a Brazilian Family Doctor Program. Public Health Nutr 15, 82–87.
    1. Monteiro CA, Cannon G, Levy R et al.. (2016) NOVA. The star shines bright. World Nutr 7, 28–38.
    1. Martínez Steele E, Baraldi LG, Louzada ML et al.. (2016) Ultra-processed foods and added sugars in the US diet: evidence from a nationally representative cross-sectional study. BMJ Open 6, e009892.
    1. Luiten C, Steenhuis IHM, Eyles H et al.. (2016) Ultra-processed foods have the worst nutrient profile, yet they are the most available packaged products in a sample of New Zealand supermarkets. Public Health Nutr 19, 530–538.
    1. Pan American Health Organization (2016) Pan American Health Organization Nutrient Profile Model. Washington, DC: PAHO.
    1. Giménez A, de Saldamando L, Curutchet MR et al.. (2016) Package design and nutritional profile of foods targeted at children available in supermarkets in Montevideo, Uruguay. Cad Saude Publica (In the Press).
    1. Colby SE, Johnson L, Scheett A et al.. (2010) Nutrition marketing of food labels. J Nutr Educ Behav 42, 92–98.
    1. Schermel A, Emrich TE, Arcand J et al.. (2013) Nutrition marketing on processed food packages in Canada: 2010 Food Label Information Program. Appl Physiol Nutr Metab 38, 666–672.
    1. Monteiro CA, Moubarac JC, Cannon G et al.. (2013) Ultraprocessed products are becoming dominant in the global food system. Obes Rev 14, 21–28.
    1. Ludwig DS & Nestle M (2008) Can the food industry play a constructive role in the obesity epidemic? JAMA 300, 1808e–1811e.
    1. Pan American Health Organization (2015) Ultra-Processed Food and Drink Products in Latin America: Trends, Impact on Obesity, Policy Implications. Washington, DC: PAHO.
    1. Cowburn G & Stockley L (2005) Consumer understanding and use of nutrition labelling: a systematic review. Public Health Nutr 8, 21–28.
    1. Grunert KG & Wills JM (2007) A review of European research on consumer response to nutrition information on food labels. J Public Health 15, 385–399.
    1. Sharf M, Sela R, Zentner G et al.. (2012) Figuring out food labels. Young adults’ understanding of nutrition information presented on food labels is inadequate. Appetite 58, 531–534.
    1. Hawley KL, Roberto CA, Bragg MA et al.. (2013) The science on front-of-package food label. Public Health Nutr 16, 430–439.
    1. Feunekes GIJ, Gortemaker IA, Willems AA et al.. (2008) Front-of-pack nutrition labelling: testing effectiveness of different nutrition labelling formats front-of-pack in four European countries. Appetite 50, 57–70.
    1. Ares G, Giménez A, Bruzzone F et al.. (2012) Attentional capture and understanding of nutrition labelling: a study based on response times. Int J Food Sci Nutr 63, 679–688.
    1. Jones G & Richardson M (2007) An objective examination of consumer perception of nutrition information based on healthiness ratings and eye movements. Public Health Nutr 10, 238–244.
    1. Hodgkins C, Barnett J, Wasowicz-Kirylo G et al.. (2012) Understanding how consumers categorise nutritional labels: a consumer derived typology for front-of-pack nutrition labelling. Appetite 59, 806–817.
    1. Roberto CA, Shivaram M, Martinez O et al.. (2012) The Smart Choices front-of-package nutrition label. Influence on perceptions and intake of cereal. Appetite 58, 651–657.
    1. Kelly B, Hughes C, Chapman K et al.. (2009) Consumer testing of the acceptability and effectiveness of front-of-pack food labelling systems for the Australian grocery market. Health Promot Int 24, 120–129.
    1. Borgmeier I & Westenhoefer J (2009) Impact of different food label formats on healthiness evaluation and food choice of consumers. A randomised-controlled study. BMC Public Health 9, 184.
    1. Antúnez L, Giménez A, Maiche A et al.. (2015) Influence of interpretation aids on attentional capture, visual processing, and understanding of front-of-package nutrition labels. J Nutr Educ Behav 47, 292–299.
    1. Aschemann-Witzel J, Grunert KG, van Trijp HCM et al.. (2013) Effects of nutrition label format and product assortment on the healthfulness of food choice. Appetite 71, 63–74.
    1. Gorton D, Ni Mhurchu C, Chen M et al.. (2009) Nutrition labels. A survey of use, understanding and preferences among ethnically diverse shoppers in New Zealand. Public Health Nutr 12, 1359–1365.
    1. Food Standards Agency (2007) Front-of-Pack Traffic Light Signpost Labelling. Technical Guidance. Issue 2. London: FSA.
    1. Genschow O, Reutner L & Wänke M (2012) The color red reduces snack food and soft drink intake. Appetite 58, 699–702.
    1. Hieke S & Wills JM (2012) Nutrition labelling. Is it effective in encouraging healthy eating? CAB Rev 7, 1–7.
    1. Sacks G, Rayner M & Swinburn B (2009) Impact of front-of-pack ‘traffic-light’ nutrition labelling on consumer food purchases in the UK. Health Promot Int 24, 344–352.
    1. Sacks G, Tikellis K, Millar L et al.. (2011) Impact of ‘traffic-light’ nutrition information on online food purchases in Australia. Aust N Z J Public Health 35, 122–126.
    1. Dodds P, Wolfenden L, Chapman K et al.. (2014) The effect of energy and traffic light labelling on parent and child fast food selection: a randomised controlled trial. Appetite 73, 23–30.
    1. Ni Mhurchu C, Volkova E, Jiang Y et al.. (2017) Effects of interpretive nutrition labels on consumer food purchases: the Starlight randomized controlled trial. Am J Clin Nutr 105, 695–704.
    1. Corvalán C, Reyes M, Garmendia ML et al.. (2013) Structural responses to the obesity and non-communicable diseases epidemic: the Chilean law of food labelling and advertising. Obes Rev 14, 79–87.
    1. Ministerio de Salud (2015) Decreto número 13, de 2015. Santiago: Ministerio de Salud.
    1. Bove MI & Cerruti F (2008) Los alimentos y bebidas en los hogares: ¿Un factor de protección o de riesgo para la salud y el bienestar de los uruguayos? Encuesta nacional de gastos e ingresos de los hogares 2005–2006. Montevideo: Instituto Nacional de Estadística.
    1. Muller L & Ruffieux B (2012) Modification des achats en réponse à l’apposition de différents logos d’évaluation nutritionnelle sur la face avant des emballages. Cah Nutr Diet 47, 171–182.
    1. Poder Ejecutivo (2006) Decreto 117/006. Montevideo: IMPO.
    1. R Core Team (2014) R: A Language and Environment for Statistical Computing. Vienna: R Foundation for Statistical Computing.
    1. Köster EP (2003) The psychology of food choice. Some often encountered fallacies. Food Qual Prefer 14, 359–373.
    1. Ares G, Machín L, Girona A et al.. (2016) Comparison of motives underlying food choice and barriers to healthy eating between low and medium income consumers in a Uruguay. Cad Saude Publica (In the Press).
    1. Satia JA, Galanko JA & Neuhouser ML (2005) Food nutrition label use is associated with demographic, behavioral, and psychosocial factors and dietary intake among African Americans in North Carolina. J Am Diet Assoc 105, 392–402.
    1. Neuhouser ML, Kristal AR & Patterson RE (1999) Use of food nutrition labels is associated with lower fat intake. J Am Diet Assoc 99, 45–53.
    1. Kreuter MW, Brennan LK, Scharff DP et al.. (1997) Do nutrition label readers eat healthier diets? Behavioral correlates of adults’ use of food labels. Am J Prev Med 13, 277–283.
    1. Capacci S, Mazzocchi M, Shankar B et al.. (2012) Policies to promote healthy eating in Europe. A structured review of instruments and their effectiveness. Nutr Rev 70, 188–200.

Source: PubMed

3
Abonnere