Evaluating the influence of traffic light labels on consumer sugar sweetened beverage choices using a discrete choice experiment in Sri Lanka
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Résumé
Fostering healthy eating has gained momentum as the link between poor diets and the rise in noncommunicable diseases (NCDs) has become more widely recognised. The current evidence suggests that food labels may help consumers make informed decisions and avoid unhealthy eating practices. However, available research mostly evaluates the impact of food labels on consumption habits or the effectiveness of various food label types. Consumers consider several factors when purchasing, including food labels, the kind of food, price, and nutritional value. Furthermore, a sizable unofficial food market may lessen exposure to packaged foods with food labels, thereby decreasing the value of food labels. Consequently, while proposing food labelling regulations, it is essential to consider the characteristics of the retail sector as well as customer behaviour. Addressing the gaps in previous literature, we examine the effectiveness of food labels on consumer choices based on various product attributes such as beverage type and price, as well as the food labels. Specifically, the study focuses on the efficacy of traffic light labels (TLLs) on sugar-sweetened beverages (SSBs) in Sri Lanka, where the regulation of TLLs on SSBs was introduced in 2016. We also assess the efficacy of food labels in informing consumers from different backgrounds. In this study, we evaluated the impact of TLLs on the consumption behaviour of SSBs in the presence of other product features using a Discrete Choice Experiment (DCE) model. We collected data through a choice experiment that assesses consumer choice of beverages in the presence of three product categories: beverage type, TLL, and price. The survey involved around 2,500 consumers across 14 districts, representing both urban and rural areas and all provinces of Sri Lanka. The data is analysed using a mixed logit model. We used the Household Income and Expenditure Survey (HIES) and primary consumer survey data to assess the exposure to products containing TLLs across different socioeconomic groups, applying the quintile distribution. Consumers base their beverage choices on a combination of product attributes, notably price, beverage type, and TLLs, assessing these both independently and jointly. The TLL regulation on SSBs significantly influences the selection of low-sugar SSBs. However, this influence considerably varies by socioeconomic group. Low-income groups are not very concerned about the TLL when making beverage choices. Product attributes, such as price and beverage type, also significantly impact beverage choices. While price sensitivity is evident across all consumer groups, it is notably higher among low-income consumers compared to their middle- and high-income counterparts. Furthermore, limited coverage of the SSB regulations disproportionately negatively affects economically disadvantaged groups, as around 75% of sweetened beverages fall outside the regulatory framework. Healthy consumer choices can be effectively influenced by the TLL system on SSBs. However, the acceptance of nutritional labelling is significantly impacted because its effectiveness differs among customers’ socioeconomic backgrounds. For various reasons, consumers from lower socioeconomic backgrounds are less influenced by TLL codes when it comes to their beverage preferences. The TLL system has little effect on those from low socioeconomic backgrounds because it does not cover the types of beverages that they typically drink. Furthermore, even if they are, their comprehension of TLL is limited. Finally, consumers from lower socioeconomic backgrounds are less affected by TLLs when making purchasing decisions, regardless of their awareness of the TLL system. This is partly because such consumers are more price-sensitive. This emphasises consumer awareness of TLL codes and making healthy beverage options affordable.
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Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
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Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
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