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Performance and perception on front-of-package nutritional labeling models in Brazil
Luisete Moraes Bandeira1, Jéssica Pedroso2, Natacha Toral2
1Universidade de Brasília. Faculdade de Ciências da Saúde. Programa de Pós-Graduação em Saúde Coletiva. Asa Norte, Campus Universitário Darcy Ribeiro, Brasília, DF, Brasil.
Objective:
To evaluate the performance and perception of five models of front-of-package nutrition labeling (FOPNL) among Brazilian consumers.
Methods:
Cross-sectional study, which applied an online questionnaire to 2,400 individuals, allocated randomly into six study groups: a control group and five others exposed to FOPNL (octagon, triangle, circle, magnifier and traffic light), applied to nine products. We evaluated the understanding of nutritional content, the perception of healthiness, the purchase intention and the perception of Brazilian consumers on the models.
Results:
All FOPNL models increased the understanding of the nutritional content and reduced the perception of healthiness and purchase intention, when compared with the control group (41.3%). FOPNL warning models - octagon (62.4%), triangle (61.9%) and circle (61.8%) - performed significantly better than the traffic light (55.0%) regarding the understanding of the nutritional content. The performance of the magnifier (59.5%) was similar to the other four tested models, including the traffic light (55.0%), for understanding nutritional content. The individual analysis of the products suggests a better performance of warnings in relation to the magnifier and the traffic light for the perception of healthiness and purchase intention. Consumers were favorable to the presence of FOPNL, perceiving it as reliable to increase the understanding to nutritional information.
Conclusion:
FOPNL must be implemented on food labels in Brazil, considering that it increases the nutritional understanding, reduces the perception of healthiness and the purchase intention of products with critical nutrients. Warnings showed a better performance when compared with other models.
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