RESUMEN
OBJECTIVE: To assess how mothers classify foods and how their eating practices interact with these classifications, with special attention to meanings and uses given to ultra-processed foods. DESIGN: Qualitative research with in-depth interviews and pile sorts. SETTING: Urban Brazilian Amazon. PARTICIPANTS: A sample of 34 mothers were selected through theoretical sampling. ANALYSIS: Content analysis for in-depth interviews and multidimensional scaling and cluster analysis for pile sorts. PHENOMENON OF INTEREST: Food classification. RESULTS: Classifications were based on context (ie, a time or a situation in which the food is eaten) and foods' healthiness. Five food groupings based on mothers' classifications were defined: (1) main meal foods, (2) fruits and fruit juices, (3) convenient foods, (4) leisure foods, and (5) canned sardines. Ultra-processed foods were classified differently from non-ultra-processed foods and considered unhealthy, consumed on special occasions or when there was no time or desire to cook. CONCLUSIONS AND IMPLICATIONS: Results highlight the potential of incorporating context-based categories and personal experiences to guide nutrition interventions and the potential of pile sorts to tailor messages to target populations.
Asunto(s)
Conducta Alimentaria , Madres , Brasil , Dieta , Comida Rápida , Femenino , Humanos , ComidasRESUMEN
The aim of this study is to have an exploratory insight on how a sample of Brazilian adults classify food, attempting to identify the main factors involved in this process, and to compare these classifications to the NOVA food classification of the 2014 Brazilian dietary guidelines. An exploratory and qualitative approach was conducted with a selected sample of teachers, administrative technicians, and students (Nâ¯=â¯24) from the Federal University of Grande Dourados, Brazil. First, using the pile sort method, participants were asked to freely classify 24 pictures of food (sourced from examples of the four food groups specified in NOVA) into food groups meaningful to them. Next, in semi-structured interviews, participants were asked to describe the food groups they created. The food groups created by participants were analyzed using non-metric multidimensional scaling followed by hierarchical cluster analysis, and the interviews were analyzed using content analysis. Participants had a mean age of 30 (±9.4) years. A total of 128 food groups were created by 24 participants (an average of five food groups per person); and a total of 55 non-mutually exclusive groups names were used by them to describe these food groups. Sixteen themes emerged from the content analysis. The most recurrent themes were food groups, nutrients, foods I consume, foods I do not consume, and food processing. Contrasting themes such as real food and junk foods, meals and ready-made foods, healthy foods and unhealthy foods were also noted. Six clusters emerged from the cluster analysis, each related to one or more themes. Overall, a striking similarity was observed between the ways the individuals classified food and the NOVA food classification.