Socioeconomic influences on the eating practices of mothers living in the Brazilian Amazon

• Grant number: 17/22378-6
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: March 01, 2018
• End date: December 31, 2019
• Field of knowledge: Health Sciences - Collective Health - Public Health
• Principal Investigator: Priscila de Morais Sato
• Grantee: Caio Pereira dos Santos
• Host Institution: Faculdade de Saúde Pública (FSP). Universidade de São Paulo (USP). São Paulo , SP, Brazil
• Associated research grant: 16/00270-6 - MINA study - Maternal and child health in Acre: birth cohort in the Western Brazilian Amazon, AP.TEM

Abstract

The study of food practices includes considering observed practices to social representations that food performs, taking into account that biological and ecological determinants will shape those practices, leading to the social space, in which possibilities of several food choices are attainable. In industrialized societies, socioeconomic status establishes wide influence on food access and food acquisition, as well as on opinions and values about food. Thus, the discussion of the influence of the social space in determining healthy or unhealthy food practices turns into the central question of this undergraduate research proposal, which uses a qualitative research model and is part of the Mina project. The purpose of this study is to understand how food practices are affected by socioeconomic status in women who live in Cruzeiro do Sul, Acre, Amazônia ocidental brasileira. The methodological approach chosen to collect data was a triangulation of methods, using in-depth semi-structured interviews and participant observation in home visits, that aims to develop a comprehensive understanding of the subject. To analyze the collected data, a content analysis method will be performed. Four steps will be used to develop the content analysis: pre-analysis, the exploratory content analysis - including the development of a codebook, the data analysis technique and, finally, the step of inference and interpretation will be made by presenting central and peripheral tendencies measures, distribution measures, intervals, details, and contexts. Therefore, the analysis will be assisted by the software MAXQDA and the data will be presented as paraphrases, literal quotes, and quantitative data. So, it will be possible to interpret the data and infer conclusions contributing to a deeper understanding of health and maternal and child nutrition determinants and how gender issues impact the acquisition of food. (AU)