Food consumption profile of rural riverside populations - Ana Medeiros; Evelyne Mainbourg (James Cook University, 2023)
Introduction: The uniqueness of the way of life of rural riverside populations is of interest because they are the largest traditional Amazonian population. Their eating habits reveal their life conditions and relationship with the urban environment and is a poorly investigated subject. This research aimed to describe and analyze the food consumption of Amazonian riverside populations based on the food types consumed and reported by the families. Methods: A cross-sectional study was carried out on the rural riverside population occupying part of the riverbank of Rio Negro, in Manaus County, North Brazil. This population can only be accessed by river. Random, systematic, stratified sampling was conducted on 287 households. A questionnaire about consumed food, socioeconomic conditions and food obtainment was applied. The analysis was performed in R software. Descriptive statistical analysis and log-binomial regression were carried out. Results: It was observed that eating habits were mainly based on in natura (unprocessed) or minimally processed foods, according to the food classification system NOVA. Food diversity was low and the most consumed food types were coffee, flour and rice. The influence of small local markets, income and traditional practices on food intake based on food processing level was also observed. Thus, the chances of eating fish in locations with a small grocery shop were lower (p=0.009) and of eating chicken were higher (p≤0.001). The chances of consuming in natura or minimally processed foods among the literate population (p=0.041) with higher income (p≤0.001) were higher. The chances of eating processed foods were lower where fishing (p=0.007) and farming (p=0.009) were practiced. Conclusion: Based on these unexpected results, the present research highlights the food consumption of a riverside population and reduces the shortage of information about the largest traditional Amazonian population.