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Food categorizations among low-income women living in three different urban contexts: The pile sorting method

机译:居住在三种不同城市背景下的低收入妇女的食品分类:桩分选方法

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摘要

Transformations in eating practices are reflected in the multiplicity of competing food-related discourses. These discourses contribute to different food categorizations among individuals. Scientists have long argued that food categorizations may help understanding cultural systems of health beliefs. However, not enough work has been conducted to improve the understanding of the dimensions of food categorizations and their interface with food choices, tastes, and culturally defined food systems. This study aims at describing and interpreting how low-income women living in three urban settings in Santos, Brazil, classify and give meaning to foods. We used the pile sorting method to investigate categorizations created by 90 women, following 6 steps: (1) creating units of analysis, (2) sorting the units of analysis into piles, (3) running multidimensional scaling analysis, (4) running cluster analyses on the multidimensional scaling coordinates, (5) labelling the clusters, and (6) analyzing consensus among the participants. The final solution to food categorizations comprised six clusters, namely: home meals, convenience foods, special meals, fish, breads and cereals, and hot dogs. Additionally, we observed four rationales for food categorization: frequency of consumption, degree of healthfulness, personal taste, and meals in which the food was usually part of. These categories highlight the importance of considering personal taste and the type of meal that the food is culturally consumed in, to propose meaningful interventions and appropriate education tools, towards promoting healthy eating practices, especially among vulnerable populations.
机译:饮食实践的转变反映在竞争与竞争的食物有关的话语的多样性中。这些话语是有助于个人的不同食品分类。科学家长期以来,粮食分类可能有助于了解健康信仰的文化系统。然而,还没有足够的工作来改善对食品分类维度的理解及其与食物选择,口味和文化定义的食物系统的界面的理解。本研究旨在描述和解释居住在桑托斯,巴西,巴西的三个城市环境中的低收入妇女对食品进行分类和意义。我们使用桩分类方法调查90名女性创建的分类,继6步:(1)创建分析单位,(2)将分析单位分类为桩,(3)运行多维缩放分析,(4)运行群集在多维缩放坐标上分析(5)标记群集,(6)分析参与者之间的共识。最终的食品分类解决方案包括六个集群,即:家庭膳食,便利食品,特殊餐,鱼,面包和谷物和热狗。此外,我们观察到食品分类的四种理由:食用频率,健康程度,食物通常是部分的膳食。这些类别突出了考虑个人味道和食物在文化上消费的膳食类型的重要性,以提出有意义的干预措施和适当的教育工具,促进促进健康的饮食实践,特别是在弱势群体中。

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