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Permanent URI for this collectionhttps://hdl.handle.net/11285/345352
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- Tailor-Made Nutrition Education for University Students through Data Science(IEEE, 2023-04-21) Gallardo, Katherina; Aguilar González, Jesús; G. Ceballos, Hector; Díaz Méndez, Rosa Elvia; Mejía Almada, Paola Gabriela; Instituto Tecnológico y de Estudios Superiores de MonterreyThis paper presents a study of daily food intake records with the help of educational technology. The aim was to analyze higher education students' patterns of eating. The study took place in a private university in northern Mexico. Two phases were defined for this study. The first was to analyze a daily record of food consumption by 1,068 students. The second corresponded to a virtual reality supermarket where 3,189 students' activities were registered from 2020 to 2022. Their food purchase decisions were studied based on each product's nutritional information. Statistically significant differences were found in their eating habits in the variables of age, gender, and physical activity. The intake of sodium, sugar, saturated fats, and other fats consumption was also analyzed. This information is considered helpful for designing auxiliary educational material to promote well-being and food habit strategies for undergraduate students.

