Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Stance4Health nutritional APP: A Path to Personalized Smart Nutrition

Version 1 : Received: 7 December 2022 / Approved: 9 December 2022 / Online: 9 December 2022 (01:11:03 CET)

A peer-reviewed article of this Preprint also exists.

Hinojosa-Nogueira, D.; Ortiz-Viso, B.; Navajas-Porras, B.; Pérez-Burillo, S.; González-Vigil, V.; de la Cueva, S.P.; Rufián-Henares, J.Á. Stance4Health Nutritional APP: A Path to Personalized Smart Nutrition. Nutrients 2023, 15, 276. Hinojosa-Nogueira, D.; Ortiz-Viso, B.; Navajas-Porras, B.; Pérez-Burillo, S.; González-Vigil, V.; de la Cueva, S.P.; Rufián-Henares, J.Á. Stance4Health Nutritional APP: A Path to Personalized Smart Nutrition. Nutrients 2023, 15, 276.

Abstract

Access to good nutritional health is one of the principal objectives of current society. Several e-services offer dietary advice. However, multifactorial and more individualized nutritional recommendations should be developed to recommend healthy menus according to the specific user's needs. In this article we present and validate a personalized nutrition system based on an application (APP) for smart devices with the capacity to offer an adaptable menu to the user. The APP was developed following a structured recommendation generation scheme, where the characteristics of the menus of 20 users were evaluated. Specific menus were generated for each user based on their preferences and nutritional requirements. These menus were evaluated by comparing their nutritional content versus the nutrient composition retrieved from dietary records. The generated menus showed great similarity to those obtained from the user dietary records. Furthermore, the generated menus showed less variability in micronutrient amounts and higher concentrations than the menus from the user records. The macronutrient deviations were also corrected in the generated menus, offering a better adaptation to the users. The presented system is a good tool for the generation of menus that are adapted to the user characteristics and a starting point to nutritional interventions.

Keywords

computational nutrition; meal plan generator; nutritional app; nutritional intervention; smartphone application; diet app; diet record.

Subject

Biology and Life Sciences, Food Science and Technology

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