Verónica González-Vigil

Background/Objectives: Diet significantly influences gut microbiota (GM), with variations in GM responses linked to the type and quantity of food consumed. These variations underscore the need for personalized nutrition. The Stance4Health (S4H) project developed the S4H Food Frequency Questionnaire (S4H-FFQ) and the i-Diet S4H app to assess dietary intake of foods affecting GM. This study aimed to validate the S4H-FFQ against the validated I.Family-FFQ and the i-Diet S4H app; Methods: The S4H-FFQ, with 200 food items across 14 food groups, evaluates dietary intake over the past month. Qualitative validation compared food group consumption frequencies from the S4H-FFQ and the I.Family-FFQ, while quantitative validation assessed nutrient and energy intake using the i-Diet S4H app. The S4H-GM score, a measure of GM-relevant food consumption, was evaluated through the S4H-FFQ and i-Diet S4H app; Results: Pearson correlations between the S4H-FFQ and the I.Family-FFQ ranged from 0.3 to 0.7 and were statistically significant across all the food groups. Quantitative validation showed lower but consistent correlations, comparable with other studies, confirming the S4H-FFQ’s ability to estimate food intake. A positive correlation was also found between the S4H-GM scores from the S4H-FFQ and the i-Diet S4H app (p < 0.001); Conclusions: The S4H-FFQ is a reliable tool for assessing dietary patterns that influence GM. Its application in nutritional studies can enhance personalized nutrition and support future research aimed at optimizing GM and improving health outcomes.

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.

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.

Unhealthy diets represent a major risk for the pathogenesis of metabolic and chronic inflammatory diseases. Improving the quality of diet is important to prevent chronic diseases, and diet-induced modifications of the gut microbiota (GM) community likely play an important role. The EU-funded Stance4Health project aims at performing a randomized clinical trial based on a nutritional intervention program in the context of normal weight and overweight adults as well as children with obesity and gluten-related disorders or allergy/intolerance to cow’s milk. The trial will evaluate the efficacy of a Smart Personalised Nutrition (SPN) service in modifying GM composition and metabolic function and improving consumer empowerment through technology adoption.

The European Commission funded project Stance4Health (S4H) aims to develop a complete personalised nutrition service. In order to succeed, sources of information on nutritional composition and other characteristics of foods need to be as comprehensive as possible. Food composition tables or databases (FCT/FCDB) are the most commonly used tools for this purpose. The aim of this study is to describe the harmonisation efforts carried out to obtain the Stance4Health FCDB. A total of 10 FCT/FCDB were selected from different countries and organizations. Data were classified using FoodEx2 and INFOODS tagnames to harmonise the information. Hazard analysis and critical control points analysis was applied as the quality control method. Data were processed by spreadsheets and MySQL. S4H’s FCDB is composed of 880 elements, including nutrients and bioactive compounds. A total of 2648 unified foods were used to complete the missing values of the national FCDB used. Recipes and dishes were estimated following EuroFIR standards via linked tables. S4H’s FCDB will be part of the smartphone app developed in the framework of the Stance4Health European project, which will be used in different personalized nutrition intervention studies. S4H FCDB has great perspectives, being one of the most complete in terms of number of harmonized foods, nutrients and bioactive compounds included.