About this Research Topic

Background

Unhealthy diets and physical inactivity have been established as key contributors to the escalating prevalence of non-communicable diseases, including obesity, diabetes, and cardiovascular disease. Fortunately, recent technological advances have led to the development of innovative dietary and physical activity (PA)-related mobile applications, designed to increase PA levels, motivate weight loss, encourage healthy food choices and lifestyle, reduce sedentary behavior, and evaluate and monitor dietary intake. However, individual responses to dietary advice and intervention are heterogeneous, showing the clear need to develop personalized nutritional approaches for each individual.

Involving many aspects (such as nutritional intake, PA, individual characteristics, dietary advice/supplements, health biomarkers, gut microbiota composition and genetic load), personalized nutrition has proven to have great potential for disease prevention. Based on this holistic perspective, mobile applications and sensing devices can offer extra opportunities due to artificial intelligence, which is crucial for understanding complex biological phenomena, and combined with the use of big data/machine learning techniques can benefit precision (personalized) nutrition.

Personalized or precision nutrition intends to tailor nutritional advice/diets in order to optimize health based on an individual's characteristics. The past two decades, we witnessed an unprecedented advance in digital technologies and their field of applications. Moreover, the synergetic integration of multiple technologies in single platforms has generated detailed insights and provided accurate information on the evolution of personalized nutrition. From this perspective, and requiring a strong increase in the scientific evidence, the advancement of personalized nutrition can be facilitated by a number of factors, for instance, (1) the development of a strong theoretical basis, (2) the evidence from well-designed nutritional intervention studies; and (3) the development of a regulatory framework designed to protect the relevant stakeholders.

In this Research Topic, we encourage authors to submit original research, review articles, and case studies on all sorts of technologies (i.e., mobile applications, wearable technologies, sensing devices, smart technologies) as they relate to personalized nutrition and eating behavior change. Some specific subtopics include, but are not limited to:
- Intelligent systems, big data, and artificial intelligence
- Real-time feedback, personalized recommendation systems, and dietary assessment
- Healthy eating and nutritional requirements, dietary assessment, and personalized nutrition advice as applied through technology
- Ethics and regulatory frameworks

Keywords: personalized nutrition, healthy eating, mobile health, smart technologies, dietary assessment, personalized recommendations, disease prevention, sensing devices, artificial intelligence, intelligent systems, ethics

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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