Novel insights on Nutritional Assessment and Body composition analysis

In recent years, the fields of nutritional assessment and body composition analysis have undergone rapid transformation, driven by technological innovation, precision health approaches, and the need for more personalised care. Traditional methods focusing solely on dietary intake or anthropometry are now being complemented by multidimensional assessments that combine clinical data, metabolomics, digital dietary tracking, and bioimpedance technologies. This paradigm shift provides novel insights into human metabolism, malnutrition, obesity, sarcopenia, and chronic disease risk.

Within this dynamic landscape, the Open Lab session serves as a collaborative environment where researchers, clinicians, engineers, and innovators can exchange expertise and co-develop new methodologies for evaluating nutritional status. Participants will engage with emerging tools such as phase angle analysis, indirect calorimetry, CT scan analysis, ultrasound, and AI-driven nutrition analytics, exploring their scientific validity, clinical applicability, and ethical implications.

The session fosters cross-sector innovation and open dialogue on how digital and physiological measurements can converge to improve health outcomes. It also promotes the creation of a shared European framework for high-quality, evidence-based nutritional assessment — bridging research, technology, and patient-centred care.

General learning outcomes

By the end of the Student Research project, participants will be able to: 

• Explain the principles and limitations of traditional and advanced methods of nutritional assessment, including dietary, anthropometric, and biochemical approaches.
• Describe the mechanisms, scientific basis, and clinical applications of modern body composition analysis techniques (e.g. BIA, DXA, indirect calorimetry, etc.).
• Interpret body composition and metabolic data, integrating phase angle, muscle mass indices, and energy expenditure into comprehensive nutritional evaluations.
• Critically appraise the role of digital and AI-based tools in the personalisation of nutrition care and public health strategies.
• Apply interdisciplinary thinking to design or prototype innovative solutions that enhance nutritional assessment in clinical or community settings.
• Collaborate effectively within a multidisciplinary EU context, exchanging expertise between nutrition science, clinical medicine, data analytics, and technology development.

   

• Reflect on ethical, regulatory, and practical aspects of using digital and physiological data in health assessment and decision-making.

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