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  • Linseisen, Jakob (3)
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Electrical impedance spectroscopy for the characterization of skin barrier in atopic dermatitis (2021)
Rinaldi, Arturo O. ; Korsfeldt, Angelica ; Ward, Siobhan ; Burla, Daniel ; Dreher, Anita ; Gautschi, Marja ; Stolpe, Britta ; Tan, Ge ; Bersuch, Eugen ; Melin, David ; Askary Lord, Nima ; Grant, Simon ; Svedenhag, Per ; Tsekova, Kristina ; Schmid‐Grendelmeier, Peter ; Möhrenschlager, Matthias ; Renner, Ellen ; Akdis, Cezmi A.
DGE position statement on more sustainable diet (2021)
Renner, Britta ; Arens-azevedo, Ulrike ; Watzl, Bernhard ; Richter, Margrit ; Virmani, Kiran ; Linseisen, Jakob
Perspective: a conceptual framework for adaptive personalized nutrition advice systems (APNASs) (2023)
Renner, Britta ; Buyken, Anette E. ; Gedrich, Kurt ; Lorkowski, Stefan ; Watzl, Bernhard ; Linseisen, Jakob ; Daniel, Hannelore ; Conrad, Johanna ; Ferrario, Paola G. ; Holzapfel, Christina ; Leitzmann, Michael ; Richter, Margrit ; Simon, Marie-Christine ; Sina, Christian ; Wirsam, Jan
Nearly all approaches to personalized nutrition (PN) use information such as the gene variants of individuals to deliver advice that is more beneficial than a generic one-size-fits-all recommendation. Despite great enthusiasm and the increased availability of commercial services, thus far, scientific studies have only revealed small to negligible effects on the efficacy and effectiveness of personalized dietary recommendations, even when using genetic or other individual information. In addition, from a public health perspective, scholars are critical of PN because it primarily targets socially privileged groups rather than the general population, thereby potentially widening health inequality. Therefore, in this perspective, we propose to extend current PN approaches by creating adaptive personalized nutrition advice systems (APNASs) that are tailored to the type and timing of personalized advice for individual needs, capacities, and receptivity in real-life food environments. These systems encompass a broadening of current PN goals (i.e., what should be achieved) to incorporate individual goal preferences beyond currently advocated biomedical targets (e.g., making sustainable food choices). Moreover, they cover the personalization processes of behavior change by providing in situ, just-in-time information in real-life environments (how and when to change), which accounts for individual capacities and constraints (e.g., economic resources). Finally, they are concerned with a participatory dialogue between individuals and experts (e.g., actual or virtual dieticians, nutritionists, and advisors), when setting goals and deriving measures of adaption. Within this framework, emerging digital nutrition ecosystems enable continuous, real-time monitoring, advice, and support in food environments from exposure to consumption. We present this vision of a novel PN framework along with scenarios and arguments that describe its potential to efficiently address individual and population needs and target groups that would benefit most from its implementation.
Data in personalized nutrition: bridging biomedical, psycho-behavioral, and food environment approaches for population-wide impact (2025)
Linseisen, Jakob ; Renner, Britta ; Gedrich, Kurt ; Wirsam, Jan ; Holzapfel, Christina ; Lorkowski, Stefan ; Watzl, Bernhard ; Daniel, Hannelore ; Leitzmann, Michael
Personalized Nutrition (PN) represents an approach aimed at delivering tailored dietary recommendations, products or services to support both prevention and treatment of nutrition-related conditions and improve individual health using genetic, phenotypic, medical, nutritional, and other pertinent information. However, current approaches have yielded limited scientific success in improving diets or in mitigating diet-related conditions. In addition, PN currently caters to a specific subgroup of the population rather than having a widespread impact on diet and health at a population level. Addressing these challenges requires integrating traditional biomedical and dietary assessment methods with psycho-behavioral, and novel digital and diagnostic methods for comprehensive data collection, which holds considerable promise in alleviating present PN shortcomings. This comprehensive approach not only allows for deriving personalized goals (“what should be achieved”) but also customizing behavioral change processes (“how to bring about change”). We herein outline and discuss the concept of “Adaptive Personalized Nutrition Advice Systems” (APNASs), which blends data from three assessment domains: 1) biomedical/health phenotyping; 2) stable and dynamic behavioral signatures; and 3) food environment data. Personalized goals and behavior change processes are envisaged to no longer be based solely on static data but will adapt dynamically in-time and in-situ based on individual-specific data. To successfully integrate biomedical, behavioral and environmental data for personalized dietary guidance, advanced digital tools (e.g., sensors) and artificial intelligence (AI)-based methods will be essential. In conclusion, the integration of both established and novel static and dynamic assessment paradigms holds great potential for transitioning PN from its current focus on elite nutrition to a widely accessible tool that delivers meaningful health benefits to the general population.
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