TY - JOUR T1 - Integration of various dimensions in food-based dietary guidelines via mathematical approaches: report of a DGE/FENS Workshop in Bonn, Germany, 23–24 September 2019Abstract JF - British Journal of Nutrition Y1 - 2021 A1 - Anne Carolin Schäfer A1 - Annemarie Schmidt A1 - Angela Bechthold A1 - Heiner Boeing A1 - Bernhard Watzl A1 - Nicole Darmon A1 - Brecht Devleesschauwer A1 - Thomas Heckelei A1 - Sara Monteiro Pires A1 - Perrine Nadaud A1 - Corné van Dooren A1 - Florent Vieux KW - Diet modelling KW - Dietary guidelines KW - Food systems KW - Food-based dietary guidelines KW - Mathematical optimisation KW - sustainability AB -

In the past, food-based dietary guidelines (FBDGs) were derived nearly exclusively by using systematic reviews on diet–health relationships and translating dietary reference values for nutrient intake into foods. This approach neglects many other implications that dietary recommendations have on society, the economy and environment. In view of pressing challenges, such as climate change and the rising burden of diet-related diseases, the simultaneous integration of evidence-based findings from different dimensions into FBDGs is required. Consequently, mathematical methods and data processing are evolving as powerful tools in nutritional sciences. The possibilities and reasons for the derivation of FBDGs via mathematical approaches were the subject of a joint workshop hosted by the German Nutrition Society (DGE) and the Federation of European Nutrition Societies (FENS) in September 2019 in Bonn, Germany. European scientists were invited to discuss and exchange on the topics of mathematical optimisation for the development of FBDGs and different approaches to integrate various dimensions into FBDGs. We concluded that mathematical optimisation is a suitable tool to formulate FBDGs finding trade-offs between conflicting goals and taking several dimensions into account. We identified a lack of evidence for the extent to which constraints and weights for different dimensions are set and the challenge to compile diverse data that suit the demands of optimisation models. We also found that individualisation via mathematical optimisation is one perspective of FBDGs to increase consumer acceptance, but the application of mathematical optimisation for population-based and individual FBDGs requires more experience and evaluation for further improvements.

VL - 126 CP - 6 M3 - 10.1017/S0007114520004857 ER -