Integration of various dimensions in food-based dietary guidelines via mathematical approaches : report of a DGE/FENS Workshop in Bonn, Germany, 23–24 September 2019
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 soc...
Gespeichert in:
Hauptverfasser: | , , , , , , , , , , , |
---|---|
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | 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. |
---|---|
ISSN: | 0007-1145 1475-2662 |