
You have already added 0 works in your ORCID record related to the merged Research product.
You have already added 0 works in your ORCID record related to the merged Research product.
<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>
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

AbstractIn 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.
Agriculture and Food Sciences, 610, Nutritional Status, Mathematical optimisation, Diet modelling, Modelling, 510, Nutrition Policy, Food-based dietary guidelines: Mathematical optimisation: Diet modelling: Dietary guidelines: Food systems: Sustainability DALY, Germany, Medicine and Health Sciences, /dk/atira/pure/sustainabledevelopmentgoals/climate_action; name=SDG 13 - Climate Action, Mathematical optimisation: Diet modelling: Dietary guidelines: Food systems: Sustainability DALY [Food-based dietary guidelines], 360, disability-adjusted life year, Food-based dietary guidelines, Diet, [SDV.AEN] Life Sciences [q-bio]/Food and Nutrition, Food systems, Dietary guidelines, Sustainability, Food system, Food, MESH: Nutrition Policy, FBDG, food-based dietary guideline, [SDV.AEN]Life Sciences [q-bio]/Food and Nutrition, mesh: mesh:Nutrition Policy
Agriculture and Food Sciences, 610, Nutritional Status, Mathematical optimisation, Diet modelling, Modelling, 510, Nutrition Policy, Food-based dietary guidelines: Mathematical optimisation: Diet modelling: Dietary guidelines: Food systems: Sustainability DALY, Germany, Medicine and Health Sciences, /dk/atira/pure/sustainabledevelopmentgoals/climate_action; name=SDG 13 - Climate Action, Mathematical optimisation: Diet modelling: Dietary guidelines: Food systems: Sustainability DALY [Food-based dietary guidelines], 360, disability-adjusted life year, Food-based dietary guidelines, Diet, [SDV.AEN] Life Sciences [q-bio]/Food and Nutrition, Food systems, Dietary guidelines, Sustainability, Food system, Food, MESH: Nutrition Policy, FBDG, food-based dietary guideline, [SDV.AEN]Life Sciences [q-bio]/Food and Nutrition, mesh: mesh:Nutrition Policy
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).11 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
