A methodological framework for deriving the German food-based dietary guidelines 2024: Food groups, nutrient goals, and objective functions
For a growing number of food-based dietary guidelines (FBDGs), diet optimization is the tool of choice to account for the complex demands of healthy and sustainable diets. However, decisions about such optimization models' parameters are rarely reported nor systematically studied. The objective...
Uloženo v:
| Vydáno v: | PloS one Ročník 20; číslo 3; s. e0313347 |
|---|---|
| Hlavní autoři: | , , , , , , , , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
United States
Public Library of Science
12.03.2025
Public Library of Science (PLoS) |
| Témata: | |
| ISSN: | 1932-6203, 1932-6203 |
| On-line přístup: | Získat plný text |
| Tagy: |
Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
|
| Abstract | For a growing number of food-based dietary guidelines (FBDGs), diet optimization is the tool of choice to account for the complex demands of healthy and sustainable diets. However, decisions about such optimization models' parameters are rarely reported nor systematically studied.
The objectives were to develop a framework for (i) the formulation of decision variables based on a hierarchical food classification system; (ii) the mathematical form of the objective function; and (iii) approaches to incorporate nutrient goals.
To answer objective (i), food groups from FoodEx2 levels 3-7 were applied as decision variables in a model using acceptability constraints (5th and 95th percentile for food intakes of German adults (n = 10,419)) and minimizing the deviation from the average observed dietary intakes. Building upon, to answer objectives (ii) and (iii), twelve models were run using decision variables from FoodEx2 level 3 (n = 255), applying either a linear or squared and a relative or absolute way to deviate from observed dietary intakes, and three different lists of nutrient goals (allNUT-DRV, incorporating all nutrient goals; modNUT-DRV excluding nutrients with limited data quality; modNUT-AR using average requirements where applicable instead of recommended intakes).
FoodEx2 food groups proved suitable as diet optimization decision variables. Regarding deviation, the largest differences were between the four different objective function types, e.g., in the linear-relative modNUT-DRV model, 46 food groups of the observed diet were changed to reach the model's goal, in linear-absolute 78 food groups, squared-relative 167, and squared-absolute 248. The nutrient goals were fulfilled in all models, but the number of binding nutrient constraints was highest in the linear-relative models (e.g. allNUT-DRV: 11 vs. 7 in linear-absolute).
Considering the various possibilities to operationalize dietary aspects in an optimization model, this study offers valuable contributions to a framework for developing FBDGs via diet optimization. |
|---|---|
| AbstractList | For a growing number of food-based dietary guidelines (FBDGs), diet optimization is the tool of choice to account for the complex demands of healthy and sustainable diets. However, decisions about such optimization models' parameters are rarely reported nor systematically studied. The objectives were to develop a framework for (i) the formulation of decision variables based on a hierarchical food classification system; (ii) the mathematical form of the objective function; and (iii) approaches to incorporate nutrient goals. To answer objective (i), food groups from FoodEx2 levels 3-7 were applied as decision variables in a model using acceptability constraints (5.sup.th and 95.sup.th percentile for food intakes of German adults (n = 10,419)) and minimizing the deviation from the average observed dietary intakes. Building upon, to answer objectives (ii) and (iii), twelve models were run using decision variables from FoodEx2 level 3 (n = 255), applying either a linear or squared and a relative or absolute way to deviate from observed dietary intakes, and three different lists of nutrient goals (allNUT-DRV, incorporating all nutrient goals; modNUT-DRV excluding nutrients with limited data quality; modNUT-AR using average requirements where applicable instead of recommended intakes). FoodEx2 food groups proved suitable as diet optimization decision variables. Regarding deviation, the largest differences were between the four different objective function types, e.g., in the linear-relative modNUT-DRV model, 46 food groups of the observed diet were changed to reach the model's goal, in linear-absolute 78 food groups, squared-relative 167, and squared-absolute 248. The nutrient goals were fulfilled in all models, but the number of binding nutrient constraints was highest in the linear-relative models (e.g. allNUT-DRV: 11 vs. 7 in linear-absolute). Considering the various possibilities to operationalize dietary aspects in an optimization model, this study offers valuable contributions to a framework for developing FBDGs via diet optimization. For a growing number of food-based dietary guidelines (FBDGs), diet optimization is the tool of choice to account for the complex demands of healthy and sustainable diets. However, decisions about such optimization models' parameters are rarely reported nor systematically studied.BACKGROUNDFor a growing number of food-based dietary guidelines (FBDGs), diet optimization is the tool of choice to account for the complex demands of healthy and sustainable diets. However, decisions about such optimization models' parameters are rarely reported nor systematically studied.The objectives were to develop a framework for (i) the formulation of decision variables based on a hierarchical food classification system; (ii) the mathematical form of the objective function; and (iii) approaches to incorporate nutrient goals.OBJECTIVESThe objectives were to develop a framework for (i) the formulation of decision variables based on a hierarchical food classification system; (ii) the mathematical form of the objective function; and (iii) approaches to incorporate nutrient goals.To answer objective (i), food groups from FoodEx2 levels 3-7 were applied as decision variables in a model using acceptability constraints (5th and 95th percentile for food intakes of German adults (n = 10,419)) and minimizing the deviation from the average observed dietary intakes. Building upon, to answer objectives (ii) and (iii), twelve models were run using decision variables from FoodEx2 level 3 (n = 255), applying either a linear or squared and a relative or absolute way to deviate from observed dietary intakes, and three different lists of nutrient goals (allNUT-DRV, incorporating all nutrient goals; modNUT-DRV excluding nutrients with limited data quality; modNUT-AR using average requirements where applicable instead of recommended intakes).METHODSTo answer objective (i), food groups from FoodEx2 levels 3-7 were applied as decision variables in a model using acceptability constraints (5th and 95th percentile for food intakes of German adults (n = 10,419)) and minimizing the deviation from the average observed dietary intakes. Building upon, to answer objectives (ii) and (iii), twelve models were run using decision variables from FoodEx2 level 3 (n = 255), applying either a linear or squared and a relative or absolute way to deviate from observed dietary intakes, and three different lists of nutrient goals (allNUT-DRV, incorporating all nutrient goals; modNUT-DRV excluding nutrients with limited data quality; modNUT-AR using average requirements where applicable instead of recommended intakes).FoodEx2 food groups proved suitable as diet optimization decision variables. Regarding deviation, the largest differences were between the four different objective function types, e.g., in the linear-relative modNUT-DRV model, 46 food groups of the observed diet were changed to reach the model's goal, in linear-absolute 78 food groups, squared-relative 167, and squared-absolute 248. The nutrient goals were fulfilled in all models, but the number of binding nutrient constraints was highest in the linear-relative models (e.g. allNUT-DRV: 11 vs. 7 in linear-absolute).RESULTSFoodEx2 food groups proved suitable as diet optimization decision variables. Regarding deviation, the largest differences were between the four different objective function types, e.g., in the linear-relative modNUT-DRV model, 46 food groups of the observed diet were changed to reach the model's goal, in linear-absolute 78 food groups, squared-relative 167, and squared-absolute 248. The nutrient goals were fulfilled in all models, but the number of binding nutrient constraints was highest in the linear-relative models (e.g. allNUT-DRV: 11 vs. 7 in linear-absolute).Considering the various possibilities to operationalize dietary aspects in an optimization model, this study offers valuable contributions to a framework for developing FBDGs via diet optimization.CONCLUSIONConsidering the various possibilities to operationalize dietary aspects in an optimization model, this study offers valuable contributions to a framework for developing FBDGs via diet optimization. BackgroundFor a growing number of food-based dietary guidelines (FBDGs), diet optimization is the tool of choice to account for the complex demands of healthy and sustainable diets. However, decisions about such optimization models’ parameters are rarely reported nor systematically studied.ObjectivesThe objectives were to develop a framework for (i) the formulation of decision variables based on a hierarchical food classification system; (ii) the mathematical form of the objective function; and (iii) approaches to incorporate nutrient goals.MethodsTo answer objective (i), food groups from FoodEx2 levels 3-7 were applied as decision variables in a model using acceptability constraints (5th and 95th percentile for food intakes of German adults (n = 10,419)) and minimizing the deviation from the average observed dietary intakes. Building upon, to answer objectives (ii) and (iii), twelve models were run using decision variables from FoodEx2 level 3 (n = 255), applying either a linear or squared and a relative or absolute way to deviate from observed dietary intakes, and three different lists of nutrient goals (allNUT-DRV, incorporating all nutrient goals; modNUT-DRV excluding nutrients with limited data quality; modNUT-AR using average requirements where applicable instead of recommended intakes).ResultsFoodEx2 food groups proved suitable as diet optimization decision variables. Regarding deviation, the largest differences were between the four different objective function types, e.g., in the linear-relative modNUT-DRV model, 46 food groups of the observed diet were changed to reach the model’s goal, in linear-absolute 78 food groups, squared-relative 167, and squared-absolute 248. The nutrient goals were fulfilled in all models, but the number of binding nutrient constraints was highest in the linear-relative models (e.g. allNUT-DRV: 11 vs. 7 in linear-absolute).ConclusionConsidering the various possibilities to operationalize dietary aspects in an optimization model, this study offers valuable contributions to a framework for developing FBDGs via diet optimization. For a growing number of food-based dietary guidelines (FBDGs), diet optimization is the tool of choice to account for the complex demands of healthy and sustainable diets. However, decisions about such optimization models' parameters are rarely reported nor systematically studied. The objectives were to develop a framework for (i) the formulation of decision variables based on a hierarchical food classification system; (ii) the mathematical form of the objective function; and (iii) approaches to incorporate nutrient goals. To answer objective (i), food groups from FoodEx2 levels 3-7 were applied as decision variables in a model using acceptability constraints (5th and 95th percentile for food intakes of German adults (n = 10,419)) and minimizing the deviation from the average observed dietary intakes. Building upon, to answer objectives (ii) and (iii), twelve models were run using decision variables from FoodEx2 level 3 (n = 255), applying either a linear or squared and a relative or absolute way to deviate from observed dietary intakes, and three different lists of nutrient goals (allNUT-DRV, incorporating all nutrient goals; modNUT-DRV excluding nutrients with limited data quality; modNUT-AR using average requirements where applicable instead of recommended intakes). FoodEx2 food groups proved suitable as diet optimization decision variables. Regarding deviation, the largest differences were between the four different objective function types, e.g., in the linear-relative modNUT-DRV model, 46 food groups of the observed diet were changed to reach the model's goal, in linear-absolute 78 food groups, squared-relative 167, and squared-absolute 248. The nutrient goals were fulfilled in all models, but the number of binding nutrient constraints was highest in the linear-relative models (e.g. allNUT-DRV: 11 vs. 7 in linear-absolute). Considering the various possibilities to operationalize dietary aspects in an optimization model, this study offers valuable contributions to a framework for developing FBDGs via diet optimization. Background For a growing number of food-based dietary guidelines (FBDGs), diet optimization is the tool of choice to account for the complex demands of healthy and sustainable diets. However, decisions about such optimization models' parameters are rarely reported nor systematically studied. Objectives The objectives were to develop a framework for (i) the formulation of decision variables based on a hierarchical food classification system; (ii) the mathematical form of the objective function; and (iii) approaches to incorporate nutrient goals. Methods To answer objective (i), food groups from FoodEx2 levels 3-7 were applied as decision variables in a model using acceptability constraints (5.sup.th and 95.sup.th percentile for food intakes of German adults (n = 10,419)) and minimizing the deviation from the average observed dietary intakes. Building upon, to answer objectives (ii) and (iii), twelve models were run using decision variables from FoodEx2 level 3 (n = 255), applying either a linear or squared and a relative or absolute way to deviate from observed dietary intakes, and three different lists of nutrient goals (allNUT-DRV, incorporating all nutrient goals; modNUT-DRV excluding nutrients with limited data quality; modNUT-AR using average requirements where applicable instead of recommended intakes). Results FoodEx2 food groups proved suitable as diet optimization decision variables. Regarding deviation, the largest differences were between the four different objective function types, e.g., in the linear-relative modNUT-DRV model, 46 food groups of the observed diet were changed to reach the model's goal, in linear-absolute 78 food groups, squared-relative 167, and squared-absolute 248. The nutrient goals were fulfilled in all models, but the number of binding nutrient constraints was highest in the linear-relative models (e.g. allNUT-DRV: 11 vs. 7 in linear-absolute). Conclusion Considering the various possibilities to operationalize dietary aspects in an optimization model, this study offers valuable contributions to a framework for developing FBDGs via diet optimization. Background For a growing number of food-based dietary guidelines (FBDGs), diet optimization is the tool of choice to account for the complex demands of healthy and sustainable diets. However, decisions about such optimization models’ parameters are rarely reported nor systematically studied. Objectives The objectives were to develop a framework for (i) the formulation of decision variables based on a hierarchical food classification system; (ii) the mathematical form of the objective function; and (iii) approaches to incorporate nutrient goals. Methods To answer objective (i), food groups from FoodEx2 levels 3-7 were applied as decision variables in a model using acceptability constraints (5 th and 95 th percentile for food intakes of German adults ( n = 10,419)) and minimizing the deviation from the average observed dietary intakes. Building upon, to answer objectives (ii) and (iii), twelve models were run using decision variables from FoodEx2 level 3 ( n = 255), applying either a linear or squared and a relative or absolute way to deviate from observed dietary intakes, and three different lists of nutrient goals (allNUT-DRV, incorporating all nutrient goals; modNUT-DRV excluding nutrients with limited data quality; modNUT-AR using average requirements where applicable instead of recommended intakes). Results FoodEx2 food groups proved suitable as diet optimization decision variables. Regarding deviation, the largest differences were between the four different objective function types, e.g., in the linear-relative modNUT-DRV model, 46 food groups of the observed diet were changed to reach the model’s goal, in linear-absolute 78 food groups, squared-relative 167, and squared-absolute 248. The nutrient goals were fulfilled in all models, but the number of binding nutrient constraints was highest in the linear-relative models (e.g. allNUT-DRV: 11 vs. 7 in linear-absolute). Conclusion Considering the various possibilities to operationalize dietary aspects in an optimization model, this study offers valuable contributions to a framework for developing FBDGs via diet optimization. |
| Audience | Academic |
| Author | Conrad, Johanna Gedrich, Kurt Schäfer, Anne Carolin Watzl, Bernhard Kroke, Anja Richter, Margrit Gazan, Rozenn Schwingshackl, Lukas Linseisen, Jakob Lorkowski, Stefan Vieux, Florent Boeing, Heiner Nöthlings, Ute Breidenassel, Christina Hauner, Hans |
| AuthorAffiliation | 10 Competence Cluster for Nutrition and Cardiovascular Health (nutriCARD), Halle-Jena-Leipzig, Germany 5 Research Group Public Health Nutrition, ZIEL—Institute for Food & Health, Technical University of Munich, Freising, Germany 1 German Nutrition Society, Bonn, Germany 6 Institute of Nutritional Medicine, Else Kröner Fresenius Center for Nutritional Medicine, School of Medicine and Health, Technical University of Munich, Munich, Germany 2 Department of Nutrition and Food Sciences, Nutritional Epidemiology, University of Bonn, Bonn, Germany Lovely Professional University, INDIA 7 Department of Nutritional, Food and Consumer Sciences, University of Applied Sciences, Fulda, Germany 11 Institute for Evidence in Medicine, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany 9 Institute of Nutritional Sciences, Friedrich Schiller University Jena, Jena, Germany 8 Epidemiology, University of Augsburg, University Hospital Augsburg, Augsburg, Germany 12 De |
| AuthorAffiliation_xml | – name: 9 Institute of Nutritional Sciences, Friedrich Schiller University Jena, Jena, Germany – name: 8 Epidemiology, University of Augsburg, University Hospital Augsburg, Augsburg, Germany – name: 7 Department of Nutritional, Food and Consumer Sciences, University of Applied Sciences, Fulda, Germany – name: 1 German Nutrition Society, Bonn, Germany – name: 10 Competence Cluster for Nutrition and Cardiovascular Health (nutriCARD), Halle-Jena-Leipzig, Germany – name: 3 Department of Epidemiology (closed), German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany – name: 4 MS-Nutrition, Marseille, France – name: 5 Research Group Public Health Nutrition, ZIEL—Institute for Food & Health, Technical University of Munich, Freising, Germany – name: Lovely Professional University, INDIA – name: 6 Institute of Nutritional Medicine, Else Kröner Fresenius Center for Nutritional Medicine, School of Medicine and Health, Technical University of Munich, Munich, Germany – name: 12 Department of Physiology and Biochemistry of Nutrition, Max Rubner-Institut, Karlsruhe, Germany – name: 2 Department of Nutrition and Food Sciences, Nutritional Epidemiology, University of Bonn, Bonn, Germany – name: 11 Institute for Evidence in Medicine, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany |
| Author_xml | – sequence: 1 givenname: Anne Carolin orcidid: 0000-0002-5607-491X surname: Schäfer fullname: Schäfer, Anne Carolin – sequence: 2 givenname: Heiner surname: Boeing fullname: Boeing, Heiner – sequence: 3 givenname: Rozenn surname: Gazan fullname: Gazan, Rozenn – sequence: 4 givenname: Johanna surname: Conrad fullname: Conrad, Johanna – sequence: 5 givenname: Kurt orcidid: 0000-0001-7321-2555 surname: Gedrich fullname: Gedrich, Kurt – sequence: 6 givenname: Christina surname: Breidenassel fullname: Breidenassel, Christina – sequence: 7 givenname: Hans surname: Hauner fullname: Hauner, Hans – sequence: 8 givenname: Anja surname: Kroke fullname: Kroke, Anja – sequence: 9 givenname: Jakob surname: Linseisen fullname: Linseisen, Jakob – sequence: 10 givenname: Stefan surname: Lorkowski fullname: Lorkowski, Stefan – sequence: 11 givenname: Ute orcidid: 0000-0002-5789-2252 surname: Nöthlings fullname: Nöthlings, Ute – sequence: 12 givenname: Margrit surname: Richter fullname: Richter, Margrit – sequence: 13 givenname: Lukas surname: Schwingshackl fullname: Schwingshackl, Lukas – sequence: 14 givenname: Florent surname: Vieux fullname: Vieux, Florent – sequence: 15 givenname: Bernhard surname: Watzl fullname: Watzl, Bernhard |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/40073305$$D View this record in MEDLINE/PubMed |
| BookMark | eNqNk1trFTEQxxep2It-A9GAIAqeY7LZa1-kFFsLhYK315BNJntyzCbHJFv1M_ilzbbb0lNEZB82mfzmPxdm9rMd6yxk2VOCl4TW5O3ajd5ys9wk8xJTQmlRP8j2SEvzRZVjunPnvJvth7DGuKRNVT3KdguMa0pxuZf9PkIDxJWTzrheC26Q8nyAH85_Q8p5JMHrS217FFeATsEP3Ca7k4uOB5BIaojc_0L9qCUYbSGgHOfFITpJDOq9GzfhDbJj9BpsRL3jJt25lch1axBRXwJSo00HZ8Pj7KFK7_Bk_h9kX07efz7-sDi_OD07PjpfiKqlcSFaShohckpyUlZdUUpBBeeVEC1XqqJ528iuU1XDaUMK3gDGjahLoFJyVXBBD7Ln17ob4wKb-xgYJXVVkbaidSLOrgnp-JptvB5Skcxxza4MzveM-6iFAdbQNs-lLECqulBKtl1LS9yVdEqHCJK03s3Rxm4AKVIfPDdbotsvVq9Y7y4ZIS2mmDZJ4dWs4N33EUJkgw4CjOEW3Dgn3uC8mRJ_cQ_9e3kz1fNUgbbKpcBiEmVHDcU1afN6Snz5Fyp9EgYt0tQpnexbDq-3HBIT4Wfs-RgCO_v08f_Zi6_b7Ms77Aq4iavgzHg1NNvgs7utvu3xzbgnoLgGhHcheFC3CMFs2qqbdrFpq9i8Vcnt8J6b0JFP4VNHtPm38x-NyCnC |
| CitedBy_id | crossref_primary_10_1016_j_cdnut_2025_107559 crossref_primary_10_1007_s00394_025_03789_5 crossref_primary_10_1055_a_2640_1098 |
| Cites_doi | 10.1016/j.foodchem.2016.11.083 10.1093/ajcn/nqaa217 10.3945/jn.109.107318 10.2903/sp.efsa.2021.EN-6507 10.1093/advances/nmaa176 10.1093/advances/nmy130 10.1038/s43016-022-00489-9 10.6027/nord2023-003 10.1016/j.jfca.2007.03.008 10.1017/S0007114520004857 10.3390/nu13103485 10.1093/advances/nmz037 10.3390/ijerph16173019 10.3390/foods12203824 10.1016/j.jfca.2006.05.004 10.1093/jn/134.4.951 10.1017/S1368980024000211 10.1017/S0029665124007274 10.1093/ajcn/69.4.632 10.1016/j.tjnut.2023.05.011 10.18637/jss.v094.i15 10.1017/S1368980009993028 10.3389/fnut.2023.1158257 10.1093/jn/136.10.2457 10.1093/jn/136.4.1021 10.3945/ajcn.111.016501 10.1017/S0007114515000744 10.1371/journal.pone.0219895 10.1016/j.amepre.2011.10.009 10.1017/S1368980019001435 10.1080/19440049.2011.576440 10.1371/journal.pone.0163411 10.1093/advances/nmy049 10.1159/000437243 10.1007/s10654-019-00523-4 10.1093/nutrit/nuab091 10.3389/fnut.2018.00048 10.1017/S1368980016000653 10.1016/j.nutres.2013.01.004 10.1093/advances/nmy033 10.1038/sj.ejcn.1600727 |
| ContentType | Journal Article |
| Copyright | Copyright: © 2025 Schäfer et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. COPYRIGHT 2025 Public Library of Science 2025 Schäfer et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. 2025 Schäfer et al 2025 Schäfer et al 2025 Schäfer et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
| Copyright_xml | – notice: Copyright: © 2025 Schäfer et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. – notice: COPYRIGHT 2025 Public Library of Science – notice: 2025 Schäfer et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. – notice: 2025 Schäfer et al 2025 Schäfer et al – notice: 2025 Schäfer et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
| DBID | AAYXX CITATION CGR CUY CVF ECM EIF NPM IOV ISR 3V. 7QG 7QL 7QO 7RV 7SN 7SS 7T5 7TG 7TM 7U9 7X2 7X7 7XB 88E 8AO 8C1 8FD 8FE 8FG 8FH 8FI 8FJ 8FK ABJCF ABUWG AEUYN AFKRA ARAPS ATCPS AZQEC BBNVY BENPR BGLVJ BHPHI C1K CCPQU D1I DWQXO FR3 FYUFA GHDGH GNUQQ H94 HCIFZ K9. KB. KB0 KL. L6V LK8 M0K M0S M1P M7N M7P M7S NAPCQ P5Z P62 P64 PATMY PDBOC PHGZM PHGZT PIMPY PJZUB PKEHL PPXIY PQEST PQGLB PQQKQ PQUKI PRINS PTHSS PYCSY RC3 7X8 5PM DOA |
| DOI | 10.1371/journal.pone.0313347 |
| DatabaseName | CrossRef Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed Gale In Context: Opposing Viewpoints Gale In Context: Science ProQuest Central (Corporate) Animal Behavior Abstracts Bacteriology Abstracts (Microbiology B) Biotechnology Research Abstracts Nursing & Allied Health Database Ecology Abstracts Entomology Abstracts (Full archive) Immunology Abstracts Meteorological & Geoastrophysical Abstracts Nucleic Acids Abstracts Virology and AIDS Abstracts Agricultural Science Collection Health & Medical Collection ProQuest Central (purchase pre-March 2016) Medical Database (Alumni Edition) ProQuest Pharma Collection Public Health Database Technology Research Database ProQuest SciTech Collection ProQuest Technology Collection ProQuest Natural Science Collection Hospital Premium Collection Hospital Premium Collection (Alumni Edition) ProQuest Central (Alumni) (purchase pre-March 2016) Materials Science & Engineering Collection ProQuest Central (Alumni Edition) ProQuest One Sustainability ProQuest Central UK/Ireland Advanced Technologies & Computer Science Collection Agricultural & Environmental Science Collection ProQuest Central Essentials Biological Science Collection ProQuest Central Technology Collection Natural Science Collection Environmental Sciences and Pollution Management ProQuest One Community College ProQuest Materials Science Collection ProQuest Central Korea Engineering Research Database Health Research Premium Collection Health Research Premium Collection (Alumni) ProQuest Central Student AIDS and Cancer Research Abstracts SciTech Premium Collection ProQuest Health & Medical Complete (Alumni) Materials Science Database Nursing & Allied Health Database (Alumni Edition) Meteorological & Geoastrophysical Abstracts - Academic ProQuest Engineering Collection ProQuest Biological Science Collection Agricultural Science Database Health & Medical Collection (Alumni Edition) Medical Database Algology Mycology and Protozoology Abstracts (Microbiology C) Biological Science Database Engineering Database Nursing & Allied Health Premium Advanced Technologies & Aerospace Database ProQuest Advanced Technologies & Aerospace Collection Biotechnology and BioEngineering Abstracts Environmental Science Database Materials Science Collection ProQuest Central Premium ProQuest One Academic (New) Publicly Available Content Database ProQuest Health & Medical Research Collection ProQuest One Academic Middle East (New) ProQuest One Health & Nursing ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Applied & Life Sciences ProQuest One Academic (retired) ProQuest One Academic UKI Edition ProQuest Central China Engineering Collection Environmental Science Collection Genetics Abstracts MEDLINE - Academic PubMed Central (Full Participant titles) DOAJ Directory of Open Access Journals |
| DatabaseTitle | CrossRef MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) Agricultural Science Database Publicly Available Content Database ProQuest Central Student ProQuest Advanced Technologies & Aerospace Collection ProQuest Central Essentials Nucleic Acids Abstracts SciTech Premium Collection ProQuest Central China Environmental Sciences and Pollution Management ProQuest One Applied & Life Sciences ProQuest One Sustainability Health Research Premium Collection Meteorological & Geoastrophysical Abstracts Natural Science Collection Health & Medical Research Collection Biological Science Collection ProQuest Central (New) ProQuest Medical Library (Alumni) Engineering Collection Advanced Technologies & Aerospace Collection Engineering Database Virology and AIDS Abstracts ProQuest Biological Science Collection ProQuest One Academic Eastern Edition Agricultural Science Collection ProQuest Hospital Collection ProQuest Technology Collection Health Research Premium Collection (Alumni) Biological Science Database Ecology Abstracts ProQuest Hospital Collection (Alumni) Biotechnology and BioEngineering Abstracts Environmental Science Collection Entomology Abstracts Nursing & Allied Health Premium ProQuest Health & Medical Complete ProQuest One Academic UKI Edition Environmental Science Database ProQuest Nursing & Allied Health Source (Alumni) Engineering Research Database ProQuest One Academic Meteorological & Geoastrophysical Abstracts - Academic ProQuest One Academic (New) Technology Collection Technology Research Database ProQuest One Academic Middle East (New) Materials Science Collection ProQuest Health & Medical Complete (Alumni) ProQuest Central (Alumni Edition) ProQuest One Community College ProQuest One Health & Nursing ProQuest Natural Science Collection ProQuest Pharma Collection ProQuest Central ProQuest Health & Medical Research Collection Genetics Abstracts ProQuest Engineering Collection Biotechnology Research Abstracts Health and Medicine Complete (Alumni Edition) ProQuest Central Korea Bacteriology Abstracts (Microbiology B) Algology Mycology and Protozoology Abstracts (Microbiology C) Agricultural & Environmental Science Collection AIDS and Cancer Research Abstracts Materials Science Database ProQuest Materials Science Collection ProQuest Public Health ProQuest Nursing & Allied Health Source ProQuest SciTech Collection Advanced Technologies & Aerospace Database ProQuest Medical Library Animal Behavior Abstracts Materials Science & Engineering Collection Immunology Abstracts ProQuest Central (Alumni) MEDLINE - Academic |
| DatabaseTitleList | MEDLINE - Academic Agricultural Science Database MEDLINE |
| Database_xml | – sequence: 1 dbid: DOA name: DOAJ Open Access Journals url: https://www.doaj.org/ sourceTypes: Open Website – sequence: 2 dbid: NPM name: PubMed url: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 3 dbid: PIMPY name: Publicly Available Content Database url: http://search.proquest.com/publiccontent sourceTypes: Aggregation Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Sciences (General) |
| DocumentTitleAlternate | Framework for Germany’s FBDG update: Food groups, nutrient goals, and objective functions |
| EISSN | 1932-6203 |
| ExternalDocumentID | 3176619637 oai_doaj_org_article_83922dd4edf74ffd9b9350b53cc9a1c1 PMC11903038 A830719271 40073305 10_1371_journal_pone_0313347 |
| Genre | Journal Article |
| GeographicLocations | Germany |
| GeographicLocations_xml | – name: Germany |
| GroupedDBID | --- 123 29O 2WC 53G 5VS 7RV 7X2 7X7 7XC 88E 8AO 8C1 8CJ 8FE 8FG 8FH 8FI 8FJ A8Z AAFWJ AAUCC AAWOE AAYXX ABDBF ABIVO ABJCF ABUWG ACCTH ACGFO ACIHN ACIWK ACPRK ACUHS ADBBV AEAQA AENEX AEUYN AFFHD AFKRA AFPKN AFRAH AHMBA ALMA_UNASSIGNED_HOLDINGS AOIJS APEBS ARAPS ATCPS BAIFH BAWUL BBNVY BBTPI BCNDV BENPR BGLVJ BHPHI BKEYQ BPHCQ BVXVI BWKFM CCPQU CITATION CS3 D1I D1J D1K DIK DU5 E3Z EAP EAS EBD EMOBN ESX EX3 F5P FPL FYUFA GROUPED_DOAJ GX1 HCIFZ HH5 HMCUK HYE IAO IEA IGS IHR IHW INH INR IOV IPY ISE ISR ITC K6- KB. KQ8 L6V LK5 LK8 M0K M1P M48 M7P M7R M7S M~E NAPCQ O5R O5S OK1 OVT P2P P62 PATMY PDBOC PHGZM PHGZT PIMPY PJZUB PPXIY PQGLB PQQKQ PROAC PSQYO PTHSS PV9 PYCSY RNS RPM RZL SV3 TR2 UKHRP WOQ WOW ~02 ~KM ADRAZ CGR CUY CVF ECM EIF ESTFP IPNFZ NPM PUEGO RIG ALIPV BBORY 3V. 7QG 7QL 7QO 7SN 7SS 7T5 7TG 7TM 7U9 7XB 8FD 8FK AZQEC C1K DWQXO FR3 GNUQQ H94 K9. KL. M7N P64 PKEHL PQEST PQUKI PRINS RC3 7X8 5PM |
| ID | FETCH-LOGICAL-c693t-c9318cc2312156b45dc3caa6cc9aff63298dbbf68a3814a8e008c75e3ddaf4ac3 |
| IEDL.DBID | FPL |
| ISICitedReferencesCount | 4 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=001443008600038&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 1932-6203 |
| IngestDate | Wed Aug 13 01:18:33 EDT 2025 Mon Nov 10 04:35:34 EST 2025 Tue Nov 04 02:03:32 EST 2025 Wed Oct 01 13:10:36 EDT 2025 Tue Oct 07 08:04:27 EDT 2025 Sat Nov 29 13:51:55 EST 2025 Sat Nov 29 10:31:20 EST 2025 Wed Nov 26 10:46:47 EST 2025 Wed Nov 26 10:46:42 EST 2025 Thu May 22 21:23:39 EDT 2025 Mon Sep 15 04:48:13 EDT 2025 Sat Nov 29 08:09:49 EST 2025 Tue Nov 18 22:14:08 EST 2025 |
| IsDoiOpenAccess | true |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 3 |
| Language | English |
| License | Copyright: © 2025 Schäfer et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Creative Commons Attribution License |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c693t-c9318cc2312156b45dc3caa6cc9aff63298dbbf68a3814a8e008c75e3ddaf4ac3 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Competing Interests: The authors have declared that no competing interests exist. |
| ORCID | 0000-0002-5607-491X 0000-0001-7321-2555 0000-0002-5789-2252 |
| OpenAccessLink | http://dx.doi.org/10.1371/journal.pone.0313347 |
| PMID | 40073305 |
| PQID | 3176619637 |
| PQPubID | 1436336 |
| PageCount | e0313347 |
| ParticipantIDs | plos_journals_3176619637 doaj_primary_oai_doaj_org_article_83922dd4edf74ffd9b9350b53cc9a1c1 pubmedcentral_primary_oai_pubmedcentral_nih_gov_11903038 proquest_miscellaneous_3176680287 proquest_journals_3176619637 gale_infotracmisc_A830719271 gale_infotracacademiconefile_A830719271 gale_incontextgauss_ISR_A830719271 gale_incontextgauss_IOV_A830719271 gale_healthsolutions_A830719271 pubmed_primary_40073305 crossref_primary_10_1371_journal_pone_0313347 crossref_citationtrail_10_1371_journal_pone_0313347 |
| PublicationCentury | 2000 |
| PublicationDate | 2025-03-12 |
| PublicationDateYYYYMMDD | 2025-03-12 |
| PublicationDate_xml | – month: 03 year: 2025 text: 2025-03-12 day: 12 |
| PublicationDecade | 2020 |
| PublicationPlace | United States |
| PublicationPlace_xml | – name: United States – name: San Francisco – name: San Francisco, CA USA |
| PublicationTitle | PloS one |
| PublicationTitleAlternate | PLoS One |
| PublicationYear | 2025 |
| Publisher | Public Library of Science Public Library of Science (PLoS) |
| Publisher_xml | – name: Public Library of Science – name: Public Library of Science (PLoS) |
| References | A Parlesak (pone.0313347.ref045) 2016; 11 K Rubens (pone.0313347.ref050) M Maillot (pone.0313347.ref057) 2011; 94 French Agency for Food, Environmental and Occupational Health & Safety (ANSES) (pone.0313347.ref066) M Maillot (pone.0313347.ref060) 2012; 42 LM Hlaing (pone.0313347.ref056) 2016 WHO (World Health Organization) (pone.0313347.ref001) 1998 R Broekema (pone.0313347.ref055) 2020; 112 C Baungaard (pone.0313347.ref054) 2024; 83 K Gedrich (pone.0313347.ref022) 1999; 53 A Berwin (pone.0313347.ref041) AC Schäfer (pone.0313347.ref007) 2021; 126 European Food Safety Authority (EFSA) (pone.0313347.ref021) 2021; 18 M Maillot (pone.0313347.ref023) 2010; 13 D Strohm (pone.0313347.ref042) 2016; 63 Deutsche Gesellschaft für Ernährung e. V. (DGE) (pone.0313347.ref044) 2015 WHO (World Health Organization) (pone.0313347.ref003) A Bechthold (pone.0313347.ref006) 2018; 9 R Gazan (pone.0313347.ref033) 2018; 238 M Berkelaar (pone.0313347.ref040) FAO (Food and Agriculture Organization), WHO (World Health Organization) (pone.0313347.ref004) 2019 L Schwingshackl (pone.0313347.ref028) 2019; 34 D van Wonderen (pone.0313347.ref067) 2023; 153 F Mariotti (pone.0313347.ref012) 2021; 12 R Core Team (pone.0313347.ref038) C Gonzalez Fischer (pone.0313347.ref005) 2016 EL Ferguson (pone.0313347.ref014) 2004; 134 JS Monteiro (pone.0313347.ref017) 2023; 12 R Blomhoff (pone.0313347.ref065) 2023 C van Dooren (pone.0313347.ref008) 2018; 5 FAO (Food and Agriculture Organization), WHO (World Health Organization) (pone.0313347.ref047) M Perignon (pone.0313347.ref062) 2016; 19 W Sichert-Hellert (pone.0313347.ref032) 2007; 20 EFSA (European Food Safety Authority) (pone.0313347.ref002) 2010; 8 M Perignon (pone.0313347.ref053) 2022; 80 D Karageorgou (pone.0313347.ref048) 2024; 27 Max Rubner-Institut, Bundesforschungsinstitut für Ernährung und Lebensmittel (MRI) (pone.0313347.ref029) 2008 X Gao (pone.0313347.ref058) 2006; 136 M Nordman (pone.0313347.ref025) 2023; 10 JB Ernst (pone.0313347.ref043) 2019; 66 T Heuer (pone.0313347.ref030) 2015; 113 C Krems (pone.0313347.ref027) G Wolfram (pone.0313347.ref037) 2015; 67 K Niforou (pone.0313347.ref026) FAO (Food and Agriculture Organization of the United Nations) (pone.0313347.ref068) R Gazan (pone.0313347.ref009) 2018; 9 M Banciu (pone.0313347.ref015) 2010 KJ Borgonjen-van den Berg (pone.0313347.ref046) 2021; 13 Australian Government, National Health and Medical Research Council (pone.0313347.ref011) EFSA (European Food Safety Authority) (pone.0313347.ref035) P Eustachio Colombo (pone.0313347.ref024) 2019; 16 S Yu-Poth (pone.0313347.ref036) 1999; 69 A Herforth (pone.0313347.ref016) 2019; 10 E Brink (pone.0313347.ref013) 2019; 22 Ministry of Agriculture Zambia (pone.0313347.ref049) BM Hartmann (pone.0313347.ref031) 2008; 21 S Theußl (pone.0313347.ref039) 2020; 94 M Maillot (pone.0313347.ref059) 2013; 33 C Merten (pone.0313347.ref019) 2011; 28 R Mazac (pone.0313347.ref061) 2022; 3 AM Babb (pone.0313347.ref052) 2019; 14 Dietary Guidelines Advisory Committee (pone.0313347.ref064) 2020 Deutsche Gesellschaft für Ernährung e. V. (DGE), Österreichische Gesellschaft für Ernährung, Schweizerische Gesellschaft für Ernährung (pone.0313347.ref034) 2021 EFSA (European Food Safety Authority) (pone.0313347.ref018) M Maillot (pone.0313347.ref051) 2009; 139 N Wilson (pone.0313347.ref010) 2019; 10 AA Yates (pone.0313347.ref063) 2006; 136 European Food Safety Authority (EFSA) (pone.0313347.ref020) 2011; 9 |
| References_xml | – volume: 238 start-page: 125 year: 2018 ident: pone.0313347.ref033 article-title: A methodology to compile food metrics related to diet sustainability into a single food database: Application to the French case publication-title: Food Chem doi: 10.1016/j.foodchem.2016.11.083 – start-page: S16-26 year: 2016 ident: pone.0313347.ref056 article-title: Local food-based complementary feeding recommendations developed by the linear programming approach to improve the intake of problem nutrients among 12-23-month-old Myanmar children publication-title: Br J Nutr – volume: 112 start-page: 1338 issue: 5 year: 2020 ident: pone.0313347.ref055 article-title: Future-proof and sustainable healthy diets based on current eating patterns in the Netherlands publication-title: Am J Clin Nutr doi: 10.1093/ajcn/nqaa217 – volume-title: Plates, pyramids, and planets. Developments in national healthy and sustainable dietary guidelines: a state of play assessment year: 2016 ident: pone.0313347.ref005 – volume-title: Food-based dietary guidelines. Third webinar: Diet modelling for food-based dietary guidelines. 2019 [updated 26 Oct 2020; cited 13 Dec 2024] ident: pone.0313347.ref068 – volume: 139 start-page: 1721 issue: 9 year: 2009 ident: pone.0313347.ref051 article-title: To meet nutrient recommendations, most French adults need to expand their habitual food repertoire publication-title: J Nutr doi: 10.3945/jn.109.107318 – volume-title: quadprog: functions to solve quadratic programming problems. Comprehensive R Archive Network (CRAN) 2019 [updated 30 Jun 2023; cited 13 Dec 2024] ident: pone.0313347.ref041 – volume: 18 start-page: EN-6507 issue: 3 year: 2021 ident: pone.0313347.ref021 article-title: FoodEx2 maintenance 2020 publication-title: EFSA Supporting Publication doi: 10.2903/sp.efsa.2021.EN-6507 – volume-title: lpSolve: Interface to ‘Lp_solve’ v. 5.5 to Solve Linear/Integer Programs. 2023 [cited 13 Dec 2024] ident: pone.0313347.ref040 – volume-title: FoodEx2 maintenance 2023. EFSA Supporting publications. 2024:EN-8813 ident: pone.0313347.ref026 – volume: 12 start-page: 590 issue: 3 year: 2021 ident: pone.0313347.ref012 article-title: Perspective: Modeling Healthy Eating Patterns for Food-Based Dietary Guidelines-Scientific Concepts, Methodological Processes, Limitations, and Lessons publication-title: Adv Nutr doi: 10.1093/advances/nmaa176 – volume: 10 start-page: 590 issue: 4 year: 2019 ident: pone.0313347.ref016 article-title: A Global Review of Food-Based Dietary Guidelines publication-title: Adv Nutr doi: 10.1093/advances/nmy130 – volume: 3 start-page: 286 issue: 4 year: 2022 ident: pone.0313347.ref061 article-title: Incorporation of novel foods in European diets can reduce global warming potential, water use and land use by over 80 publication-title: Nat Food doi: 10.1038/s43016-022-00489-9 – volume-title: Nordic nutrition recommendations 2023 year: 2023 ident: pone.0313347.ref065 doi: 10.6027/nord2023-003 – volume: 63 start-page: 2 issue: 2 year: 2016 ident: pone.0313347.ref042 article-title: Sonderdruck: Speisesalzzufuhr in Deutschland, gesundheitliche Folgen und resultierende Handlungsempfehlung publication-title: Ernährungs Umschau – volume-title: R: A language and environment for statistical computing. Vienna, Austria: 2024 [cited 2 Dec 2024] ident: pone.0313347.ref038 – volume-title: Preparation and use of food-based dietary guidelines. Joint FAO/WHO Consultation year: 1998 ident: pone.0313347.ref001 – volume: 21 start-page: S115 year: 2008 ident: pone.0313347.ref031 article-title: The German nutrient database: Basis for analysis of the nutritional status of the German population publication-title: Journal of Food Composition and Analysis doi: 10.1016/j.jfca.2007.03.008 – volume: 126 start-page: 942 issue: 6 year: 2021 ident: pone.0313347.ref007 article-title: 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 publication-title: Br J Nutr doi: 10.1017/S0007114520004857 – volume: 13 start-page: 3485 issue: 10 year: 2021 ident: pone.0313347.ref046 article-title: Sensitivity of Food-Based Recommendations Developed Using Linear Programming to Model Input Data in Young Kenyan Children publication-title: Nutrients doi: 10.3390/nu13103485 – volume-title: Zambia Food-Based Dietary Guidelines. Technical recommendations. 2021 [cited 13 Dec 2024] ident: pone.0313347.ref049 – volume: 10 start-page: S389 issue: Suppl_4 year: 2019 ident: pone.0313347.ref010 article-title: Achieving Healthy and Sustainable Diets: A Review of the Results of Recent Mathematical Optimization Studies publication-title: Adv Nutr doi: 10.1093/advances/nmz037 – volume: 16 start-page: 3019 issue: 17 year: 2019 ident: pone.0313347.ref024 article-title: Optimizing School Food Supply: Integrating Environmental, Health, Economic, and Cultural Dimensions of Diet Sustainability with Linear Programming publication-title: Int J Environ Res Public Health doi: 10.3390/ijerph16173019 – volume: 12 start-page: 3824 issue: 20 year: 2023 ident: pone.0313347.ref017 article-title: Is There a Convergence between the Food Classification Adopted by Food-Based Dietary Guidelines and Food Science and Technology? publication-title: Foods doi: 10.3390/foods12203824 – volume: 20 start-page: 63 issue: 1 year: 2007 ident: pone.0313347.ref032 article-title: German food composition database for dietary evaluations in children and adolescents publication-title: Journal of Food Composition and Analysis doi: 10.1016/j.jfca.2006.05.004 – volume: 134 start-page: 951 issue: 4 year: 2004 ident: pone.0313347.ref014 article-title: Food-based dietary guidelines can be developed and tested using linear programming analysis publication-title: J Nutr doi: 10.1093/jn/134.4.951 – volume: 27 start-page: e47 issue: 1 year: 2024 ident: pone.0313347.ref048 article-title: Harmonising dietary datasets for global surveillance: methods and findings from the Global Dietary Database publication-title: Public Health Nutr doi: 10.1017/S1368980024000211 – volume: 83 year: 2024 ident: pone.0313347.ref054 article-title: Operationalising dietary acceptability: A systematic review on how acceptability is applied in dietary optimisation models publication-title: Proc Nutr Soc doi: 10.1017/S0029665124007274 – volume: 69 start-page: 632 issue: 4 year: 1999 ident: pone.0313347.ref036 article-title: Effects of the National Cholesterol Education Program’s Step I and Step II dietary intervention programs on cardiovascular disease risk factors: a meta-analysis publication-title: Am J Clin Nutr doi: 10.1093/ajcn/69.4.632 – volume: 8 start-page: 1460 year: 2010 ident: pone.0313347.ref002 article-title: Scientific opinion on establishing food-based dietary guidelines publication-title: EFSA J – volume-title: Nationale Verzehrsstudie II. Ergebnisbericht, Teil 2. Die bundesweite Befragung zur Ernährung von Jugendlichen und Erwachsenen year: 2008 ident: pone.0313347.ref029 – volume-title: Fettzufuhr und Prävention ausgewählter ernährungsmitbedingter Krankheiten - Evidenzbasierte Leitlinie. 2nd ed year: 2015 ident: pone.0313347.ref044 – volume-title: Overview on tolerable upper intake levels as derived by the Scientific Committee on Food (SCF) and the EFSA Panel on Dietetic Products, Nutrition and Allergies (NDA). 2024 [cited 12 Dec 2024] ident: pone.0313347.ref035 – volume: 153 start-page: 2125 issue: 7 year: 2023 ident: pone.0313347.ref067 article-title: Iron Bioavailability Should be Considered when Modeling Omnivorous, Vegetarian, and Vegan Diets publication-title: J Nutr doi: 10.1016/j.tjnut.2023.05.011 – volume: 94 year: 2020 ident: pone.0313347.ref039 article-title: ROI: An Extensible R Optimization Infrastructure publication-title: J Stat Soft doi: 10.18637/jss.v094.i15 – volume: 13 start-page: 1178 issue: 8 year: 2010 ident: pone.0313347.ref023 article-title: Are the lowest-cost healthful food plans culturally and socially acceptable? publication-title: Public Health Nutr doi: 10.1017/S1368980009993028 – volume-title: Dual simplex. In: Cochran JJ, Cox LA, Keskinocak P, Kharoufeh JP, Smith JC, editors. Wiley Encyclopedia of Operations Research and Management Science year: 2010 ident: pone.0313347.ref015 – volume: 10 start-page: 1158257 year: 2023 ident: pone.0313347.ref025 article-title: Exploring healthy and climate-friendly diets for Danish adults: an optimization study using quadratic programming publication-title: Front Nutr doi: 10.3389/fnut.2023.1158257 – volume-title: Updating of the PNNS guidelines: revision of the food-based dietary guidelines. Request No 2012-SA-0103. 2016 [cited 9 Jan 2025] ident: pone.0313347.ref066 – volume: 136 start-page: 2457 issue: 10 year: 2006 ident: pone.0313347.ref063 article-title: Which dietary reference intake is best suited to serve as the basis for nutrition labeling for daily values? publication-title: J Nutr doi: 10.1093/jn/136.10.2457 – volume: 136 start-page: 1021 issue: 4 year: 2006 ident: pone.0313347.ref058 article-title: The maximal amount of dietary alpha-tocopherol intake in U.S. adults (NHANES 2001-2002) publication-title: J Nutr doi: 10.1093/jn/136.4.1021 – volume: 9 start-page: 2097 issue: 3 year: 2011 ident: pone.0313347.ref020 article-title: Use of the EFSA Comprehensive European Food Consumption Database in Exposure Assessment publication-title: EFSA J – volume: 94 start-page: 1127 issue: 4 year: 2011 ident: pone.0313347.ref057 article-title: The shortest way to reach nutritional goals is to adopt Mediterranean food choices: evidence from computer-generated personalized diets publication-title: Am J Clin Nutr doi: 10.3945/ajcn.111.016501 – volume: 113 start-page: 1603 issue: 10 year: 2015 ident: pone.0313347.ref030 article-title: Food consumption of adults in Germany: results of the German National Nutrition Survey II based on diet history interviews publication-title: Br J Nutr doi: 10.1017/S0007114515000744 – ident: pone.0313347.ref011 article-title: A modelling system to inform the revision of the Australian guide to healthy eating. 2011 [cited 13 Dec 2024]. – volume: 14 start-page: e0219895 issue: 7 year: 2019 ident: pone.0313347.ref052 article-title: A critique of the objective function utilized in calculating the Thrifty Food Plan publication-title: PLoS One doi: 10.1371/journal.pone.0219895 – volume-title: Scientific Report of the 2020 Dietary Guidelines Advisory Committee: Advisory Report to the Secretary of Health and Human Services and the Secretary of Agriculture year: 2020 ident: pone.0313347.ref064 – ident: pone.0313347.ref003 article-title: Food-based dietary guidelines in the WHO European Region. Copenhagen: 2003 [cited 19 Dec 2024]. – volume: 42 start-page: 174 issue: 2 year: 2012 ident: pone.0313347.ref060 article-title: A conflict between nutritionally adequate diets and meeting the 2010 dietary guidelines for sodium publication-title: Am J Prev Med doi: 10.1016/j.amepre.2011.10.009 – volume-title: FAO/WHO Global Individual Food consumption data Tool (FAO/WHO GIFT). Project brief updated as per August 10th, 2017. 2017 [updated 10 Aug 2017; cited 13 Dec 2024] ident: pone.0313347.ref047 – volume: 22 start-page: 2419 issue: 13 year: 2019 ident: pone.0313347.ref013 article-title: Development of healthy and sustainable food-based dietary guidelines for the Netherlands publication-title: Public Health Nutr doi: 10.1017/S1368980019001435 – volume-title: Food and environmentally responsible consumption: towards healthy food patterns for a healthy planet. Background document for the food triangle recommendations. 2021 [cited 13 Dec 2024] ident: pone.0313347.ref050 – volume: 66 start-page: 26 year: 2019 ident: pone.0313347.ref043 article-title: Quantitative Empfehlung zur Zuckerzufuhr in Deutschland. Kurzfassung des Konsensuspapiers der Deutschen Adipositas-Gesellschaft e. V. (DAG), der Deutschen Diabetes Gesellschaft e. V. (DDG) und der Deutschen Gesellschaft für Ernährung e. V. (DGE) publication-title: Ernährungs Umschau – volume: 28 start-page: 975 issue: 8 year: 2011 ident: pone.0313347.ref019 article-title: Methodological characteristics of the national dietary surveys carried out in the European Union as included in the European Food Safety Authority (EFSA) Comprehensive European Food Consumption Database publication-title: Food Addit Contam Part A Chem Anal Control Expo Risk Assess doi: 10.1080/19440049.2011.576440 – volume: 11 start-page: e0163411 issue: 10 year: 2016 ident: pone.0313347.ref045 article-title: Use of Linear Programming to Develop Cost-Minimized Nutritionally Adequate Health Promoting Food Baskets publication-title: PLoS One doi: 10.1371/journal.pone.0163411 – volume: 9 start-page: 602 issue: 5 year: 2018 ident: pone.0313347.ref009 article-title: Mathematical Optimization to Explore Tomorrow’s Sustainable Diets: A Narrative Review publication-title: Adv Nutr doi: 10.1093/advances/nmy049 – volume-title: Sustainable healthy diets - Guiding principles. Rome year: 2019 ident: pone.0313347.ref004 – volume: 67 start-page: 141 issue: 3 year: 2015 ident: pone.0313347.ref037 article-title: Evidence-Based Guideline of the German Nutrition Society: Fat Intake and Prevention of Selected Nutrition-Related Diseases publication-title: Ann Nutr Metab doi: 10.1159/000437243 – start-page: 40 volume-title: Lebensmittelverzehr und Nährstoffzufuhr - Ergebnisse der Nationalen Verzehrsstudie II. In: Deutsche Gesellschaft für Ernährung e. V., editor. 12. Ernährungsbericht 2012 ident: pone.0313347.ref027 – volume: 34 start-page: 765 issue: 8 year: 2019 ident: pone.0313347.ref028 article-title: Intake of 12 food groups and disability-adjusted life years from coronary heart disease, stroke, type 2 diabetes, and colorectal cancer in 16 European countries publication-title: Eur J Epidemiol doi: 10.1007/s10654-019-00523-4 – volume: 80 start-page: 579 issue: 3 year: 2022 ident: pone.0313347.ref053 article-title: Advantages and limitations of the methodological approaches used to study dietary shifts towards improved nutrition and sustainability publication-title: Nutr Rev doi: 10.1093/nutrit/nuab091 – volume: 5 start-page: 48 year: 2018 ident: pone.0313347.ref008 article-title: A Review of the Use of Linear Programming to Optimize Diets, Nutritiously, Economically and Environmentally publication-title: Front Nutr doi: 10.3389/fnut.2018.00048 – ident: pone.0313347.ref018 article-title: The food classification and description system FoodEx2 (revision 2). 2015 [cited 13 Dec 2024]. – volume: 19 start-page: 2662 issue: 14 year: 2016 ident: pone.0313347.ref062 article-title: How low can dietary greenhouse gas emissions be reduced without impairing nutritional adequacy, affordability and acceptability of the diet? A modelling study to guide sustainable food choices publication-title: Public Health Nutr doi: 10.1017/S1368980016000653 – volume: 33 start-page: 188 issue: 3 year: 2013 ident: pone.0313347.ref059 article-title: Food pattern modeling shows that the 2010 Dietary Guidelines for sodium and potassium cannot be met simultaneously publication-title: Nutr Res doi: 10.1016/j.nutres.2013.01.004 – volume: 9 start-page: 544 issue: 5 year: 2018 ident: pone.0313347.ref006 article-title: Perspective: Food-Based Dietary Guidelines in Europe-Scientific Concepts, Current Status, and Perspectives publication-title: Adv Nutr doi: 10.1093/advances/nmy033 – volume-title: Referenzwerte für die Nährstoffzufuhr. 2nd ed. Bonn year: 2021 ident: pone.0313347.ref034 – volume: 53 start-page: 309 issue: 4 year: 1999 ident: pone.0313347.ref022 article-title: How optimal are computer-calculated optimal diets? publication-title: Eur J Clin Nutr doi: 10.1038/sj.ejcn.1600727 |
| SSID | ssj0053866 |
| Score | 2.4991066 |
| Snippet | For a growing number of food-based dietary guidelines (FBDGs), diet optimization is the tool of choice to account for the complex demands of healthy and... Background For a growing number of food-based dietary guidelines (FBDGs), diet optimization is the tool of choice to account for the complex demands of healthy... BackgroundFor a growing number of food-based dietary guidelines (FBDGs), diet optimization is the tool of choice to account for the complex demands of healthy... Background For a growing number of food-based dietary guidelines (FBDGs), diet optimization is the tool of choice to account for the complex demands of healthy... |
| SourceID | plos doaj pubmedcentral proquest gale pubmed crossref |
| SourceType | Open Website Open Access Repository Aggregation Database Index Database Enrichment Source |
| StartPage | e0313347 |
| SubjectTerms | Adult Biology and Life Sciences Constraints Deviation Diet Dietary guidelines Female Food Food - classification Food groups Food habits Food intake Fruits Germany Grain Guidelines Health aspects Humans Male Mathematical models Meat Meat products Medicine and Health Sciences Middle Aged Models, Theoretical Nutrients Nutrition Nutrition Policy Objective function Oils & fats Optimization Optimization models People and Places Physical Sciences Poultry Requirements Vegetable oils |
| SummonAdditionalLinks | – databaseName: DOAJ Directory of Open Access Journals dbid: DOA link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1Lj9MwELZQxYELYnltdwsYhARIm900ThyHW0EUkNCCeGlvlh9xt2iVVE2LxG_gTzMTO1GDVloOXHqwv1bpzHge7fgbQp7GXKtEZTrKrFJRmsCLLoyOksJYnkNB5rymP-Snp-LsrPi0M-oLe8I8PbAX3AkG8MTatLQuT52zhS5YFuuMGVOoqWkLH8h6umLK-2A4xZyHi3Isn54EvRyv6qo8RrZChuNUdgJRy9ffe-XR6qJuLks5_-6c3AlF81vkZsgh6cw_-x65Vla3yV44pQ19HqikX9whv2fUj4juXBx1XTMWhWyVWrA__EWBQhpI36KTrmC9thEGN0vtstyo9S-62CIZFjbI0wSi7Us6BwxtL4Q0R7RCQn94UrqowZaPqKosrfUP70kpBs7Wtu-Sb_M3X1-_i8L4hcjwgm0iU8B5NwYSQEgLuE4za5hRiqPgneMsKYTV2nGhIOqnSpSQTpg8K5m1yqXKsHtkVIHA9wl1Uxu7KazGhoGTMIUwqUtKnXIoUK2wY8I6XUgTuMlxRMaFbP9wy6FG8aKVqEEZNDgmUf-ulefmuAL_CtXcY5FZu10Ae5PB3uRV9jYmj9BIpL-m2vsHORPgLSFdzgHxpEUgu0aF7TsLtW0a-f7j938Affk8AD0LIFeDOIwKVybgOyFr1wA5GSDBR5jB9j6adCeVRjLkBUXnC0KZdGZ--fbjfhs_FFvyqrLeBoyA9BQw9_2p6CWbtrNA42xMxOC8DEQ_3KmW5y25-RQyVEirxMH_UNYhuZHgvGbsv0wmZLRZb8sH5Lr5uVk264ety_gD8eN1OA priority: 102 providerName: Directory of Open Access Journals – databaseName: Biological Science Database dbid: M7P link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1Lj9MwELagcOACLK8tLGAQEiBtdps4D4cLKogCElpWvLS3yB7HpWiVlKZF4jfwp5lxnLBBK0Di0kM8iWp75vPnZPwNYw8mqVaRSnSQGKWCOMIfnYMOohxMmuGGzLYz_SY7OJBHR_mhf-HW-LTKDhMdUJsa6B35viAlQ3KX7Onya0BVo-jrqi-hcZadI5UE4VL3DjskxlhOU39cTmThvp-dvWVdlXukWSioqMqJ5cip9vfYPFoe181pxPP3_MkTC9Ls0v925TK76Kkon7a-s8XOlNUVtuWDveGPvCL146vsx5S3laY7pOS2y-niSHq5QTemFxMc2SR_SVhf4fXaBLRGGm4W5VqtvvP5hjS1KM-eR7hoP-EztOHuXEmzyyuqC4Bd5fMaQ2KXq8rwWn9pAZnT-utC5Br7OHvx4fmrwFdxCCDNxTqAHGEDAHkkzlCq48SAAKVSgFxZm4ool0Zrm0qF5CFWskRWAllSCmOUjRWI62xU4YxtM25DM7EhXp2AQKyBXEJso1LHKe5zjTRjJrrJLMBLnFOljePCfbfLcKvTDm1BLlB4FxizoL9r2Up8_MX-GflJb0sC3e5CvZoXPt4L4p2RMXFpbBZba3Kdi2SiE0HdDiEcs7vkZUV72rWHmWIqEXSRdWdocd9ZkEhHRVlAc7VpmuL120__YPT-3cDooTeyNQ4HKH_yAvtE4l8Dy52BJUINDJq3KSa6UWmKX56Md3a-fnrzvb6ZHkqZfVVZb7yNRJaLNjfasOpHNnYlRSfJmMlBwA2GfthSLT47jfQQiS6yM3nzz__rFrsQUUFnStCMdthovdqUt9l5-LZeNKs7Dk1-AoQDgoA priority: 102 providerName: ProQuest |
| Title | A methodological framework for deriving the German food-based dietary guidelines 2024: Food groups, nutrient goals, and objective functions |
| URI | https://www.ncbi.nlm.nih.gov/pubmed/40073305 https://www.proquest.com/docview/3176619637 https://www.proquest.com/docview/3176680287 https://pubmed.ncbi.nlm.nih.gov/PMC11903038 https://doaj.org/article/83922dd4edf74ffd9b9350b53cc9a1c1 http://dx.doi.org/10.1371/journal.pone.0313347 |
| Volume | 20 |
| WOSCitedRecordID | wos001443008600038&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVAON databaseName: DOAJ Open Access Journals customDbUrl: eissn: 1932-6203 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0053866 issn: 1932-6203 databaseCode: DOA dateStart: 20060101 isFulltext: true titleUrlDefault: https://www.doaj.org/ providerName: Directory of Open Access Journals – providerCode: PRVHPJ databaseName: ROAD: Directory of Open Access Scholarly Resources customDbUrl: eissn: 1932-6203 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0053866 issn: 1932-6203 databaseCode: M~E dateStart: 20060101 isFulltext: true titleUrlDefault: https://road.issn.org providerName: ISSN International Centre – providerCode: PRVPQU databaseName: Advanced Technologies & Aerospace Database customDbUrl: eissn: 1932-6203 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0053866 issn: 1932-6203 databaseCode: P5Z dateStart: 20061201 isFulltext: true titleUrlDefault: https://search.proquest.com/hightechjournals providerName: ProQuest – providerCode: PRVPQU databaseName: Agricultural Science Database customDbUrl: eissn: 1932-6203 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0053866 issn: 1932-6203 databaseCode: M0K dateStart: 20061201 isFulltext: true titleUrlDefault: https://search.proquest.com/agriculturejournals providerName: ProQuest – providerCode: PRVPQU databaseName: Biological Science Database customDbUrl: eissn: 1932-6203 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0053866 issn: 1932-6203 databaseCode: M7P dateStart: 20061201 isFulltext: true titleUrlDefault: http://search.proquest.com/biologicalscijournals providerName: ProQuest – providerCode: PRVPQU databaseName: Engineering Database customDbUrl: eissn: 1932-6203 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0053866 issn: 1932-6203 databaseCode: M7S dateStart: 20061201 isFulltext: true titleUrlDefault: http://search.proquest.com providerName: ProQuest – providerCode: PRVPQU databaseName: Environmental Science Database customDbUrl: eissn: 1932-6203 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0053866 issn: 1932-6203 databaseCode: PATMY dateStart: 20061201 isFulltext: true titleUrlDefault: http://search.proquest.com/environmentalscience providerName: ProQuest – providerCode: PRVPQU databaseName: Materials Science Database customDbUrl: eissn: 1932-6203 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0053866 issn: 1932-6203 databaseCode: KB. dateStart: 20061201 isFulltext: true titleUrlDefault: http://search.proquest.com/materialsscijournals providerName: ProQuest – providerCode: PRVPQU databaseName: Nursing & Allied Health Database customDbUrl: eissn: 1932-6203 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0053866 issn: 1932-6203 databaseCode: 7RV dateStart: 20061201 isFulltext: true titleUrlDefault: https://search.proquest.com/nahs providerName: ProQuest – providerCode: PRVPQU databaseName: ProQuest - Health & Medical Complete保健、医学与药学数据库 customDbUrl: eissn: 1932-6203 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0053866 issn: 1932-6203 databaseCode: 7X7 dateStart: 20061201 isFulltext: true titleUrlDefault: https://search.proquest.com/healthcomplete providerName: ProQuest – providerCode: PRVPQU databaseName: ProQuest Central customDbUrl: eissn: 1932-6203 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0053866 issn: 1932-6203 databaseCode: BENPR dateStart: 20061201 isFulltext: true titleUrlDefault: https://www.proquest.com/central providerName: ProQuest – providerCode: PRVPQU databaseName: Public Health Database customDbUrl: eissn: 1932-6203 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0053866 issn: 1932-6203 databaseCode: 8C1 dateStart: 20061201 isFulltext: true titleUrlDefault: https://search.proquest.com/publichealth providerName: ProQuest – providerCode: PRVPQU databaseName: Publicly Available Content Database customDbUrl: eissn: 1932-6203 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0053866 issn: 1932-6203 databaseCode: PIMPY dateStart: 20061201 isFulltext: true titleUrlDefault: http://search.proquest.com/publiccontent providerName: ProQuest – providerCode: PRVATS databaseName: Public Library of Science (PLoS) Journals Open Access customDbUrl: eissn: 1932-6203 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0053866 issn: 1932-6203 databaseCode: FPL dateStart: 20060101 isFulltext: true titleUrlDefault: http://www.plos.org/publications/ providerName: Public Library of Science |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3db9MwELdYxwMvwPhaoRSDkABpKUmcD4e3dlph2laijk2Fl8ix41I0JVXTIvE38E9zly_ItAl4uQf75yg--84_J-czIS9NLxa2cGPDVUIYjg0iDmRs2IFUng8bMl2O9LE_mfDZLAh_bxQv_cFnvvW20ulgmaXJADMNMsffIts28zwM4RqHx7XnBdv1vOp43HUtW8tPkaW_8cWd5UWWX0U0L8dL_rEAje_876vfJbcrqkmH5dzYITeS9B7ZqYw5p6-rjNNv7pOfQ1reJF17QqrrmC0KpJYqmKb44YECW6Tv0ZenUJ4pA9dARdUiWYvVDzrfYM4sjKOnNizK7-gYMLQ4N5Lv0RTz_kPX6DyDKb9HRapoFn8rHS7F9bUwgQfkbHzwaf-DUd3SYEgvYGtDBuAWpASeCOzBix1XSSaF8KQMhNYeswOu4lh7XAA5cARPgHVI302YUkI7QrKHpJOCgnYJ1ZYytQWlpmTgS2TApaPtJHY82McqrrqE1YMXySqFOd6kcREV_-V82MqUqo1Q41Gl8S4xmlbLMoXHX_AjnBcNFhNwFwUwtFFlzxHySlspJ1Had7RWQRww14xdht22pNUlz3BWReVp1saNREMOThVYtQ-IFwUCk3CkGOUzF5s8jw4_nv8D6HTaAr2qQDoDdUhRnayAPmFyrxay10KCK5Gt6l20gVorecQwfSj6aFBKr7aLq6ufN9X4UIzcS5NsU2E4sFjAPCrNqNGsU1wZarpdwlsG1lJ9uyZdfC1yoFtAZIF98cfXv_ITcsvGy5ox-NLukc56tUmekpvy-3qRr_pky5-eo5z5heQg-b7VJ9ujg0k47RcfZ_qFfwF5NBqAPDGPUPphIU9Bhu4XaBEenoSffwHT_n1L |
| linkProvider | Public Library of Science |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1Lb9NAEF6VgAQXoLwaKHRBIECq23jXTySEwiM0aiiolKq3Zb3rDUGVHeIE1N_Af-E3MmOvTY0q4NIDlxy8n614PPPNrD0PQu73gkQy6SeOr6V0PAY_SawSh8VKByFsyEz1pEfhzk50cBC_WyI_6loYTKusObEkap0rfEe-ybGTIapL-Gz6xcGpUfh1tR6hUanFdnr0DbZsxdPhS3i-DxgbvNp7seXYqQKOCmI-d1QMaqwUxDXg7YLE87XiSspAqVgaE3AWRzpJTBBJcGaejFLwkir0U661NJ5UHK57hpwFHncxhSzc3a-ZH7gjCGx5Hg_dTasNG9M8SzewRyLHIS7H3F85JaDxBZ3pYV6cFOj-nq95zAEOLv1vortMLtpQm_Yr21gmS2l2hSxbMivoI9tx-_FV8r1Pq0natSegps5ZoxDUUw1mii9eKETL9DX6sgyO59rBGEBTPUnncnZExwvsGYZ1BJRBUPKEDgBDy7qZYp1mOPcAREvHOZj8OpWZpnnyuXI4FOOLkgKukQ-nIpTrpJOBhqwQalzdMy4c7SkOXKriSHmGpYkXwD5eR7pLeK08QtkW7jhJ5FCU3yVD2MpVohWocsKqXJc4zVnTqoXJX_DPUS8bLDYgLw_ks7GwfCYwrmZae6k2oWeMjpOY-73E53jbrnK7ZA21WlTVvA2Nin4ETgV2FSEg7pUIbEKSYZbTWC6KQgzf7v8D6P1uC_TQgkwO4lDSVpbAPWFzsxZytYUEKlWt5RW0wVoqhfhlOXBmbVsnL99tlvGimLmYpfnCYiKI4gFzozLjRrJeOTK153dJ1DLwlujbK9nkU9kD3oVAHqLP6Oaf_9caOb-192YkRsOd7VvkAsPh1ZiMylZJZz5bpLfJOfV1Pilmd0omo-Tjadv_T0kh4f8 |
| linkToPdf | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1Jb9NAFB6VgBAXoGwNFDogECDVTezxioRQaAlErULFpt6GWTwhqLJDnID6G_hH_Dres8emRhVw6YFLDp7PVvz8lm_stxByvx9K4YlAOoEWwvE9-JGJko6XKB1GsCEz1ZPei8bj-OAg2V8hP-paGEyrrH1i6ah1rvAdeY9hJ0NUl6hnbFrE_s7w2eyLgxOk8EtrPU6jUpHd9OgbbN-Kp6MdeNYPPG_44t32K8dOGHBUmLCFoxJQaaWA40DkC6UfaMWUEKFSiTAmZF4SaylNGAsIbL6IU4iYKgpSprUwvlAMrnuGnI0YaDFWqW836SXgR8LQluqxyO1Zzdia5Vm6hf0SGQ50ORYKy4kBTVzozA7z4iTS-3vu5rFgOLz0P4vxMrloKTgdVDazSlbS7ApZtU6uoI9sJ-7HV8n3Aa0mbNcRgpo6l40C2acazBdfyFBg0fQlxrgMjufaQW6gqZ6mCzE_opMl9hLD-gLqAVl5QoeAoWU9TbFJM5yHAGKmkxxcwSYVmaa5_FwFIoq8o3QN18j7UxHKddLJQFvWCDWu7hsXjvYVAx-rklj5xkulH8L-Xse6S1itSFzZ1u44YeSQl98rI9jiVaLlqH7cql-XOM1Zs6q1yV_wz1FHGyw2Ji8P5PMJt36OI9_2tPZTbSLfGJ3IhAV9GTC8bVe5XbKBGs6rKt_GvfJBDMEGdhsRIO6VCGxOkqF-TsSyKPjo9Yd_AL190wI9tCCTgziUsBUncE_Y9KyFXG8hwcWq1vIa2mMtlYL_siI4s7azk5fvNst4UcxozNJ8aTExsHvA3KhMupGsX45S7QddEreMvSX69ko2_VT2hneB4AMrjW_--X9tkPNg9nxvNN69RS54ONMac1S9ddJZzJfpbXJOfV1Mi_md0qlR8vG0zf8nPt3qWg |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=A+methodological+framework+for+deriving+the+German+food-based+dietary+guidelines+2024%3A+Food+groups%2C+nutrient+goals%2C+and+objective+functions&rft.jtitle=PloS+one&rft.au=Sch%C3%A4fer%2C+Anne+Carolin&rft.au=Boeing%2C+Heiner&rft.au=Gazan%2C+Rozenn&rft.au=Conrad%2C+Johanna&rft.date=2025-03-12&rft.issn=1932-6203&rft.eissn=1932-6203&rft.volume=20&rft.issue=3&rft.spage=e0313347&rft_id=info:doi/10.1371%2Fjournal.pone.0313347&rft.externalDBID=NO_FULL_TEXT |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1932-6203&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1932-6203&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1932-6203&client=summon |