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Integrating the Totality of Food and Nutrition Evidence for Public Health Decision Making and Communication
The interpretation and integration of epidemiological studies detecting weak associations (RR < 2) with data from other study designs (e.g., animal models and human intervention trials) is both challenging and vital for making science-based dietary recommendations in the nutrition and food safety...
Autores principales: | , , , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
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Taylor & Francis
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3024840/ https://www.ncbi.nlm.nih.gov/pubmed/21132578 http://dx.doi.org/10.1080/10408398.2010.526825 |
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author | Navia, Juan L. Byers, Tim Djordjevic, Darinka Hentges, Eric King, Janet Klurfeld, David Llewellyn, Craig Milner, John Skrypec, Daniel Weed, Douglas |
author_facet | Navia, Juan L. Byers, Tim Djordjevic, Darinka Hentges, Eric King, Janet Klurfeld, David Llewellyn, Craig Milner, John Skrypec, Daniel Weed, Douglas |
author_sort | Navia, Juan L. |
collection | PubMed |
description | The interpretation and integration of epidemiological studies detecting weak associations (RR < 2) with data from other study designs (e.g., animal models and human intervention trials) is both challenging and vital for making science-based dietary recommendations in the nutrition and food safety communities. The 2008 ILSI North America “Decision-Making for Recommendations and Communication Based on Totality of Food-Related Research” workshop provided an overview of epidemiological methods, and case-study examples of how weak associations have been incorporated into decision making for nutritional recommendations. Based on the workshop presentations and dialogue among the participants, three clear strategies were provided for the use of weak associations in informing nutritional recommendations for optimal health. First, enable more effective integration of data from all sources through the use of genetic and nutritional biomarkers; second, minimize the risk of bias and confounding through the adoption of rigorous quality-control standards, greater emphasis on the replication of study results, and better integration of results from independent studies, perhaps using adaptive study designs and Bayesian meta-analysis methods; and third, emphasize more effective and truthful communication to the public about the evolving understanding of the often complex relationship between nutrition, lifestyle, and optimal health. |
format | Text |
id | pubmed-3024840 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | Taylor & Francis |
record_format | MEDLINE/PubMed |
spelling | pubmed-30248402011-01-24 Integrating the Totality of Food and Nutrition Evidence for Public Health Decision Making and Communication Navia, Juan L. Byers, Tim Djordjevic, Darinka Hentges, Eric King, Janet Klurfeld, David Llewellyn, Craig Milner, John Skrypec, Daniel Weed, Douglas Crit Rev Food Sci Nutr Article The interpretation and integration of epidemiological studies detecting weak associations (RR < 2) with data from other study designs (e.g., animal models and human intervention trials) is both challenging and vital for making science-based dietary recommendations in the nutrition and food safety communities. The 2008 ILSI North America “Decision-Making for Recommendations and Communication Based on Totality of Food-Related Research” workshop provided an overview of epidemiological methods, and case-study examples of how weak associations have been incorporated into decision making for nutritional recommendations. Based on the workshop presentations and dialogue among the participants, three clear strategies were provided for the use of weak associations in informing nutritional recommendations for optimal health. First, enable more effective integration of data from all sources through the use of genetic and nutritional biomarkers; second, minimize the risk of bias and confounding through the adoption of rigorous quality-control standards, greater emphasis on the replication of study results, and better integration of results from independent studies, perhaps using adaptive study designs and Bayesian meta-analysis methods; and third, emphasize more effective and truthful communication to the public about the evolving understanding of the often complex relationship between nutrition, lifestyle, and optimal health. Taylor & Francis 2010-12-04 2010-12 /pmc/articles/PMC3024840/ /pubmed/21132578 http://dx.doi.org/10.1080/10408398.2010.526825 Text en © 2010 Taylor & Francis http://www.informaworld.com/mpp/uploads/iopenaccess_tcs.pdf This is an open access article distributed under the Supplemental Terms and Conditions for iOpenAccess articles published in Taylor & Francis journals (http://www.informaworld.com/mpp/uploads/iopenaccess_tcs.pdf) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Article Navia, Juan L. Byers, Tim Djordjevic, Darinka Hentges, Eric King, Janet Klurfeld, David Llewellyn, Craig Milner, John Skrypec, Daniel Weed, Douglas Integrating the Totality of Food and Nutrition Evidence for Public Health Decision Making and Communication |
title | Integrating the Totality of Food and Nutrition Evidence for Public Health Decision Making and Communication |
title_full | Integrating the Totality of Food and Nutrition Evidence for Public Health Decision Making and Communication |
title_fullStr | Integrating the Totality of Food and Nutrition Evidence for Public Health Decision Making and Communication |
title_full_unstemmed | Integrating the Totality of Food and Nutrition Evidence for Public Health Decision Making and Communication |
title_short | Integrating the Totality of Food and Nutrition Evidence for Public Health Decision Making and Communication |
title_sort | integrating the totality of food and nutrition evidence for public health decision making and communication |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3024840/ https://www.ncbi.nlm.nih.gov/pubmed/21132578 http://dx.doi.org/10.1080/10408398.2010.526825 |
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