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The Development and Evaluation of a Literature-Based Dietary Index for Gut Microbiota

OBJECTIVES: To develop and evaluate a novel dietary index for gut microbiota (DI-GM) that captures dietary composition related to gut microbiota profiles. METHODS: A literature review of longitudinal studies on the effect of diet on gut microbiota in adult populations was conducted, extracting those...

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Autores principales: Kase, Bezawit Eyob, Liese, Angela, Zhang, Jiajia, Murphy, E Angela, Zhao, Longgang, Steck, Susan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9193695/
http://dx.doi.org/10.1093/cdn/nzac054.026
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author Kase, Bezawit Eyob
Liese, Angela
Zhang, Jiajia
Murphy, E Angela
Zhao, Longgang
Steck, Susan
author_facet Kase, Bezawit Eyob
Liese, Angela
Zhang, Jiajia
Murphy, E Angela
Zhao, Longgang
Steck, Susan
author_sort Kase, Bezawit Eyob
collection PubMed
description OBJECTIVES: To develop and evaluate a novel dietary index for gut microbiota (DI-GM) that captures dietary composition related to gut microbiota profiles. METHODS: A literature review of longitudinal studies on the effect of diet on gut microbiota in adult populations was conducted, extracting those dietary components with evidence of beneficial or harmful effects on gut microbiota. Using 24-hour dietary recall data collected on two separate days from the National Health and Nutrition Examination Survey (NHANES, 2005–2010, n = 3,821), DI-GM scores were computed and associations with biomarkers of gut microbiota diversity (urinary enterodiol and enterolactone) were examined using linear regression. Analyses were adjusted for potential confounding effect of sociodemographic and lifestyle factors. Lastly, congruence of the DI-GM with pre-existing dietary indices (Healthy Eating Index (HEI-2015) and Mediterranean Diet Score (MDS)) were examined. RESULTS: From a review of 121 articles, 14 foods were identified as components of the DI-GM, including fermented dairy, chickpeas, soybean, whole grains, fiber, cranberries, avocados, broccoli, coffee, and green tea (beneficial components) and red meat, processed meat, refined grains, and high fat diet (≥40% of energy from fat) (harmful components). Each component was scored 0 or 1 based on sex-specific median intakes and scores were summed to develop the DI-GM score. In NHANES, DI-GM scores ranged from 0–13 because intake of green tea was not reported, and the mean DI-GM was 4.8 (SD = 0.04). Positive associations between DI-GM and urinary enterodiol (β=0.123, 95%CI: 0.079, 0.166) and enterolactone (β=0.138, 95%CI: 0.091, 0.184) were observed in multivariable-adjusted models. The DI-GM showed moderate positive correlation with HEI-2015 (r = 0.537, p < 0.001) and MDS (r = 0.423, p < 0.001). CONCLUSIONS: A novel DI-GM was developed based on published literature to score the quality of diet in terms of maintaining healthy gut microbiota. The DI-GM was significantly associated with markers of gut microbiota diversity in NHANES, signifying the potential utility of this index for gut-health related studies. FUNDING SOURCES: None.
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spelling pubmed-91936952022-06-14 The Development and Evaluation of a Literature-Based Dietary Index for Gut Microbiota Kase, Bezawit Eyob Liese, Angela Zhang, Jiajia Murphy, E Angela Zhao, Longgang Steck, Susan Curr Dev Nutr Dietary Patterns OBJECTIVES: To develop and evaluate a novel dietary index for gut microbiota (DI-GM) that captures dietary composition related to gut microbiota profiles. METHODS: A literature review of longitudinal studies on the effect of diet on gut microbiota in adult populations was conducted, extracting those dietary components with evidence of beneficial or harmful effects on gut microbiota. Using 24-hour dietary recall data collected on two separate days from the National Health and Nutrition Examination Survey (NHANES, 2005–2010, n = 3,821), DI-GM scores were computed and associations with biomarkers of gut microbiota diversity (urinary enterodiol and enterolactone) were examined using linear regression. Analyses were adjusted for potential confounding effect of sociodemographic and lifestyle factors. Lastly, congruence of the DI-GM with pre-existing dietary indices (Healthy Eating Index (HEI-2015) and Mediterranean Diet Score (MDS)) were examined. RESULTS: From a review of 121 articles, 14 foods were identified as components of the DI-GM, including fermented dairy, chickpeas, soybean, whole grains, fiber, cranberries, avocados, broccoli, coffee, and green tea (beneficial components) and red meat, processed meat, refined grains, and high fat diet (≥40% of energy from fat) (harmful components). Each component was scored 0 or 1 based on sex-specific median intakes and scores were summed to develop the DI-GM score. In NHANES, DI-GM scores ranged from 0–13 because intake of green tea was not reported, and the mean DI-GM was 4.8 (SD = 0.04). Positive associations between DI-GM and urinary enterodiol (β=0.123, 95%CI: 0.079, 0.166) and enterolactone (β=0.138, 95%CI: 0.091, 0.184) were observed in multivariable-adjusted models. The DI-GM showed moderate positive correlation with HEI-2015 (r = 0.537, p < 0.001) and MDS (r = 0.423, p < 0.001). CONCLUSIONS: A novel DI-GM was developed based on published literature to score the quality of diet in terms of maintaining healthy gut microbiota. The DI-GM was significantly associated with markers of gut microbiota diversity in NHANES, signifying the potential utility of this index for gut-health related studies. FUNDING SOURCES: None. Oxford University Press 2022-06-14 /pmc/articles/PMC9193695/ http://dx.doi.org/10.1093/cdn/nzac054.026 Text en © The Author 2022. Published by Oxford University Press on behalf of The International Society for Human and Animal Mycology. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Dietary Patterns
Kase, Bezawit Eyob
Liese, Angela
Zhang, Jiajia
Murphy, E Angela
Zhao, Longgang
Steck, Susan
The Development and Evaluation of a Literature-Based Dietary Index for Gut Microbiota
title The Development and Evaluation of a Literature-Based Dietary Index for Gut Microbiota
title_full The Development and Evaluation of a Literature-Based Dietary Index for Gut Microbiota
title_fullStr The Development and Evaluation of a Literature-Based Dietary Index for Gut Microbiota
title_full_unstemmed The Development and Evaluation of a Literature-Based Dietary Index for Gut Microbiota
title_short The Development and Evaluation of a Literature-Based Dietary Index for Gut Microbiota
title_sort development and evaluation of a literature-based dietary index for gut microbiota
topic Dietary Patterns
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9193695/
http://dx.doi.org/10.1093/cdn/nzac054.026
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