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Associations Between Different Dietary Vitamins and the Risk of Obesity in Children and Adolescents: A Machine Learning Approach
BACKGROUNDS: Simultaneous dietary intake of vitamins is considered as a common and real scenario in daily life. However, limited prospective studies have evaluated the association between multivitamins intake and obesity in children and adolescents. OBJECTIVES: This study aimed to evaluate the relat...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8893992/ https://www.ncbi.nlm.nih.gov/pubmed/35250848 http://dx.doi.org/10.3389/fendo.2021.816975 |
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author | Tang, Weifeng Zhan, Wenqiang Wei, Mengdan Chen, Qian |
author_facet | Tang, Weifeng Zhan, Wenqiang Wei, Mengdan Chen, Qian |
author_sort | Tang, Weifeng |
collection | PubMed |
description | BACKGROUNDS: Simultaneous dietary intake of vitamins is considered as a common and real scenario in daily life. However, limited prospective studies have evaluated the association between multivitamins intake and obesity in children and adolescents. OBJECTIVES: This study aimed to evaluate the relationship between the intake of different dietary vitamins and the risk of obesity in children (6-11 years) and adolescents (12-19 years). METHODS: We conducted a cross-sectional study based on data from U.S. National Health and Nutrition Examination Survey, 2013-2016. A total of 3634 children and adolescents were included who had available data on dietary vitamins, obesity and covariates. We analyzed the dietary intake levels of nine vitamins, including vitamin A, vitamin B(1), vitamin B(2), vitamin B(6), vitamin B(12), vitamin C, vitamin D, vitamin E, vitamin K. Multivariate logistic regression was used to model the associations between vitamins and obesity. Bayesian kernel machine regression (BKMR) was employed to explore the joint and independent effects of vitamins on obesity among children and adolescents. RESULTS: In the multivariate logistic regression model, five vitamins (vitamin A, vitamin B(1), vitamin B(2), vitamin B(12), and vitamin D) were negatively associated with obesity in children and adolescents. BKMR analysis showed that when the concentration of the nine vitamins was at or above the 55th percentile compared with the median value, the combined intake of these vitamins could significantly reduce the risk of obesity in children and adolescents. Potential interactions between vitamin B(2) and vitamin B(12) in increasing the risk of obesity in children and adolescents were observed. CONCLUSIONS: We determine the combined effects of multivitamins on obesity in children and adolescents, and observe a significant interaction between vitamin B(2) and vitamin B(12). Further cohort studies are needed to clarify the health effects of multivitamins intake in a larger population. |
format | Online Article Text |
id | pubmed-8893992 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-88939922022-03-04 Associations Between Different Dietary Vitamins and the Risk of Obesity in Children and Adolescents: A Machine Learning Approach Tang, Weifeng Zhan, Wenqiang Wei, Mengdan Chen, Qian Front Endocrinol (Lausanne) Endocrinology BACKGROUNDS: Simultaneous dietary intake of vitamins is considered as a common and real scenario in daily life. However, limited prospective studies have evaluated the association between multivitamins intake and obesity in children and adolescents. OBJECTIVES: This study aimed to evaluate the relationship between the intake of different dietary vitamins and the risk of obesity in children (6-11 years) and adolescents (12-19 years). METHODS: We conducted a cross-sectional study based on data from U.S. National Health and Nutrition Examination Survey, 2013-2016. A total of 3634 children and adolescents were included who had available data on dietary vitamins, obesity and covariates. We analyzed the dietary intake levels of nine vitamins, including vitamin A, vitamin B(1), vitamin B(2), vitamin B(6), vitamin B(12), vitamin C, vitamin D, vitamin E, vitamin K. Multivariate logistic regression was used to model the associations between vitamins and obesity. Bayesian kernel machine regression (BKMR) was employed to explore the joint and independent effects of vitamins on obesity among children and adolescents. RESULTS: In the multivariate logistic regression model, five vitamins (vitamin A, vitamin B(1), vitamin B(2), vitamin B(12), and vitamin D) were negatively associated with obesity in children and adolescents. BKMR analysis showed that when the concentration of the nine vitamins was at or above the 55th percentile compared with the median value, the combined intake of these vitamins could significantly reduce the risk of obesity in children and adolescents. Potential interactions between vitamin B(2) and vitamin B(12) in increasing the risk of obesity in children and adolescents were observed. CONCLUSIONS: We determine the combined effects of multivitamins on obesity in children and adolescents, and observe a significant interaction between vitamin B(2) and vitamin B(12). Further cohort studies are needed to clarify the health effects of multivitamins intake in a larger population. Frontiers Media S.A. 2022-02-17 /pmc/articles/PMC8893992/ /pubmed/35250848 http://dx.doi.org/10.3389/fendo.2021.816975 Text en Copyright © 2022 Tang, Zhan, Wei and Chen https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Endocrinology Tang, Weifeng Zhan, Wenqiang Wei, Mengdan Chen, Qian Associations Between Different Dietary Vitamins and the Risk of Obesity in Children and Adolescents: A Machine Learning Approach |
title | Associations Between Different Dietary Vitamins and the Risk of Obesity in Children and Adolescents: A Machine Learning Approach |
title_full | Associations Between Different Dietary Vitamins and the Risk of Obesity in Children and Adolescents: A Machine Learning Approach |
title_fullStr | Associations Between Different Dietary Vitamins and the Risk of Obesity in Children and Adolescents: A Machine Learning Approach |
title_full_unstemmed | Associations Between Different Dietary Vitamins and the Risk of Obesity in Children and Adolescents: A Machine Learning Approach |
title_short | Associations Between Different Dietary Vitamins and the Risk of Obesity in Children and Adolescents: A Machine Learning Approach |
title_sort | associations between different dietary vitamins and the risk of obesity in children and adolescents: a machine learning approach |
topic | Endocrinology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8893992/ https://www.ncbi.nlm.nih.gov/pubmed/35250848 http://dx.doi.org/10.3389/fendo.2021.816975 |
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