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A Data-Driven Assessment of the Metabolic Syndrome Criteria for Adult Health Management in Taiwan

According to the modified Adult Treatment Panel III, five indices are used to define metabolic syndrome (MetS): waist circumference (WC), high blood pressure, fasting glucose, triglycerides (TG), and high-density lipoprotein cholesterol. Our work evaluates the importance of these indices. In additio...

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Autores principales: Chen, Ming-Shu, Chen, Shih-Hsin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6339104/
https://www.ncbi.nlm.nih.gov/pubmed/30602658
http://dx.doi.org/10.3390/ijerph16010092
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author Chen, Ming-Shu
Chen, Shih-Hsin
author_facet Chen, Ming-Shu
Chen, Shih-Hsin
author_sort Chen, Ming-Shu
collection PubMed
description According to the modified Adult Treatment Panel III, five indices are used to define metabolic syndrome (MetS): waist circumference (WC), high blood pressure, fasting glucose, triglycerides (TG), and high-density lipoprotein cholesterol. Our work evaluates the importance of these indices. In addition, we attempted to identify whether trends and patterns existed among young, middle-aged, and older people. Following the analysis, a decision tree algorithm was used to analyze the importance of the five criteria for MetS because the algorithm in question selects the attribute with the highest information gain as the split node. The most important indices are located on the top of the tree, indicating that these indices can effectively distinguish data in a binary tree and the importance of this criterion. That is, the decision tree algorithm specifies the priority of the influence factors. The decision tree algorithm examined four of the five indices because one was excluded. Moreover, the tree structures differed among the three age groups. For example, the first key index for middle-aged and older people was TG whereas for younger people it was WC. Furthermore, the order of the second to fourth indices differed among the groups. Because the key index was identified for each age group, researchers and practitioners could provide different health care strategies for individuals based on age. High-risk middle-aged and healthy older people maintained low values of TG, which might be the most crucial index. When a person can avoid the first and second indices provided by the decision tree, they are at lower risk of MetS. Therefore, this paper provides a data-driven guideline for MetS prevention.
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spelling pubmed-63391042019-01-23 A Data-Driven Assessment of the Metabolic Syndrome Criteria for Adult Health Management in Taiwan Chen, Ming-Shu Chen, Shih-Hsin Int J Environ Res Public Health Article According to the modified Adult Treatment Panel III, five indices are used to define metabolic syndrome (MetS): waist circumference (WC), high blood pressure, fasting glucose, triglycerides (TG), and high-density lipoprotein cholesterol. Our work evaluates the importance of these indices. In addition, we attempted to identify whether trends and patterns existed among young, middle-aged, and older people. Following the analysis, a decision tree algorithm was used to analyze the importance of the five criteria for MetS because the algorithm in question selects the attribute with the highest information gain as the split node. The most important indices are located on the top of the tree, indicating that these indices can effectively distinguish data in a binary tree and the importance of this criterion. That is, the decision tree algorithm specifies the priority of the influence factors. The decision tree algorithm examined four of the five indices because one was excluded. Moreover, the tree structures differed among the three age groups. For example, the first key index for middle-aged and older people was TG whereas for younger people it was WC. Furthermore, the order of the second to fourth indices differed among the groups. Because the key index was identified for each age group, researchers and practitioners could provide different health care strategies for individuals based on age. High-risk middle-aged and healthy older people maintained low values of TG, which might be the most crucial index. When a person can avoid the first and second indices provided by the decision tree, they are at lower risk of MetS. Therefore, this paper provides a data-driven guideline for MetS prevention. MDPI 2018-12-31 2019-01 /pmc/articles/PMC6339104/ /pubmed/30602658 http://dx.doi.org/10.3390/ijerph16010092 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Chen, Ming-Shu
Chen, Shih-Hsin
A Data-Driven Assessment of the Metabolic Syndrome Criteria for Adult Health Management in Taiwan
title A Data-Driven Assessment of the Metabolic Syndrome Criteria for Adult Health Management in Taiwan
title_full A Data-Driven Assessment of the Metabolic Syndrome Criteria for Adult Health Management in Taiwan
title_fullStr A Data-Driven Assessment of the Metabolic Syndrome Criteria for Adult Health Management in Taiwan
title_full_unstemmed A Data-Driven Assessment of the Metabolic Syndrome Criteria for Adult Health Management in Taiwan
title_short A Data-Driven Assessment of the Metabolic Syndrome Criteria for Adult Health Management in Taiwan
title_sort data-driven assessment of the metabolic syndrome criteria for adult health management in taiwan
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6339104/
https://www.ncbi.nlm.nih.gov/pubmed/30602658
http://dx.doi.org/10.3390/ijerph16010092
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