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Using the changes of several simple anthropometric indices to predict the occurrence of metabolic syndrome: Findings from medically under-resourced communities in rural China
BACKGROUND: Various anthropometric indices have been proved to be useful to predict metabolic syndrome(MetS), but the association between changes in anthropometric indices and the onset of MetS is unclear. This study selected six indices that are easy to measure and calculate in daily life and evalu...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9618802/ https://www.ncbi.nlm.nih.gov/pubmed/36325456 http://dx.doi.org/10.3389/fendo.2022.1014541 |
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author | Li, Qiyu Wang, Pengbo Li, Guangxiao Chang, Ye Guo, Xiaofan Sun, Yingxian Zhang, Xingang |
author_facet | Li, Qiyu Wang, Pengbo Li, Guangxiao Chang, Ye Guo, Xiaofan Sun, Yingxian Zhang, Xingang |
author_sort | Li, Qiyu |
collection | PubMed |
description | BACKGROUND: Various anthropometric indices have been proved to be useful to predict metabolic syndrome(MetS), but the association between changes in anthropometric indices and the onset of MetS is unclear. This study selected six indices that are easy to measure and calculate in daily life and evaluated the relationships. METHODS: We established a prospective cohort in rural China during 2012-2013 and involved 5,221 participants without MetS. The follow-up visit was conducted in 2015 to repeat anthropometric indices measurements and assess MetS onset. Binary logistic regression model was used to calculate the association between changes in anthropometric indices and MetS onset. Receiver operating characteristic (ROC) curve was drawn to compare their abilities in MetS prediction. RESULTS: Over a median follow-up time of 2.42 years, 1,367 participants (26.2%) developed MetS. The increase in all the six indices is associated with an increased risk of MetS. Changes in WC and WHtR are the strongest predictors, with a 5 cm increase in WC and a 0.025 increase in WHtR giving the best prediction of MetS onset. CONCLUSIONS: People should be aware of changes in these six anthropometric indices in daily life, as their increase is closely related to an increased risk of MetS, especially WC and WHtR. We recommend an increase of 5 cm in WC and 0.025 in WHtR as the optimal cut-off for the MetS prediction. |
format | Online Article Text |
id | pubmed-9618802 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-96188022022-11-01 Using the changes of several simple anthropometric indices to predict the occurrence of metabolic syndrome: Findings from medically under-resourced communities in rural China Li, Qiyu Wang, Pengbo Li, Guangxiao Chang, Ye Guo, Xiaofan Sun, Yingxian Zhang, Xingang Front Endocrinol (Lausanne) Endocrinology BACKGROUND: Various anthropometric indices have been proved to be useful to predict metabolic syndrome(MetS), but the association between changes in anthropometric indices and the onset of MetS is unclear. This study selected six indices that are easy to measure and calculate in daily life and evaluated the relationships. METHODS: We established a prospective cohort in rural China during 2012-2013 and involved 5,221 participants without MetS. The follow-up visit was conducted in 2015 to repeat anthropometric indices measurements and assess MetS onset. Binary logistic regression model was used to calculate the association between changes in anthropometric indices and MetS onset. Receiver operating characteristic (ROC) curve was drawn to compare their abilities in MetS prediction. RESULTS: Over a median follow-up time of 2.42 years, 1,367 participants (26.2%) developed MetS. The increase in all the six indices is associated with an increased risk of MetS. Changes in WC and WHtR are the strongest predictors, with a 5 cm increase in WC and a 0.025 increase in WHtR giving the best prediction of MetS onset. CONCLUSIONS: People should be aware of changes in these six anthropometric indices in daily life, as their increase is closely related to an increased risk of MetS, especially WC and WHtR. We recommend an increase of 5 cm in WC and 0.025 in WHtR as the optimal cut-off for the MetS prediction. Frontiers Media S.A. 2022-10-17 /pmc/articles/PMC9618802/ /pubmed/36325456 http://dx.doi.org/10.3389/fendo.2022.1014541 Text en Copyright © 2022 Li, Wang, Li, Chang, Guo, Sun and Zhang 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 Li, Qiyu Wang, Pengbo Li, Guangxiao Chang, Ye Guo, Xiaofan Sun, Yingxian Zhang, Xingang Using the changes of several simple anthropometric indices to predict the occurrence of metabolic syndrome: Findings from medically under-resourced communities in rural China |
title | Using the changes of several simple anthropometric indices to predict the occurrence of metabolic syndrome: Findings from medically under-resourced communities in rural China |
title_full | Using the changes of several simple anthropometric indices to predict the occurrence of metabolic syndrome: Findings from medically under-resourced communities in rural China |
title_fullStr | Using the changes of several simple anthropometric indices to predict the occurrence of metabolic syndrome: Findings from medically under-resourced communities in rural China |
title_full_unstemmed | Using the changes of several simple anthropometric indices to predict the occurrence of metabolic syndrome: Findings from medically under-resourced communities in rural China |
title_short | Using the changes of several simple anthropometric indices to predict the occurrence of metabolic syndrome: Findings from medically under-resourced communities in rural China |
title_sort | using the changes of several simple anthropometric indices to predict the occurrence of metabolic syndrome: findings from medically under-resourced communities in rural china |
topic | Endocrinology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9618802/ https://www.ncbi.nlm.nih.gov/pubmed/36325456 http://dx.doi.org/10.3389/fendo.2022.1014541 |
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