Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Li, Qiyu, Wang, Pengbo, Li, Guangxiao, Chang, Ye, Guo, Xiaofan, Sun, Yingxian, Zhang, Xingang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
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
_version_ 1784821134916583424
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
work_keys_str_mv AT liqiyu usingthechangesofseveralsimpleanthropometricindicestopredicttheoccurrenceofmetabolicsyndromefindingsfrommedicallyunderresourcedcommunitiesinruralchina
AT wangpengbo usingthechangesofseveralsimpleanthropometricindicestopredicttheoccurrenceofmetabolicsyndromefindingsfrommedicallyunderresourcedcommunitiesinruralchina
AT liguangxiao usingthechangesofseveralsimpleanthropometricindicestopredicttheoccurrenceofmetabolicsyndromefindingsfrommedicallyunderresourcedcommunitiesinruralchina
AT changye usingthechangesofseveralsimpleanthropometricindicestopredicttheoccurrenceofmetabolicsyndromefindingsfrommedicallyunderresourcedcommunitiesinruralchina
AT guoxiaofan usingthechangesofseveralsimpleanthropometricindicestopredicttheoccurrenceofmetabolicsyndromefindingsfrommedicallyunderresourcedcommunitiesinruralchina
AT sunyingxian usingthechangesofseveralsimpleanthropometricindicestopredicttheoccurrenceofmetabolicsyndromefindingsfrommedicallyunderresourcedcommunitiesinruralchina
AT zhangxingang usingthechangesofseveralsimpleanthropometricindicestopredicttheoccurrenceofmetabolicsyndromefindingsfrommedicallyunderresourcedcommunitiesinruralchina