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Association of metabolic syndrome with TyG index and TyG-related parameters in an urban Chinese population: a 15-year prospective study

BACKGROUND: The metabolic syndrome (Mets) is a multiplex risk factor for atherosclerotic cardiovascular diseases. The aims of the study were to assess the association of the Mets with TyG index and TyG-related parameters in an urban Chinese population. METHODS: The data were collected in 1992 and th...

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Autores principales: Zhang, Xin, Zhang, Ting, He, Sen, Jia, Shanshan, Zhang, Zhipeng, Ye, Runyu, Yang, Xiangyu, Chen, Xiaoping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9202163/
https://www.ncbi.nlm.nih.gov/pubmed/35706038
http://dx.doi.org/10.1186/s13098-022-00855-4
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author Zhang, Xin
Zhang, Ting
He, Sen
Jia, Shanshan
Zhang, Zhipeng
Ye, Runyu
Yang, Xiangyu
Chen, Xiaoping
author_facet Zhang, Xin
Zhang, Ting
He, Sen
Jia, Shanshan
Zhang, Zhipeng
Ye, Runyu
Yang, Xiangyu
Chen, Xiaoping
author_sort Zhang, Xin
collection PubMed
description BACKGROUND: The metabolic syndrome (Mets) is a multiplex risk factor for atherosclerotic cardiovascular diseases. The aims of the study were to assess the association of the Mets with TyG index and TyG-related parameters in an urban Chinese population. METHODS: The data were collected in 1992 and then again in 2007 from the same group of 590 individuals (363 males and 227 females) without Mets in 1992. The fasting lipid profile and blood glucose were measured. TyG index and related parameters were calculated, and Mets defined according to the harmonized criteria. The area under the curve (AUC) of receiver operating characteristic curves was used to evaluate TyG index and related parameters for their diagnostic ability to identify people with Mets. Odd ratios (OR) for Mets prediction were calculated using stepwise logistic regression analyses. RESULTS: The incidence of Mets was 18.64% over the 15-year follow-up period.During 15 years’ follow-up, TyG-waist to height ratio (TyG-WHtR) shows the largest AUC for Mets detection (0.686) followed by TyG-waist circumference (TyG-WC) (0.660), TyG-waist-to-hip ratio (TyG-WHpR) (0.564), and TyG index (0.556) in all participants. Gender analysis revealed that TyG-WHtR and TyG-WC have the largest AUC in both genders. TyG-WHtR significantly predicted Mets in all participants, with an unadjusted odds ratio of 5.63 (95% CI 3.23–9.83 P < 0.001). Associations remained significant after adjustment for smoking, drinking, physical exercise and components of Mets. CONCLUSIONS: TyG-WHtR might be a strong and independent predictor for Mets in all participants in an urban Chinese population. TyG-related markers that combine obesity markers with TyG index are superior to other parameters in identifying Mets in both genders.
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spelling pubmed-92021632022-06-17 Association of metabolic syndrome with TyG index and TyG-related parameters in an urban Chinese population: a 15-year prospective study Zhang, Xin Zhang, Ting He, Sen Jia, Shanshan Zhang, Zhipeng Ye, Runyu Yang, Xiangyu Chen, Xiaoping Diabetol Metab Syndr Research BACKGROUND: The metabolic syndrome (Mets) is a multiplex risk factor for atherosclerotic cardiovascular diseases. The aims of the study were to assess the association of the Mets with TyG index and TyG-related parameters in an urban Chinese population. METHODS: The data were collected in 1992 and then again in 2007 from the same group of 590 individuals (363 males and 227 females) without Mets in 1992. The fasting lipid profile and blood glucose were measured. TyG index and related parameters were calculated, and Mets defined according to the harmonized criteria. The area under the curve (AUC) of receiver operating characteristic curves was used to evaluate TyG index and related parameters for their diagnostic ability to identify people with Mets. Odd ratios (OR) for Mets prediction were calculated using stepwise logistic regression analyses. RESULTS: The incidence of Mets was 18.64% over the 15-year follow-up period.During 15 years’ follow-up, TyG-waist to height ratio (TyG-WHtR) shows the largest AUC for Mets detection (0.686) followed by TyG-waist circumference (TyG-WC) (0.660), TyG-waist-to-hip ratio (TyG-WHpR) (0.564), and TyG index (0.556) in all participants. Gender analysis revealed that TyG-WHtR and TyG-WC have the largest AUC in both genders. TyG-WHtR significantly predicted Mets in all participants, with an unadjusted odds ratio of 5.63 (95% CI 3.23–9.83 P < 0.001). Associations remained significant after adjustment for smoking, drinking, physical exercise and components of Mets. CONCLUSIONS: TyG-WHtR might be a strong and independent predictor for Mets in all participants in an urban Chinese population. TyG-related markers that combine obesity markers with TyG index are superior to other parameters in identifying Mets in both genders. BioMed Central 2022-06-15 /pmc/articles/PMC9202163/ /pubmed/35706038 http://dx.doi.org/10.1186/s13098-022-00855-4 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Zhang, Xin
Zhang, Ting
He, Sen
Jia, Shanshan
Zhang, Zhipeng
Ye, Runyu
Yang, Xiangyu
Chen, Xiaoping
Association of metabolic syndrome with TyG index and TyG-related parameters in an urban Chinese population: a 15-year prospective study
title Association of metabolic syndrome with TyG index and TyG-related parameters in an urban Chinese population: a 15-year prospective study
title_full Association of metabolic syndrome with TyG index and TyG-related parameters in an urban Chinese population: a 15-year prospective study
title_fullStr Association of metabolic syndrome with TyG index and TyG-related parameters in an urban Chinese population: a 15-year prospective study
title_full_unstemmed Association of metabolic syndrome with TyG index and TyG-related parameters in an urban Chinese population: a 15-year prospective study
title_short Association of metabolic syndrome with TyG index and TyG-related parameters in an urban Chinese population: a 15-year prospective study
title_sort association of metabolic syndrome with tyg index and tyg-related parameters in an urban chinese population: a 15-year prospective study
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9202163/
https://www.ncbi.nlm.nih.gov/pubmed/35706038
http://dx.doi.org/10.1186/s13098-022-00855-4
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