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Study on Dynamic Progression and Risk Assessment of Metabolic Syndrome Based on Multi-State Markov Model

AIM: Metabolic syndrome (MetS) coexists with the occurrence and even death of cardiovascular disease and diabetes mellitus. It is essential to study the factors in the dynamic progression of MetS in the interest of prevention and control. PURPOSE: The aim of this study was to analyze the dynamic pro...

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Autores principales: Razbek, Jaina, Zhang, Yan, Xia, Wen-Jun, Xu, Wan-Ting, Li, De-Yang, Yin, Zhe, Cao, Ming-Qin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9392490/
https://www.ncbi.nlm.nih.gov/pubmed/35996564
http://dx.doi.org/10.2147/DMSO.S362071
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author Razbek, Jaina
Zhang, Yan
Xia, Wen-Jun
Xu, Wan-Ting
Li, De-Yang
Yin, Zhe
Cao, Ming-Qin
author_facet Razbek, Jaina
Zhang, Yan
Xia, Wen-Jun
Xu, Wan-Ting
Li, De-Yang
Yin, Zhe
Cao, Ming-Qin
author_sort Razbek, Jaina
collection PubMed
description AIM: Metabolic syndrome (MetS) coexists with the occurrence and even death of cardiovascular disease and diabetes mellitus. It is essential to study the factors in the dynamic progression of MetS in the interest of prevention and control. PURPOSE: The aim of this study was to analyze the dynamic progression of Mets and explore the potential factors influencing the progression or reversal of MetS. PATIENTS AND METHODS: This study involved 5581 individuals from two waves of the China Health and Retirement Longitudinal Study: 2011 and 2015. A multistate Markov model containing 4 states (free of metabolic disorder (FMD), mild metabolic disorder (MMD), severe metabolic disorder (SMD) and MetS) was adopted to study the dynamic progression of MetS and its influencing factors. RESULTS: After follow-up, a total of 2862 cases (50.28% of the total number) had disease state transition. The intensity of transition from MetS to SMD is the same as that from SMD to MMD, and is greater than that from MMD to Mets (0.06 vs 0.05). For the MetS state, a mean of 1/0.08=12.5 years was spent in the MetS state before recovery. The exercise, smoke, drink, BMI level, hyperuricemia had statistically significant effects on progression of MetS status (P<0.05). The obesity or overweight, little exercise, smoke, drink and hyperuricemia increased the risk of forward progression of MetS disease status. There were significant nonmodifiable (age, gender) and modifiable factors (exercise, drink, BMI level, or high HbA1c) associated with reversion of MetS state. CONCLUSION: The likelihood of progression from MMD to MetS is less likely than that of reversion from MetS to SMD and SMD to MMD. Old females were more resistant to recover from worse states than males. Prevention and intervention measures should be adopted early when MMD or SMD onset occurs.
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spelling pubmed-93924902022-08-21 Study on Dynamic Progression and Risk Assessment of Metabolic Syndrome Based on Multi-State Markov Model Razbek, Jaina Zhang, Yan Xia, Wen-Jun Xu, Wan-Ting Li, De-Yang Yin, Zhe Cao, Ming-Qin Diabetes Metab Syndr Obes Original Research AIM: Metabolic syndrome (MetS) coexists with the occurrence and even death of cardiovascular disease and diabetes mellitus. It is essential to study the factors in the dynamic progression of MetS in the interest of prevention and control. PURPOSE: The aim of this study was to analyze the dynamic progression of Mets and explore the potential factors influencing the progression or reversal of MetS. PATIENTS AND METHODS: This study involved 5581 individuals from two waves of the China Health and Retirement Longitudinal Study: 2011 and 2015. A multistate Markov model containing 4 states (free of metabolic disorder (FMD), mild metabolic disorder (MMD), severe metabolic disorder (SMD) and MetS) was adopted to study the dynamic progression of MetS and its influencing factors. RESULTS: After follow-up, a total of 2862 cases (50.28% of the total number) had disease state transition. The intensity of transition from MetS to SMD is the same as that from SMD to MMD, and is greater than that from MMD to Mets (0.06 vs 0.05). For the MetS state, a mean of 1/0.08=12.5 years was spent in the MetS state before recovery. The exercise, smoke, drink, BMI level, hyperuricemia had statistically significant effects on progression of MetS status (P<0.05). The obesity or overweight, little exercise, smoke, drink and hyperuricemia increased the risk of forward progression of MetS disease status. There were significant nonmodifiable (age, gender) and modifiable factors (exercise, drink, BMI level, or high HbA1c) associated with reversion of MetS state. CONCLUSION: The likelihood of progression from MMD to MetS is less likely than that of reversion from MetS to SMD and SMD to MMD. Old females were more resistant to recover from worse states than males. Prevention and intervention measures should be adopted early when MMD or SMD onset occurs. Dove 2022-08-16 /pmc/articles/PMC9392490/ /pubmed/35996564 http://dx.doi.org/10.2147/DMSO.S362071 Text en © 2022 Razbek et al. https://creativecommons.org/licenses/by-nc/3.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/ (https://creativecommons.org/licenses/by-nc/3.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Razbek, Jaina
Zhang, Yan
Xia, Wen-Jun
Xu, Wan-Ting
Li, De-Yang
Yin, Zhe
Cao, Ming-Qin
Study on Dynamic Progression and Risk Assessment of Metabolic Syndrome Based on Multi-State Markov Model
title Study on Dynamic Progression and Risk Assessment of Metabolic Syndrome Based on Multi-State Markov Model
title_full Study on Dynamic Progression and Risk Assessment of Metabolic Syndrome Based on Multi-State Markov Model
title_fullStr Study on Dynamic Progression and Risk Assessment of Metabolic Syndrome Based on Multi-State Markov Model
title_full_unstemmed Study on Dynamic Progression and Risk Assessment of Metabolic Syndrome Based on Multi-State Markov Model
title_short Study on Dynamic Progression and Risk Assessment of Metabolic Syndrome Based on Multi-State Markov Model
title_sort study on dynamic progression and risk assessment of metabolic syndrome based on multi-state markov model
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9392490/
https://www.ncbi.nlm.nih.gov/pubmed/35996564
http://dx.doi.org/10.2147/DMSO.S362071
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