Study on Dynamic Progression and Risk Assessment of Metabolic Syndrome Based on Multi-State Markov Model
- PMID: 35996564
- PMCID: PMC9392490
- DOI: 10.2147/DMSO.S362071
Study on Dynamic Progression and Risk Assessment of Metabolic Syndrome Based on Multi-State Markov Model
Abstract
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.
Keywords: backward reversal; forward progression; metabolic syndrome; multi-state Markov model.
© 2022 Razbek et al.
Conflict of interest statement
The authors declare that they have no conflicts of interest in relation to this work.
Figures
Similar articles
-
Causal association study of the dynamic development of the metabolic syndrome based on longitudinal data.Sci Rep. 2024 Mar 5;14(1):5448. doi: 10.1038/s41598-024-55693-3. Sci Rep. 2024. PMID: 38443462 Free PMC article.
-
Prediction of the development of metabolic syndrome by the Markov model based on a longitudinal study in Dalian City.BMC Public Health. 2018 Jun 7;18(1):707. doi: 10.1186/s12889-018-5599-y. BMC Public Health. 2018. PMID: 29879952 Free PMC article.
-
Transition Patterns of Weight Status and Their Predictive Lipid Markers Among Chinese Adults: A Longitudinal Cohort Study Using the Multistate Markov Model.Diabetes Metab Syndr Obes. 2021 Jun 14;14:2661-2671. doi: 10.2147/DMSO.S308913. eCollection 2021. Diabetes Metab Syndr Obes. 2021. PMID: 34163194 Free PMC article.
-
Dynamic behavior of metabolic syndrome progression: a comprehensive systematic review on recent discoveries.BMC Endocr Disord. 2021 Mar 22;21(1):54. doi: 10.1186/s12902-021-00716-7. BMC Endocr Disord. 2021. PMID: 33752643 Free PMC article.
-
Use of the RBANS to Evaluate Cognition in Patients with Schizophrenia and Metabolic Syndrome: a Meta-Analysis of Case-Control Studies.Psychiatr Q. 2022 Mar;93(1):137-149. doi: 10.1007/s11126-021-09889-9. Epub 2021 Mar 22. Psychiatr Q. 2022. PMID: 33751356 Review.
Cited by
-
Causal association study of the dynamic development of the metabolic syndrome based on longitudinal data.Sci Rep. 2024 Mar 5;14(1):5448. doi: 10.1038/s41598-024-55693-3. Sci Rep. 2024. PMID: 38443462 Free PMC article.
-
A Longitudinal Assessment of Metabolic Syndrome.J Clin Med. 2025 Jan 24;14(3):747. doi: 10.3390/jcm14030747. J Clin Med. 2025. PMID: 39941416 Free PMC article.
References
LinkOut - more resources
Full Text Sources