ArticleBMC public health2018
Prediction of the development of metabolic syndrome by the Markov model based on a longitudinal study in Dalian City.
Article in BMC public health, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
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16 citing papers in PubMed, 1 synthesis or guideline pooled it, 21 citations in OpenAlex.
- Dynamic behavior of metabolic syndrome progression: a comprehensive systematic review on recent discoveries.BMC endocrine disorders · 2021Pooled it
- Multistate markov model analysis of metabolic syndrome progression in a community-based longitudinal cohort study.Diabetology & metabolic syndrome · 2026Article
- Stage-Specific Lifestyle Effects on the Dynamic Transitions of Metabolic Multimorbidity - Jiangsu Province, China, 2019-2024.China CDC weekly · 2026Article
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- Incidence of metabolic syndrome among radiation workers exposed to low dose radiation: a national cohort study in Korea.BMC public health · 2025Article
- Predictive modelling of metabolic syndrome in Ghanaian diabetic patients: an ensemble machine learning approach.Journal of diabetes and metabolic disorders · 2024Article
- Development and validation of a chronic kidney disease progression model using patient-level simulations.Renal failure · 2024Article
- Associations of the cardiometabolic index with insulin resistance, prediabetes, and diabetes in U.S. adults: a cross-sectional study.BMC endocrine disorders · 2024Article
- Causal association study of the dynamic development of the metabolic syndrome based on longitudinal data.Scientific reports · 2024Article
- Body mass index as a dominant risk factor for metabolic syndrome among indonesian adults: a 6-year prospective cohort study of non-communicable diseases.BMC nutrition · 2024Article
- Study on Dynamic Progression and Risk Assessment of Metabolic Syndrome Based on Multi-State Markov Model.Diabetes, metabolic syndrome and obesity : targets and therapy · 2022Article
- Predicting the natural history of metabolic syndrome with a Markov-system dynamic model: a novel approach.BMC medical research methodology · 2021Article
- The dynamics of metabolic syndrome development from its isolated components among Iranian adults: findings from 17 years of the Tehran lipid and glucose study (TLGS).Journal of diabetes and metabolic disorders · 2021Article
- Dynamics of detailed components of metabolic syndrome associated with the risk of cardiovascular disease and death.Scientific reports · 2021Article
- Transition Patterns of Weight Status and Their Predictive Lipid Markers Among Chinese Adults: A Longitudinal Cohort Study Using the Multistate Markov Model.Diabetes, metabolic syndrome and obesity : targets and therapy · 2021Article
- Noninvasive and Convenient Screening of Metabolic Syndrome Using the Controlled Attenuation Parameter Technology: An Evaluation Based on Self-Paid Health Examination Participants.Journal of clinical medicine · 2019Article
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2 authors at 1 institution in 1 country.
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Abstract
backgroundMetabolic syndrome (MetS) increases the incidence of cardiovascular disease and diabetes mellitus. It is essential to study the natural progression of MetS in the interest of prevention. Information on the dynamic changes in MetS in developing countries is limited. This study aimed to simulate the progression of each component of MetS and explore the potential role of these components in early prevention and intervention.
methodsThis study involved 5881 individuals, aged 20 to 60 at study entry, who underwent at least two consecutive years of health check-ups in the seven-year study period at our institution's health check-up center. Participants were divided into four groups by age (a 20- to- 40-year-old group and a 40- to 60-year-old group) and gender. A Markov model containing 7 stages (no components, isolated hypertension, isolated obesity, isolated hyperglycemia, isolated dyslipidemia, a 2-component state, and the MetS state) was constructed for each group.
resultsIn women and young men (20- to 40-year-old men), dyslipidemia and obesity were the two most probable states for individuals who were transitioning from no components to one of the other six states. Among those who had no components and were 30 years old at study entry, MetS was estimated to develop within 10 years in 11.42% of men and 3.04% of women. Among those who had no components and were 50 years old at study entry, MetS was estimated to develop within 10 years in 25.04% of men and 7.09% of women. The estimated prevalence of MetS over the next 10 years was higher in individuals starting with the obesity component than in individuals starting with any other isolated component. In a comparison of interventions targeting single components, simulations showed that the obesity intervention produced the largest relative reduction in the prevalence of MetS.
conclusionMarkov models are suitable for describing and predicting the dynamic development of MetS. The occurrence of MetS most frequently began with dyslipidemia or obesity. Obesity played a predominant role in the development of MetS. Early obesity intervention was extremely important for MetS prevention.
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