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Description and prediction of the development of metabolic syndrome in Dongying City: a longitudinal analysis using the Markov model.

Chen X, Chen Q, Chen L, Zhang P, Xiao J, Wang S - BMC Public Health (2014)

Bottom Line: The Markov model was able to give a better description of the evolutionary history of MS, and to predict the future course based on past evidence.In the elderly population, many individuals initiating with hypertension or 2 components besides the above two states.Individuals with the isolated hyperglycemia had greater chances to develop MS than other isolated MS' components.

View Article: PubMed Central - PubMed

Affiliation: Department of Epidemiology and Biostatistics, School of Public Health, Shandong University, Jinan, China. wshm@sdu.edu.cn.

ABSTRACT

Background: Metabolic Syndrome (MS) is increasingly becoming a major worldwide clinical and public health issue. Thus it is extremely important to study the history of MS and search for the most likely component contributing to start the cascade of confusions of MS.

Methods: A longitudinal cohort was involved which included the data of 7510 individuals who had at least two routine health check-ups in a six-year follow-up. Based on the data, a Markov model with each chain containing seven states (no component state, four isolated states, 2-component state, and MS state) was built. Annual transition probability was the mean of five probabilities for the transition between the given states between each pair of consecutive years.

Results: The transition probabilities from the no component state to MS were higher in men than that in women in four age groups. In the young people (men <60 years and women <50 years), the probabilities to the overweight or obesity state and dyslipidemia state were the first two biggest probabilities in transition from no component to the rest six states. However, in the elderly population, the probabilities to hypertension state and 2-component state increased, even surpassed the above two states. The individuals initiating with 2-component states and the isolated hyperglycemia state were more likely to develop MS than the others.

Conclusions: The Markov model was able to give a better description of the evolutionary history of MS, and to predict the future course based on past evidence. The occurrence of the MS process mostly began with overweight or obesity and dyslipidemia in young people. In the elderly population, many individuals initiating with hypertension or 2 components besides the above two states. Individuals with the isolated hyperglycemia had greater chances to develop MS than other isolated MS' components.

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Related in: MedlinePlus

A 7-state Markov model to describe the progression of metabolic components.
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Fig1: A 7-state Markov model to describe the progression of metabolic components.

Mentions: 7 states were included in each Markov chain: the no component state, isolated overweight or obesity state, isolated hypertension state, isolated dyslipidemia state, isolated hyperglycemia state, 2-component state, and MS state. Any two combinations of overweight or obesity, hypertension, dyslipidemia or hyperglycemia formed a 2-component state. These states were mutually exclusive and collectively exhaustive. A cycle-based Markov model was built and the graphical expression of the model was shown in Figure 1. The development of MS is a complex process and any state can develop into MS. Mutual transitions were allowed between the 7 states, so a reversible multistate Markov model was adopted. In every Markov cycle, the state could maintain or transition into any of the other 6 states.Figure 1


Description and prediction of the development of metabolic syndrome in Dongying City: a longitudinal analysis using the Markov model.

Chen X, Chen Q, Chen L, Zhang P, Xiao J, Wang S - BMC Public Health (2014)

A 7-state Markov model to describe the progression of metabolic components.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4209018&req=5

Fig1: A 7-state Markov model to describe the progression of metabolic components.
Mentions: 7 states were included in each Markov chain: the no component state, isolated overweight or obesity state, isolated hypertension state, isolated dyslipidemia state, isolated hyperglycemia state, 2-component state, and MS state. Any two combinations of overweight or obesity, hypertension, dyslipidemia or hyperglycemia formed a 2-component state. These states were mutually exclusive and collectively exhaustive. A cycle-based Markov model was built and the graphical expression of the model was shown in Figure 1. The development of MS is a complex process and any state can develop into MS. Mutual transitions were allowed between the 7 states, so a reversible multistate Markov model was adopted. In every Markov cycle, the state could maintain or transition into any of the other 6 states.Figure 1

Bottom Line: The Markov model was able to give a better description of the evolutionary history of MS, and to predict the future course based on past evidence.In the elderly population, many individuals initiating with hypertension or 2 components besides the above two states.Individuals with the isolated hyperglycemia had greater chances to develop MS than other isolated MS' components.

View Article: PubMed Central - PubMed

Affiliation: Department of Epidemiology and Biostatistics, School of Public Health, Shandong University, Jinan, China. wshm@sdu.edu.cn.

ABSTRACT

Background: Metabolic Syndrome (MS) is increasingly becoming a major worldwide clinical and public health issue. Thus it is extremely important to study the history of MS and search for the most likely component contributing to start the cascade of confusions of MS.

Methods: A longitudinal cohort was involved which included the data of 7510 individuals who had at least two routine health check-ups in a six-year follow-up. Based on the data, a Markov model with each chain containing seven states (no component state, four isolated states, 2-component state, and MS state) was built. Annual transition probability was the mean of five probabilities for the transition between the given states between each pair of consecutive years.

Results: The transition probabilities from the no component state to MS were higher in men than that in women in four age groups. In the young people (men <60 years and women <50 years), the probabilities to the overweight or obesity state and dyslipidemia state were the first two biggest probabilities in transition from no component to the rest six states. However, in the elderly population, the probabilities to hypertension state and 2-component state increased, even surpassed the above two states. The individuals initiating with 2-component states and the isolated hyperglycemia state were more likely to develop MS than the others.

Conclusions: The Markov model was able to give a better description of the evolutionary history of MS, and to predict the future course based on past evidence. The occurrence of the MS process mostly began with overweight or obesity and dyslipidemia in young people. In the elderly population, many individuals initiating with hypertension or 2 components besides the above two states. Individuals with the isolated hyperglycemia had greater chances to develop MS than other isolated MS' components.

Show MeSH
Related in: MedlinePlus