Estimating transition probability of different states of type 2 diabetes and its associated factors using Markov model

Aims

Type 2 diabetes is a chronic metabolic disorder and one of the most common non-contagious diseases which is on the rise all over the world. The present study aims to assess the trend of change in fasting blood sugar (FBS) and factors associated with the progression and regression of type 2 diabetes. Moreover, this study estimates transition intensities and transition probabilities among various states using the multi-state Markov model.

Methods

In this study Multi-Ethnic Study of Atherosclerosis (MESA) dataset, from a longitudinal study, was used. The study, at the beginning, included 6814 individuals who were followed during the five phases of the study. FBS, serving as the criterion to assess the progression of diabetes, was classified into four states including (a) normal (FBS < 100 mg/dl), (b) impaired fasting glucose I (IFG I) (100 mg/dl < FBS < 110 mg/dl), (c) impaired fasting glucose II (IFG II) (110 mg/dl < FBS < 126 mg/dl), and (d) diabetes status (FBS > 126 mg/dl). A continuous-time Markov process was used to describe the evaluation of disease changes over the four states. The model estimated the mean sojourn time for each state.

Results

Based on the results obtained from fitting the Markov model, the transition probability for a normal individual to remain in the same status over a 10-year period was 0.63, while the probability for a person in the diabetes state was 0.40. The mean sojourn time for the normal and diabetic individuals aged 45–84 years was 6.26 and 5.20 respectively. The covariates of age, race, body mass index (BMI), physical activity, waist-to-hip ratio (WHR) and blood pressure, significantly affected the progression and regression of diabetes.

Conclusion

An increase in physical activity could be the most important factor in the regression of diabetes, while an increase in WHR and BMI could be the most significant factors in progression of the disease.