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Modeling diabetes progression with risk factors: A case study in China
Shilu Yao1, Yangling Shen1, Jianling Xiong1
1School of Mathematics and Computing Science, Guilin University of Electronic Technology, Guilin, 541004, China.
Computers in Biology and Medicine
|December 31, 2024
Summary
Type 2 diabetes mellitus (T2DM) in China is projected to rise significantly. Lifestyle interventions targeting high BMI, smoking, and low physical activity are crucial for reducing T2DM incidence.
Area of Science:
- Epidemiology
- Public Health
- Biostatistics
Background:
- Type 2 diabetes mellitus (T2DM) affects over 537 million adults globally, with China having the largest affected population.
- Understanding T2DM epidemiological mechanisms is vital for effective diabetes surveillance and control strategies.
Purpose of the Study:
- To develop a modeling framework projecting the future burden of T2DM in China.
- To quantify the impact of genetic and lifestyle factors on T2DM progression.
Main Methods:
- Utilized Global Burden of Disease 2021 data for T2DM and risk factor exposure.
- Employed a systems of difference equations model to characterize diabetes progression stages.
- Applied Markov chain Monte Carlo (MCMC) algorithm for model fitting to longitudinal T2DM patient data.
Main Results:
- The model achieved 98% R-squared for T2DM cases in China (1990-2021).
- Projected T2DM incidence rates to increase from 299.93/100,000 in 2022 to 500.16/100,000 by 2080.
- Prevalence may reach 34.83% by 2080; high BMI, smoking, and low physical activity were identified as key risk factors.
Conclusions:
- The study presents a robust modeling framework for analyzing T2DM development mechanisms.
- Results underscore the substantial T2DM burden in China.
- Emphasizes the critical role of lifestyle interventions in mitigating T2DM progression.
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