Forecasting Diabetes Prevalence in California: A Microsimulation

INTRODUCTION Setting a goal for controlling type 2 diabetes is important for planning health interventions. The purpose of this study was to explore what may be a feasible goal for type 2 diabetes prevention in California. METHODS We used the UCLA Health Forecasting Tool, a microsimulation model that simulates individual life courses in the population, to forecast the prevalence of type 2 diabetes in California's adult population in 2020. The first scenario assumes no further increases in average body mass index (BMI) for cohorts entering adolescence after 2003. The second scenario assumes a gradual BMI decrease for children entering adolescence after 2010. The third scenario builds on the second by extending the same BMI decrease to people aged 12 to 65 years. The fourth scenario builds on the third by eliminating racial/ethnic disparities in physical activity. RESULTS We found the predicted diabetes prevalence of the first, second, third, and fourth scenarios in 2020 to be 9.93%, 9.91%, 9.76%, and 9.77%, respectively. We found obesity prevalence for type 2 diabetes patients in 2020 to be 34.2%, 34.0%, 25.7%, and 25.6% for the 4 scenarios. Life expectancy in the third (80.56 y) and fourth (80.94 y) scenarios compared favorably with that of the first (80.32 y) and second (80.32 y) scenarios. CONCLUSION For the next 10 years, behavioral risk factor modifications are more likely to affect obesity prevalence and life expectancy in the general population and obesity prevalence among diabetic patients than to alter type 2 diabetes prevalence in the general population. We suggest setting more specific goals for reducing the prevalence of diabetes, such as reducing obesity-related diabetes complications, which may be more feasible and easier to evaluate than the omnibus goal of lowering overall type 2 diabetes prevalence by 2020.