摘要：Health planners in the Division of Diabetes Translation and others from the National Center for Chronic Disease Prevention and Health Promotion of the Centers for Disease Control and Prevention used system dynamics simulation modeling to gain a better understanding of diabetes population dynamics and to explore implications for public health strategy. A model was developed to explain the growth of diabetes since 1980 and portray possible futures through 2050. The model simulations suggest characteristic dynamics of the diabetes population, including unintended increases in diabetes prevalence due to diabetes control, the inability of diabetes control efforts alone to reduce diabetes-related deaths in the long term, and significant delays between primary prevention efforts and downstream improvements in diabetes outcomes. DIABETES MELLITUS IS A growing health problem worldwide. In the United States, the number of people with diabetes has grown since 1990 at a rate much greater than that of the general population; it was estimated at 20.8 million in 2005. Total costs of diabetes in the United States in 2002 were estimated at $132 billion, with $92 billion of that amount in direct medical expenditures and the other $40 billion in indirect costs because of disability and premature mortality. 1 There are no quick or easy fixes for addressing the health and cost burdens of diabetes. Like other dynamically complex problems, diabetes is characterized by long delays between causes and effects, and the public health effort to address it is characterized by multiple concurrent goals that may conflict with one another. For example, although planners have called for reductions both in the prevalence of diabetes and in deaths because of its complications, 2 the fact is that fewer deaths, other things being equal, would lead to increased, not decreased, prevalence. Given such interconnections, a satisfactory solution will be found not in focusing on just 1 aspect of the overall health system—such as disease management, or detection, or risk factor reduction—but rather in addressing all major components together as a system. We report results of simulation experiments with a system dynamics model developed to explore the past and future burden of diabetes—its morbidity, mortality, and costs—in the United States. Model development was sponsored by the Division of Diabetes Translation and the Division of Adult and Community Health at the Centers for Disease Control and Prevention (CDC). For background on system dynamics methodology and applications, see Sterman’s comprehensive textbook. 3
