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Charting Plausible Futures for Diabetes Prevalence in the United States: A Role for System Dynamics Simulation Modeling

Date Activated: 10/08/2007 (Last Updated 05/18/2009)
Contributed By: California Diabetes Program
Author: Milstein B, Jones A, Homer JB, Murphy D, Essien J, Seville D.

Milstein B, Jones A, Homer JB, Murphy D, Essien J, Seville D. (2007) Charting plausible futures for diabetes prevalence in the United States: a role for system dynamics simulation modeling. Preventing Chronic Disease. Full article available at link below.

Abstract

Introduction
Healthy People 2010 (HP 2010) objectives call for a 38% reduction in the prevalence of diagnosed diabetes mellitus, type 1 and type 2, by the year 2010. The process for setting this objective, however, did not focus on the achievability or the compatibility of this objective with other national public health objectives. We used a dynamic simulation model to explore plausible trajectories for diabetes prevalence in the wake of rising levels of obesity in the U.S. population. The model helps to interpret historic trends in diabetes prevalence in the United States and to anticipate plausible future trends through 2010.

Methods
We conducted simulation experiments using a computer model of diabetes population dynamics to 1) track the rates at which people develop diabetes, are diagnosed with the disease, and die, and 2) assess the effects of various preventive-care interventions. System dynamics modeling methodology based on data from multiple sources guided the analyses.

Results
With the number of new cases of diabetes being much greater than the number of deaths among those with the disease, the prevalence of diagnosed diabetes in the United States is likely to continue to increase. Even a 29% reduction in the number of new cases (the HP 2010 objective) would only slow the growth, not reverse it. Increased diabetes detection rates or decreased mortality rates — also HP 2010 objectives — would further increase diagnosed prevalence.

Conclusion
The HP 2010 objective for reducing diabetes prevalence is unattainable given the historical processes that are affecting incidence, diagnosis, and mortality, and even a zero-growth future is unlikely. System dynamics modeling shows why interventions to protect against chronic diseases have only gradual effects on their diagnosed prevalence.

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