A dynamic Markov model for forecasting diabetes prevalence in the United States through 2050

被引：77

作者：

Amanda A. Honeycutt

James P. Boyle

Kristine R. Broglio

Theodore J. Thompson

Thomas J. Hoerger

Linda S. Geiss

K.M. Venkat Narayan

机构：

[1] Division of Diabetes Translation, Centers for Dis. Contr. and Prev., MS K-10, Atlanta, GA 30341-3724, 4770 Buford Hwy, NE

来源：

Health Care Management Science | 2003年 / 6卷 / 3期

关键词：

Diabetes incidence; Diabetes prevalence; Forecasts; Markov model;

D O I：

10.1023/A:1024467522972

中图分类号：

学科分类号：

摘要：

This study develops forecasts of the number of people with diagnosed diabetes and diagnosed diabetes prevalence in the United States through the year 2050. A Markov modeling framework is used to generate forecasts by age, race and ethnicity, and sex. The model forecasts the number of individuals in each of three states (diagnosed with diabetes, not diagnosed with diabetes, and death) in each year using inputs of estimated diagnosed diabetes prevalence and incidence; the relative risk of mortality from diabetes compared with no diabetes; and U.S. Census Bureau estimates of current population, live births, net migration, and the mortality rate of the general population. The projected number of people with diagnosed diabetes rises from 12.0 million in 2000 to 39.0 million in 2050, implying an increase in diagnosed diabetes prevalence from 4.4% in 2000 to 9.7% in 2050.

引用

页码：155 / 164

页数：9

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