Skip to main content
SpringerLink
Log in

A Dynamic Markov Model for Forecasting Diabetes Prevalence in the United States through 2050

  • Published:
Health Care Management Science Aims and scope Submit manuscript

Abstract

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Centers for Disease Control and Prevention, Diabetes Surveillance (1999) Ch. 1, The Public Health Burden of Diabetes Mellitus in the United States. (Available at http://www.cdc.gov/diabetes/statistics/ survl99/chap1/contents.htm, accessed April 2001.)

    Google Scholar 

  2. American Diabetes Association, Economic consequences of diabetes mellitus in the U.S. in 1997, Diabetes Care 21(2) (1998) 296-309.

    Google Scholar 

  3. R.B. Helms, Implications of population growth on prevalence of diabetes: A look at the future, Diabetes Care 15(S1) (1992) 6-9.

    Google Scholar 

  4. H. King, R.E. Aubert and W.H. Herman, Global burden of diabetes, 1995-2025: Prevalence, numerical estimates, and projections, Diabetes Care 21(9) (1998) 1414-1431.

    Google Scholar 

  5. J.P. Boyle, A.A. Honeycutt, K.M. Venkat-Narayan, T.J. Hoerger, L.S. Geiss, H. Chen and T.J. Thompson, Projection of diabetes burden and cost through 2050: Impact of changing demography and disease prevalence in the U.S., Diabetes Care 24(11) (2001) 1936-1940.

    Google Scholar 

  6. D. Ruwaard, R.T. Hoogenveen, H. Verkleij, D. Kromhout, A.F. Casparie and E.A. van der Veen, Forecasting the number of diabetic patients in The Netherlands in 2005, American Journal of Public Health 83(7) (1993) 989-995.

    Google Scholar 

  7. Centers for Disease Control and Prevention, Diabetes Surveillance, Prevalence and Incidence (1999) Ch. 2. (Available at http://www.cdc. gov/diabetes/statistics/surv1999/chap2/contents.htm, accessed February 2002.)

  8. U.S. Census Bureau, Annual Projections of the Resident Population by Age, Sex, Race and Hispanic Origin: Lowest, Middle, Highest, and Zero International Migration Series, 1999 to 2100, Population Projections Program, Population Division, U.S. Census Bureau, Washington, DC (2000).

    Google Scholar 

  9. S.L. Botman, T.F. Moore, C.L. Moriarity and V.L. Parsons, Design and estimation for the National Health Interview Survey, 1995-2004, National Center for Health Statistics, Vital and Health Statistics 2(130) (2000).

  10. P.J. O'Conner, W.A. Rush, N.P. Pronk and L.M. Cherney, Identifying diabetes mellitus or heart disease among health maintenance organization members: Sensitivity, specificity, predictive value, and cost of survey and database methods, American Journal of Management Care 4 (1998) 335-342.

    Google Scholar 

  11. W.S. Edwards, D.M. Winn and V. Kurlantzick, Evaluation of National Health Interview Survey diagnostic reporting, Vital and Health Statistics 2(120).

  12. C.F. Turner, T.K. Smith and L.K. Fitterman, The quality of health care data obtained in a new survey of elderly Americans: A validation study of the proposed Medicare beneficiary health status registry, Journal of Gerontology: Social Sciences 52B (1997) S49-S58.

    Google Scholar 

  13. S.J. Kenney, R.E. Aubert and L.S. Geiss, Prevalence and incidence of non-insulin-dependent diabetes, in: Diabetes in America, 2nd Ed., ed. M.I. Harris, NIH pub. No. 95-1468 (1995).

  14. G. Schwarz, Estimating the dimension of a model, Annals of Statistics 6 (1978) 461-464.

    Google Scholar 

  15. D.W. Hosmer and S. Lemeshow, Goodness-of-fit tests for the multiple logistic regression model, Communications in Statistics - Theory and Methods 9 (1980) 1043-1069.

    Google Scholar 

  16. F.W. Hollmann, T.J. Mulder and J.E. Kallan, U.S. Census Bureau, Methodology and Assumptions for the Population Projections of the United States, 1999 to 2100, Population Division Working Paper No. 38, U.S. Census Bureau, Washington, DC. (Available at http:// www.census.gov/population/www/documentation/twps0038.pdf, January 13, 2000.)

    Google Scholar 

  17. U.S. Census Bureau, Component Assumptions of the Resident Population by Age, Sex, Race, and Hispanic Origin: Lowest, Middle, and Highest Series, 1999 to 2100, Population Projections Program, Population Division, U.S. Census Bureau, Washington, DC (2000).

    Google Scholar 

  18. E.F. Tierney, L.S. Geiss, M.M. Engelgau, T.J. Thompson, D. Schaubert, L.A. Shireley, P.J. Vukelic and S.L. McDonough, Population-based estimates of mortality associated with diabetes: Use of a death certificate check box in North Dakota, American Journal of Public Health 91(1) (2001) 84-92.

    Google Scholar 

  19. J.S. Dorman, R.E. Laporte, L.H. Kuller, K.J. Cruickshanks, T.J. Orchard, D.K. Wagener, D.J. Becker, D.E. Cavender and A.L. Drash, The Pittsburgh insulin-dependent diabetes mellitus (IDDM) morbidity and mortality study: Mortality results, Diabetes 33(3) (1984) 271-276.

    Google Scholar 

  20. S.E. Moss, R. Klein and B.E. Klein, Cause-specific mortality in a population-based study of diabetes, American Journal of Public Health 81(9) (1991) 1158-1162.

    Google Scholar 

  21. R. Lipton, G. Good, T. Mikhailov, S. Freels and E. Donoghue, Ethnic differences in mortality from insulin-dependent diabetes mellitus among people less than 25 years of age, Pediatrics 103(5) (1999) 952-956.

    Google Scholar 

  22. K. Gu, C.C. Cowe and M.I. Harris, Mortality in adults with and without diabetes in a national cohort of the U.S. population, 1971-1993, Diabetes Care 21(7) (1998) 1138-1145.

    Google Scholar 

  23. Diabetes Prevention Program Research Group, Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin, New England Journal of Medicine 346(6) (2002) 393-403.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Research Triangle Institute (RTI), USA

    Amanda A. Honeycutt, Kristine R. Broglio & Thomas J. Hoerger

  2. Division of Diabetes Translation, Centers for Disease Control and Prevention (CDC), 4770 Buford Hwy, NE, MS K-10, Atlanta, GA, 30341-3724

    James P. Boyle, Theodore J. Thompson, Linda S. Geiss & K.M. Venkat Narayan

Authors
  1. Amanda A. Honeycutt
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. James P. Boyle
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Kristine R. Broglio
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Theodore J. Thompson
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Thomas J. Hoerger
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Linda S. Geiss
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. K.M. Venkat Narayan
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

About this article

Cite this article

Honeycutt, A.A., Boyle, J.P., Broglio, K.R. et al. A Dynamic Markov Model for Forecasting Diabetes Prevalence in the United States through 2050. Health Care Management Science 6, 155–164 (2003). https://doi.org/10.1023/A:1024467522972

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1024467522972

Search

Navigation