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Future prevalence of type 2 diabetes—A comparative analysis of chronic disease projection methods

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  • Dina Voeltz
  • Thaddäus Tönnies
  • Ralph Brinks
  • Annika Hoyer

Abstract

Background: Accurate projections of the future number of people with chronic diseases are necessary for effective resource allocation and health care planning in response to changes in disease burden. Aim: To introduce and compare different projection methods to estimate the number of people with diagnosed type 2 diabetes (T2D) in Germany in 2040. Methods: We compare three methods to project the number of males with T2D in Germany in 2040. Method 1) simply combines the sex- and age-specific prevalence of T2D in 2010 with future population distributions projected by the German Federal Statistical Office (FSO). Methods 2) and 3) additionally account for the incidence of T2D and mortality rates using partial differential equations (PDEs). Method 2) models the prevalence of T2D employing a scalar PDE which incorporates incidence and mortality rates. Subsequently, the estimated prevalence is applied to the population projection of the FSO. Method 3) uses a two-dimensional system of PDEs and estimates future case numbers directly while future mortality of people with and without T2D is modelled independently from the projection of the FSO. Results: Method 1) projects 3.6 million male people with diagnosed T2D in Germany in 2040. Compared to 2.8 million males in 2010, this equals an increase by 29%. Methods 2) and 3) project 5.9 million (+104% compared to 2010) and 6.0 million (+116%) male T2D patients, respectively. Conclusions: The results of the three methods differ substantially. It appears that ignoring temporal trends in incidence and mortality may result in misleading projections of the future number of people with chronic diseases. Hence, it is essential to include these rates as is done by method 2) and 3).

Suggested Citation

  • Dina Voeltz & Thaddäus Tönnies & Ralph Brinks & Annika Hoyer, 2022. "Future prevalence of type 2 diabetes—A comparative analysis of chronic disease projection methods," PLOS ONE, Public Library of Science, vol. 17(3), pages 1-14, March.
  • Handle: RePEc:plo:pone00:0264739
    DOI: 10.1371/journal.pone.0264739
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