BMC Medical Research Methodology (Feb 2023)

Estimating incidence of type 1 and type 2 diabetes using prevalence data: the SEARCH for Diabetes in Youth study

  • Annika Hoyer,
  • Ralph Brinks,
  • Thaddäus Tönnies,
  • Sharon H. Saydah,
  • Ralph B. D’Agostino,
  • Jasmin Divers,
  • Scott Isom,
  • Dana Dabelea,
  • Jean M. Lawrence,
  • Elizabeth J. Mayer-Davis,
  • Catherine Pihoker,
  • Lawrence Dolan,
  • Giuseppina Imperatore

DOI
https://doi.org/10.1186/s12874-023-01862-3
Journal volume & issue
Vol. 23, no. 1
pp. 1 – 8

Abstract

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Abstract Background Incidence is one of the most important epidemiologic indices in surveillance. However, determining incidence is complex and requires time-consuming cohort studies or registries with date of diagnosis. Estimating incidence from prevalence using mathematical relationships may facilitate surveillance efforts. The aim of this study was to examine whether a partial differential equation (PDE) can be used to estimate diabetes incidence from prevalence in youth. Methods We used age-, sex-, and race/ethnicity-specific estimates of prevalence in 2001 and 2009 as reported in the SEARCH for Diabetes in Youth study. Using these data, a PDE was applied to estimate the average incidence rates of type 1 and type 2 diabetes for the period between 2001 and 2009. Estimates were compared to annual incidence rates observed in SEARCH. Precision of the estimates was evaluated using 95% bootstrap confidence intervals. Results Despite the long period between prevalence measures, the estimated average incidence rates mirror the average of the observed annual incidence rates. Absolute values of the age-standardized sex- and type-specific mean relative errors are below 8%. Conclusions Incidence of diabetes can be accurately estimated from prevalence. Since only cross-sectional prevalence data is required, employing this methodology in future studies may result in considerable cost savings.

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