Background: Population rates of obesity, hypertension, diabetes, age, and race can be used in simulation models to develop projections of ESRD incidence and prevalence. Such projections can inform long-range planning for ESRD resources needs.
Methods: We used an open compartmental simulation model to estimate the incidence and prevalence of ESRD in the United States through 2030 on the basis of wide-ranging projections of population obesity and ESRD death rates. Population trends in age, race, hypertension, and diabetes were on the basis of data from the Centers for Disease Control and Prevention's National Health and Nutrition Examination Survey and the US Census.
Results: The increase in ESRD incidence rates within age and race groups has leveled off and/or declined in recent years, but our model indicates that population changes in age and race distribution, obesity and diabetes prevalence, and ESRD survival will result in a 11%-18% increase in the crude incidence rate from 2015 to 2030. This incidence trend along with reductions in ESRD mortality will increase the number of patients with ESRD by 29%-68% during the same period to between 971,000 and 1,259,000 in 2030.
Conclusions: The burden of ESRD will increase in the United States population through 2030 due to demographic, clinical, and lifestyle shifts in the population and improvements in RRT. Planning for ESRD resource allocation should allow for substantial continued growth in the population of patients with ESRD. Future interventions should be directed to preventing the progression of CKD to kidney failure.
Keywords: United States Renal Data System; computer simulation; demographic trends; end stage kidney disease.
Copyright © 2019 by the American Society of Nephrology.