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The Future Burden of CKD in the United States: A Simulation Model for the CDC CKD Initiative
Open accessAbstract
Background Awareness of chronic kidney disease (CKD), defined by kidney damage or reduced glomerular filtration rate, remains low in the United States, and few estimates of its future burden exist.Study design We used the CKD Health Policy Model to simulate the residual lifetime incidence of CKD and project the prevalence of CKD in 2020 and 2030. The simulation sample was based on nationally representative data from the 1999 to 2010 National Health and Nutrition Examination Surveys.Setting & population Current US population.Model, perspective, & timeline Simulation model following up individuals from current age through death or age 90 years.Outcomes Residual lifetime incidence represents the projected percentage of persons who will develop new CKD during their lifetimes. Future prevalence is projected for 2020 and 2030.Measurements Development and progression of CKD are based on annual decrements in estimated glomerular filtration rates that depend on age and risk factors.Results For US adults aged 30 to 49, 50 to 64, and 65 years or older with no CKD at baseline, the residual lifetime incidences of CKD are 54%, 52%, and 42%, respectively. The prevalence of CKD in adults 30 years or older is projected to increase from 13.2% currently to 14.4% in 2020 and 16.7% in 2030.Limitations Due to limited data, our simulation model estimates are based on assumptions about annual decrements in estimated glomerular filtration rates.Conclusions For an individual, lifetime risk of CKD is high, with more than half the US adults aged 30 to 64 years likely to develop CKD. Knowing the lifetime incidence of CKD may raise individuals' awareness and encourage them to take steps to prevent CKD. From a national burden perspective, we estimate that the population prevalence of CKD will increase in coming decades, suggesting that development of interventions to slow CKD onset and progression should be considered.
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“From data from NHANES 1999 to 2010, the lifetime risk of developing (or “progressing to”) moderate-stage CKD from normal baseline kidney function is 54% (age, 30–49 years), 52% (age, 50–64 years), and 42% (age ≥65 years).299”
From Resistant Hypertension: Detection, Evaluation, and Management: A Scientific Statement From the American Heart Association (2018) · cites this paper as [299]
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Metadata
- Authors
- Hoerger, T. J., Simpson, S. A., Yarnoff, B. O., Pavkov, M. E., Ríos Burrows, N., Saydah, S. H., Williams, D. E., & Zhuo, X.
- Affiliations
- RTI International (US)
- Centers for Disease Control and Prevention (US)
- Corresponding author
- Hoerger, Thomas J.
- ORCID
- Venue
- American Journal of Kidney Diseases
- Publisher
- Elsevier BV
- Published
- 2015-03
- Volume
- 65
- Issue
- 3
- Pages
- 403-411
- ISSN
- 0272-6386 (ISSN-L)
- PMC
- PMC11000251
- OpenAlex
- W2103852969
- Cited by
- 299
- References
- 35
- Citations by year
- 2026: 6 · 2025: 22 · 2024: 20 · 2023: 22 · 2022: 27 · 2021: 29 · 2020: 37 · 2019: 19 · 2018: 34 · 2017: 26 · 2016: 34 · 2015: 23
- FWCI
- 21.87
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- American Journal of Kidney Diseases (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (CC999999)
- Topics
- Health Sciences › Medicine › Nephrology › Chronic Kidney Disease and Diabetes
- Health Sciences › Medicine › Nephrology › Dialysis and Renal Disease Management
- Health Sciences › Medicine › Epidemiology › Chronic Disease Management Strategies
- Keywords
- chronic kidney disease, estimated glomerular filtration rate decline, chronic kidney disease progression, CKD risk factors, CKD prevention
- MeSH terms
- Adult, Aged, Aged, 80 and over, Centers for Disease Control and Prevention, U.S., Female, Forecasting, Humans, Male, Middle Aged, Models, Theoretical, Nutrition Surveys, United States, Cohort Studies, Cost of Illness, Renal Insufficiency, Chronic
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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