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Core regional metrics of chronic kidney disease (CKD) prevalence in the GBD 2019 Study

Authors: Boris, Bikbov;

Core regional metrics of chronic kidney disease (CKD) prevalence in the GBD 2019 Study

Abstract

Chronic kidney disease (CKD) is an important contributor to morbidity and mortality from noncommunicable diseases, and is a highly relevant topic in global health.The Global Burden of Disease, Injuries and Risk Factors (GBD) study presents a comprehensive assessment of the global epidemiology of CKD both as a direct cause of mortality and morbidity and as a risk factor for other diseases. The GBD uses term "impaired kidney function (IKF)" to indicate the CKD as a risk factor for ischaemic heart disease, stroke, peripheral vascular disease, and gout, and underline the difference from the term "CKD" itself that refers to a direct cause of morbidity and mortality due to kidney disease.Scientific-Tools.Org created a series of infographics highlighting different aspects of CKD epidemiology at global, regional and country levels.Suggested citation: Bikbov B. (Scientific-Tools.Org). Core regional metrics of chronic kidney disease (CKD) prevalence in the GBD 2019 Study. Zenodo. DOI https://doi.org/10.5281/zenodo.8312901This work is licensed under a Creative Commons Attribution NoDerivatives License.See other infographics on CKD epidemiology: https://scientific-tools.org/portfolio-item/infographics-on-chronic-kidney-disease-ckd-epidemiologyThe creation of these visualizations and infographics has not been financed by any funds. You can donate to support this and other visualizations at https://scientific-tools.org/support-us/

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Keywords

Caribbean, kidney, impaired kidney function, Asia, Australasia, GBD, prevalence, Oceania, morbidity, Global Health, Europe, Middle East, Latin America, Africa, North America, CKD, Global Burden of Disease Study, epidemiology, Public Health, chronic kidney disease

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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