Exploratory Cluster Analysis to Identify Patterns of Chronic Kidney Disease in the 500 Cities Project

Chronic kidney disease is a leading cause of death in the United States. We used cluster analysis to explore patterns of chronic kidney disease in 500 of the largest US cities. After adjusting for socio-demographic characteristics, we found that unhealthy behaviors, prevention measures, and health o...

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Detalles Bibliográficos
Autores principales: Liu, Shelley H., Li, Yan, Liu, Bian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Centers for Disease Control and Prevention 2018
Materias:
Brief
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5985899/
https://www.ncbi.nlm.nih.gov/pubmed/29786500
http://dx.doi.org/10.5888/pcd15.170372
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author Liu, Shelley H.
Li, Yan
Liu, Bian
author_facet Liu, Shelley H.
Li, Yan
Liu, Bian
author_sort Liu, Shelley H.
collection PubMed
description Chronic kidney disease is a leading cause of death in the United States. We used cluster analysis to explore patterns of chronic kidney disease in 500 of the largest US cities. After adjusting for socio-demographic characteristics, we found that unhealthy behaviors, prevention measures, and health outcomes related to chronic kidney disease differ between cities in Utah and those in the rest of the United States. Cluster analysis can be useful for identifying geographic regions that may have important policy implications for preventing chronic kidney disease.
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spelling pubmed-59858992018-06-13 Exploratory Cluster Analysis to Identify Patterns of Chronic Kidney Disease in the 500 Cities Project Liu, Shelley H. Li, Yan Liu, Bian Prev Chronic Dis Brief Chronic kidney disease is a leading cause of death in the United States. We used cluster analysis to explore patterns of chronic kidney disease in 500 of the largest US cities. After adjusting for socio-demographic characteristics, we found that unhealthy behaviors, prevention measures, and health outcomes related to chronic kidney disease differ between cities in Utah and those in the rest of the United States. Cluster analysis can be useful for identifying geographic regions that may have important policy implications for preventing chronic kidney disease. Centers for Disease Control and Prevention 2018-05-17 /pmc/articles/PMC5985899/ /pubmed/29786500 http://dx.doi.org/10.5888/pcd15.170372 Text en https://creativecommons.org/licenses/by/4.0/This is a publication of the U.S. Government. This publication is in the public domain and is therefore without copyright. All text from this work may be reprinted freely. Use of these materials should be properly cited.
spellingShingle Brief
Liu, Shelley H.
Li, Yan
Liu, Bian
Exploratory Cluster Analysis to Identify Patterns of Chronic Kidney Disease in the 500 Cities Project
title Exploratory Cluster Analysis to Identify Patterns of Chronic Kidney Disease in the 500 Cities Project
title_full Exploratory Cluster Analysis to Identify Patterns of Chronic Kidney Disease in the 500 Cities Project
title_fullStr Exploratory Cluster Analysis to Identify Patterns of Chronic Kidney Disease in the 500 Cities Project
title_full_unstemmed Exploratory Cluster Analysis to Identify Patterns of Chronic Kidney Disease in the 500 Cities Project
title_short Exploratory Cluster Analysis to Identify Patterns of Chronic Kidney Disease in the 500 Cities Project
title_sort exploratory cluster analysis to identify patterns of chronic kidney disease in the 500 cities project
topic Brief
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5985899/
https://www.ncbi.nlm.nih.gov/pubmed/29786500
http://dx.doi.org/10.5888/pcd15.170372
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