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

RESEARCH BRIEF — Volume 15 — May 17, 2018

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This figure presents the hierarchical relationship and partitions among the 500 cities, plus Washington, DC, using a tree structure to depict clustering. The states initially split into two clusters of approximately equal size. Then, Utah split from the other states in its cluster; the split height is high, meaning that Utah’s characteristics are dissimilar from other states. Meanwhile, several states have low split heights, indicating high similarity. These states are also geographically close to one another and share state borders; they include Arkansas and Oklahoma; Colorado and New Mexico; Arizona and Nevada; Iowa and Illinois; and Minnesota and South Dakota.

Figure 1.
Cluster analysis of 500 US cities, summarized at the state level, plus Washington, DC, based on kidney disease–related factors (unhealthy behaviors, prevention measures, and outcomes related to CKD) and adjusted for socio-demographic characteristics.

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Figure 2.
Variability of kidney disease–related factorsa in Utah cities compared with other cities in the United States.

Utah City Binge Smoking No Leisure-Time Physical Activity Obesity Less Sleep No Insurance Check-up Blood Pressure Meds High Blood Pressure Diabetes Chronic Kidney Disease
Layton −4.41 −2.93 −0.30 −0.22 0.98 0.23 −1.29 −0.30 0.06 0.42 0.40
Ogden −3.47 −1.56 0.12 1.19 1.66 1.74 −1.07 −0.23 0.86 1.00 1.15
Orem −4.75 −4.32 −1.19 −0.47 0.34 0.31 −2.28 −0.65 −1.33 −0.31 1.33
Provo −4.50 −4.33 −1.40 −1.38 0.50 0.86 −2.32 −2.76 −1.86 −1.57 0.55
St. George −3.36 −3.99 −0.83 −0.31 −0.64 0.90 −1.65 −0.62 −1.35 −0.76 0.66
Salt Lake City −2.56 −3.42 −1.23 −0.07 −0.54 0.58 −1.36 −0.27 −0.67 0.02 0.87
Sandy −2.52 −3.01 −1.16 −0.60 −0.07 −0.48 −1.32 −0.72 −0.89 −0.07 0.43
West Jordan −2.40 −2.00 −0.66 −0.76 0.89 0.38 −1.80 −1.89 −1.69 −0.43 0.27
West Valley City −2.66 −2.34 −0.51 −0.27 −0.18 1.72 −1.69 0.14 −0.71 0.36 1.18

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