Introduction: Type 2 diabetes (T2D) represents the leading cause of Chronic Kidney Disease (CKD) worldwide. While variation in T2D prevalence in the U.S. is well established, regional variation in the prevalence of CKD in patients with or without (w/o) T2D is less well characterized and may inform targeted implementation of risk-reducing interventions.

Objective: We explored regional variations in the prevalence of CKD in patients with or w/o T2D in the U.S.

Method: Data from January 1, 2013 through December 31, 2017 from an employer-based claims database (MarketScan) was used for this analysis. Continuously enrolled patients aged ≥18 years diagnosed with CKD with or w/o T2D were identified using International Classification of Disease diagnosis codes. We estimated overall CKD, CKD+T2D, and CKD w/o T2D prevalence for each year from 2013 to 2017. Geo-mapping was used to visualize the prevalence of CKD. Univariate and differential local indicators for spatial analyses (LISA) were performed to describe the geographic differences of CKD prevalence.

Results: The overall prevalence of CKD doubled from 1.50% in 2013 to 3.11% in 2017. Within the CKD population, 46.3% had T2D in 2017. The prevalence of CKD+T2D increased from 0.70% in 2013 to 1.44% in 2017. From 2013 to 2017, low-low clusters from univariate LISA were consistently observed in the Northwest regions (e.g., MT, WY) (P<0.05), indicating the consistently low prevalence of CKD in these areas. High-high clusters from differential LISA, which implied the clusters of increasing CKD prevalence, were found in the Southeast regions (e.g., FL, MS) (P<0.05).

Conclusion: This study provides real-world evidence of regional variations in CKD prevalence in the U.S. Additionally, this study identified lower CKD prevalence than previously cited in the literature, which may indicate major under-coding in the employer-based claims database. Further characterization of CKD patients with or w/o T2D could help understand these variations.


X. Feng: None. R. Farej: Employee; Self; Bayer U.S. F. Xia: None. A.S. Gaiser: None. S. Kong: None. J. Elliott: None. S. Lindemann: None. R. Singh: None.

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