For a study, it was determined that the prevalence of chronic kidney disease (CKD) in patients with and without type 2 diabetes mellitus (T2DM) was not adequately studied in terms of regional variation. Comparative spatial and temporal analysis was used in the study design. Patients with CKD in general and subgroups of patients with CKD with and without T2DM in the United States were identified using MarketScan datasets. CKD prevalence trends by year, regional clusters of CKD between years, and patient features in high-prevalence states. From 2013 to 2018, mapping was used to illustrate state-level data on CKD prevalence. To assess geographic differences in prevalence, researchers utilized univariate local indicators of spatial association (LISA), differential LISA for changes in CKD prevalence over time, and the X2 test to identify patient features in the top-20th percentile states for CKD prevalence. Low-low clusters, in which a state had a low CKD prevalence and the surrounding states had a below-average CKD prevalence, were observed throughout the study period in the northwest region, regardless of T2DM status, indicating a consistently low prevalence of CKD clustered in these areas in univariate LISA. High-high clusters were reported in the southeast region, irrespective of T2DM status, indicating an increased CKD prevalence in the area. The estimates were based on claims data, which likely understated the true prevalence. Health insurance enrollment may not have been typical of the United States. Geographic differences in CKD prevalence were becoming more pronounced, increasing in the United States’ southeastern region. This rise was particularly concerning because individuals with CKD in high-prevalence states were more likely to develop chronic diseases than those in the rest of the country.
Source – www.sciencedirect.com/science/article/pii/S2590059521002284
