Spatial statistics detect clustering patterns of kidney diseases in south-eastern Romania

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Medical geography was conceptualized almost ten years ago due to its obvious usefulness in epidemiological research. Still, numerous diseases in many regions were neglected in these aspects of research, and the prevalence of kidney diseases in Eastern Europe is such an example. We evaluated the spatial patterns of main kidney diseases in south-eastern Romania, and highlighted the importance of spatial modeling in medical management in Romania. We found two statistically significant hotspots of kidney diseases prevalence. We also found differences in the spatial patterns between categories of diseases. We propose to speed up the process of creating a national database of records on kidney diseases. Offering the researchers access to a national database will allow further epidemiology studies in Romania and finally lead to a better management of medical services.

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  • 1. Gatrell A.C. & Bailey T.C. (1996). Interactive spatial data analysis in medical geography. Social Science & Medicine. 42(6) 843-855.

  • 2. Waller L.A. & Gotway C.A. (2004). Applied spatial statistics for public health data. New Jersey: John Wiley & Sons Inc.

  • 3. Hjalmars U.L.F. Kulldorff M. Gustafsson G. & Nagarwalla N (1996) Childhood leukaemia in Sweden: Using GIS and a spatial scan statistic for cluster detection. Statistics in Medicine 15(7-9):707-715.

  • 4. Curhan G.C. (2007). Epidemiology of Stone Disease. Urologic Clinics of North America. 34(3) 287-293.

  • 5. Soucie J.M. Coates R.J. McClellan W.M. Austin H. & Thun M. (1996). Relation between geographic variability in kidney stones prevalence and risk factors for stones. American Journal of Epidemiology 143(5) 487-495.

  • 6. Getis A. & Ord J.K. (2010). The analysis of spatial association by use of distance statistics. Geographical Analysis 24 189–206.

  • 7. Ord J.K. & Getis A. (1995). Local spatial autocorrelation statistics: distributional issues and an application. Geographical analysis. 27 286–306.

  • 8. Klebe B. Irving J. Stevens P.E. O’Donoghue D.J. de Lusignan S. Cooley R. Hobbs H. Lamb E.J. John I. Middleton R. New J. & Farmer C.K. (2007). The cost of implementing UK guidelines for the management of chronic kidney disease. Nephrology Dialysis Transplantation. 22(9) 2504-2512.

  • 9. McClellan A.C. Plantinga L. & McClellan W.M. (2012). Epidemiology geography and chronic kidney disease. Current Opinion in Nephrology and Hypertension. 21 323–328.

  • 10. Stengel B. Combe C. Jacquelinet C. et al. (2014). The French Chronic Kidney Disease-Renal Epidemiology and Information Network (CKD-REIN) cohort study. Nephrology Dialysis Transplantation. 29(8) 1500-1507

  • 11. Hsu R.K. McCulloch C.E. Ku E. Dudley R.A. & Hsu C. (2013). Regional Variation in the Incidence of Dialysis-Requiring AKI in the United States. Clinical Journal of the American Society of Nephrology : CJASN. 8(9) 1476-1481.

  • 12. Xie Y. & Chen X. (2008). Epidemiology major outcomes risk factors prevention and management of Chronic Kidney Disease in China. Am J Nephrol 28 1-7.

  • 13. Stefanovic V. Radovanovic Z. (2008). Balkan endemic nephropathy and associated urothelial cancer. Nature Reviews Urology. 5(2) 105-112.

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