Advertisement

GeoJournal

, Volume 80, Issue 5, pp 711–720 | Cite as

Using a dual kernel density estimate as a preliminary evaluation of the spatial distribution of diagnosed chronic kidney disease (CKD) in Edo State, Nigeria

  • Osaretin Isoken Oviasu
Article

Abstract

Chronic kidney disease (CKD) is a growing problem in Nigeria, presenting challenges to the nation’s health and economy. This study presents an analysis of 442 patients with CKD referred to the renal department at the University of Benin Teaching Hospital, Nigeria between 2006 and 2009. It investigates the spatial distribution of the disease across the study area using the kernel density estimate to evaluate the spatial distribution of CKD cases within the state. It involves the analysis of the distribution of CKD cases in relation to their underlying population to determine the areas of high and low density of diagnosed CKD cases across the state. The result highlighted the spatial distribution of diagnosed CKD and also highlighted the areas of concern regarding the spatial distribution of diagnosed CKD within the state. The findings derived from this study would be helpful in the preliminary assessment needed for policy-making decisions that pertain to the strategic allocation of resources for CKD treatment within the health sector.

Keywords

Dual kernel density estimate Spatial analysis Chronic kidney disease Edo State 

References

  1. Agee, M. D. (2010). Reducing child malnutrition in Nigeria: Combined effects of income growth and provision of information about mothers’ access to health care services. Social Science and Medicine, 71(11), 1973–1980. doi: 10.1016/j.socscimed.2010.09.020.CrossRefGoogle Scholar
  2. Akinsola, A., Adelekun, T., & Arogundade, F. (2004). Magnitude of the problem of CRF in Nigerians. African Journal of Nephrology, 8, 24–26.Google Scholar
  3. Arije, A., Kadiri, S., & Akinkugbe, O. O. (2000). The viability of hemodialysis as a treatment option for renal failure in a developing economy. African Journal of Medicine and Medical Sciences, 29(3–4), 311–314.Google Scholar
  4. Arogundade, F. A., & Barsoum, R. S. (2008). CKD Prevention in Sub-Saharan Africa: A call for governmental, nongovernmental, and community support. American Journal of Kidney Diseases, 51(3), 515–523. doi: 10.1053/j.ajkd.2007.12.006.CrossRefGoogle Scholar
  5. Awoyemi, T. T., Obayelu, O. A., & Opaluwa, H. I. (2011). Effect of distance on utilization of health care services in rural Kogi state, Nigeria. Journal of Human Ecology, 35(1), 1–9.Google Scholar
  6. Bamgbose, J. A. (2009). Falsification of population census data in a heterogeneous Nigerian state: The fourth republic example. African Journal of Political Science and International Relations, 3, 311–319.Google Scholar
  7. Bamgboye, E. L. (2003). Hemodialysis: Management problems in developing countries, with Nigeria as a surrogate. Kidney International, 63, 93–95.CrossRefGoogle Scholar
  8. Carlos, H. A., Shi, X., Sargent, J., Tanski, S., & Berke, E. M. (2010). Density estimation and adaptive bandwidths: A primer for public health practitioners. International Journal of Health Geographics, 9(39). doi:  10.1186/1476-072x-9-39.
  9. Dobson, J. E., Bright, E. A., Coleman, P. R., Durfee, R. C., & Worley, B. A. (2000). LandScan: A global population database for estimating populations at risk. Photogrammetric Engineering and Remote Sensing, 66(7), 849–857.Google Scholar
  10. Igah, E., & Okpokpo, E. (1998). The Nigerian demographic problem: The political and economic issues at stake. Acta Geographica, 114, 17–30.Google Scholar
  11. Kidney Consultants International. (2007). Kidney Care. Kidney Consultants International Retrieved 12 May, 2009, from www.kcinigeria.org.
  12. Levine, N. (2004). CrimeStat III: A spatial statistics program for the analysis of crime incident locations (version 3.3). Washington, DC: Ned Levine & Associates, Houston, TX, and the National Institute of Justice. Retrieved from http://www.icpsr.umich.edu/CrimeStat/download.html.
  13. Mak, R. H., & Bakris, G. (2010). Pediatrics masked hypertension: A risk factor in children with CKD. Nature Reviews Nephrology, 6(3), 132–134.Google Scholar
  14. Nigerian Association of Nephrology. (2007). Nigeria: Report on World Kidney Day 2007 activities. World Kidney Day 2007 event: Nigeria Retrieved 14 December, 2010, from http://worldkidneyday.pavtest.com/UserFiles/File/event07/Nigeria%20activity%20report(1).pdf.
  15. NPoC. (2005). 2005 Census awareness attitude survey. National Population Commission Executive Summary for CAAS. Retrieved 25 August, 2010, from http://www.population.gov.ng/files/caas_executive_summary.pdf.
  16. Okolo, A. (1999). The Nigerian census: Problems and prospects. The American Statistician, 53(4), 321–325.Google Scholar
  17. Olowu, W. (2003). Renal failure in Nigerian children: Factors limiting access to dialysis. Pediatric Nephrology, 18(12), 1249–1254.CrossRefGoogle Scholar
  18. Saland, J. M., Pierce, C. B., Mitsnefes, M. M., Flynn, J. T., Goebel, J., Kupferman, J. C., et al. (2010). Dyslipidemia in children with chronic kidney disease. Kidney International, 78(11), 1154–1163.CrossRefGoogle Scholar
  19. Ulasi, I. I., & Ijoma, C. K. (2010). The enormity of chronic kidney disease in Nigeria: The situation in a teaching hospital in South-East Nigeria. Journal of Tropical Medicine, 2010(501957), 1–6. doi: 10.1155/2010/501957.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  1. 1.Regional Centre for Training in Aerospace Surveys (RECTAS)Ile-IfeNigeria

Personalised recommendations