Oluseyi Olubunimi FABIYI*1, Oluwashogo Elizabeth GARUBA2
* Corresponding author
1 Obafemi Awolowo University, Department of Cartography, Regional Centre for Training in Aerospace Surveys, Ile-Ife, NIGERIA
2 Obafemi Awolowo University, Department of Geographic Information Science, Regional Centre for Training in Aerospace Surveys, Ile-Ife, NIGERIA
E-mail: fabiyi@rectas.org, seyifabiyi@yahoo.com
Pages: 61-69. URL: https://geografie.ubbcluj.ro/ccau/jssp/arhiva_1_2015/07JSSP012015.pdf
Cite: Fabiyi O. O., Garuba O. E. (2015), Geo-Spatial Analysis of Cardiovascular Disease and Biomedical Risk Factors in Ibadan, South-Western Nigeria. Journal of Settlements and Spatial Planning, 6(1), 61-69. URL: https://geografie.ubbcluj.ro/ccau/jssp/arhiva_1_2015/07JSSP012015.pdf
Abstract. The burden of the cardiovascular disease (CVD) is increasing in both developing and developed countries. CVD is now a major cause of death globally killing people in their productive years more than any other disease. In Nigeria, CVDs account for about 12% of all deaths recorded among the low and middle income group. This study examined the spatial pattern of the CVD disease burden in Ibadan city and among the neighbourhoods and the spatial pattern of biomedical risk factors. Hospital records, population data and geocode map of Ibadan were acquired for the study. Global Moran, Anselin Moran, Geographically Weighted Regression (GWR) and logistic regression were employed to examine the spatial pattern of CVD, and correlation between CVD and biomedical risk factors. At the global level a random pattern was observed at a significance level of 0.05, the spatial pattern of CVD at Moran’s I of -0.04 is random, while a clustered pattern was observed at neighbourhood level. The relationship between the spatial pattern of CVD and the biomedical risk factors was statistically significant (R2= 0.634) which indicated a very strong positive spatial autocorrelation in the study area.
K e y w o r d s: cardiovascular disease; risk-factor, spatial pattern; medical statistics, spatial clustering, GIS