Spatial Associations Between Contaminated Land and Socio Demographics in Ghana

International Journal of Environmental Research and Public Health

Russell Dowling²  Bret Ericson²  Jack Caravanos³  Patrick Grigsby²  Yaw Amoyaw-Osei¹ 

[1] Green Advocacy Ghana, P.O. Box SK 482, Sakumono Estates, Tema, Ghana; E-Mail:;Pure Earth, Formerly Blacksmith Institute, 475 Riverside Drive, Suite 860, New York, NY 10115, USA; E-Mails:;School of Public Health, City University of New York, 2180 Third Ave, New York, NY 10035, USA; E-Mail:

关键词: Ghana;    contaminated sites;    socio demographics;    environmental justice;   

DOI  :  10.3390/ijerph121013587

来源: mdpi

【 摘 要 】

Associations between contaminated land and socio demographics are well documented in high-income countries. In low- and middle-income countries, however, little is known about the extent of contaminated land and possible demographic correlations. This is an important yet sparsely researched topic with potentially significant public health implications as exposure to pollution remains a leading source of morbidity and mortality in low-income countries. In this study, we review the associations between several socio demographic factors (population, population density, unemployment, education, and literacy) and contaminated sites in Ghana. Within this context, both correlation and association intend to show the relationship between two variables, namely contaminated sites and socio demographics. Aggregated district level 2010 census data from Ghana Statistical Service and contaminated site location data from Pure Earth’s Toxic Sites Identification Program (TSIP) were spatially evaluated using the number of sites per kilometer squared within districts as the unit of measurement. We found a low to medium positive correlation (ρ range: 0.285 to 0.478) between contaminated sites and the following socio demographics: higher population density, higher unemployment, greater education, and higher literacy rate. These results support previous studies and suggest that several socio demographic factors may be reasonably accurate predictors of contaminated site locations. More research and targeted data collection is needed to better understand these associations with the ultimate goal of developing a predictive model.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.