Title of article :
Multiple correspondence analysis as a tool for analysis of large health surveys in African settings
Author/Authors :
Ayele, Dawit University of KwaZulu-Natal - School of Mathematics, Statistics and Computer Science, South Africa , Zewotir, Temesgen University of KwaZulu-Natal - School of Mathematics, Statistics and Computer Science, South Africa , Mwambi, Henry University of KwaZulu-Natal - School of Mathematics, Statistics and Computer Science, South Africa , ayele, d. school of mathematics,statistics and computer science,university of kwazulu-natal pietermaritzburg,private bag x01, South Africa , zewotir, t. school of mathematics,statistics and computer science,university of kwazulu-natal pietermaritzburg,private bag x01, South Africa , mwambi, h. school of mathematics,statistics and computer science,university of kwazulu-natal pietermaritzburg,private bag x01, South Africa
From page :
1036
To page :
1045
Abstract :
Background: More than two thirds of the total population of Ethiopia is estimated to be at risk of malaria. Therefore, malaria is the leading public health problem in Ethiopia. Objective: To investigate the determinants of malaria Rapid Diagnosis Test (RDT) result and the association between socio-economic, demographic and geographic factors. Method: The study used data from household cluster malaria survey which was conducted from December 2006 to January 2007. A total of 224 clusters of about 25 households each were selected from the Amhara, Oromiya and Southern Nation Nationalities and People (SNNP) regions of Ethiopia. A multiple correspondence analysis was used to jointly analyse malaria RDT result, socio-economic, demographic and geographic factors. Results: The result from multiple correspondence analysis shows that there is association between malaria RDT result and different socio-economic, demographic and geographic variables. Conclusion: There is an indication that some socio-economic, demographic and geographic factors have joint effects. It is important to confirm the association between socio-economic, demographic and geographic factors using advanced statistical techniques.
Keywords :
MCA , CA , malaria , RDT
Journal title :
African Health Sciences
Journal title :
African Health Sciences
Record number :
2634476
Link To Document :
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