Research
Principal component analysis of socioeconomic factors and their association with malaria in children from the Ashanti Region, Ghana
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* Corresponding author: Anne C Krefis krefis@bni-hamburg.de
1 Bernhard-Nocht-Institute for Tropical Medicine, Infectious Disease Epidemiology, Bernhard-Nocht-Straße 74, 20359 Hamburg, Germany
2 Environmental Health Research Institute (IUF), Heinrich Heine University of Düsseldorf, Germany
3 Kumasi Centre for Collaborative Research in Tropical Medicine, Kumasi, Ghana
4 Kwame Nkrumah University of Science and Technology, School of Medical Sciences, Kumasi, Ghana
Malaria Journal 2010, 9:201 doi:10.1186/1475-2875-9-201
Published: 13 July 2010Abstract
Background
The socioeconomic and sociodemographic situation are important components for the design and assessment of malaria control measures. In malaria endemic areas, however, valid classification of socioeconomic factors is difficult due to the lack of standardized tax and income data. The objective of this study was to quantify household socioeconomic levels using principal component analyses (PCA) to a set of indicator variables and to use a classification scheme for the multivariate analysis of children < 15 years of age presented with and without malaria to an outpatient department of a rural hospital.
Methods
In total, 1,496 children presenting to the hospital were examined for malaria parasites and interviewed with a standardized questionnaire. The information of eleven indicators of the family's housing situation was reduced by PCA to a socioeconomic score, which was then classified into three socioeconomic status (poor, average and rich). Their influence on the malaria occurrence was analysed together with malaria risk co-factors, such as sex, parent's educational and ethnic background, number of children living in a household, applied malaria protection measures, place of residence and age of the child and the mother.
Results
The multivariate regression analysis demonstrated that the proportion of children with malaria decreased with increasing socioeconomic status as classified by PCA (p < 0.05). Other independent factors for malaria risk were the use of malaria protection measures (p < 0.05), the place of residence (p < 0.05), and the age of the child (p < 0.05).
Conclusions
The socioeconomic situation is significantly associated with malaria even in holoendemic rural areas where economic differences are not much pronounced. Valid classification of the socioeconomic level is crucial to be considered as confounder in intervention trials and in the planning of malaria control measures.