Exploratory Factor Analysis of Demographic Characteristics of Antenatal Clinic Attendees and their Association with HIV Risk
This research was conducted to determine the applicability of the exploratory factor analysis (EFA) technique to study the correlation between demographic characteristics and HIV risk amongst pregnant women attending antenatal clinics in South Africa. EFA was therefore used as a factor reduction technique to identify the number of latent constructs and underlying factor structure amongst demographic characteristics with regards to their influence on the risk of HIV infection. An iterated principal axis factor (IPAF) technique with three factors and varimax rotation was used as a method of extraction. IPAF method refines the communalities until they converge and has the advantage of analysing both the correlation and covariances. The findings revealed a high positive correlation between agewoman and agepartner (0.81), agewoman and gravidity (0.69), agewoman and parity (0.67) and gravidity and parity (0.93). However, a negative correlation was observed between parity and educational level of the pregnant woman. Based on a scree plot of eigenvalues against demographic characteristics, three components were selected that accounted for 55 percent of total variance. The interpretation of the principal components was based on determining which demographic characteristics factors were strongly correlated within each component. The first component was highly correlated with time dependent demographic characteristics such as age of pregnant women, male sexual partners, gravidity and parity. The second component was found to be highly correlated with spatially related demographic characteristics such as province. The third component was correlated with sexually transmitted diseases such as HIV and syphilis. However, the study showed that the three extracted components were not at all correlated. In summary, this research demonstrated that it is possible to reduce the annual South African antenatal HIV seroprevalence data from eleven demographic characteristics to three principal components using a factor analysis with a principal component extraction method.
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Mediterranean Journal of Social Sciences ISSN 2039-9340(Print) ISSN 2039-2117(Online)
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