an examination of the role of antenatal care attendance in ...

(v) Highest educational level
Education is likely to influence frequency of antenatal care visits. A number of studies show that
women with high levels of education are likely to utilize health care facilities available to them unlike
women with lower levels of education (Magadi et al. 2003; Nielsen et al. 2001 and Morrison 1989).
The education variable was used as an independent variable and was divided into four categories: 'no
education', 'primary education', secondary education', and 'tertiary education'.
(yi) Demographic factors
Several studies suggest that there are differences in antenatal care attendance based on the demographic
characteristics of the mother (Grjibovski et al. 2002; Fuentes-Afflick and Hessol 2000 and Fraser et al.
1995). Some of the socio-demographic characteristics used in the study include age of the mother,
parity, place of residence, and ethnicity.
3.2 Statistical Techniques
Data was analyzed using Statistical Package for Social Sciences (SPSS) program. The following test
statistics were used:
Univariate analysis is used to describe the characteristics of the women in the sample, frequency of
antenatal care and adverse birth outcome. Bivariate analysis was used to examine the effect of sociodemographic
characteristics on antenatal care and the effect of antenatal care on birth outcomes. First,
the effect of socio-economic and demographic factors (age of the mother, highest education level, API,
place of residence and parity) on antenatal care was analysed. Second, the effect of antenatal care
factors (number of antenatal care visits and timing of first antenatal care visit) on birth outcomes were
also analysed. Chi squared test for homogeneity was used in the bivariate analysis to identify factors
significantly associated with the outcome variable since the dependant variables were categorical.
Multivariate analysis (specifically binary logistic regression) was used to examine the impact of sociodemographic
characteristics and antenatal care on birth outcomes. The odd ratios were calculated,
where the event of adverse birth outcome was coded as 1 and 0 where there was no event.
The binary logistic regression is usually represented by the following equation:
Y
=Pxx^P2x2+-PpxP+Jui
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