Introduction:
This study explored the demographic and social correlates differentiating women receiving optimal antenatal care (ANC) from those receiving sub-optimal care in Ghana.

Methods:
A national sample (n=1970) was studied. The sample consisted of women aged 15-49 years from all the ten regions, and from both urban and rural parts of Ghana. Data for the study were obtained from the Measure Demographic and Health Survey 2008 (Measure DHS+ 2008). The variable of optimal and sub-optimal antenatal care was composed by determining the number and timing of antenatal care visits to health facilities and the content of the service package given to women at ANC facilities. The influence of a wide array of variables on optimal antenatal care was tested through bivariate and logistic regression analyses performed using IBM’s SPSS version 19.

Results:
Only one classical social determinant of health, wealth, was statistically significantly associated with optimal antenatal care. The other variables that were not classical social determinants of health but also statistically significant were; health insurance coverage, participating in a literacy program, getting money for medical treatment and concern about the availability of drugs at medical facility after controlling for age. Wealth was by far the strongest predictor of optimal care after controlling for age. Compared to women living in households in the richest quintile as the reference group, women in the middle quintile were 1.7 times more likely to have received sub-optimal antenatal care. The odds of receiving sub-optimal care were 2.1 and 2.9 in the poorer and poorest quintiles, respectively compared to the reference category. Compared to the reference category which was women having health insurance, women without health insurance were 1.3 times more likely to have received sub-optimal antenatal care. With regards to participating in a literacy program, the odds of receiving sub-optimal care was twice for not participating in a literacy program compared to participating in a literacy program which was the reference category. In relation to getting money for medical treatment, women who had difficulty getting money for medical treatment were 1.2 times less likely to have received optimal care compared to the reference group which was having no problem getting money for medical treatment. Finally, regarding the concern for the availability of drugs at medical facilities, no risks were found associated with this variable. Despite the statistical significance of the associations, the fit of the logistic regression model was poor, with just between 4 and 11 percent of the variance in the antenatal care variable accounted for by variance in the predictor variances combined.

Discussion:
With only one classical social determinant of health being a predictor of optimal antenatal care and other widely used measures such as education and occupation not being successful at predicting optimal care, the indication is that there are other factors such as structural and cultural factors that could help explain what factors differentiate women receiving optimal care from those receiving sub-optimal care which were not addressed by this survey. The results of this study however confirm findings in other studies on antenatal care especially in developing countries.

Conclusion:
The outcome of this research makes it imperative for a follow-up qualitative study to study into the life situations of both women receiving optimal and sub-optimal care to determine what factors differentiate the two groups of women.