The framework for analysing the determinants of maternal mortality in McCarthy (1997:S17) and the behavioural model of health services utilisation (Andersen & Newman 2005:12) were used as the conceptual framework for this study. In the exploration of how SECs of women influences the proximate determinant of maternal mortality, McCarthy (1997:S18) argued that any intervention to reduce maternal death (the ultimate maternal health benefit) must pass through one of three pathways to: (1) reduce the number of pregnancies; (2) reduce the number of complications; or (3) reduce the likelihood that a complication will result in death. The three pathways were contextualised into the four maternal healthcare services in this study (Table 1).

The behavioural model of health services utilisation (Andersen & Newman 2005:12) guided further insight into how SECs of women contribute to exclusion from maternal health benefits. The model was based on the assumption that utilisation of (maternal) health services is dependent on three categories of individual determinants, namely: (1) the predisposition of the individual to use the service; (2) the ability of the individual to secure the service (enabling factor); and (3) the illness level of the individual. This study focused on the predisposing and enabling factors, as the physiological state of pregnancy already defined the ‘illness level’ amongst the study population.

Whilst several efforts and investments were made to improve maternal health in Nigeria, little is known about the complex interplay of the SECs of women on maternal healthcare service utilisation. Available evidence was limited to the consequence of economic hardship on health-seeking behaviours (Akpomuvie 2010:48). A study to describe the impact of women's SECs on the determinants of maternal mortality is therefore required in order to understand the contribution of SECs of women to maternal health benefits in AMAC, Abuja, Nigeria. This study will contribute toward the achievement of MDG 5 and national targets on maternal health in Nigeria.

The maternal health benefit encompasses interventions to reduce death related to pregnancy and its complications. Understanding the predictors (socioeconomic characteristics) of utilisation of these interventions is important with regard to optimisation of the outcome for women. The researchers are of the opinion that policy and programme review informed by the effect of multiple predictors will result in a more effective and equitable outcome than those reviews that consider the influence of the predictors independently. This means that maternal health benefit is not only dependent on availability of maternal healthcare services, but also on the predisposing and enabling factors of utilisation amongst women.

The reliability of the measurement was assured through investigator consistency by using trained professional data collection personnel. This was reinforced by standardising the conditions for measurements by interviewing the women at ANC clinics so as to limit external influence (Cooper & Schindler 2003:239). In addition, the survey instrument was finalised based on the findings from the pilot and the research subjects (pregnant women) were relevant to the study (Babbie & Mouton 2004:121).

The face validity of the research instrument lay in the fact that the question items were derived from an existing questionnaire with established face and content validity (Araoye 2003:151; Patten 2002:55). Content validity of the survey instrument was further assured by basing the questionnaire design on the conceptual framework for the study (Araoye 2003:153; Babbie & Mouton 2004:123). The probability sampling technique in subject selection and the calculation of large sample size for this study contributed to external validity (Araoye 2003:151; Cooper & Schindler 2003:231). Other measures to assure external validity included the design of the questionnaire based on rules for questionnaire construction, the pre-testing of the instrument and ethical rigour, especially with regard to assuring anonymity (the questionnaire identification number cannot be traced to particular respondents).

The socio-demographic characteristics of the respondents are presented in Table 3. The median annual household income was Naira 699 996.00. Regarding income category, 285 (74%) respondents were categorised into the lower income group, 44 (12%) into the average income group and 55 (14%) into the higher income group. Amongst the 91 (24%) respondents who were covered by health insurance, 47 (52%) had public health insurance, 28 (31%) had private or commercial health insurance, 4 (4%) had community-based health insurance and 12 (13%) had other forms of insurance.

The utilisation of maternal healthcare services varied amongst women of different SECs in AMAC (Table 4). Overall, 295 (77%) women utilised ANC, 249 (65%) received skilled delivery care and 245 (64%) received PNC. Although 307 (80%) respondents were aware of contraceptives, the mean knowledge score of contraceptive methods was 2.24 (SD ± 1.88) out of a total score of 13. Amongst the respondents, 52 (14%) had good knowledge of contraceptive methods, 230 (60%) had average knowledge and 102 (27%) had poor knowledge. It was therefore consistent that only 199 (52%) respondents had used modern contraceptive methods.

The differential in the utilisation of modern contraceptive methods (p = 0.002), ANC (p = 0.000), skilled delivery care (p = 0.000) and PNC (p = 0.000) amongst women of different age groups was statistically significant. Similar to earlier studies in Kenya (Okech, Wawire & Mburu 2011:29) and Nigeria (NBS et al. 2013:129; NPC & MEASURE DHS 2013:15), the majority of adolescent respondents in AMAC were excluded from the utilisation of the four maternal healthcare services. This situation reinforces the earlier argument by the WHO (2011:12), which stated that socioeconomic inequities resulting from limited access to funds, requirement of parental consent, societal exclusion because of early marriage or sexual coercion, or discrimination by judgmental health workers faced by adolescents, limits their access to maternal healthcare.

Unlike the trend in earlier reports (Awusi et al. 2009:23; Mekonnen & Mekonnen 2003:375–376), the majority of respondents who utilised the four maternal healthcare services in AMAC had experienced more than one birth. The observed trend was, however, similar to the use of modern contraceptive methods in Kenya (Okech et al. 2011:30). Other than the use of modern contraceptive methods (p = 0.493), the differential in the use of ANC (p = 0.000), skilled delivery care (p = 0.000) and PNC (p = 0.000) amongst respondents with different birth order was statistically significant.

As expected (NBS et al. 2013:130–145; NPC & ICF Macro 2009:69–136; NPC & MEASURE DHS 2013:16–22), the proportion of respondents who used the four maternal healthcare services in this study increased along with an increasing level of maternal education. Likewise in Kenya, Okech et al. (2011:30) reported an increasing proportion of utilisation of modern contraceptive methods amongst women with an increasing level of education. The use of modern contraceptive methods (p = 0.000), skilled delivery care (p = 0.019) and PNC (p = 0.006) amongst respondents with different educational levels was significant. The use of ANC (p = 0.057) amongst women with different education levels was, however, not statistically significant.

Consistent with earlier studies in Nigeria (NBS et al. 2013:129–148; NPC & MEASURE DHS 2013:15–22) and Ethiopia (Mekonnen & Mekonnen 2003:376–378), the majority of respondents who used the four maternal healthcare services lived in urban settings. However, only the differential in the use of modern contraceptive methods (p = 0.000) amongst women resident in different locations (urban/rural) in AMAC was significant. The use of ANC (p = 0.921), skilled delivery care (p = 0.176) and PNC (p = 0.240) were not influenced significantly by location of residence. Divergent influences of location of residence on the use of the different maternal healthcare services were reported in Jamaica and India. According to Say and Raine (2007:815), urban women in Jamaica were significantly less likely (p < 0.05) to attend ANC than rural women. In contrast, studies from India, reviewed in Say and Raine (2007:814), either reported no difference or a significant difference (p < 0.01) in the utilisation of skilled health workers at delivery in favour of urban women.

In general, membership of a health insurance plan is expected to contribute toward higher service utilisation amongst scheme members (Soors, Waelkens & Criel 2008:160). In this study, however, overall coverage of health insurance was low and a lower proportion of respondents who utilised the four maternal healthcare services were covered by health insurance. These findings may be attributed to the documented equity concerns with regard to the coverage and benefit of health insurance in low- and middle-income countries (Meng et al. 2011:94). Other than the use of modern contraceptive methods (p = 0.060), procured largely outside of health facilities, the differential in the use of ANC (p = 0.021), skilled delivery care (p = 0.000) and PNC (p = 0.000) amongst respondents with different health insurance coverage were statistically significant. Amongst the 201 (52%) respondents who had procured contraceptives in this study, only 28 (14%) had procured these from health facilities whilst the remaining 173 (86%) had procured their contraception from street vendors, non-governmental organisations and local pharmaceutical stores.

The highest proportion of respondents who utilised the four maternal healthcare services in AMAC were in the lower income category. Unlike earlier reports (NBS et al. 2013:130–145; NPC & ICF Macro 2009:71–136), this study did not establish a pattern of service utilisation along household income categories. A lower proportion of respondents in the average income category compared with those in the higher income category utilised the four maternal healthcare services. In addition, only the differential in the use of modern contraceptive methods (p = 0.017) amongst women in different income categories was significant. The use of ANC (p = 0.294), skilled delivery care (p = 0.080) and PNC (p = 0.104) were not influenced significantly by income categories of the respondents.

The median direct payment for maternal healthcare service utilisation amongst respondents was Naira 2150.00; and ranged from no payment to Naira 252 000.00. The concentration index (CI) for each of the four maternal healthcare services (Table 5), however, depict inequality that favours the rich (CI was positive) in service utilisation. The inequality was more pronounced in the use of modern contraceptive methods (CI = 0.06) compared to ANC (CI = 0.02), skilled delivery care (CI = 0.03) and PNC (CI = 0.03). These findings might be related to the fact that the median annual household income of Naira 699 996.00 amongst the respondents was higher than the annual national average income in Nigeria (Federal Government of Nigeria 2011:3).

In Figure 2, the Lorenz curve (Gini-coefficient = 0.555) indicated that the distribution of total household income was not equitable amongst the respondents. The Kakwani index, calculated as the difference between CI of direct payment and Gini-coefficient (0.106–0.555) was -0.449. Since K < 1 and the direct payment concentration curve lay above the Lorenz curve, the analysis indicated that respondents in lower income categories spent more than their total income share on health and those in higher income categories spent less than their share. The payment system for maternal healthcare service utilisation in AMAC was therefore regressive and unfair on the poor.

The independent effects (bivariate analysis) of the six SECs included in this study on maternal healthcare service utilisation varied when analysed, controlling for the effects of other independent variables in the logistic regression (Table 6).

Maternal age, birth order and maternal education were the predisposing factors included in this study. The influence of maternal age and birth order on the use of ANC, skilled delivery care and PNC were consistent in both the bivariate and multivariate analyses and similar to findings in Nigeria (Awusi et al. 2009:22) and Ethiopia (Mekonnen & Mekonnen 2003:375). Whilst the influence of birth order on the use of modern contraceptive methods was consistent, that for maternal age was contradictory. In AMAC, maternal age was established as a significant predisposing factor for the use of ANC (p = 0.000), skilled delivery care (p = 0.009) and PNC (p = 0.004). This study, however, indicated that older women were less likely than adolescent women (the reference group) to use the four maternal healthcare services. Exposure to better information on healthcare and limited pregnancy-related experience (a motivating factor) amongst younger women could contribute to the observed pattern. A significant predisposing effect of birth order on the use of ANC (p = 0.000), skilled delivery care (p = 0.000) and PNC (p = 0.000) was established. There were, however, concerns that respondents who had experienced more than one birth had a lower likelihood of utilising maternal healthcare services. This observation might be related to the (perceived) poor quality of care received, which could be a disincentive for continuing service utilisation. The predisposing effects of maternal age (p = 0.256) and birth order (p = 0.849) on the use of modern contraceptive methods were not significant.

The influence of maternal education was consistent for the use of modern contraceptive methods in the bivariate and multivariate analyses, but contradictory for the use of ANC, skilled delivery care and PNC services. Maternal education was, however, established as a significant predisposing factor for the use of modern contraceptive methods (p = 0.000) and ANC (p = 0.021) in AMAC. The predisposing effect of maternal education on the use of skilled delivery care (p = 0.130) and PNC (p = 0.058) was not significant. Unlike earlier studies (Adanu 2010:155; Butawa et al. 2010:75), women with a higher level of education were less predisposed than those with no or a primary level of education (reference group) to utilise the four maternal healthcare services. Although not of statistical significance (p-value > 0.05), a similar (negative) predisposing effect of maternal education on the use of family planning services (OR = 0.001) was reported in Kenya (Okech et al. 2011:34).

This study included location of residence, health insurance coverage and household income as enabling factors for maternal healthcare service utilisation. The influence of location of residence was consistent for the use of the four maternal healthcare services in the bivariate and multivariate analyses. Location of residence was established as a significant enabling factor for the utilisation of modern contraceptive methods (p = 0.008) in AMAC. Although the enabling effect of location of residence for the use of ANC (p = 0.067), skilled delivery care (p = 0.493) and PNC (p = 0.338) was not statistically significant, the findings of this study suggest that respondents in urban areas had a higher likelihood of utilising the three maternal healthcare services (ANC, skilled delivery care and PNC). Women in urban areas of AMAC, however, had a lower likelihood of using modern contraceptive methods when compared to women in rural areas (reference group). A mixed effect of location of residence on the utilisation of the different maternal healthcare services were reported across several studies (Mekonnen & Mekonnen 2003:376–378; Say & Raine 2007:814; Zere et al. 2010:5), with an overall pattern in favour of urban women for delivery care and a somewhat mixed pattern for ANC service.

The influence of health insurance coverage was consistent for the use of modern contraceptive methods, skilled delivery care and PNC service in the bivariate and multivariate analyses, but contradictory for the use of ANC. In AMAC, health insurance coverage was established as a significant enabling factor for the use of skilled delivery care (p = 0.007) and PNC (p = 0.016). However, the likelihood of utilising health facility-based services (ANC, delivery care and PNC) was lower amongst respondents covered by health insurance when compared with those who were not (reference group). In contrast, respondents covered by health insurance had a higher likelihood of using modern contraceptive methods procured largely outside the health facilities. The enabling effect of health insurance coverage on the use of modern contraceptive methods (p = 0.574) and ANC (p = 0.16) was not significant. In addition to the fact that only 91 (24%) respondents were covered by health insurance, the limited benefit coverage of health insurance schemes in low- and middle-income countries (Ibiwoye & Adeleke 2000:220; Meng et al. 2011:94) might explain the observed effect.

The influence of household income was consistent for the use of ANC, skilled delivery care and PNC in the bivariate and multivariate analyses, but contradictory for the use of modern contraceptive methods. Household income was, however, not established as a significant enabling factor for the use of modern contraceptive methods (p = 0.313), ANC (p = 0.251), skilled delivery care (p = 0.196) and PNC (p = 0.224) in AMAC. These findings were consistent with the argument in Wilkinson (1997:593), stating that absolute income was unrelated to health. This study suggest that women in the higher income category were less likely to utilise the four maternal healthcare services when compared with those in the lower income category (reference group). However, respondents in the average income category had a higher likelihood of using ANC, skilled delivery care and PNC services when compared to the reference group.