Wealth, education and urban-rural inequality and maternal healthcare service usage in Malawi

Abstract

Background: Malawi is among the 5 sub-Saharan African countries presenting with very high maternal mortality rates, which remain a challenge. This study aims to examine the impact of wealth inequality and area of residence (urban vs rural) and education on selected indicators of maternal healthcare services (MHS) usage in Malawi.

Methods: This study was based on data from the 5th round of Multiple Indicator Cluster Surveys (MICS) conducted in 2013-2014 in Malawi. Study participants were 7572 mothers aged between 15 and 49 years. The outcome variable was usage status of maternal health services of the following types: antenatal care, skilled delivery assistance and postpartum care. Univariate, bivariate and multivariate methods were used to describe the pattern of MHS usage in the sample population. Association between household wealth status, education as well as the type of residence, whether urban or rural, as independent variables and usage of MHS as dependent variables were analysed using the generalised estimating equations (GEE) method.

Results: Mean age of the sample population was 26.88 (SD 6.68). Regarding the usage of MHS, 44.7% of women had at least 4 ANC visits, 87.8% used skilled delivery attendants and 82.2% of women had used postnatal care. Regarding the wealth index, about a quarter of the women were in the poorest wealth quintile (23.6%) while about 1/6 were in the highest wealth quintile (15%). Rate of usage for all 3 types of services was lowest among women belonging to the lowest wealth quintile. In terms of education, only 1/5 completed their secondary or a higher degree (20.1%) and nearly 1/10 of the population lives in urban areas (11.4%) whereas the remaining majority live in rural areas (88.6%). The rates of usage of MHS, although reasonable on an overall basis, were consistently lower in women with lower education and those residing in rural areas.

Conclusions: Maternal health service usage in Malawi appears to be reasonable, yet the high maternal mortality rate is disturbing and calls for analysing factors hindering the achievement of maternal health-related Sustainable Development Goals (SDGs). The findings of this study underscore the need to minimise the wealth inequality, urban-rural divide and the low level of education among mothers to improve the usage of MHS. An equity-based policy approach considering the sociodemographic inequity in terms of wealth index, education and urban-rural divide might prove beneficial in further improving the MHS usage, as well as addressing the possible issues of quality gaps in MHS, which might be beneficial towards reducing maternal mortality. It should be noted that the study of quality gaps in MHS is beyond the scope of this paper and calls for further research in this arena.

Figure 1

Use of MHS by type in Malawi. MICS 2013–2014. ANC, antenatal care; MHS, maternal healthcare service; MICS, Multiple Indicator Cluster Survey; PNC, postnatal care; SBA, skilled birth assistance.

Figure 2

Utilisation rate of MHS at different education levels in Malawi. MICS 2013–2014. ANC, antenatal care; MHS, maternal healthcare service; MICS, Multiple Indicator Cluster Survey; PNC, postnatal care; SBA, skilled birth assistance.

Figure 3

Utilisation rate of MHS in different wealth groups in Malawi. MICS 2013–2014. ANC, antenatal care; MHS, maternal healthcare service; MICS, Multiple Indicator Cluster Survey; PNC, postnatal care; SBA, skilled birth assistance.

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Figure 4

Utilisation rate of MHS in different areas in Malawi. MICS 2013–2014. ANC, antenatal care; MHS, maternal healthcare service; MICS, Multiple Indicator Cluster Survey; PNC, postnatal care; SBA, skilled birth assistance.