Date Published: June 3, 2019
Publisher: Public Library of Science
Author(s): Lisa Cameron, Diana Contreras Suarez, Katy Cornwell, David Hotchkiss.
For countries to contribute to Sustainable Development Goal 3.1 of reducing the global maternal mortality ratio (MMR) to less than 70 per 100,000 live births by 2030, identifying the drivers of maternal mortality is critically important. The ability of countries to identify the key drivers is however hampered by the lack of data sources with sufficient observations of maternal death to allow a rigorous analysis of its determinants. This paper overcomes this problem by utilising census data. In the context of Indonesia, we merge individual-level data on pregnancy-related deaths and households’ socio-economic status from the 2010 Indonesian population census with detailed data on the availability and quality of local health services from the Village Census. We use these data to test the hypothesis that health service access and quality are important determinants of maternal death and explain the differences between high maternal mortality and low maternal mortality provinces.
The 2010 Indonesian Population Census identifies 8075 pregnancy-related deaths and 5,866,791 live births. Multilevel logistic regression is used to analyse the impacts of demographic characteristics and the existence of, distance to and quality of health services on the likelihood of maternal death. Decomposition analysis quantifies the extent to which the difference in maternal mortality ratios between high and low performing provinces can be explained by demographic and health service characteristics.
Health service access and characteristics account for 23% (CI: 17.2% to 28.5%) of the difference in maternal mortality ratios between high and low-performing provinces. The most important contributors are the number of doctors working at the community health centre (8.6%), the number of doctors in the village (6.9%) and distance to the nearest hospital (5.9%). Distance to health clinics and the number of midwives at community health centres and village health posts are not significant contributors, nor is socio-economic status. If the same level of access to doctors and hospitals in lower maternal mortality Java-Bali was provided to the higher maternal mortality Outer Islands of Indonesia, our model predicts 44 deaths would be averted per 100,000 pregnancies.
Indonesia has employed a strategy over the past several decades of increasing the supply of midwives as a way of decreasing maternal mortality. While there is evidence of reductions in maternal mortality continuing to accrue from the provision of midwife services at village health posts, our findings suggest that further reductions in maternal mortality in Indonesia may require a change of focus to increasing the supply of doctors and access to hospitals. If data on maternal death is collected in a subsequent census, future research using two waves of census data would prove a useful validation of the results found here. Similar research using census data from other countries is also likely to be fruitful.
The Sustainable Development Goals aim to reduce the global maternal mortality ratio (MMR) to less than 70 per 100,000 live births by 2030 . Identifying key determinants of maternal mortality and their relative importance is critical to priority setting in policy development, yet a surprisingly small number of studies have quantified the role of such determinants. That very small numbers of maternal deaths are observed in even large random samples of the population presents challenges for analyses of determinants. For example, the Indonesia Demographic and Health Survey which, owing to the absence of accurate civil registration and death reporting, is used to generate the official estimates of maternal mortality rates, surveyed 45,607 women and estimated an MMR of 359 deaths per 100,000 live births in 2012 on the basis of reports of a total of just 92 maternal deaths over the preceding five year period. It is not possible to estimate a model of the determinants of maternal mortality with such data as too few deaths are captured.
The national MMR implied from the census data of 8075 maternal deaths and 5,866,791 live births, is 137 deaths per 100,000 live births. Fig 2 shows the variation in MMRs across the Indonesian archipelago as calculated from the census. MMRs are lower in the less-remote and more economically-developed regions of Java and Bali.
The national MMR implied from the census data is lower but not so different from the World Bank estimate for 2010 of 165 deaths per 100,000 live births  which is much lower than that calculated from the 2012 DHS of 359 per 100,000 live births . Calculating an MMR for Indonesia is complicated as there is not reliable civil registration and death reporting and differing data sources and modelling assumptions produce very different results. Further, estimates using methods that allow an examination of trends over time differ wildly—declines in the MMR of 8% (using estimates from the DHS) and 52% (Maternal Mortality Estimation Inter-Agency Group modelling). The challenges of calculating an accurate MMR for Indonesia, and using census data more generally, are discussed in more detail in S4 Appendix.