3 M ETHODOLOGY
R 2 Deviance statistics AIC Mean Errors
4.7 Conclusions
South Sudan is amongst the countries with the highest maternal mortality rate. Factors contributing to the high maternal mortality rate are socio-economic, macro-economic, and physiological factors. The chapter investigated socio-economic factors and physiological causes of MMR based on international and national literature. Thirty years of South Sudan data was used to identify the most significant socio-economic factors and physiological causes of maternal mortality.
Studies on predictors of logarithmic multi-regression models provided distinct evidence that increasing skilled attendants at birth (SAB) and reducing the general fertility rate (GFR), while leaving the gross domestic product (GDP) constant at 1,772, can reduce the MMR in South Sudan by the year 2030 to the limits proposed by the UN agencies (WHO, USAID, UNICEF and the World Bank, 2015) and beyond.
Statistical analysis indicates that increasing SAB by 1.22% per year would reduce MMR by 1.4%. [95% CI (0.4%–5%)], while reducing GFR by 1.22% per year would reduce MMR by 1.8% [95% CI (0.5%–6.26)], when the GDP is held constant
Comparing the findings of this study to other similar studies suggests that reducing GFR is more effective and achievable than increasing SAB, when aiming to reduce MMR.
0 10 20 30 40 50 60 70 80 90 2010 2015 2020 2025 2030 2035 (MMR) targeting 21 Haemorrhage Unsafe Abortion
For the first time, optimisation has been deployed to develop the yearly profile limits for MMR, SAB, and GFR to achieve recommended lower and upper levels of MMR by 2030. The optimal profile limits provide a quantitative guideline for the government and partners in terms of yearly SAB and GFR targets to reduce MMR to the level recommended by the UN. Furthermore, analysis shows that haemorrhaging; microbial infections, preeclampsia, cardiovascular disease, liver disease, sepsis, and gastro-intestinal hepatic diseases are the most common physiological factors of MMR. Amongst these, deaths related to haemorrhaging, sepsis, and eclampsia are more common.
Poisson regression was used to develop a prediction model to estimate maternal mortality based on the top five significant physiological causes. The results show that these causes contributed 97.43% to the variations in MMR. Judging by their corresponding variance inflation factor (VIF) and p-value, we can conclude that all five causes are statistically significant. However, based on the literature recommendations, we have developed the reduced Poisson regression models based on haemorrhaging only and the two significant physiological causes of haemorrhaging and unsafe abortion that can be controlled by the Government and other stakeholders by regulating and enlightening people of South Sudan about the negative side of unsafe abortion. To reduce the impact of the sample size on the reliability of the developed reduced Poisson models, we repeated the random sample selection 30 times using Bernoulli distribution with a probability of 0.67 to select two thirds of the data to build the models, and one third to assess efficacy. The results show that haemorrhaging alone is responsible for 90.27% of variation in MMR in South Sudan. The results of error analysis show that the proposed reduced model can predict MMR for a given level of haemorrhaging with a mean error of -34.5517 and standard error of mean 0.0151. The proposed reduced model is based on the average coefficient of 30 models. Moreover, the outcomes of the analysis show that the two significant causes of haemorrhaging and unsafe abortion are responsible for 92.68% of the variation in MMR and their outcome error analysis demonstrates that the
mean 0.022677. The reduced Poisson model is also based on the average coefficient of 30 models as shown in Table 4.16
For the first time, this chapter has deployed optimisation procedures to develop yearly lower and upper profile limits for MMR, targeting the UN’s recommended lower and upper MMR levels by 2030. The MMR profile limits have been accompanied in by the profile limits for optimal yearly values of SAB and GFR levels. Further, the MMR profile limits have been also developed and accompanied by the profile limits for optimal values of haemorrhaging and unsafe abortion.
To reduce MMR, the following actions are recommended. Haemorrhaging and unsafe abortion are potentially life threatening and need to be managed effectively and in a timely manner to prevent adverse outcomes. The effective management of haemorrhaging and unsafe abortion can reduce MMR by a substantial amount. However, this requires policies and interventions at a number of levels. The hospital infrastructure should provide the necessary items and equipment to manage haemorrhaging. These include the availability of blood for transfusion, supply of oxytocin hormones, surgical items, and items to help prevent bleeding. Hospital staff, including midwives, nurses, doctors, and TBAs should have the necessary expertise and training to effectively deal with haemorrhaging. The measures will require a significant investment by the government, UN agencies, and other stakeholders. The investment is required to build more upgraded medical facilities, update the training of medical personnel, and improve roads, transport, and communication. In addition, the investment should provide home delivery services for pregnant women who live in rural areas or poorer communities. This conclusion outlines the important of increasing SAB and reducing GFR to achieve the UN targeted level by 2030. Further, information on how to achieve an increase in SAB and reduction in GFR, haemorrhaging and unsafe abortion are provided in Chapter 6 under Recommended Policies.
The outcomes of this study can effectively aid authorities to make informed evidence-based intervention decisions on resource allocation to reduce the MMR. The findings of this study
will also provide useful guidelines for healthcare development programmes to prioritise and effectively distribute their limited health resources to areas of urgent need.
These findings are pivotal as they provide some guidance to policy makers and other stakeholders on resource allocation in South Sudan’s public health to target specific socio- economic factors (SAB, GFR, and GDP) and physiological causes (haemorrhaging, sepsis, unsafe abortion, and indirect causes) with the aim of minimising MMR.