Women’s education and health inequalities in under-five mortality in selected sub-saharan African countries, 1990-2015

Background The aim of the study was to analyse trends in the relationship between mother’s educational level and mortality of children under the year of five in Sub-Saharan Africa, from 1990 to 2015. Data and Methods Data used in this study came from different waves of Demographic and Health Surveys (DHS) of Sub-Saharan countries. Logistic regression and Buis’s decomposition method were used to explore the effect of mother’s educational level on the mortality of children under five years. Results Although the results of our study in the selected countries show that under-five mortality rates of children born to mothers without formal education are higher than the mortality rates of children of educated mothers, it appears that differences in mortality were reduced over the past two decades. In selected countries for our study, we noticed a significant decline in mortality among children of non-educated mothers compared to the decrease in mortality rates among children of educated mothers during the period of 1990-2010. The results show that the decline in mortality of children under five years was much higher among the children born to mothers who have never received formal education-112 points drop in Malawi, over 80 in Zambia and Zimbabwe, 65 points in Burkina Faso, 56 in Congo, 43 in Namibia, 27 in Guinea, Cameroon, and 22 to 15 in Niger. However, we noted a variation in results among the countries selected for the study-in Burkina Faso (OR = 0.7), in Cameroon (OR = 0.8), in Guinea (OR = 0.8) and Niger (OR = 0.8). It is normally observed that children of mothers with 0-6 years of education are about 20% more likely to survive until their fifth year compared to children of mothers who have not been to school. Conversely, the results did not reveal significant differences between the under-five deaths of children born to non-educated mothers and children of low-level educated mothers in Congo, Malawi and Namibia. Conclusion The decline in under-five mortality rates, during last two decades, can be partly due to the government policies on women’s education. It is evident that women’s educational level has resulted in increased maternal awareness about infant health and hygiene, thereby bringing about a decline in the under-five mortality rates. This reduction is due to improved supply of health care programmes and health policies in reducing economic inequalities and increasing access to health care. Huge progress has been made over the last decades to improve the literacy status of adult women around the Sub-Saharan Africa[34]. While gender disparities in adult literacy rates remain wide in Sub-Saharan Africa due to many factors including culture and lack of infrastructures, evidences indicate that some progress has been made at regional and country levels to improve the literacy level of women[34]. Fig 1 presents the trend of female primary education completion rates in the countries selected for this study. The results show that although the level of women’s education has greatly improved during the period 1980–2010, there is a slower increase in the West African countries. The results show that the rate of increase in female education has been 30.7% in Niger, 34.3% in Burkina Faso and 47.5% in Guinea, for the period 2005–2010, compared to other countries that record an increase of above 56%. Data used in this study come from different waves of DHS of Sub-Saharan countries (Table 1), including Burkina Faso, Niger, Guinea, Cameroon, Congo, Malawi, Zambia, and Namibia. The countries were selected according to a sub-regional basis selecting at least two countries from each sub-region of the Sub-Saharan Africa (Western Africa, Central Africa, Eastern and Southern Africa). The selected countries have already realised at least two DHS rounds in the period 1990–2015. First, DHS waves of survey data of each selected country were pooled, and then data from all the countries were pooled for the purpose of analysis. DHS data were collected using a standardised questionnaire, which was used in all the countries and for different waves of DHS. This offers an advantage for data analysis and comparison of results across countries. This study used birth history data from DHS. Table 2given below presents the number of children under five years and the survival status of each birth cohort by country. The birth history (birth cohort) dataset contained information on the date of birth of all the children born to a woman during her lifetime, starting from the first child to the total number of children born at the time of the survey. Additionally, information on child’s survival (dead or alive) was available in these datasets [35]. Birth histories were collected from a sample of women aged 15–49, at the time of the survey. The complete birth histories (including date of the birth and survival status of each child born to these women until the time of survey) of women aged 15 to 49 years old is considered to be useful data for computing child mortality indicators. DHS data are cross-sectional data, and therefore the survey data represents the entire population. In this context, the information collected during the study included demographic, socioeconomic, and maternal and child health data. The sample design of these surveys is a nationally representative sample and a stratified two-stage cluster design. The datasets used in this study were obtained from the DHS program thanks to the authorisation received to download the dataset on the website (https://dhsprogram.com/data/available-datasets.cfm). The dependent variable of this study is the child survival status (alive or dead) during the duration of the survey. The wealth indexes, the mother’s educational level, and the place of residence (rural/urban) are the main explanatory variables that assess the inequalities in child mortality. Households were grouped into five categories of wealth index (poorest, poor, middle, rich and richest). In terms of maternal education, we categorised the mothers into three groups (not attended school, 1–6 years of education and more than 6 years of education). The other covariate variables included sex and birth order of the child, parity, mother’s age during childbirth and the size of the household. First, the study used concentration index as well as absolute and relative ratios of mortality rates to measure inequality in health. The concentration index ranges between -1 and 1, and a negative value in this study means the deaths are more concentrated among children born to less educated mothers. Two logistic regression models were built to estimate the effect of mother educational level on the probability of a child to die before reaching his fifth birthday: Model 1 gave the unadjusted effect and Model 2 gave the adjusted effect of the co-variables. This study used the method proposed by Buis [36] which decomposes the total association between a categorical, discrete or continuous exposure variable, and an outcome from a direct effect and an indirect effect. The decomposition method proposed by Buis is described in his article published in 2010. In the current study, it is assumed that the dependent variable Y represents the child’s mortality and X represents the mother’s educational level. X is the main dependent variable by which we seek to quantify the direct effect, and Z is the indirect effect of the effect of all other covariates in our study. OR is considered as the risk of child to die before reaching his fifth birthday. From Eq 1, the total effect (ln(ORx = 1,z|x = 1)−ln(ORx = 0,z|x = 0)) is the sum of the direct effect (ln(ORx = 0,z|x = 1)−ln(ORx = 0,z|x = 0)) and direct effect (ln(ORx = 1,z|x = 1)−ln(ORx = 0,z|x = 1))) After transformation of the Eq (1), we obtain the Eq (2) below where: ln(ORx=1,z|x=1ORx=0,z|x=0) is the total effect, ln(ORx=0,z|x=1ORx=0,z|x=0) and ln(ORx=1,z|x=1ORx=0,z|x=1) are respectively the indirect and direct effect.