Trends in maternal education-based inequalities in under-five mortality in Ethiopia: multilevel, decomposition and concentration index analyses
Bibliographic record
Abstract
In 2021, a staggering five million children globally succumbed to mortality before celebrating their fifth birthdays. Alarmingly, children residing in Sub-Saharan African nations faced mortality risks 15 and 19 times higher than their counterparts in Europe and Northern America, as well as the region encompassing Australia and New Zealand, respectively. Ethiopia, situated in Sub-Saharan Africa, shoulders a significant burden of under-five mortality, securing the third position in Africa and the tenth globally. The primary objective of this study was to scrutinize the trends in under-five mortality inequalities based on maternal education in Ethiopia from 2000 to 2016. The analysis utilized data from repeated cross-sectional surveys, drawing upon a pooled total sample of 35,404 children aged 0–59 months. This sample was derived from the Ethiopian Demography and Health Surveys conducted in 2000, 2005, 2011, and 2016. To explore the determinants of under-five mortality among this age group, we employed multilevel binary logistic regression analysis. This approach allowed us to assess the impact of various factors at the individual, household, and community levels. Additionally, we conducted multivariate decomposition, concentration index, and decomposition rate analyses to scrutinize the evolving trends in maternal education-based disparities in under-five mortality. Maternal education emerged as a significant factor influencing under-five mortality in Ethiopia. Notably, approximately one-third (31%) of the observed inequalities in under-five mortality based on maternal education could be accounted for by the effects of observed characteristics. Over the years, there has been a noteworthy reduction in absolute inequalities in under-five mortality. Specifically, a decline of 0.14 was observed between 2000 and 2005, and a more substantial decrease of 0.32 occurred in the period spanning 2000 to 2016, resulting in an overall change of 56.25%. Furthermore, this study revealed that about 43.12% of the reduction in under-five mortality could be attributed to the narrowed gap in maternal education during the survey period. The implications drawn from these findings underscore the importance of directing interventions aimed at reducing early mortality toward the promotion of maternal education. It is evident that addressing maternal education plays a pivotal role in mitigating inequalities in under-five mortality. Additionally, there is a pressing need to revisit and enhance existing population and health policies. Establishing stronger linkages between child survival issues and the education sector is crucial for achieving the targets outlined in the Sustainable Development Goals related to under-five mortality. By aligning policies with these insights, there is a greater likelihood of fostering sustainable improvements in child survival and advancing towards the overarching goal of reducing under-five mortality.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".