The Effects of Reproductive Variables on Child Mortality in Ethiopia: Evidence from Demographic and Health Surveys from 2000 to 2016
Bibliographic record
Abstract
Abstract Background The level and trends of child mortality are key indicators that explain the health and socioeconomic status of a country. In the last three decades, the world has shown significant improvement in reducing early childhood mortality. However, developing regions, particularly Southern Asia and sub-Saharan Africa, still account for the largest proportion of newborn deaths. Ethiopia is one of five countries that account for half of new-born deaths worldwide. Methods The objective of this study was to investigate the association between selected reproductive factors and under-five mortality in Ethiopia. The study applies a discrete-time survival model to the data from four Ethiopian Demographic and Health Surveys (EDHS) from 2000 to 2016 to analyze the main and combined influence of three variables (preceding birth interval, maternal age at childbirth, and birth order) on child mortality. Results It was found that lengthening the preceding birth interval to 18–23, 24–35, 36–47 or 48 + months reduces the risk of under-five deaths by 30 percent (OR = 0.70), 46 percent (OR = 0.54), 56 percent (OR = 0.44) and 60 percent (OR = 0.40), respectively, compared to very short birth intervals (less than 18 months). Giving birth at ages 20–34 and 35 + reduces the risk by 34 percent (OR = 0.66) and 8 percent (OR = 0.92), respectively, compared to giving birth below age 20. The risk of under-five death of a child born 7th is higher by 17 percent (OR = 0.83) than that of a 2nd or 3rd -order child. Furthermore, the combined effect analysis shows that the risk of under-five mortality is high in births with a higher birth order at a young maternal age. In addition, lower birth order in older maternal age groups is associated with a high risk of under-five mortality. On the other hand, a relative analysis of the combined effect of maternal age at childbirth and birth interval shows that the risk of a short birth interval is higher among older than much younger mothers. Finally, the study also identified the risk of very short birth intervals, which is worst among higher birth order children. Conclusion It is not only one reproductive health variable that negatively affects child survival but their combination has the strongest effect. It is therefore recommended that policies in Ethiopia should address short birth intervals, young age of childbearing, and order of birth through an integrated strategy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".