The maternal and child mortality in the Middle East and North Africa between 2000 and 2020: the role of health financing
Bibliographic record
Abstract
BACKGROUND: Improving maternal and child health (MCH) outcomes is a critical agenda item in global development. Health financing factors play a crucial role in affecting MCH outcomes, which vary substantially in the Middle East and North Africa (MENA) region. This study aims to examine the trends in maternal mortality rate (MMR), infant mortality rate (IMR), and under-5 mortality rate (U5MR) in the MENA region and the potential impact of health financing factors on them. METHODS: We compiled data on MCH mortalities and potential determinants, including health financing factors, for all countries in the MENA region from 2000 to 2020. We calculated the growth rate of mortalities and explored the association between mortality rates and potential determinants using fixed-effects models. RESULTS: The average MMR, IMR, and U5MR showed an overall descending trend in the region. Middle-income countries experienced the highest reduction rates (3.46-3.73%), followed by high-income countries (2.97-3.02%) and then low-income countries (0.33-0.92%). Gross domestic product (GDP) per capita, current health expenditure (CHE) per capita, urbanization, and fragility were consistently associated with all three mortality rates (p < 0.05). GDP elasticity of MMR, IMR, and U5MR was estimated at - 0.121, - 0.076, and - 0.138, respectively, while corresponding CHE elasticity was - 0.319, - 0.275, and - 0.225, with a larger magnitude. Fragility was positively associated with higher MMR, IMR, and U5MR. Additionally, government health spending, air pollution, and immigration were associated with MMR, but not with IMR and U5MR. CONCLUSIONS: Low-income countries in the MENA region, with the highest mortality rates, face greater challenges in reducing MCH mortality rates, necessitating tailored interventions to expand evidence-based MCH services and/or reinforce their effectiveness. Total investment in health plays a critical role in reducing mortality rates. Efforts to build a sustainable health financing system are key to improving MCH outcomes. Besides, endeavors to address broader socioeconomic factors and political stability should be prioritized in countries with major concerns of poverty and conflict.
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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 | 0.003 | 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 | 0.001 | 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".