Proximate and socio-economic determinants of under-five mortality in Benin, 2017/2018
Bibliographic record
Abstract
BACKGROUND: Globally, under-five mortality has declined significantly, but still remains a critical public health problem in sub-Saharan African countries such as Benin. Yet, there is no empirical information in the country using a nationally representative data to explain this phenomenon. The aim of this study was to examine how proximate and socio-economic factors are associated with mortality in under-five children in Benin. METHODS: . Results were reported as adjusted odds ratios (aORs). All comparisons were considered to be statistically significant at p<0.05. RESULTS: The study revealed an under-five mortality rate of 96 deaths per 1000 live births in Benin. Regarding the socio-economic determinants, the risk of death was found to be higher in children born in the Plateau region (aOR=3.05; 95% CI: 1.29 to 7.64), in rural areas (aOR=1.45; 95% CI: 1.07 to 1.98) and children with ≥4 birth rank and >2 years of birth interval (aOR=1.52; 95% CI: 1.07 to 2.17). Among the proximate determinants, we found the probability of death to be higher in children whose mothers had no postnatal check-up (PNC) visits after delivery (aOR=1.79; 95% CI: 1.22 to 2.63), but there was no significant association between individual-level/household-level factors and under-five mortality. CONCLUSION: This study has established that socio-economic and proximate factors are important determinants of under-five mortality in Benin. Our findings have shown the need to implement both socio-economic and proximate interventions, particularly those related to PNC visits when planning on under-five mortality. To achieve this, a comprehensive, long-term public health interventions, which consider the disparity in the access and utilisation of healthcare services in Benin are key.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".