Childhood mortality and its association with household wealth in rural and semi-urban Burkina Faso
Bibliographic record
Abstract
BACKGROUND: This study aimed to investigate the relationship between household wealth and under-5 year mortality in rural and semi-urban Burkina Faso. METHODS: The study included 15 543 children born between 2005 and 2010 in the Nouna Health and Demographic Surveillance System. Information on household wealth was collected in 2009. Two separate wealth indicators were calculated by principal components analysis for the rural and the semi-urban households, which were then divided into quintiles accordingly. Multivariable Cox proportional hazards regression was used to study the effect of the respective wealth measure on under-5 mortality. RESULTS: We observed 1201 childhood deaths, corresponding to 5-year survival probability of 93.6% and 88% in the semi-urban and rural area, respectively. In the semi-urban area, household wealth was significantly related to under-5 mortality after adjustment for confounding. There was a similar but non-significant effect of household wealth on infant mortality, too. There was no effect of household wealth on under-5 mortality in rural children. CONCLUSIONS: Results from this study indicate that the more privileged children from the semi-urban area with access to piped water and electricity have an advantage in under-5 survival, while under-5 mortality in the rural area is rather homogeneous and still relatively high.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".