Childhood morbidity and its determinants: evidence from 31 countries in sub-Saharan Africa
Bibliographic record
Abstract
BACKGROUND: Although under-five mortality reduced globally from 93 per 1000 live births in 1990 to 39 in 2018, sub-Saharan Africa witnessed an increase from 31% in 1990 to 54% in 2018. Morbidity has been reported to contribute largely to these deaths. This study examined the factors that are associated with childhood morbidity in sub-Saharan Africa. METHODS: Demographic and Health Surveys of 31 countries in sub-Saharan Africa were used in this study. The study involved 189 069 children who had or did not have fever, cough or diarrhoea in the 2 weeks preceding the surveys. Descriptive statistics and binary logistic regression were applied in the analysis. RESULTS: About 22% of the children suffered from fever, 23% suffered from cough and 16% suffered from diarrhoea. While the odds of experiencing fever increased by 37% and 18%, respectively, for children from poorest and poorer households, children of women aged 15-24 and 25-34 years are 47% and 23%, respectively, more likely to experience diarrhoea. The probability of suffering from morbidity increased for children who are 12-23 months, of higher order birth, small in size at birth and from households with non-improved toilet facility. CONCLUSIONS: This study has shown that childhood morbidity remains a major health challenge in sub-Saharan Africa with socioeconomic, maternal, child's and environmental factors playing significant roles. Efforts at addressing this problem should consider these factors.
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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".