Traditional medicine used in childbirth and for childhood diarrhoea in Nigeria's Cross River State: interviews with traditional practitioners and a statewide cross-sectional study
Bibliographic record
Abstract
OBJECTIVES: Examine factors associated with use of traditional medicine during childbirth and in management of childhood diarrhoea. DESIGN: Cross-sectional cluster survey, household interviews in a stratified last stage random sample of 90 census enumeration areas; unstructured interviews with traditional doctors. SETTING: Oil-rich Cross River State in south-eastern Nigeria has 3.5 million residents, most of whom depend on a subsistence agriculture economy. PARTICIPANTS: 8089 women aged 15-49 years in 7685 households reported on the health of 11,305 children aged 0-36 months in July-August 2011. PRIMARY AND SECONDARY OUTCOME MEASURES: Traditional medicine used at childbirth and for management of childhood diarrhoea; covariates included access to Western medicine and education, economic conditions, engagement with the modern state and family relations. Cluster-adjusted analysis relied on the Mantel-Haenszel procedure and Mantel extension. RESULTS: 24.1% (1371/5686) of women reported using traditional medicine at childbirth; these women had less education, accessed antenatal care less, experienced more family violence and were less likely to have birth certificates for their children. 11.3% (615/5425) of young children with diarrhoea were taken to traditional medical practitioners; these children were less likely to receive BCG, to have birth certificates, to live in households with a more educated head, or to use fuel other than charcoal for cooking. Education showed a gradient with decreasing use of traditional medicine for childbirth (χ(2) 135.2) and for childhood diarrhoea (χ(2) 77.2). CONCLUSIONS: Use of traditional medicine is associated with several factors related to cultural transition and to health status, with formal education playing a prominent role. Any assessment of the effectiveness of traditional medicine should anticipate confounding by these factors, which are widely recognised to affect health in their own right.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".