Increased use of recommended maternal health care as a determinant of immunization and appropriate care for fever and diarrhoea in Ghana: an analysis pooling three demographic and health surveys
Bibliographic record
Abstract
OBJECTIVE: Enhancing maternal and child health are key Millennium Development Goals (MDGs). This study examined whether increased utilization of recommended maternal health care (MHC), is associated with factors that improve children's health; specifically, complete immunization and appropriate care for fever and diarrhoea in Ghana. DESIGN: Data from the 1998, 2003, and 2008 Ghana Demographic and Health Surveys were pooled for a nationally representative sample of 6786 women aged 15-49 years who had a child in the previous 5 years. Children aged 12-23 months were considered fully immunized if they received all eight basic immunizations. Appropriate care for children under-five was receipt of medical treatment for fever or oral rehydration therapy for diarrhoea. The effect of recommended MHC utilization (characterized as poor, intermediate or best use) on immunization and appropriate care for fever and diarrhoea was determined through logistic regression with Andersen's Behavioural Model guiding co-variate selection. RESULTS: Increased MHC utilization (reference: intermediate MHC use) increased the odds of immunization [poor use: odds ratio (OR) = 0.54, 95% confidence interval (CI): 0.42-0.69; best use: OR = 1.29, 95% CI: 1.01-1.67], as well as appropriate care for fever (poor use: OR = 0.55, 95% CI: 0.35-0.88; best use: OR = 1.72, 95% CI: 1.17-2.52) and diarrhoea (poor use: OR = 0.63, 95% CI: 0.43-0.93). Survey year and region also predicted each outcome. Other determinants of immunization were maternal education, ethnicity, religion, media exposure, wealth and birth weight. Determinants of appropriate care for fever included paternal education, media exposure and wealth, and for diarrhoea, child's age and birth weight. CONCLUSION: This study proposes a linkage between MDGs; initiatives to improve maternal health through promoting increased use of recommended MHC may enhance children's health-related care. This could be useful for countries with limited resources in achieving MDGs, especially in sub-Saharan Africa where under-five mortality is the highest.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".