Women empowerment indicators and uptake of child health services in sub-Saharan Africa: a multilevel analysis using cross-sectional data from 26 countries
Bibliographic record
Abstract
BACKGROUND: The sustainable development goal 3, target 2, seeks to reduce under-five mortality to as low as 25 deaths per 1000 live births by 2030. As such, seeking child health services has become a priority concern for all countries, particularly those in sub-Saharan Africa (SSA). Evidence suggests that empowered women are more likely to seek child health services. Hence, this study examined the association between women empowerment indicators and uptake of child health services in SSA. METHODS: The study used data from the Demographic and Health Surveys of 26 SSA countries, which were conducted between 2010 and 2019. Two different samples were considered in the study: a total of 12 961 children within the vaccination age of 12-23, and 9489 children under age 5 with diarrhoea symptoms in the last 2 weeks before the survey. Women empowerment indicators comprised disagreement with reasons to justify wife beating, decision-making power and knowledge level, while child health services constituted complete vaccination uptake and seeking diarrhoea treatment. Frequencies, percentages and multivariable, multilevel binary logistic regression models were employed. RESULTS: The study shows that women with high decision-making power [adjusted odds ratio (AOR) = 1.20, 95% confidence interval (CI) = 1.07, 1.35] had higher odds of seeking treatment for childhood diarrhoea compared to those with low decision-making power. It was also observed that among children aged 12-23 months [AOR = 1.28, 95% CI = 1.14, 1.43], mothers had higher odds of seeking diarrhoea treatment for them compared to those who were aged less than 12 months. Children whose mothers had medium decision-making power [AOR = 1.30, 95% CI = 1.19, 1.41] were more likely to seek complete immunization for their children compared to those with low decision-making power. Also, those with medium [AOR = 1.19, 95% CI = 1.07, 1.31] and high knowledge [AOR = 1.25, 95% CI = 1.10, 1.42] had higher odds of completing immunization for their children compared to those with low knowledge. Women with medium acceptance had lower odds [AOR = 0.76, 95% CI = 0.67, 0.83] of completing immunization for their children compared with those with low acceptance of wife beating. CONCLUSIONS: This study has demonstrated a strong association between women empowerment indicators and the uptake of child health services. Therefore, efforts should be made to seek policy tools to empower women to help improve the well-being of women and the children they care for.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".