Girl child marriage and its association with maternal healthcare services utilization in sub-Saharan Africa
Bibliographic record
Abstract
BACKGROUND: Previous studies on child marriage have revealed its association with adverse health behaviors and outcomes, such as increased fertility, reduced modern family planning, less safe delivery, mental health disorders, suicidal attempt, and ideation, poor socio-economic status, morbidity, and mortality of children under- five. In this study, we investigate the association between child marriage and the utilization of maternal healthcare services in sub-Saharan Africa. METHODS: We utilized data from 29 sub-Saharan African countries' Demographic and Health Surveys conducted between 2010 and 2018. A total of 36,215 childbearing young women between the ages of 20-24 years constituted our sample size. A multilevel binary logistic regression analysis was carried out to examine the association between child marriage and the utilization of maternal healthcare services, and the results were presented as crude and adjusted odds ratios at 95% confidence interval. RESULTS: Young women who experienced child marriage were less likely to have ≥4 antenatal care visits during pregnancy [cOR = 0.60, CI = 0.57-0.63] compared to those who did not experience child marriage, and this was persistent after controlling for individual and community-level factors [aOR = 0.88, CI = 0.84-0.93]. Young women who experienced child marriage were less likely to use skilled birth attendance during delivery [cOR = 0.45, CI = 0.43-0.48] compared to those who did not experience child marriage, and this was persistent after controlling for individual and community-level factors [aOR = 0.87, CI = 0.82-0.93]. Young women who experienced child marriage were less likely to use postnatal care services [cOR = 0.79, CI = 0.75-0.82] compared to those who did not experience child marriage, but this was insignificant after controlling for individual and community-level factors. CONCLUSION: Our study found child marriage to be a major contributor to the low use of maternal healthcare services, including antenatal care visit and the use of skilled birth attendance during child delivery. Hence, there is a need to develop an intervention to address child marriage in sub-Saharan Africa and strengthen existing ones. In addition, framework that considers child marriage as a key determinant of maternal healthcare utilization must be developed as part of policies in sub-Saharan African countries to enable universal achievement of low maternal mortality ratio by 2030 as a target of the Sustainable Development Goals.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".