Incidence of child marriage among refugees and internally displaced persons in the Middle East and South Asia: evidence from six cross-sectional surveys
Bibliographic record
Abstract
OBJECTIVE: To examine incidence of child marriage among displaced and host populations in humanitarian settings. DESIGN: Cross-sectional surveys. SETTING: Data were collected in Djibouti, Yemen, Lebanon and Iraq in the Middle East and in Bangladesh and Nepal in South Asia. PARTICIPANTS: Adolescent girls aged 10-19 in the six settings and age cohort comparators. OUTCOME MEASURES: Cumulative incidence of marriage by age 18. RESULTS: In Bangladesh and Iraq, the hazard of child marriage did not differ between internally displaced populations (IDPs) and hosts (p value=0.25 and 0.081, respectively). In Yemen, IDPs had a higher hazard of child marriage compared with hosts (p value<0.001). In Djibouti, refugees had a lower hazard of child marriage compared with hosts (p value<0.001). In pooled data, the average hazard of child marriage was significantly higher among displaced compared with host populations (adjusted HR (aHR) 1.3; 95% CI 1.04 to 1.61).In age cohort comparisons, there was no significant difference between child marriage hazard across age cohorts in Bangladesh (p value=0.446), while in Lebanon and Nepal, younger cohorts were less likely to transition to child marriage compared with older comparators (p value<0.001). Only in Yemen were younger cohorts more likely to transition to child marriage, indicating an increase in child marriage rates after conflict (p value=0.034). Pooled data showed a downward trend, where younger age cohorts had, on average, a lower hazard of child marriage compared with older cohorts (aHR 0.36; 95% CI 0.29 to 0.4). CONCLUSIONS: We did not find conclusive evidence that humanitarian crises are associated with universal increases in child marriage rates. Our findings indicate that decision-making about investments in child marriage prevention and response must be attuned to the local context and grounded in data on past and current trends in child marriage among communities impacted by crisis.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".