Maternal and newborn health inequality among Syrian refugees in Turkey: a systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVE: In this meta-analysis we explore significant health disparities in maternal and newborn health among Syrian refugees residing in Turkey. METHOD: The study protocol was registered in PROSPERO. We conducted a comprehensive literature search across six databases, including sources in English and Turkish, as well as relevant UN agencies, covering the period from 2011 (the onset of the Syrian conflict) to September 2024. This research specifically targets Syrian mothers aged 15 to 49 who were either pregnant or had recently given birth in Turkey, including studies with observational cross-sectional or retrospective designs. The quality of the included studies was evaluated using the JBI Critical Appraisal Checklist. Statistical analyses were performed using R version 4.4.1. RESULT: Of 382 studies in English and Turkish, 29 papers, 2 reports and 1 postgraduate thesis were selected for full-text evaluation. Syrian migrants were more at risk of anemia in the third trimester of pregnancy [RR: 2.27 (95% CI: 1.57 to 3.32)], and had less access to antenatal care [RR: 0.39 (95% CI: 0.26 to 0.58)] and iron supplementation during pregnancy [RR: 0.69 (95% CI: 0.46 to 0.96)] compared to the native population. The risks of adolescent pregnancy [RR: 3.78 (95% CI: (3.06 to 4.88)] and home birth [RR: 3.68 (95% CI: (2.53 to 5.27)] were higher among migrants [RR: 3.78 (95% CI: (3.06to 4.88)]. Conversely, migration was an important factor in gestational diabetes [RR: 0.44 (95% CI: (0.21 to 0.90)] and newborn macrosomia [RR: 0.54 (95% CI: (0.50 to 0.58)] as well as preeclampsia [RR: 0.56 (95% CI: (0.32 to 0.98)]. CONCLUSION: Our data revealed that Syrian migrant mothers face a higher risk of anemia, limited access to antenatal care and iron supplements, and higher rates of adolescent pregnancies and home births compared to their native counterparts. However, migration appears to have a protective effect on gestational diabetes and preeclampsia. The results underscore the need for targeted health interventions and policies that address access to maternal healthcare services.
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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 | 0.011 | 0.026 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.032 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".