Bibliographic record
Abstract
Background: It is unclear whether refugee groups have poorer maternal health and pregnancy outcomes compared to non-refugee migrant groups or whether specific refugee groups have particularly poor outcomes. This study aimed to describe maternal health, pregnancy care attendance and pregnancy outcomes among women of refugee background from African countries compared to non-refugee migrant women. Method: Retrospective, observational study of singleton births, at the largest maternity service in Victoria, Australia 2002–2011, to women born in humanitarian source countries (HSC) and non-HSC from North Africa (n = 1361), Middle and East Africa (n = 706) and West Africa (n = 106). Results: Compared to non-HSC groups, risk factors related to social disadvantage were generally more common across the HSC groups: interpreter need (13–56%), multiparity (69–80%), age <20 years (2–13%) and living in relatively socio-economic disadvantaged areas (53–78%). Vitamin D insufficiency was generally more common among the HSC groups (23–32%) as was female genital mutilation (5–14%). Birth before arrival (3.6%) was particularly high in the North African HSC group. HSC-birth was independently associated with gestational diabetes (OR = 3.5 95%CI: 1.8–7.1) among women from Middle and East Africa. The West African HSC group had the highest stillbirth incidence (4.4%). Conclusions: Resettled refugees from different African regions may be at higher risk of specific adverse pregnancy outcomes compared to nonrefugee migrant women. Awareness of differing risks and health needs would assist provision of appropriate care to improve the health of women of refugee background and their babies.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.754 | 0.568 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".