Refugee maternal and perinatal health in Ontario, Canada: a retrospective population-based study
Bibliographic record
Abstract
OBJECTIVES: Immigrants are thought to be healthier than their native-born counterparts, but less is known about the health of refugees or forced migrants. Previous studies often equate refugee status with immigration status or country of birth (COB) and none have compared refugee to non-refugee immigrants from the same COB. Herein, we examined whether: (1) a refugee mother experiences greater odds of adverse maternal and perinatal health outcomes compared with a similar non-refugee mother from the same COB and (2) refugee and non-refugee immigrants differ from Canadian-born mothers for maternal and perinatal outcomes. DESIGN: This is a retrospective population-based database study. We implemented two cohort designs: (1) 1:1 matching of refugees to non-refugee immigrants on COB, year and age at arrival (±5 years) and (2) an unmatched design using all data. SETTING AND PARTICIPANTS: Refugee immigrant mothers (n=34 233), non-refugee immigrant mothers (n=243 439) and Canadian-born mothers (n=615 394) eligible for universal healthcare insurance who had a hospital birth in Ontario, Canada, between 2002 and 2014. PRIMARY OUTCOMES: Numerous adverse maternal and perinatal health outcomes. RESULTS: Refugees differed from non-refugee immigrants most notably for HIV, with respective rates of 0.39% and 0.20% and an adjusted OR (AOR) of 1.82 (95% CI 1.19 to 2.79). Other elevated outcomes included caesarean section (AOR 1.04, 95% CI 1.00 to 1.08) and moderate preterm birth (AOR 1.08, 95% CI 0.99 to 1.17). For the majority of outcomes, refugee and non-refugee immigrants experienced similar AORs when compared with Canadian-born mothers. CONCLUSIONS: Refugee status was associated with a few adverse maternal and perinatal health outcomes, but the associations were not strong except for HIV. The definition of refugee status used herein may not sensitively identify refugees at highest risk. Future research would benefit from further refining refugee status based on migration experiences.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".