Association between migration and severe maternal outcomes in high-income countries: Systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Literature focusing on migration and maternal health inequalities is inconclusive, possibly because of the heterogeneous definitions and settings studied. We aimed to synthesize the literature comparing the risks of severe maternal outcomes in high-income countries between migrant and native-born women, overall and by host country and region of birth. METHODS AND FINDINGS: Systematic literature review and meta-analysis using the Medline/PubMed, Embase, and Cochrane Library databases for the period from January 1, 1990 to April 18, 2023. We included observational studies comparing the risk of maternal mortality or all-cause or cause-specific severe maternal morbidity in high-income countries between migrant women, defined by birth outside the host country, and native-born women; used the Newcastle-Ottawa scale tool to assess risk of bias; and performed random-effects meta-analyses. Subgroup analyses were planned by host country and region of birth. The initial 2,290 unique references produced 35 studies published as 39 reports covering Europe, Australia, the United States of America, and Canada. In Europe, migrant women had a higher risk of maternal mortality than native-born women (pooled risk ratio [RR], 1.34; 95% confidence interval [CI], 1.14, 1.58; p < 0.001), but not in the USA or Australia. Some subgroups of migrant women, including those born in sub-Saharan Africa (pooled RR, 2.91; 95% CI, 2.03, 4.15; p < 0.001), Latin America and the Caribbean (pooled RR, 2.77; 95% CI, 1.43, 5.35; p = 0.002), and Asia (pooled RR, 1.57, 95% CI, 1.09, 2.26; p = 0.01) were at higher risk of maternal mortality than native-born women, but not those born in Europe or in the Middle East and North Africa. Although they were studied less often and with heterogeneous definitions of outcomes, patterns for all-cause severe maternal morbidity and maternal intensive care unit admission were similar. We were unable to take into account other social factors that might interact with migrant status to determine maternal health because many of these data were unavailable. CONCLUSIONS: In this systematic review of the existing literature applying a single definition of "migrant" women, we found that the differential risk of severe maternal outcomes in migrant versus native-born women in high-income countries varied by host country and region of origin. These data highlight the need to further explore the mechanisms underlying these inequities. TRIAL REGISTRATION: PROSPERO CRD42021224193.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".