Combining immigration records with a postpartum population-based survey to assess prevalence of perinatal psychosocial and behavioral risk factors among immigrant subgroups.
Bibliographic record
Abstract
ObjectivesPerinatal risk factors can vary by immigration status. To advance knowledge on sociobehavioral health risks among pregnant and childbearing immigrant women, we compared perinatal health indicators between immigrant and non-immigrants, overall, and according to key immigrant characteristics (refugee status, secondary migration, birth region, and duration of residence). ApproachWe conducted a population-based cross-sectional study of 33,754 immigrant and 172,342 non-immigrant childbearing women in Manitoba, Canada, aged 15-55 years, who had newborn screening data completed by public health nurses within two weeks postpartum from 2000 to 2017. The screening data was linked to a Canadian national immigration database. Additional databases were linked to collect demographic and perinatal clinical information. Logistic regression models were used to examine the associations between immigration characteristics and perinatal health indicators, such as social isolation, relationship distress, partner violence, depression, alcohol, smoking, substance use and late prenatal care initiation. ResultsMore immigrant women reported being socially isolated (12.3%) than non-immigrants (3.0%) (Adjusted Odds Ratio (aOR): 6.90, 95% Confidence Interval (CI): 6.53, 7.28) but exhibited lower odds of other outcomes. In the analysis restricted to immigrants, recent immigrants (< 5 years of stay) had higher odds of being socially isolated (aOR: 9.29, 95% CI: 7.80, 11.06) and late prenatal care (aOR: 1.73, 95% CI: 1.23, 2.42) compared to long-term immigrants, but lower odds relationship distress, depression, alcohol, smoking and substance use. Refugee status was positively associated with social isolation, relationship distress, depression, and late prenatal care whereas secondary migration was protective for social isolation, relationship distress, and smoking. Relationship distress and behavioral health indicators varied by maternal birth region. ConclusionThe novel linkage of birth screening data with the immigration data advances knowledge on immigrant perinatal health by identifying risk patterns for multiple psychosocial and behavioral health indicators, highlighting subgroups at higher and lower risk of exposures that may contribute to adverse perinatal health outcomes.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".