Psychosocial and behavioral health indicators among immigrant and non-immigrant recent mothers
Bibliographic record
Abstract
BACKGROUND: Perinatal risk factors can vary by immigration status. We examined psychosocial and behavioral perinatal health indicators according to immigration status and immigrant characteristics. METHODS: We conducted a population-based cross-sectional study of 33,754 immigrant and 172,342 non-immigrant childbearing women residents in Manitoba, Canada, aged 15-55 years, who had a live birth and available data from the universal newborn screen completed within 2 weeks postpartum, between January 2000 and December 2017. Immigration characteristics were from the Canadian federal government immigration database. Logistic regressions models were used to obtain Odds Ratios (OR) with 95% confidence intervals (CI) for the associations between immigration characteristics and perinatal health indicators, such as social isolation, relationship distress, partner violence, depression, alcohol, smoking, substance use, and late initiation of prenatal care. RESULTS: More immigrant women reported being socially isolated (12.3%) than non-immigrants (3.0%) (Adjusted Odds Ratio (aOR): 6.95, 95% CI: 6.57 to 7.36) but exhibited lower odds of depression, relationship distress, partner violence, smoking, alcohol, substance use, and late initiation of prenatal care. In analyses restricted to immigrants, recent immigrants (< 5 years) had higher odds of being socially isolated (aOR: 9.04, 95% CI: 7.48 to 10.94) and late initiation of prenatal care (aOR: 1.50, 95% CI: 1.07 to 2.12) compared to long-term immigrants (10 years or more) but lower odds of relationship distress, depression, alcohol, smoking and substance use. Refugee status was positively associated with relationship distress, depression, and late initiation of prenatal care. Secondary immigrants, whose last country of permanent residence differed from their country of birth, had lower odds of social isolation, relationship distress, and smoking than primary migrants. There were also differences by maternal region of birth. CONCLUSION: Immigrant childbearing women had a higher prevalence of social isolation but a lower prevalence of other psychosocial and behavioral perinatal health indicators than non-immigrants. Health care providers may consider the observed heterogeneity in risk to tailor care approaches for immigrant subgroups at higher risk, such as refugees, recent immigrants, and those from certain world regions.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".