Are Newborns of Immigrant Mothers More at Risk of Poorer Perinatal Health Than Those of Natives-born Mothers? One Size Does Not Fit All. A Population-based Study, Montreal, Quebec.
Bibliographic record
Abstract
Abstract Background The risk of unfavourable pregnancy outcomes for immigrant mothers varies according to their birthplace, socioeconomic status (SES) and comparison group. This study aims to identify the characteristics of Montreal newborns who are more or less at risk of LBW, prematurity and SGA, according to the mother's birthplace and SES. Methods The analysis focuses on all singleton live births in Montreal between 2003 and 2012 (N=214,620). Logistic regression models were estimated using generalized estimating equations in order to: 1) compare the risk of adverse pregnancy outcomes between Canadian-born and immigrant mothers. The latter were categorised into 8 groups according to world regions; 2) estimate the odds ratio of the association between adverse pregnancy outcomes and the mother's SES (education and income quintile) for each group. Results The risk of LBW, prematurity and SGA vary considerably depending on the mother’s birthplace. For these three outcomes, mothers from the Caribbean and South Asia have a higher prevalence than all other groups. Three other groups compare favourably to Canadian-born mothers: mothers from North Africa, Europe & the USA, and Central and West Asia. The association between SES and unfavourable pregnancy outcomes varies from one group of mothers to another. Among Canadian-born mothers, there is a classic health gradient, with low SES mothers being particularly vulnerable. While income is not associated with the risk of adverse outcomes among immigrant mothers, education is for many groups. The association is however weaker than for Canadian-born mothers. Conclusions It is important to assess the influence of both immigration and SES to better identify the children who are most at risk of experiencing perinatal health concerns. In Montreal, some immigrant women are particularly vulnerable, but so are socioeconomically disadvantaged native Canadian women. Conversely, North African-born mothers with low SES present a particularly low risk. It has also been found that a high level of education reduces the risk among several groups of immigrant women, as opposed to findings in other contexts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".