Area-Level Constrained Income, Immigrant Status and Adverse Maternal and Neonatal Birth Outcomes in Ontario, Canada
Bibliographic record
Abstract
Living in low-income neighbourhoods, or being an immigrant, are each associated with adverse pregnancy outcomes. However, little is known about the comparative risk of adverse pregnancy outcomes among immigrant vs. non-immigrant women living in low-income areas. This dissertation is comprised of three original epidemiologic studies of the risk of adverse maternal and neonatal outcomes among women residing exclusively in low-income areas in Ontario, Canada. The studies assessed whether the risk of these outcomes was influenced by maternal migration status, and separately, maternal neighbourhood income upward mobility. Each used a retrospective population-based cohort design, comprising administrative data housed at ICES.The first study compared the risk of severe maternal morbidity and maternal mortality (SMM-M) between immigrant and non-immigrant women residing exclusively within low-income urban neighborhoods. The overall risk of SMM-M was slightly lower among immigrant than non-immigrant women (adjusted relative risk [RR] 0.92, 95% confidence interval [CI] 0.88-0.97). There was heterogeneity in the RR estimates depending on the immigrant source country. The second study compared the risk of severe neonatal morbidity and neonatal mortality (SNM-M) between newborns of immigrant and nonimmigrant women residing exclusively in low-income urban neighbourhoods. Newborns of immigrant women had an overall lower risk of SNM-M than non-immigrant women (adjusted RR 0.76, 95% CI 0.74-0.79), with considerable variation by maternal country of origin and duration of residence in Ontario. The third study included mothers living in low-income urban neighbourhoods, and evaluated their subsequent risk of SMM-M and SNM-M. Those who achieved upward area-level income mobility between 2 consecutive births were compared to those who did not experience such upward mobility. Women who moved to a higher-income area between births had a lower associated risk of SMM-M in their second pregnancy, compared to those who remained in low-income areas between births (adjusted RR 0.86, 95% CI 0.78 to 0.93). A similar effect was seen for their newborns, who also experienced a lower associated risk of SNM-M (adjusted RR 0.91, 95% CI 0.87 to 0.95) Together, these findings make a substantial contribution towards the understanding of adverse maternal and neonatal birth outcomes among women residing exclusively in lowest-income urban neighbourhoods.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 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".