Access to perinatal healthcare in minority Anglophones: Hospital type and birth outcomes
Bibliographic record
Abstract
OBJECTIVES: We assessed the relationship between hospital characteristics and risk of adverse birth outcomes among minority Anglophones in Montreal, Canada. METHODS: The study included 124,670 births among Anglophones in metropolitan Montreal between 1998 and 2019. We estimated risk ratios (RR) and 95% confidence intervals (CI) for the association between hospital characteristics, including residential proximity to hospitals and language in which medical services are provided, and risks of preterm birth and stillbirth. Models were adjusted for maternal socioeconomic status and other characteristics. RESULTS: In this study, 8% of Anglophones had a preterm birth and 0.4% a stillbirth. Anglophone women who delivered at a farther French hospital had a greater risk of stillbirth (RR 1.67, 95% CI 1.28-2.18) than preterm birth (RR 1.21, 95% CI 1.14-1.30), compared with delivery at hospitals closer to home. In contrast, delivery at a farther English hospital was associated with similar risks of stillbirth (RR 1.36, 95% CI 1.08-1.71) and preterm birth (RR 1.36, 95% CI 1.29-1.44). The greater risk of stillbirth with delivery at a farther French hospital, versus greater risk of preterm birth at a farther English hospital, remained present in analyses stratified by maternal age, education, material deprivation, and region of origin. CONCLUSION: Minority Anglophones in Montreal who travel to a farther French hospital for delivery have a greater risk of stillbirth than Anglophones who travel to a farther English hospital. This novel observation suggests the need to determine if access to perinatal healthcare in a woman's language may help reduce the risk of stillbirth.
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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 | 0.000 | 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 | 0.001 | 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".