The Association Between Rural‐Urban Continuum, Maternal Education and Adverse Birth Outcomes in Québec, Canada
Bibliographic record
Abstract
CONTEXT: Rural relative to urban area and low socioeconomic status (SES) are associated with adverse birth outcomes. Whether a graded association of increasing magnitude is present across the urban-rural continuum, accounting for SES, is unclear. We examined the association between rural-urban continuum, SES and adverse birth outcomes. METHODS: Singleton births from 1999 to 2003 (n = 356,147) were linked to Québec municipalities ranked on a continuum of 3 urban and 4 rural areas based on population and economic base. Maternal education was used to represent SES. Odds ratios (OR) were calculated for preterm birth (PTB), low birth weight (LBW), and small-for-gestational-age (SGA) birth, accounting for municipality and individual-level covariates. We used stratified analyses to examine interaction between SES and rural-urban continuum. FINDINGS: Relative to metropolitan area residence, living in small urban or rural areas was associated with adverse birth outcomes. Living in rural areas was associated with SGA birth (OR 1.11, 95% CI 1.05-1.17) and LBW (OR 1.15, 95% CI 1.05-1.26), and living in small urban areas was associated with PTB (OR 1.14, 95% CI 1.08-1.20). Upon stratification by education, living in remote rural relative to metropolitan areas was associated with adverse birth outcomes among university educated mothers only, and living in small urban areas was associated with adverse birth outcomes among mothers with lesser but not higher education. An SES gradient was present in all rural-urban areas, particularly for SGA birth. CONCLUSION: Differences in perinatal health exist across the rural-urban continuum, and maternal education has a modifying influence.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".