Disparities in Birth Outcomes by Neighborhood Income
Bibliographic record
Abstract
BACKGROUND: Knowledge of socioeconomic disparities in health is of interest to both the general public and public health policymakers. It is unclear how disparities in birth outcomes by socioeconomic status have changed over time, particularly in settings with universal health insurance and favorable socioeconomic conditions. METHODS: We identified a cohort of all births (n = 713,950) registered in British Columbia, 1985-2000. We compared rates and relative risks (RRs) of preterm birth, small-for-gestational-age (SGA), stillbirth, and neonatal and postneonatal death across neighborhood-income quintiles from Q1 (richest, the reference) to Q5 (poorest) by 4-year intervals in rural and urban areas. Logistic regression was used to control for maternal and pregnancy characteristics. RESULTS: Maternal characteristics varied widely across neighborhood-income quintiles in both rural and urban areas. There were moderate and persistent disparities in birth outcomes across neighborhood-income quintiles in urban but not rural areas. The relative disparities in urban areas did not diminish over time for all birth outcomes and actually rose for postneonatal mortality. For example, crude RRs (95% confidence intervals) for Q5 versus Q1 in urban areas for SGA were 1.44 (1.37-1.52) in 1985-1988 and 1.41 (1.33-1.49) in 1997-2000; for postneonatal death, the corresponding results were 1.61 (1.17-2.20) and 2.20 (1.24-3.92), respectively. Most of the observed disparities could not be explained by observed maternal and pregnancy characteristics. CONCLUSION: Moderate disparities in birth outcomes by neighborhood income persist in urban areas (although not rural areas) of British Columbia, despite a universal health insurance system and generally favorable socioeconomic conditions.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".