Unconditional Prenatal Income Supplement and Birth Outcomes
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Perinatal outcomes have improved in developed countries but remain poor for disadvantaged populations. We examined whether an unconditional income supplement to low-income pregnant women was associated with improved birth outcomes. METHODS: This study included all mother-newborn pairs (2003-2010) in Manitoba, Canada, where the mother received prenatal social assistance, the infant was born in the hospital, and the pair had a risk screen (N = 14 591). Low-income women who received the income supplement (Healthy Baby Prenatal Benefit [HBPB], n = 10 738) were compared with low-income women who did not receive HBPB (n = 3853) on the following factors: low birth weight, preterm, small and large for gestational age, Apgar score, breastfeeding initiation, neonatal readmission, and newborn hospital length of stay (LOS). Covariates from risk screens were used to develop propensity scores and to balance differences between groups in regression models; γ sensitivity analyses were conducted to assess sensitivity to unmeasured confounding. Population-attributable and preventable fractions were calculated. RESULTS: HBPB was associated with reductions in low birth weight (aRR, 0.71 [95% CI, 0.63-0.81]), preterm births (aRR, 0.76 [95% CI, 0.69-0.84]) and small for gestational age births (aRR, 0.90 [95% CI, 0.81-0.99]) and increases in breastfeeding (aRR, 1.06 [95% CI, 1.03-1.09]) and large for gestational age births (aRR, 1.13 [95% CI, 1.05-1.23]). For vaginal births, HBPB was associated with shortened LOS (weighted mean, 2.86; P < .0001). Results for breastfeeding, low birth weight, preterm birth, and LOS were robust to unmeasured confounding. Reductions of 21% (95% CI, 13.6-28.3) for low birth weight births and 17.5% (95% CI, 11.2-23.8) for preterm births were associated with HBPB. CONCLUSIONS: Receipt of an unconditional prenatal income supplement was associated with positive outcomes. Placing conditions on income supplements may not be necessary to promote prenatal and perinatal health.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".