Maternal Education and Stillbirth
Bibliographic record
Abstract
BACKGROUND: Associations between risk factors and perinatal outcomes may be biased at preterm gestational ages, if preterm delivery behaves as an effect modifier due to other unmeasured factors in the causal pathway. We evaluated whether fetuses-at-risk denominators could be used in regression models instead of conventional denominators to obtain less biased estimates of the association between maternal education and stillbirth at preterm gestational intervals. METHODS: Data included 2,143,134 live-born and 8946 stillborn singletons from 1981 through 2006 in Québec, Canada. Odds ratios and 95% confidence intervals were estimated for the relationship between education and stillbirth according to cause of fetal death, adjusting for maternal age, marital status, home language, parity, and period. We examined associations for 4 gestational intervals (<28, 28-31, 32-36, and ≥37 completed weeks), using both conventional denominators (ie, preterm live births) and fetuses-at-risk denominators. RESULTS: Stillbirth rates were greater for mothers with fewer years of education at all gestational intervals. Using conventional denominators, low education (relative to high education) was more strongly associated with term than preterm stillbirth and was apparently protective at <28 weeks. Using fetuses-at-risk denominators, low education was more strongly associated with preterm stillbirth than term stillbirth, even at <28 weeks. Low education was most strongly associated with diabetic-related stillbirth at ≥28 weeks (odds ratio = 5.04) relative to high education. CONCLUSIONS: Low education is associated with stillbirth throughout gestation, especially diabetic-related stillbirth. Use of fetuses-at-risk denominators in regression models can avoid potentially biased estimates obtained with conventional denominators at preterm gestational ages.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".