Effects of maternal exposure to acute stress on birth outcomes: a quasi-experiment study
Bibliographic record
Abstract
Abstract Numerous studies have shown associations between maternal stress and poor birth outcomes, but evidence is unclear for causal inference. Natural disasters provide an opportunity to study effects of quasi-randomized hardship with an accurate measure of onset and duration. In a population-based quasi-experimental study, we examined the effect of maternal exposure to the January 1998 Québec ice storm on birth outcomes by comparing pregnant mothers who lived in an area hard hit by the ice storm with those in two unaffected regions. In a total of 147,349 singleton births between 1995 and 2001, we used a difference-in-differences method to estimate the effects of the ice storm on gestational age at delivery (GA), preterm birth (PTB), weight-for-gestational-age z-scores (BWZ), large for gestational age (LGA), and small for gestational age (SGA). After adjusting for maternal and sociodemographic characteristics, there were no differences between the exposed and the unexposed mothers for birth outcomes. The estimated differences (exposed vs. unexposed) were 0.01 SDs (95% CI: −0.02, 0.05) for BWZ; 0.10% point (95% CI: −0.95%, 1.16%) for SGA; 0.25% point (95% CI: −0.78%, 1.28%) for LGA; −0.01 week (95% CI: −0.07, 0.05) for GA; and 0.16% point (95% CI: −0.66%, 0.97%) for PTB. Neither trimester-specific nor dose–response associations were observed. Overall, exposure to the 1998 Québec ice storm as a proxy for acute maternal stress in pregnancy was not associated with poor birth outcomes. Our results suggest that acute maternal hardship may not have a substantial effect on adverse birth outcomes.
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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 | 0.017 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".