Sex-specific association of high maternal psychological stress during pregnancy on newborn birthweight
Bibliographic record
Abstract
Birthweight is an important predictor of newborn health and has been linked to maternal psychological stress during pregnancy. However, it is unclear whether prenatal stress affects birthweight similarly for both male and female infants. We used a well-established pregnancy cohort to investigate the impact of high maternal psychological stress during pregnancy on birthweight as a function of infant sex. Overall, 5702 mother-newborn pairs were analysed. Of these, 198 mothers reported high levels of stress using the Psychological Stress Measure (nine-items version; PSM-9). Maternal psychological stress was assessed between the 24th and 28th week of gestation and analyses were performed jointly and independently as a function of neonatal sex (separate analyses for male and female infants). Newborns exposed to high maternal psychological stress during pregnancy (a score above 26 measured using the PSM-9 questionnaire, corresponding to >97.5th percentile) were compared to newborns of mothers who reported lower stress. ANCOVAs revealed that high levels of maternal stress during pregnancy were linked to infant birthweight as a function of infant sex. Male infants of mothers who reported high levels of stress had a greater birthweight whereas female infants had a lower birthweight under the same conditions, in comparison to mothers who did not report greater levels of stress. Although the effect size is small, these results underline the possibility that male and female fetuses may use different strategies when adapting to maternal adversity and highlight the need to consider infant sex as a moderator of the association between maternal psychological stress during pregnancy and infant birthweight.
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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 | 0.000 | 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".