Maternal exposure to childhood traumatic events, but not multi-domain psychosocial stressors, predict placental corticotrophin releasing hormone across pregnancy
Bibliographic record
Abstract
Maternal psychosocial stress increases the risk of adverse birth and postnatal outcomes for the mother and child, but the role of maternal exposure to childhood traumatic events (CTE) and multi-domain psychosocial stressors for the level and rise of placental Corticotrophin-Releasing Hormone (pCRH) across pregnancy has been understudied. In a sociodemographically and racially diverse sample of 1303 women (64% Black, 36% White/others) with low-medical risk pregnancies at enrollment from Shelby County, Tennessee, USA, blood samples were drawn twice, corresponding roughly to second and third trimester, and extracted prior to conducting radioimmune assays for pCRH. Mothers reported CTE (physical abuse, sexual abuse, or family violence, in childhood), adulthood traumatic events, and interpersonal violence during pregnancy. Neighborhood crime/deprivation was derived using geospatially-linked objective databases. General linear and mixed models tested associations between stress exposure variables and pCRH levels and rate of rise, adjusting for obstetric/clinical/health related factors. Maternal CTE did not predict pCRH levels at time 1, but positively predicted levels at time 2, and the rate of rise in pCRH across pregnancy. Race did not moderate this association. No additional maternal stress exposures across adulthood or during pregnancy predicted pCRH outcomes. Findings indicate that childhood violence or abuse exposure can become biologically embedded in a manner predicting later prenatal physiology relevant for maternal and offspring health, and that such embedding may be specific to childhood, but not adulthood, stress. Findings also highlight the placental-fetal unit as a mechanistic pathway through which intergenerational transmission of the adverse effects of childhood adversities may occur.
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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 | 0.003 |
| 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) | 0.001 | 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".