Prepartum and Postpartum Maternal Depressive Symptoms Are Related to Children’s Brain Structure in Preschool
Bibliographic record
Abstract
BACKGROUND: Perinatal maternal depression is a serious health concern with potential lasting negative consequences for children. Prenatal depression is associated with altered brain gray matter in children, though relations between postpartum depression and children's brains and the role of white matter are unclear. METHODS: We studied 52 women who provided Edinburgh Postnatal Depression Scale (EPDS) scores during each trimester of pregnancy and at 3 months postpartum and their children who underwent magnetic resonance imaging at age 2.6 to 5.1 years. Associations between maternal depressive symptoms and magnetic resonance imaging measures of cortical thickness and white matter structure in the children were investigated. RESULTS: Women's second trimester EPDS scores negatively correlated with children's cortical thickness in right inferior frontal and middle temporal regions and with radial and mean diffusivity in white matter emanating from the inferior frontal area. Cortical thickness, but not diffusivity, correlations survived correction for postpartum EPDS. Postpartum EPDS scores negatively correlated with children's right superior frontal cortical thickness and with diffusivity in white matter originating from that region, even after correcting for prenatal EPDS. CONCLUSIONS: Higher maternal depressive symptoms prenatally and postpartum are associated with altered gray matter structure in children; the observed white matter correlations appear to be uniquely related to the postpartum period. The reduced thickness and diffusivity suggest premature brain development in children exposed to higher maternal perinatal depressive symptoms. These results highlight the importance of ensuring optimal women's mental health throughout the perinatal period, because maternal depressive symptoms appear to increase children's vulnerability to nonoptimal brain development.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".