The association between prenatal maternal stress, infant brain volumes, and temperament during the COVID-19 pandemic
Bibliographic record
Abstract
Prenatal maternal stress (PNMS) is associated with altered trajectories of infant socio-emotional and brain development, including brain structures such as the amygdala and prefrontal cortex (PFC). During the COVID-19 pandemic, which was a major global stressor, PNMS was significantly elevated, yet the impact on infant neurodevelopment remains uncertain. The objective of the present study was to determine whether PNMS during the pandemic was associated with infant amygdala and PFC volumes as well as temperament. In addition, we examined whether social support and resilience during pregnancy were protective factors.\nParticipants were enrolled in the Canadian ‘Pregnancy during the COVID-19 Pandemic’ cohort study. Pregnant individuals had their perceived stress, pandemic-related objective hardship, mental health, social support, and resilience measured. Infant magnetic resonance imaging (MRI) scans (n =100) were conducted at 3 months of age, and parents reported on infant temperament at 6 months of age. General linear models were used to examine the associations among PNMS, brain volumes, and developmental outcomes and to assess the role of protective factors.\nThe results found that prenatal maternal anxiety negatively predicted 3-month left infant amygdala volumes. Smaller left amygdala volumes were also associated with greater infant 6-month negative affectivity. Maternal stress was associated with smaller infant PFC volumes, and this relationship was moderated by social support and resilience. This study provides evidence for infant brain alterations related to prenatal maternal perceived stress and anxiety, indicating that the impact of PNMS on infant development during the COVID-19 pandemic may have long-lasting implications for children’s health. Our findings suggest that social support, resilience, and mental health may be key areas for screening and intervention during pregnancy to best support healthy infant 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 | 0.000 | 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".