Prenatal maternal stress was not associated with birthweight or gestational age at birth during <scp>COVID</scp>‐19 restrictions in Australia: The <scp>BITTOC</scp> longitudinal cohort study
Bibliographic record
Abstract
BACKGROUND: Various forms of prenatal maternal stress (PNMS) have been reported to increase risk for preterm birth and low birthweight. However, the associations between specific components of stress - namely objective hardship and subjective distress - and birth outcomes are not well understood. AIMS: Here, we aimed to determine the relationship between birthweight and gestational age at birth and specific prenatal factors (infant gender and COVID-19 pandemic-related objective hardship, subjective distress, change in diet), and to determine whether effects of hardship are moderated by maternal subjective distress, change in diet, or infant gender. MATERIALS AND METHODS: As part of the Birth in the Time of COVID (BITTOC study), women (N = 2285) who delivered in Australia during the pandemic were recruited online between August 2020 and February 2021. We assessed objective hardship and subjective distress related to the COVID pandemic and restrictions, and birth outcomes through questionnaires that were completed at recruitment and two months post-partum. Analyses included hierarchical multiple regressions. RESULTS: No associations between maternal objective hardship or subjective distress and gestational age at birth or birthweight were identified. Lower birthweight was significantly associated with female gender (adjusted β = 0.083, P < 0.001) and with self-reported improvement in maternal diet (adjusted β = 0.059, P = 0.015). CONCLUSIONS: In a socioeconomically advantaged sample, neither objective hardship nor subjective distress related to COVID-19 were associated with birth outcomes. Further research is warranted to understand how other individual factors influence susceptibility to PNMS and how these findings are applicable to women with lower socioeconomic status.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".