The Influence of Anxiety and Depressive Symptoms During Pregnancy on Birth Size
Bibliographic record
Abstract
BACKGROUND: Mental health problems during pregnancy can influence fetal growth. However, studies examining the influence of maternal mental health across the normal range of birth outcomes are uncommon. This study examined the associations between symptoms of maternal depression and anxiety during pregnancy on birth size among term Asian infants. METHODS: One thousand forty-eight Asian pregnant women from a cohort Growing Up in Singapore Towards Healthy Outcomes were recruited between 2009 to 2010 at two Singaporean maternity hospitals. At 26 weeks gestation, depressive symptoms were measured with the Edinburgh Postnatal Depression Scale (EPDS) and the Beck Depression Inventory II (BDI-II), and anxiety was measured with the Spielberger State-Trait Anxiety Inventory (STAI). Health personnel recorded birthweight, birthlength, gestational age, and head circumference at birth. RESULTS: Nine hundred forty-six women who delivered term infants had complete data. For this sample, the mean birthweight was 3146.6 g [standard deviation (SD) 399.0], the mean birthlength was 48.9 cm (SD 2.0). After controlling for several potential confounders, there was a significant negative association between STAI and birthlength [β = -0.248, confidence interval (CI) [-0.382, -0.115], P < 0.001] and a small negative association between EPDS and birthlength (β = -0.169, CI [-0.305, -0.033], P = 0.02). No associations were found between scores on the EPDS, BDI-II, and STAI with birthweight or head circumference. CONCLUSIONS: Our preliminary data suggest that among term infants, anxiety and depressive symptoms are not associated with birthweight, while anxiety and depressive symptoms are associated with a shorter birthlength.
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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 | 0.001 | 0.004 |
| 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".