The association between maternal depression and anxiety symptoms during pregnancy and child sleep patterns at age 3 years
Bibliographic record
Abstract
BACKGROUND: Childhood sleep problems are common and impact physical and emotional health. Prior work suggests that prenatal maternal depression and anxiety associate with disturbed child sleep in infancy. The current study evaluated whether these same associations extend to children at 3 years of age, and if so, whether the timing of symptoms in pregnancy is relevant. METHODS: This study included 490 mother-child dyads from the Ontario Birth Study. The dependent variables included child sleep latency, total sleep duration and nighttime awakenings at 3 years of age assessed via maternal reports. The main independent variables were maternal depressive and anxiety symptoms assessed using the Patient Health Questionnaire at 12-16 and 28-32 weeks of pregnancy. We used linear regressions to evaluate the predictive value of maternal symptoms on each sleep measure. RESULTS: After controlling for potential confounding variables including maternal depression and anxiety scores at the time of the sleep assessments, there was a robust association between maternal depressive symptoms at 28-32 weeks of pregnancy and the number of child awakenings at age 3 (t = 3.08, p = .002). No significant associations between maternal prenatal anxiety and child sleep patterns were found in the multivariate analyses. CONCLUSIONS: During weeks 28-32 of pregnancy, fetal exposure to maternal symptoms of depression associates with increased child awakenings at age 3 years. These results were not attributable to reporting bias related to maternal affective symptoms at the time of the sleep assessments. These findings point to a possible fetal programming effect on sleep that continues into the pre-school years.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".