Foetal origins of depression? A systematic review and meta-analysis of low birth weight and later depression
Bibliographic record
Abstract
BACKGROUND: The foetal origins hypothesis suggests an association between low birth weight and later depression, yet evidence supporting this association has been inconsistent. METHOD: We systematically reviewed evidence for an association between low birth weight and adult depression or psychological distress in the general population by meta-analysis. We searched EMBASE, Medline, PsycINFO and ISI Web of Science for studies reporting observational data with low birth weight as the exposure and self- or clinician-rated depression or psychological distress measures as an outcome. Selective studies of exposures such as famine or outcomes such as severe illness only were excluded. Altogether,1454 studies were screened for relevance, 26 were included in the qualitative synthesis, 18 were included in the meta-analysis. A random effects meta-analysis method was used to obtain a pooled estimate of effect size. RESULTS: The odds of depression or psychological distress was greater for those of low birth weight (<2500 g) compared to those of normal birth weight (>2500 g) or greater [odds ratio (OR) 1.15, 95% confidence intervals (CI) 1.00-1.32]. However, this association became non-significant after trim-and-fill correction for publication bias (OR 1.08, 95% CI 0.92-1.27). Using meta-regression, no differences in effect size were observed by gender, outcome measure of depression or psychological distress, or whether the effect size was adjusted for possible confounders. CONCLUSIONS: We found evidence to support a weak association between low birth weight and later depression or psychological distress, which may be due to publication bias. It remains possible that the association may vary according to severity of symptoms or other factors.
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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 | 0.019 | 0.047 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.027 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".