Postpartum and Youth Depression in the Context of Vitamin D Supplementation: Systematic Review and Meta-analysis
Bibliographic record
Abstract
ABSTRACT Background We conducted a systematic review and meta-analysis to assess the effect of vitamin D supplementation on depression among adolescents and young adults compared with placebo and baseline. Methods We searched databases and reference lists from inception to May 2024 for English-language studies, including cohort studies, case studies, and randomized clinical trials. Study quality was assessed using the Cochrane RoB2 tool and the Newcastle-Ottawa Scale. Random-effects meta-analyses estimated the standardized mean difference (SMD) in depression scores (primary outcome) and anxiety scores (secondary outcome). Heterogeneity was assessed using the I² statistic. Results Fifteen studies (2010–2024) from 7,638 citations met inclusion criteria. The mean sample size was 5,271 (range: 38–74,840). Meta-analysis of nine studies showed that vitamin D supplementation significantly reduced depression scores versus placebo (SMD: −0.43; 95%CI: −0.75 to −0.12; p=0.007; I²=78%). Of six studies not included in the meta-analysis, five reported significant associations between supplementation and lower depression. Subgroup effects were observed for postpartum women (SMD: −0.55; 95%CI: −1.04 to −0.06; p<0.05; I²=83%) and young adults (SMD: −1.38; 95%CI: −1.65 to −1.10; p<0.001; I²=76%). Meta-analysis of four studies found no significant association with anxiety (SMD: −0.31; 95%CI: −0.75 to 0.12; p=0.16; I²=77%). Limitations Variability in study sample sizes may affect interpretation and generalizability. Conclusions Vitamin D supplementation was associated with lower depression scores, with effects varying by subgroup.
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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 | 0.015 | 0.042 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.033 |
| Bibliometrics | 0.009 | 0.008 |
| 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".