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Record W3110191470 · doi:10.1111/jcpp.13358

Research Review: Developmental origins of depression – a systematic review and meta‐analysis

2020· review· en· W3110191470 on OpenAlexaff
Yingying Su, Carl D’Arcy, Xiangfei Meng

Bibliographic record

VenueJournal of Child Psychology and Psychiatry · 2020
Typereview
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsMcGill UniversityDouglas CollegeUniversity of Saskatchewan
FundersMedical Research CouncilWellcome Trust
KeywordsOffspringMeta-analysisCohort studyDepression (economics)AnxietyConfoundingAntenatal depressionPopulationMedicineProspective cohort studyLow birth weightPsychologyPregnancySystematic reviewPsychiatryMEDLINEInternal medicineEnvironmental healthBiology

Abstract

fetched live from OpenAlex

BACKGROUND: Many observational studies have found a direct association between adverse in utero, perinatal and postnatal exposures and offspring's depression. These findings are consistent with the 'developmental origins of disease hypothesis'. But no review has comprehensively summarized the roles of these exposures. This review aims to systematically scrutinize the strength of associations between individual prenatal, perinatal, and postnatal exposures and subsequent depression in offspring. METHODS: We conducted a systematic review and meta-analysis to synthesize the literature from the EMBASE, HealthStar, PsychoInfo, and Medline databases since their inception to September 1, 2019. English language articles on population-based prospective cohort studies examining the associations between in utero, perinatal, and postnatal exposures and offspring's depression were searched. Random-effects models were used to calculate pooled estimates, and heterogeneity and sensitivity tests were conducted to explore potential confounders in the relationships of depression and early-life factors. Qualitative analysis was also conducted. RESULTS: Sixty-four prospective cohort studies with 28 exposures studied in the relationships to offspring's depression met inclusion criteria. The meta-analysis found 12 prenatal, perinatal, and postnatal characteristics were associated with an increased risk of depression in offspring: low birth weight, premature birth, small gestational age, maternal education, socioeconomic status, having younger parents (<20 years), having older parents (≥35 years), maternal smoking, paternal smoking, maternal stress, maternal anxiety, and prenatal depression. Heterogeneity and sensitivity tests supported the findings. By and large, study characteristics had no effects on conclusions. Qualitative analyses generally supported the findings of meta-analysis and reported on additional risk factors. CONCLUSIONS: This review provides a robust and comprehensive overview of the lasting psychopathological effects of in utero, perinatal, and postnatal exposures. The findings highlight the need for clinical and public health interventions focusing on the identified risk factors. Large prospective cohort studies are warranted to investigate the combined effects of multiple co-existing early-life exposures.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.036
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.013
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.036
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0130.021
Bibliometrics0.0080.009
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.103
GPT teacher head0.462
Teacher spread0.359 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations53
Published2020
Admission routes1
Has abstractyes

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