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Record W4387651710 · doi:10.1186/s12916-023-03071-7

Association of breastfeeding with mental disorders in mother and child: a systematic review and meta-analysis

2023· review· en· W4387651710 on OpenAlexaffabout
Polina Bugaeva, I A Arkusha, Rinat Bikaev, Igor Kamenskiy, Aleksandra Pokrovskaya, Yasmin El-Taravi, Valeria Caso, А С Аведисова, Derek K. Chu, Jon Genuneit, Gabriel Torbahn, Timothy R. Nicholson, Dina Baimukhambetova, Aigun Mursalova, Anastasia Kolotilina, Svetlana Gadetskaya, Elena Kondrikova, Mikhail Zinchuk, R G Akzhigitov, Robert Boyle, Alla Guekht, Daniel Munblit

Bibliographic record

VenueBMC Medicine · 2023
Typereview
Languageen
FieldMedicine
TopicBreastfeeding Practices and Influences
Canadian institutionsMcMaster UniversityImpact
Fundersnot available
KeywordsMedicineBreastfeedingMental healthPsychiatryAnxietyObservational studyMeta-analysisOdds ratioPediatrics

Abstract

fetched live from OpenAlex

Abstract Background Breastfeeding has long been associated with numerous benefits for both mothers and infants. While some observational studies have explored the relationship between breastfeeding and mental health outcomes in mothers and children, a systematic review of the available evidence is lacking. The purpose of this study is to systematically evaluate the association between breastfeeding and mental health disorders in mothers and children. Methods We systematically searched MEDLINE and EMBASE from inception to June 2, 2023. The inclusion criteria consisted of all studies evaluating links between breastfeeding and development of mental health disorders in children and mothers. Risk of bias was assessed using the Newcastle–Ottawa Scale (NOS) while grading of Recommendations Assessment, Development and Evaluation (GRADE) was used to assess the certainty of evidence. A random-effects meta-analysis was used if possible, to estimate the odds ratio for the association between breastfeeding and mental health outcomes. The Mantel–Haenszel method was utilised for pooling ORs across studies. Study heterogeneity was assessed using the I 2 statistic. Results Our review identified twenty-one original study. Of these, 18 focused on the association between breastfeeding and child health, assessing depressive disorders, schizophrenia, anxiety disorders, eating disorders and borderline personality disorder. Three studies evaluated the associations between breastfeeding and maternal mental health disorders. Three studies looking at outcomes in children showed no significant association between breastfeeding and occurrence of schizophrenia later in life (OR 0.98; 95% CI 0.57–1.71; I 2 = 29%). For depressive disorders (5 studies) and anxiety disorders (3 studies), we found conflicting evidence with some studies showing a small protective effect while others found no effect. The GRADE certainty for all these findings was very low due to multiple limitations. Three studies looking at association between breastfeeding and maternal mental health, were too heterogeneous to draw any firm conclusions. Conclusions We found limited evidence to support a protective association between breastfeeding and the development of mental health disorders in children later in life. The data regarding the association between breastfeeding and maternal mental health beyond the postnatal period is also limited. The methodological limitations of the published literature prevent definitive conclusions, and further research is needed to better understand the relationship between breastfeeding and mental health in mothers and children.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.701
Threshold uncertainty score0.727

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0080.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.073
GPT teacher head0.367
Teacher spread0.295 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
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

Citations21
Published2023
Admission routes2
Has abstractyes

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