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Record W1605258932 · doi:10.1016/j.jped.2013.01.003

Maternal education level and low birth weight: a meta-analysis

2013· review· en· W1605258932 on OpenAlexaboutno aff
Sonia Silvestrin, Clécio Homrich da Silva, Vânia Naomi Hirakata, André Akira Sueno Goldani, Patrícia Pelufo Silveira, Marcelo Zubarán Goldani

Bibliographic record

VenueJornal de Pediatria · 2013
Typereview
Languageen
FieldMedicine
TopicGestational Diabetes Research and Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineLow birth weightMeta-analysisSocioeconomic statusPublication biasCohort studyDemographyBirth weightPregnancyPopulationEnvironmental health

Abstract

fetched live from OpenAlex

To assess the association between maternal education level and birth weight, considering the circumstances in which the excess use of technology in healthcare, as well as the scarcity of these resources, may result in similar outcomes. A meta-analysis of cohort and cross-sectional studies was performed; the studies were selected by systematic review in the MEDLINE database using the following Key**words socioeconomic factors, infant, low birth weight, cohort studies, cross-sectional studies. The summary measures of effect were obtained by random effect model, and its results were obtained through forest plot graphs. The publication bias was assessed by Egger's test, and the Newcastle-Ottawa scale was used to assess study quality. The initial search found 729 articles. Of these, 594 were excluded after reading the title and abstract; 21, after consensus meetings among the three reviewers; 102, after reading the full text; and three for not having the proper outcome. Of the nine final articles, 88.8% had quality ≥ six stars (Newcastle-Ottawa Scale), showing good quality studies. The heterogeneity of the articles was considered moderate. High maternal education showed a 33% protective effect against low birth weight, whereas medium degree of education showed no significant protection when compared to low maternal education. The hypothesis of similarity between the extreme degrees of social distribution, translated by maternal education level in relation to the proportion of low birth weight, was not confirmed. Analisar a associação entre grau de escolaridade materna e peso de nascimento, considerando-se a hipótese de que a utilização em excesso das tecnologias na área da saúde, assim como a escassez de recursos, pode produzir desfechos similares. Realizou-se uma meta-análise com estudos transversais e de coorte, selecionados por revisão sistemática na base de dados bibliográficos MEDLINE com os descritores: socioeconomic factors; infant, low birth weight; cohort studies; cross-sectional studies. As medidas de sumário de efeito foram obtidas pelo modelo de efeito aleatório, e os seus resultados apresentados por intermédio dos gráficos Forest Plot. O viés de publicação foi analisado pelo Teste de Egger, e a avaliação da qualidade dos estudos utilizou a Escala de Newcastle-Ottawa. A busca inicial encontrou 729 artigos. Destes, foram excluídos 594, após a leitura do título e do resumo; 21, após reuniões de consenso entre os três revisores; 102, após leitura do texto completo; e três, por não possuírem o desfecho adequado. Dos nove artigos finais, 88,8% apresentavam uma qualidade igual ou superior a seis estrelas (Escala de Newcastle-Ottawa), configurando boa qualidade aos estudos. A heterogeneidade dos artigos foi considerada moderada. A escolaridade materna elevada mostrou um efeito protetor de 33% sobre o baixo peso ao nascer, enquanto que o grau médio não apresentou proteção significativa, quando comparados à escolaridade materna baixa. A hipótese de similaridade entre os graus extremos da distribuição social, traduzidas pelo nível de escolaridade materna, em relação à proporção de baixo peso ao nascer, não foi confirmada.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.728
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.002
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)0.0030.000

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 head0.132
GPT teacher head0.394
Teacher spread0.261 · 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.

Study designOther design
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

Citations144
Published2013
Admission routes1
Has abstractyes

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