SynthesisZhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics2017
[Association between depression during pregnancy and low birth weight in neonates: a Meta analysis].
Synthesis in Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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0 citing papers in PubMed, 4 citations in OpenAlex.
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
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Abstract
objectiveTo study the association between depression during pregnancy and low birth weight in neonates, and to provide a scientific basis for the prevention of low birth weight.
methodsCohort studies on the association between depression during pregnancy and low birth weight were collected and a Meta analysis was performed. Data were extracted independently by two investigators, and quality assessment was performed according to Newcastle-Ottawa Scale. The Egger's test was used to evaluate publication bias.
resultsA total of 12 cohort studies with 37 192 samples were included. The results of the Meta analysis showed that depression during pregnancy was associated with low birth weight (Z=2.08, P=0.038), and the neonates whose mothers had depression during pregnancy tended to have a high risk of low birth weight (RR=1.303, 95%CI: 1.015-1.672). The sensitivity analysis showed that the results of this Meta analysis were stable and reliable, and the Egger's test showed no publication bias.
conclusionsDepression during pregnancy may be a risk factor for low birth weight in neonates.
Indexed as
Identifiers
28899470PMC7403062W3012918211What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.