Prevalence of self-reported mental disorders in pregnancy and associations with adverse neonatal outcomes: a population-based cross-sectional study

孕期自我报告精神障碍的患病率及其与不良新生儿结局的关联:一项基于人群的横断面研究

阅读:1

Abstract

BACKGROUND: Mental disorders in pregnancy are common causes of morbidity and mortality with associated risks of adverse neonatal outcomes. Our aims were to evaluate the prevalence of self-reported mental disorders in women presenting to maternity services and to determine the association between history of self-reported maternal mental disorder and adverse neonatal outcomes. METHODS: Data on all singleton pregnancies known to maternity services in Northern Ireland over the period 2010 to 2015 were extracted from the Northern Ireland Maternity System (NIMATS), including frequency data for number of pregnancies where the mother reported a history of mental disorder. Odds ratios were derived from logistic regression analyses to determine the associations between self-reported maternal mental disorder and preterm birth, low infant birth weight and APGAR scores. RESULTS: In total, 140,569 singleton pregnancies were registered using NIMATS over this period. In 18.9% of these pregnancies, the mother reported a history of at least one mental disorder. After adjustment for potential confounding factors, significant associations were demonstrated between self-reported maternal mental disorder and preterm birth (odds ratio [OR] 1.31, 95% confidence interval [CI] 1.25-1.37), low infant birth weight (OR 1.29, 95% CI 1.21-1.38) and APGAR score < 7 at 1 min (OR 1.14, 95% CI 1.10-1.19) and 5 min (OR 1.23, 95% CI 1.12 to 1.34). CONCLUSIONS: These findings emphasise the critical importance of routine enquiry regarding psychiatric history when women present to maternity services and the impact of maternal mental illnesses upon outcomes for their infants.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。