Women's mental illness in pregnancy: Exploring contact with secondary mental health services and links with offspring health and education outcomes

据报道，英国每4名妇女中就有1名在围产期患有精神疾病，这构成了一个代价高昂的公共卫生问题，与家庭福祉下降、产科并发症和不良儿童结局有关。对于那些在获得心理健康支持方面面临障碍的人来说，重大的健康负担更大。例如，年轻妇女和少数民族或社会经济地位较低的妇女不太可能在英国精神卫生服务机构寻求和接受治疗。此外，尽管在这方面缺乏强有力的因果证据，但妇女对后代在怀孕期间接触精神疾病感到恐惧和耻辱。我以前的工作表明，关于母亲在怀孕期间的精神疾病对儿童结局的因果影响仍然存在不确定性。我建议设立一个为期18个月的奖学金来应对这些挑战，确定哪些家庭可以从进一步的支持中受益，直接解决父母自己的问题。我将使用来自“关联数据的教育和儿童健康洞察”（ECHILD）数据库的关联行政数据，该数据库拥有自1984年以来在英国出生的2000万人的英国行政健康和教育记录。我将策划一个相关的纵向国家数据集，以探索母亲的围产期心理健康和与后代发育结果的联系。我的工作将由一个家长咨询小组和慈善机构心理健康中心指导和加强。首先，我将探讨妇女在怀孕期间与二级心理保健服务接触的不平等现象，重点关注有边缘化风险的人口群体（即，探索妇女的年龄，种族，孩子的数量，和邻里剥夺）。我将重点关注2010年4月至2022年3月期间爱婴儿童与发展方案中妇女的生育情况。我将描述在此期间妇女与二级精神卫生服务的接触趋势，同时记录医院事件统计和精神卫生服务数据集的数据质量和可用性的细微差别。我将在时间管理数据库和政策变化的背景下解释趋势，例如从2016年开始政府对专业围产期心理健康服务的投资。我将探讨服务提供中的不公平现象随着时间的推移而保持的程度，为进一步的政策行动提供信息。第二，我将把母亲的怀孕数据与出生和后代结果数据联系起来，把医院事件统计和国家学生数据库中的儿童记录联系起来。我将严格测试和提高数据链接的质量，以确保队列中母子和子女兄弟姐妹对的准确性。我将描述最终的样本特征，包括后代的数量和数据的可用性。因此，我将为及时进行新的代际研究提供宝贵的资源，帮助英国行政数据基础设施与斯堪的纳维亚人口层面的旗舰数据资源保持一致，将家庭成员的记录大规模联系起来。（出生体重、胎龄、胎儿和新生儿死亡、慢性健康状况和小学教育程度）。我的研究结果将有助于了解后代早期健康和发育的起源。我将在数据质量的背景下解释相关性，并通过我以前的学习获得信息。几个准实验方法，包括“同胞比较设计”，然后可以应用于测试母亲和孩子变量之间的因果关系，跨越我的奖学金结束。因此，这项工作铺平了道路，为家庭，临床医生和决策者提供强大的，以证据为基础的信息，围产期精神疾病的可能代际影响。

1 in 4 women in the UK are reported to experience mental illness in the perinatal period, constituting a costly public health issue linked to reduced family wellbeing, obstetric complications, and adverse child outcomes. The significant health burden is greater for those facing barriers to accessing mental health support. For example, young women and women with minoritised ethnicities or lower socio-economic status are less likely to seek and receive treatment in British mental health services. Further, women face fears and stigma regarding offspring exposure to their mental illness during pregnancy, despite a lack of robust causal evidence in this area. My previous work shows that uncertainties remain regarding the causal impact of mothers' mental illness in pregnancy on child outcomes.I propose an 18-month fellowship to address these challenges, identifying families who could benefit from further support, directly addressing parents' own concerns. I will use linked administrative data from the 'Education and Child Health Insights from Linked Data' (ECHILD) database, holding English administrative health and education records for 20 million individuals born in England since 1984. I will curate a linked longitudinal national dataset to explore mothers' perinatal mental health and links with offspring developmental outcomes. My work will be guided and enhanced by a parent advisory group and the charity Centre for Mental Health.First, I will explore inequities in women's contact with secondary mental healthcare services during pregnancy, focusing on demographic groups at risk of marginalization (i.e., exploring women's age, ethnicity, number of children, and neighborhood deprivation). I will focus on maternity episodes for women in ECHILD between April 2010 - March 2022. I will describe trends in women's contact with secondary mental health services across this period, while documenting nuances in data quality and availability from Hospital Episode Statistics and the Mental Health Services Datasets. I will interpret trends in the context of temporal administrative database and policy changes, for example following government investment in specialist perinatal mental health services from 2016. I will explore the extent to which inequities in service provision appear maintained over time, informing further policy action.Second, I will connect mothers' pregnancy data with birth and offspring outcome data, linking child records from Hospital Episode Statistics and the National Pupil Database. I will rigorously test and improve the quality of data linkages, to ensure accuracy of mother-child and child sibling pairs in the cohort. I will describe the final sample characteristics, including the number of offspring and data availability. Thus, I will produce a valuable resource for timely new intergenerational research, helping move the UK administrative data infrastructure towards alignment with flagship Scandinavian population-level data resources, linking records across family members at scale.Third, I will quantify associations between mothers' mental illness in pregnancy and offspring outcomes (birthweight, gestational age, foetal and neonatal death, chronic health conditions, and primary school attainment). My results will contribute knowledge on the origins of offspring early health and development. I will interpret correlations in the context of the data quality, informed by my earlier learning. Several quasi-experimental methods, including 'sibling-comparison designs', can then be applied to test causal pathways between mother and child variables, spanning beyond my fellowship end. Thus, this work paves the way to provide families, clinicians, and policymakers with robust, evidence-based information on the possible intergenerational effects of perinatal mental illness.