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

妇女妊娠期精神疾病：探索与二级心理健康服务的联系以及与后代健康和教育成果的联系

• 批准号: ES/Z502492/1
• 负责人: Yasmin Ahmadzadeh
• 金额: $ 18.41万
• 依托单位: King's College London
• 依托单位国家: 英国
• 项目类别: Fellowship
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=ES%2FZ502492%2F1
• 关键词: Women; mental; illness; pregnancy; Exploring

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.

据报道，英国四分之一的女性在围产期患有精神疾病，这是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，健康负担更大。例如，年轻女性和少数族裔或社会经济地位较低的女性不太可能在英国心理健康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，但妇女仍面临着对后代在怀孕期间遭受精神疾病的恐惧和耻辱。我之前的工作表明，母亲妊娠期精神疾病对孩子结局的因果影响仍然存在不确定性。我提议提供为期 18 个月的研究金来应对这些挑战，确定可以从进一步支持中受益的家庭，直接解决父母自己的担忧。我将使用“关联数据的教育和儿童健康洞察”(ECHILD) 数据库中的关联管理数据，该数据库保存了自 1984 年以来在英格兰出生的 2000 万个人的英语行政健康和教育记录。我将策划一个关联的纵向国家数据集来探索母亲的围产期心理健康及其与后代发育结果的联系。我的工作将得到家长咨询小组和慈善心理健康中心的指导和加强。首先，我将探讨女性在怀孕期间接触二级心理保健服务的不平等现象，重点关注面临边缘化风险的人口群体（即探索女性在怀孕期间接受二级心理保健服务的机会）。年龄、种族、儿童数量和邻里贫困）。我将重点关注 2010 年 4 月至 2022 年 3 月期间 ECHILD 中女性的产妇发作情况。我将描述这一时期女性与二级心理健康服务接触的趋势，同时记录医院发作统计数据和心理健康服务的数据质量和可用性方面的细微差别数据集。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 年起政府对专业围产期心理健康服务进行投资之后。我将探讨随着时间的推移，服务提供中的不平等现象在多大程度上得以维持，为进一步的政策行动提供信息。其次，我将把母亲的怀孕数据与出生和后代结果数据联系起来，将医院事件统计数据和国家学生数据库中的儿童记录联系起来。我将严格测试并提高数据链接的质量，以确保队列中母子和兄弟姐妹对的准确性。我将描述最终的样本特征，包括后代数量和数据可用性。因此，我将为及时的新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级旗舰数据资源保持一致，大规模连接家庭成员的记录。第三，我将量化母亲心理之间的关联妊娠疾病和后代结局（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。我将根据我之前的学习，在数据质量的背景下解释相关性。然后可以应用几种准实验方法，包括“兄弟姐妹比较设计”，来测试母亲和孩子变量之间的因果路径，超越我的奖学金范围。因此，这项工作为家庭、临床医生和政策制定者提供关于围产期精神疾病可能的代际影响的可靠、基于证据的信息铺平了道路。