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

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.