Maternal Depression and Anxiety Disorders: Longitudinal Secondary Data Analysis, 2020-2022

DOI

In this project, we aimed to increase what is known about the negative effects of maternal depression and anxiety disorders (MDAD) on the mental health outcomes of children. Mental health is a topical area of research that is receiving increasing attention in the media and is one of five ESRC strategic priorities for investment. The main aim of the project was to help develop an understanding of how mental depression and anxiety disorders are transmitted from one generation to the next and ultimately help to design interventions better able to reduce the consequences of maternal mental health for children. We have used data from QResearch, a large consolidated database derived from anonymized health records from general practices in England matched with hospital administrative data, the Hospital Episode Statistics (HES). Further information is available under Related Resources.Problems relating to Maternal Depression and Anxiety Disorders (MDAD) are common and are known to affect child health and development. In the UK, the cost of perinatal mental health problems has been estimated at £8.1 billion for each birth cohort of children, and 72 percent of this cost is related to the direct impact on the children. The overarching aim of our proposed research is to examine the effect of MDAD on child health outcomes, with a special focus on the role that MDAD plays in the development of child depression and anxiety disorders (CDAD) in adolescence. In particular, this research will provide robust empirical evidence to understand how depression and anxiety disorders are transmitted from one generation to the next and to help design interventions aimed at reducing the negative consequences of poor maternal mental health for children. To achieve this aim, we will address the following research questions: 1) Are the negative effects of MDAD on children exclusively explained by genetic transmission and family background characteristics? Or are these negative effects also explained by changes in the child's home environment? If the transmission of mental and anxiety disorders is explained exclusively by genetic traits and family background characteristics, then interventions targeted at reducing the negative effect of MDAD on maternal behaviour, e.g. through cognitive behavioural therapy, would be ineffective. On the contrary, evidence on significant effects of MDAD after controlling for genetic and family background characteristics would suggest that MDAD can lead to changes in the child home environment, e.g. changes in maternal behaviour, harsher parenting style and lower time investments in the child, with negative consequences on children. 2) Do school policies and health practices have a role in attenuating the negative effect of maternal depression on children? We will answer this research question by focusing on whether starting school earlier harms or protects children who are exposed to MDAD, and on whether an early diagnosis of maternal depression can attenuate the negative effects suffered by children. We will develop and use state-of-the-art estimation methods in combination with a novel administrative dataset covering general practices and hospitals created by merging two population-based health databases from England - namely QResearch and Hospital Episode Statistics. Using this merged database, we will create a longitudinal household dataset that will allow us to study the mental health of mothers and their children at different stages of the children's lives up to adolescence. We are a multi-disciplinary team from the Universities of Oxford and York, consisting of experts in applied econometric methods, child and maternal mental health, psychology, general practice, and on the data that we plan to utilise. We will translate our research findings into advice for policy-makers to help them design new interventions aimed at achieving better outcomes for patients suffering from maternal mental health issues and their children. Our research will also have an impact on health practitioners, psychologists, academics and charities working with mothers and children. We will produce papers aimed at academics as well as non-technical outputs to engage with policy-makers and a non-academic audience. Furthermore, by sharing and explaining our data and estimation methods to academics, we will build capacity for further research based on large health datasets. The final central element of the project will be to build the capacity of early career researchers to undertake and lead large interdisciplinary projects.

QResearch is a large, anonymised database of GP records from over 35 million patients with longitudinal data tracking back over 30 years & is linked to mortality, cancer registration & hospital data. In our analysis, we use individual-level information on general practice diagnostics, drug prescriptions, and maternity records from HES, which allows us to link children with their respective mothers. The QResearch linked database has high-quality data to support world-leading research to improve our understanding of disease and improve patient care. Our data includes all singletons born between 2002 and 2010.The mother-baby linkage in QResearch is done via maternal identifiers and year of birth.

Identifier
DOI https://doi.org/10.5255/UKDA-SN-856044
Metadata Access https://datacatalogue.cessda.eu/oai-pmh/v0/oai?verb=GetRecord&metadataPrefix=oai_ddi25&identifier=11dc15d2d2ed51b6ad26b47502a6f387c9f533cad7b51ad510381fcca548120a
Provenance
Creator Nicodemo, C, University of Oxford
Publisher UK Data Service
Publication Year 2023
Funding Reference ESRC
Rights Catia Nicodemo, University of Oxford; The Data Collection only consists of metadata and documentation as the data could not be archived due to legal, ethical or commercial constraints. For further information, please contact the contact person for this data collection.
OpenAccess true
Representation
Language English
Resource Type Numeric
Discipline Economics; Social and Behavioural Sciences
Spatial Coverage England; England