Understanding the links between maternal infections and stress during pregnancy and children's developmental and social-emotional outcomes

Infections and stress during pregnancy are a common occurrence and can have detrimental effects on a child's later development. Whilst the effects of maternal health during pregnancy on offspring development have been studied for some clinical conditions using epidemiological date, there is a limited understanding of the potential impact away from the most severe forms of both infections and developmental outcome. This is partly because of the complexity of identifying effects, which may only be detected several years after the originating infections, but also because of the difficulty in gathering data from the relevant stakeholders including parents, healthcare professionals, educational services and behavioural specialists. The proposed project is an exciting opportunity to leverage data from existing ESRC datasets and other sources to improve our understanding of this subject, which has not kept pace with animal models. This will be accomplished using two ESRC data sources; 1) Avon Longitudinal Study of Parents and Children (ALSPAC) and 2) Millenium Cohort Study, in addition to a comprehensive dataset from the Glasgow Cohort encompassing NHS and Education records from 30,000 children born between 2003-2011. This final dataset provides a unique opportunity to create an internationally leading resource by using Scotland's unique ability to link medical and healthcare records through the Community Health Index, providing an integrated dataset containing maternal and child medical data (hospital, GP) alongside data from education services. All three datasets comprise comprehensive information about maternal health during pregnancy as well as children's developmental outcomes. Furthermore, all data sets include information about deprivation. A secondary aim of the project will be to examine how deprivation may affect the association between maternal health during pregnancy and children's developmental outcomes. The project findings will be of international interest and relevant to parents, healthcare providers and policy makers.
The project will meet all of the ESRC goals for the ESRC studentship. We will firstly make use of data available from two existing ESRC datasets, these being the ALSPAC and MCS. These datasets represent a rich resource of information gathered over multiple years, which can be used to assess the impact of prenatal maternal health on child development, behaviour and education. Over 30,000 records are available between these two datasets. Secondly, we will focus on secondary data analysis of the Glasgow Cohort collected as part of the Glasgow ChILD (Childhood Information for Learning and Development) project. This is a dataset which will bring together information gathered by multiple stakeholders over several years, and provides powerful insight into 30,000 children from the Glasgow area. The proposed study will have unique access to this resource, which is unique internationally in its depth and scope for such a broad population. Evaluation of data from all three datasets will require different but complementary skills in complex data analysis. Throughout the PhD study, the student will receive on-going training in data analysis from the supervisors, who each have considerable experience in large scale data analysis. In particular, Dr Booth has published extensively on the subject of statistical techniques and will provide on-going support as needed. The student is already well versed in many aspects of statistical analysis, and will also receive formal training at the beginning of the programme. Findings will be disseminated through publication in internationally recognised scientific journals, as well as through public engagement. It is expected that findings will be of interest to policy makers and scientists alike. Both supervisors have extensive experience in external public engagement and will prioritise communicating the value of scientific analysis for complex challenges emerging in our field.