Data Science and Pregnancy-Child Cohort Studies

We approach complications in pregnancy and childhood through prospective cohort studies; using observational studies and by linkage of routine electronic health records across primary, community, and secondary care. More detailed studies are enabled through linkages with individually collected data using patient portals. Discovery science is facilitated by associated bioresources.

Our observational cohort studies are designed to:

• understand the aetiology of premature birth through longitudinal data and sample collection in pregnancy
• develop accurate tools for risk assessment of common complication of pregnancy; e.g. premature birth, pre-eclampsia and gestational diabetes
• understand the burden of placental disease for the mother and child in Sub Saharan Africa
• define the consequences of living with obesity for pregnant women and the long- term consequences for the child
• better understand the origins of gestational diabetes, and provide targeted management
• investigate the impact of healthcare and health system interventions, as natural experiments and quasi-experimental studies

Our Electronic Health Record linkages are designed to:

• profile ‘real time’ trends in the health of pregnant women and their children in our deprived, multi-ethnic inner-city population
• understand interactions between physical and mental health in pregnancy
• evaluate the long-term consequences for the child of adverse physical/mental/environmental health exposures in pregnancy
• evaluate in ‘real time’, through interrupted time series or ‘real world trials’ methods the effect of novel management or population health interventions in pregnant women and children

Related Departments:

• School of Life Course and Population Health Sciences
• Department: Women and Children’s Health