Optimising the identification of high-risk populations and modifiable risk factors to reduce ethnic and socioeconomic inequalities in perinatal mortality

Supervisors

• Professor Bradley Manktelow (brad.manktelow@le.ac.uk)
• Professor Lucy Smith (lucy.smith@le.ac.uk)

The project

This PhD studentship offers an exciting opportunity to use innovative statistical methods to reduce inequalities in health outcomes for mothers, babies and families across the UK.

Wide inequalities exist in stillbirth rates in the UK with mothers and babies from Black and Asian ethnic groups and those living in the most deprived areas experiencing significantly higher rates of stillbirth and neonatal death compared to mothers and babies from White affluent backgrounds1,2. These figures highlight the need for urgent research into understanding and addressing these inequalities.

It is vital to identify those populations at highest risk and to target interventions on modifiable risk factors. This is recognised by NHS England as a key focus of their COREPLUS5 approach which aims to improve maternity outcomes for those living in the 20% most deprived areas and for mothers of Black and Asian ethnicity, particularly focusing on a local population approach 3.

In this project, the student will utilise large-scale timely data on risk factors and poor perinatal outcomes for births in Leicester, Leicestershire and Rutland in order to:

1. Develop innovative statistical techniques to optimise identification of those groups and individuals at highest risk of poor perinatal outcomes providing granular level neighbourhood data
2. Implement graphical chain modelling 4 of causal pathways to determine modifiable factors to ensure effectiveness of interventions
3. Identify best practice for knowledge mobilisation by the Leicester, Leicestershire and Rutland Integrated Care Board (LLR-ICB) to support high quality clinical care working

This work will directly facilitate the LLR-ICB to achieve their priority to “Accelerate preventative programmes that engage those at greatest risk of poor health outcomes” identified in their Equity and Equality Action Plan and deliver effective change. 

Training

The student will be integrated into the interdisciplinary and research active TIMMS Research Group within the Department of Population Health Sciences at the University of Leicester. The TIMMS group focus on policy-relevant research to improve health outcomes for mothers, parents, babies and children.

This studentship brings together a supervisory team of national perinatal mortality experts from MBRRACE-UK and the developers of the successful LLR-ICB perinatal inequalities dashboard to facilitate improvements in health for high-risk groups.

This project offers an exciting opportunity for a student to use and develop advanced statistical methodology to optimise the identification of high-risk populations and modifiable risk factors for local policy planning to improve health outcomes for mothers, babies and families. 

References

1. Draper ES, Gallimore ID, Smith LK, Matthews RJ, Fenton AC, Kurinczuk JJ, Smith PW, Manktelow BN, on behalf of the MBRRACE-UK Collaboration. MBRRACE-UK Perinatal Mortality Surveillance, UK Perinatal Deaths for Births from January to December 2021: State of the Nation Report. Leicester: The Infant Mortality and Morbidity Studies, Department of Population Health Sciences, University of Leicester. 2023. MBRRACE-UK report
2. Matthews RJ, Draper ES, Manktelow BN On behalf of the MBRRACE-UK Collaboration, et al. Understanding ethnic inequalities in stillbirth rates: a UK population-based cohort study. BMJ Open 2022;12
3. NHS England. Core20PLUS5
4. Lauritzen, S. L. and Wermuth, N. Graphical models for associations between variables, some of which are qualitative and some quantitative. Ann. Statist. 1989; 17: 31-54