Cookies on this website
We use cookies to ensure that we give you the best experience on our website. If you click 'Continue' we'll assume that you are happy to receive all cookies and you won't see this message again. Click 'Find out more' for information on how to change your cookie settings.

NDPH/0003/MT15

Name of supervisor

Jenny KurinczukProfessor Jenny Kurinczuk, National Perinatal Epidemiological Unit

Name of second supervisor

Maria QuigleyMs Maria Quigley, National Perinatal Epidemiological Unit

Project Summary

Background

Congenital anomalies, congenital abnormalities, birth defects and congenital malformations are all terms used to describe developmental disorders of the embryo and fetus. There are several hundred separate anomalies* which fall under these headings including structural, functional, chromosomal, metabolic and hereditary conditions; the underlying cause of most anomalies is not known. Although the vast majority of infants born with a congenital anomaly will survive, congenital anomalies are nevertheless the second commonest cause of infant deaths in England and Wales (https://www.npeu.ox.ac.uk/downloads/files/infant-mortality/Infant-Mortality-Briefing-Paper-3.pdf ). Infant and child mortality rates in the UK compare unfavourably with many of our European counterparts.

Surveillance of congenital anomalies in England and Wales is carried out via a series of regional congenital anomaly registers which cover about 48% of all births, although Public Health England (the current funder) has plans to extend this nationally. The National Perinatal Epidemiology Unit runs the Congenital Anomaly Register for Oxfordshire, Berkshire and Buckinghamshire (CAROBB). CAROBB holds data on fetuses and babies with suspected and confirmed anomalies notified since 2005 and before that we have data for Oxford back to 1991. CAROBB contributes data to the national ‘hub’ and the pooled data collected by the hub are reported nationally by BINOCAR. CAROBB also contributes data to the European-wide congenital anomaly data collection EUROCAT.  

The increasing national capacity for data linkage opens up a number of possibilities in terms of research which includes (although is not limited to): investigating the completeness of case notifications and the exploration of the potential added value of primary care data in the identification and surveillance of congenital anomalies; identifying outcomes in terms of mortality, hospitalization in childhood and use of primary care services by babies affected by specific congenital anomalies; and exploring the underlying causes of international variations in infant and child mortality rates associated with congenital anomalies.   

*Examples of anomalies include: cleft lip and palate, Down’s syndrome, congenital heart defects, such as a ‘hole in the heart’, limb defects and absent limbs.

Research experience, research methods and skills training

The studentship is open to the development of a DPhil project which might focus on different aspects concerning congenital anomalies which are outlined in brief above (but could be extended) and therefore can potentially be guided by the specific interests of the candidate.

Each will need to involve the linkage of CAROBB data (and could potentially include data from other regional congenital anomalies registers) with routine data sources which might include mortality data, hospital episode statistics (HES), primary care data and other relevant sources of national data as they come on-stream, for example the national maternity and children’s data sets.

Each of the proposed projects will require review of the existing literature which would be anticipated to form a structured review using systematic review methods. Data handling will be highly analytical in nature and will provide experience of dealing with a moderate number of subjects potentially linked to extensive amounts of data thus giving experience of handling and cleaning a complex record-linked dataset. Standard analytical methods such as linear and logistic regression, repeated measures and survival analysis are likely to be used. The specific training needed will depend upon the prior experience of the candidate and their existing skills. 

Prospective candidates

This project would suit someone with an interest in child health who wants to conduct quantitative research and is planning a career in the field of epidemiology.