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Developing a Multidisciplinary Ecosystem to study Lifecourse Determinants of Complex Mid-life Multimorbidity using Artificial Intelligence (MELD)

Chief Investigator: Dr Simon Fraser – University of Southampton

Project Team Members: Dr Nisreen Alwan – Associate Professor in Public Health, School of Primary Care, Population Sciences and Medical Education, University of Southampton, Professor Michael Boniface – Director of the University of Southampton IT Innovation Centre and Web Science Institute, Professor Ben MacArthur – Mathematical Sciences University of Southampton, Professor Rebecca Hoyle – Mathematical Sciences University of Southampton, Dr Sarah Crozier – Associate Professor of Statistical Epidemiology, MRC Lifecourse Epidemiology Unit, Faculty of Medicine, University of Southampton, Mr William Ware – Patient and Public Involvement Contributor, Mr James McMahon – Patient and Public Involvement Contributor, Dr Emilia Holland – Public Health Specialty Registrar, School of Primary Care, Population Sciences and Medical Education, Faculty of Medicine, University of Southampton, Dr Zlatko Zlatev – Senior Enterprise Fellow, Electronics & Computer Science, University of Southampton


As with many countries we are facing challenges related to the growing number of people living with multiple long-term health conditions like diabetes, heart disease or dementia. All the way through peoples’ lives many things influence the chances of developing such conditions.

This includes some things that are hard to research - broader issues throughout life such as the environment people grew up in, their education, work, and so on. Sadly, people from more socially and economically disadvantaged backgrounds are more likely to develop multiple conditions at an earlier age. There is also evidence that the order of developing conditions varies considerably and influences what then happens to people. This makes understanding these broader issues and how they affect that order vital to inform when and how we should intervene to prevent conditions developing.

To achieve this, we need to study large numbers of people over their whole lifetime, but such datasets do not exist. Very large health datasets collected from NHS GPs are helpful but haven’t been running long enough to track from birth to later life. They include lots of information on long term conditions but not much about broader issues.

In our Development Award (called ‘MELD’) we had access to one such dataset of about 700,000 people, which we used to identify health conditions. We also accessed data from the ‘1970 British Cohort Study’ – a long-running research study called a ‘birth cohort’


Early-onset burdensome multimorbidity: an exploratory analysis of sentinel conditions, condition accrual sequence and duration of three long-term conditions using the 1970 British Cohort Study

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