Southampton researchers will lead a new project to help prevent people from developing multiple, burdensome, long-term conditions at an early age.
Increasing numbers of people are living with long-term conditions. These include diabetes, heart disease, depression and dementia. Having many of these at the same time is known as multimorbidity.
Identifying risk factors
Various factors influence the risk of developing these conditions. These include both biological factors and behaviours. Broader life experiences, such as education and work, are also linked to this risk.
People from disadvantaged backgrounds and some ethnic minorities may be more likely to develop multimorbidity at a younger age.
The researchers aim to understand what factors shape the development of early, burdensome multimorbidity. ‘Burdensome’ will be defined as part of the project. They define ‘early’ as developing multiple conditions before age 65.
Using artificial intelligence
The study will be led by Dr Simon Fraser and Dr Nisreen Alwan from the University of Southampton. It will use artificial intelligence (AI) and statistical methods to analyse information from two large electronic health record datasets and three birth cohort studies.
Birth cohorts have followed people who were all born in the same week of a particular year (e.g. 1970) throughout their lives.
The researchers will investigate the order in which people develop conditions. They will also study how they group together to become burdensome.
The NIHR will fund the £2.2 million study. It will bring together researchers from five UK universities and Southampton City Council, with patient and public involvement expertise from colleagues in University Hospital Southampton. They will come from public health, primary care, maths and computer science. The research team will work with public and patient contributors to ensure the research is timely and relevant.
The study forms part of the NIHR AIM programme.
Dr Fraser, Associate Professor of Public Health, said:
“Multiple long-term condition multimorbidity is more likely to develop at a younger age among people from more socioeconomically deprived backgrounds and certain ethnicities.
"Using AI techniques will allow us to study the whole lifecourse and identify key targets and timepoints for public health preventive action.
"I am delighted to be working with colleagues in maths, statistics, computer science, and policy across a number of institutions along with members of the public to address this pressing public health issue.”
Dr Alwan, Associate Professor in Public Health, said:
“This is a great opportunity to develop a co-produced approach, with the public and colleagues from various disciplines, that aims to investigate the early determinants of multimorbidity and examine how lifecourse health inequalities are shaped, and thus how to tackle them.”