Approved research Skip to navigation Skip to main content Skip to footer Menu Search Search Researcher log in Enable your research Register Apply for access Manage your project Costs About our data Approved research Publications Research Analysis Platform Researcher log in Participant log in Explore your participation Stay involved Contribute further Understanding genetics Following your health Basis of your participation Imaging study updates Participant log in Contact us Learn more about UK Biobank About us Governance Our impact News COVID-19 hub Scientific Conference 2022 Contact us Careers Contact us Search Search Search Approved research Register Apply for access Manage your project Costs About our data Approved research Publications Research Analysis Platform Understanding the biological, lifestyle and environmental risks and outcomes for multimorbidity in psychiatric disorders Principal Investigator: Dr Claire Niedzwiedz Approved Research ID: 41686 Approval date: July 24th 2018 University of Glasgow Lay summary People with mental health disorders such as depression and anxiety have a higher chance of getting a physical health condition such as heart disease. This is a significant health inequality and contributes to the shortened life expectancy among people with mental health disorders. The aim of this research project is to add to our understanding of the things that increase people's chance of developing different health conditions (e.g. dementia and cancer) if they have experienced a mental health disorder. The research will use novel techniques derived from computer science (e.g. machine learning) to uncover whether they can help us better understand why people develop multimorbidity (two or more health conditions experienced by one person) and what health conditions increase the chances of being hospitalised and dying. Multimorbidity is a growing public health concern and places significant pressure on the health service. Better understanding of multimorbidity is required to enable us to better prevent the development of multiple health conditions and also develop more effective treatments. The research will make use of methods from different academic disciplines. Machine learning is a set of tools that can use the vast amounts of information now available to researchers to learn from patterns in the data and help us predict who might develop multimorbidity and what might happen to them afterwards. The application of machine learning to better understand public health and, in particular, multimorbidity is novel and has the potential to identify new factors that heighten people's risk of developing certain health conditions. We will then investigate whether or not these factors are a potential true cause of particular illnesses. The research will take place over the course of the next three years and will make a significant contribution to our understanding of multimorbidity which can lead to the development of new treatments and prevention efforts. View our activity on Twitter View our activity on YouTube View our activity on LinkedIn Enable your research Register Apply for access Manage your project About our data Approved research Publications Explore your participation Contribute further Stay involved Understanding genetics Following your health Basis of your participation Learn more about UK Biobank About us Governance Our impact News COVID-19 latest results Contact us Careers Privacy Policy Cookie Policy Terms and Conditions Accessibility statement Call the Participant Resource Centre: 0800 0276 276 Email: ukbiobank@ukbiobank.ac.uk © UK Biobank Limited 2022 | Registered in England and Wales with company number 4978912. Registered as a charity in England and Wales (number 1101332) and in Scotland (number SC039230). Registered office Units 1-2 Spectrum Way, Stockport, Cheshire, SK3 0SA.