University of Cambridge

Academic Institute

OFHS250150

In the context of this study, fairness (or equity) is defined as a state in which all groups would achieve their best health results, given their genetic background. However, we do not know what is achievable, nor where our limited resources may be best spent to obtain the highest return. Our aims are: 1. To quantify the expected phenotypic variation attributable to genetic variation across diverse groups in the Our Future Health cohort. 2. To compare these genetic expectation benchmarks with observed differences, and identify traits and groups where outcomes differ substantially. 3. To produce clear, usable benchmarks that researchers and policymakers can use to prioritise and allocate interventions to improve health equity. Our main measure is the average difference between genetically expected and observable traits, evaluated for each group and trait. These may then serve as evidence-based targets for fairness in health: large differences suggest modifiable environmental or system causes and point to interventions; small differences suggest biological factors may be more important and may require biologically targeted approaches. In this study we define fairness (equity) as a state in which all groups achieve the best possible health given their genetic backgrounds. Clear targets for what is achievable do not exist, making it difficult to prioritise limited resources. Genetic differences between groups can contribute to differences in certain traits; however, the overall size of these effects across different traits is not well understood. We need evidence-based benchmarks to show where each group could reach optimal health. For example, people of African and South Asian ancestry have about two- to three-fold higher rates of type 2 diabetes than people of European ancestry. These gaps reflect genetic, lifestyle, environmental and social determinants, but the proportion attributable to genetics versus environmental causes is unclear. We will assess the extent to which our future health may be influenced by inherited factors and compare these expectations with the outcomes we observe. If observed outcomes are different than the expectations from genetics, changeable factors (environment, access to care, social drivers) are likely the cause and should be prioritised. If outcomes match genetic expectations, biological factors may partly explain the difference and may need biological approaches. These benchmarks may then guide equitable research and policy priorities.

People from different ancestry and ethnic backgrounds often face very different risks of disease, such as diabetes or heart disease. These gaps in health outcomes place extra strain on patients, families, and the NHS. Genomic medicine, the use of genetic information to improve healthcare, has the potential to transform prevention and treatment, but if introduced without care, it could also risk reinforcing existing disparities. Our study aims to find new evidence to help to reduce this risk. By estimating the variation in peoples’ health that could be due to genetic differences alone, and comparing this with what is observed in real life, we will provide useful benchmarks that show where health disparities may be most responsive to change. This will support the fair allocation of resources and ensure that changes in healthcare are directed towards areas where they are most likely to make a difference. In the coming decade, our findings may help guide prevention and treatment plans that recognise the diversity of people in the UK. Additionally, this work could inform new health screening programmes, medical guidance in the NHS, and public health plans that improve fairness in healthcare for all.

Public Health Research

18/05/2026

17/03/2026

TRE