Measurement and Analysis of Socioeconomic Inequalities in Health
Our Measurement and Analysis of Socioeconomic Inequalities in Health programme works to improve methods for analysing routinely collected health data and population-based studies. The programme uses novel linkages to social data to improve our understanding of inequalities in health and to improve intervention strategies.
Health inequalities in the UK were highlighted in the Black Report in 1980. Despite moving near the top of the health agenda since then, inequalities have persisted or increased across Western Europe.
Routine data have great potential for health research as a largely untapped resource. While some research groups – including our programme – have considerable experience working with such data, recent developments in the UK have enabled new linkages across health and social data. The ability to link social data makes it possible to study the impact of individual characteristics such as educational attainment or employment status. This provides further opportunities to inform interventions and policies, and to understand their impact on health and health inequalities.
Our focus on existing data sources reflects our funders’ commitment to improve the uses of patient data, and capitalises on the substantial investment made in surveys, cohorts and ‘big data’.
- Alastair Leyland (Workstream leader: Health Inequalities and Linked Data Analysis)
- Mirjam Allik
- Denise Brown
- Esther Curnock
- Geoff Der
- Ruth Dundas (Workstream leader: Health Inequalities and Linked Data Analysis)
- Linsay Gray (Workstream leader: Enhancing Cohort, Survey and Routine Data Sources)
- Michael Green
- Mary-Kate Hannah
- Paul Henery
- Vittal Katikireddi (Workstream leader: Natural Experiments from Observational Data)
- Megan McMinn
- Drew Millard
- Oarabile Molaodi
- Anna Pearce
- Frank Popham (Workstream leader: Natural Experiments from Observational Data & Enhancing Cohort, Survey and Routine Data Sources)
- Emily Tweed
- Welcome Wami
- Elise Whitley