The EQUIPOL Research Group brings together expertise in economics, epidemiology, population-level informatics and ethics across a range of projects that develop and apply methods for analysing the equity impacts of policies.

Core projects

Modelling the long-term outcomes of childhood policies using the best available scientific knowledge and data

The project aims to build a model of life course outcomes that simulates the long-run outcomes of heterogeneous childhood policy options, allowing economic appraisal, targeting analysis and distributional analysis of which kinds of investments are most worthwhile in what circumstances. It will initially model life course outcomes for a single birth cohort in England, focusing on the most important causal pathways linking family circumstances at birth, skills and human capital formation in childhood and adolescence, and economic, social and health outcomes in adulthood.

LifeSim project materials

Equipol lead – Prof Richard Cookson

Health Equity Indicators

The project will apply previously developed ‘equity indicators’ for monitoring local NHS equity performance to measure the equity impact of new models of care across the NHS. Over the next few years the NHS will be an exceptionally rich laboratory for policy learning, as local NHS areas respond to financial pressures by experimenting with diverse new models of care. The project will exploit this experimentation in a series of natural experiments to improve our understanding of the effectiveness of local NHS commissioning organizations in reducing health inequalities, and provide information about the health equity impacts of alternative delivery models. It will also explore how this equity-focused approach to performance monitoring and evaluation can be applied to other organizations (e.g. hospitals), other countries (e.g. Canada and the US) and other policy sectors (e.g. local government and education).

Equipol lead – Prof Richard Cookson

Developing Diabetes Interventions for People with Severe Mental Illness

The project explores the causes of variation in diabetes outcomes for people with severe mental illness (SMI), and will test self-management programmes for people with co-morbid SMI and diabetes. People with SMI have poorer physical health and a lower life expectancy than the general population, often dying of preventable physical illnesses. Diabetes contributes significantly to this health inequality; it is three times more prevalent in people with SMI and is associated with more severe illness and poorer health outcomes. As diabetes prevalence in the general population increases, the difference in prevalence between people with and without SMI is likely to widen. This project will first identify the determinants of diabetes and explore variation in diabetes outcomes for people with SMI. It will then develop and evaluate a tailored diabetes self-management intervention for people with severe mental illness, and explore how this approach can be adapted for other long-term conditions.

Equipol lead – Prof Tim Doran

Socio-economic Impact of Policy Instruments for Health Research Dissemination

This project assesses the impact of policy instruments that translate research on quality and equity of care into practice. Health research produces crucial knowledge for enhancing a number of personal and societal outcomes, for example reducing morbidity and mortality, and sustaining labour market attachment. Effective dissemination and adoption of research-based practice is an essential part of the research process. This project focuses on the impact of policy instruments that are guided by health and medical research, or that support the translation of research into practice.

Equipol lead – Prof Tim Doran

Developing and Applying Methods for Longitudinal Spatial Analysis of the Social Determinants of Health

This project develops and applies novel methods of spatial analysis to describe longitudinal patterns of health and its social determinants. Socio-economic deprivation is a key determinant for health, but little is known about its spatial clustering or persistence across time. This project will use multiple administrative datasets at a low geographical level in England – including chronic condition prevalence and management data, funding data for primary care practices, and small area deprivation data – to investigate geographical variation and spatial clustering of health and its social determinants.

Equipol lead – Prof Evan Kontopantelis