Completed Public Health & Healthcare Society, Politics & Law

Measuring and Analysing Socioeconomic Inequalities in Health

In plain English

AI plain-English summary

A person's postcode and pay packet still predict how long and how well they will live, and the gap is not closing. This matters because health inequalities—the systematic differences in health between richer and poorer groups—have proven stubbornly resistant to policy. Despite decades of public health efforts, the link between socioeconomic position and health outcomes remains constant or is widening. The research addresses a critical gap: we lack robust methods to measure these inequalities accurately and to identify which interventions actually work. The team is improving analytical techniques for routinely collected health data, surveys, and new linkages between health records and social data. By treating existing data sources—including Scotland's world-class linked health records—as a cost-effective resource, they can analyse natural experiments and test intervention strategies without expensive new trials. If successful, this work will give policymakers sharper tools to spot which inequalities are growing, which interventions reduce them, and where to target resources. The impact is not a new drug or device but better decisions about public spending—decisions that could narrow the health gap between the richest and poorest communities.

View original technical description
The health of individuals varies according to socioeconomic characteristics reflecting, at least in part, different exposures to factors that influence health. Since populations comprise groups of individuals, and these groups tend not to be random, e.g. groups defined by geography or on the basis of occupation, there are differences between the health of different populations. Understanding such health inequalities plays an important part in improving the health of the population. Health inequalities remain constant or are increasing and it is unclear how to reduce them. We are improving methods to analyse routinely collected health data and surveys and using new linkages of health to social data, aiming to improve our understanding of inequalities in health and improve intervention strategies. The programme is organised into three themes: Health inequalities and linked data analysis; Natural experiments from observational data; and Enhancing cohort, survey and routine data sources. Our focus on existing data sources represents a cost-effective means of working, capitalising on substantial investment in surveys and cohorts as well as ‘big data’. We benefit from our location in Scotland with its outstanding systems of linked routine health data, and our research team is recognised internationally for expertise in the analysis of these data and for methodological rigour and innovation.

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Researchers

Alastair Leyland (Principal Investigator)

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Original classification

Intramural

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