An ethnic group specific deprivation index for measuring neighbourhood inequalities in England and Wales

Abstract

The measurement of deprivation for small areas in the UK has provided the basis for the development of policies and targeting of resources aimed at reducing spatial inequalities. Most measures summarise the aggregate level of deprivation across all people in a given area, and no account is taken of differences between people with differing characteristics, such as age, sex or ethnic group. In recognition of the marked inequalities between ethnic groups in the UK, and the distinctive geographies of these inequalities, this paper presents a new ethnic group‐specific neighbourhood deprivation measure—the Ethnic Group Deprivation Index (EGDI). This index, using a custom cross‐tabulated 2021 Census dataset on employment, housing tenure, education and health by ethnic group, reveals the small area geographies of ethnic inequalities that have to date received scant attention, and yet have profound impacts on life chances and well‐being. Drawing on the methodological framework of the widely used English Index of Multiple Deprivation (IMD) and for the same geographies (Lower Layer Super Output Areas), the EGDI measures deprivation for each ethnic group using data from the 2021 Census of England and Wales. The EGDI reveals the complex geographies of ethnic inequality and demonstrates that while one ethnic group in a neighbourhood may have high relative levels of deprivation, another ethnic group in that same neighbourhood may experience very low relative levels. The EGDI explores ethnic inequalities within and between neighbourhoods, complementing and augmenting existing measures by offering an important means of better understanding ethnic inequalities. The EGDI can be used to help shape locally and culturally sensitive policy development and resource allocation.

50-year deprivation trajectories: local area change in England and Wales, 1971-2021

“…For future work, there may be merit in comparing our current outputs with a scheme which excludes the car ownership variable (as in Exeter et al, 2007). Finally, the census itself is a 'gold standard' source providing comparable input variables and geographies (with adjustments, as demonstrated in this paper) and for crosstabulated variables which provide greater insights into the characteristics of deprived populations (e.g., see Lloyd et al, 2023a). However, there may still be geographical biases since respondents in more deprived areas may be less likely to respond to the requirement for their information .…”