Describing socio-economic variation in life expectancy according to an individual's education, occupation and wage in England and Wales: An analysis of the ONS Longitudinal Study. (June 2021)

• Record Type: Journal Article
• Authors: Ingleby, Fiona C.; Woods, Laura M.; Atherton, Iain M.; Baker, Matthew; Elliss-Brookes, Lucy; Belot, Aurélien
• Is Part Of: SSM - population health. Volume 14(2021)
• Publication Date: 2021-06
• Subjects: Life expectancy -- Mortality -- Socio-economic status -- Income -- Educational status -- Occupational groups -- Census data; Social medicine -- Periodicals; Medical anthropology -- Periodicals; Public health -- Periodicals; Psychology -- Periodicals; Medicine -- Periodicals; 362.105
• DOI: 10.1016/j.ssmph.2021.100815
• Languages: English
• ISSNs: 2352-8273

Abstract

Abstract: People who live in more deprived areas have poorer health outcomes, and this inequality is a major driver of health and social policy. Many interventions targeting these disparities implicitly assume that poorer health is predominantly associated with area-level factors, and that these inequalities are the same for men and women. However, health differentials due to individual socio-economic status (SES) of men and women are less well documented. We used census data linked to the ONS Longitudinal Study to derive individual-level SES in terms of occupation, education and estimated wage, and examined differences in adult mortality and life expectancy. We modelled age-, sex- and SES-specific mortality using Poisson regression, and summarised mortality differences using life expectancy at age 20. We compared the results to those calculated using area-level deprivation metrics. Wide inequalities in life expectancy between SES groups were observed, although differences across SES groups were smaller for women than for men. The widest inequalities were found across men's education (7.2-year (95% CI: 3.0–10.1) difference in life expectancy between groups) and wage (7.0-year (95% CI: 3.5–9.8) difference), and women's education (5.4-year (95% CI: 2.2–8.1) difference). Men with no qualifications had the lowest life expectancy of all groups. In terms of the number of years' difference in life expectancy, the inequalities measured here with individual-level data were of a similar magnitude to inequalities identified previously using area-level deprivation metrics. These data show that health inequalities are as strongly related to individual SES as to area-level deprivation, highlighting the complementary usefulness of these different metrics. Indeed, poor outcomes are likely to be a product of both community and individual influences. Current policy which bases health spending decisions on evidence of inequalities between geographical areas may overlook individual-level SES inequalities for those living in affluent areas, as well as missing important sex differences. Highlights: Health policy to reduce inequalities targets individuals, although often based on area-level data. We show wide inequalities in health outcomes using individual-level socio-economic data. Individual-level inequalities are of a similar magnitude to those observed with area-level data. We find important sex differences in inequalities which are undetectable in area-level analyses. Both individual and area-level factors should be considered in policy aimed at reducing inequality.