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.

Aurélien Belot,Lucy Elliss-Brookes,Laura M. Woods,Fiona C. Ingleby,Matthew Baker,Iain M. Atherton

doi:10.1016/j.ssmph.2021.100815

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

In many high-income countries, people who live in socioeconomically deprived localities have higher all-cause mortality than those living in more affluent localities (Bennett et al, 2018; Butler et al, 2010; Rey et al, 2009; Singh & Siahpush, 2002; Woods et al, 2005)
We have recently shown that the concordance between aggregated deprivation metrics at a small-area level and the observed individual socio-economic status (SES) can be relatively low, such that describing small-area pop ulations with only aggregated statistics will tend to overlook significant numbers of deprived individuals who reside outside deprived areas (Ingleby et al, 2020)
Differences across wage quintiles and to some extent across occupational groups were relatively small for women compared to large differences seen across the same groups in men (Fig. 2), whereas the extent of differences in mortality across educational groups were more similar between the sexes

Summary

Introduction

In many high-income countries, people who live in socioeconomically deprived localities have higher all-cause mortality than those living in more affluent localities (Bennett et al, 2018; Butler et al, 2010; Rey et al, 2009; Singh & Siahpush, 2002; Woods et al, 2005). The comprehensive documentation of this trend in the UK has rightly motivated an increased policy focus on reducing inequalities (Marmot et al, 2021) The importance of these inequalities has more recently been elevated within the NHS (National Health Service) long-term plan for 2020–2030 (NHS, 2019); the latest re-imagining of NHS priorities for England. Within this refreshed policy, funding is directly linked to measured socio-economic inequalities, being based upon “a more accurate assessment of health inequalities and unmet need” whilst all major national programmes and local areas have a specific responsibility “to set out specific measurable goals and mechanisms by which they will contribute to narrowing health inequalities over the five and ten years”. There are practical issues that will influence whether health policies target individualised or area-level inequality issues; further research will be especially important given the recent context of an increasing focus on individualised care within the NHS, as well as recent support for the potential to tackle socio-economic inequalities via increased attention to individual circumstances (Moscrop et al, 2020)

Methods

Results

Conclusion