1. Life Events and Population Sources Division: Health Gaps by Socioeconomic Position Chris White November 2014

2. Introduction Tackling health inequalities - a high profile policy objective across the UK both for health improvement and pensions Evidence of health inequality by measures of advantage are widespread in the literature (however) Only census data has the depth of detail needed to measure inequality among individuals within areas age, sex, social strata within defined administrative boundaries enables measurement of health gap magnitudes between areas provokes examination of possible explanations for why area differences exist

3. Background 2001 census analysis showed: Inverse relationship between SAH and socioeconomic disadvantage Higher managers\profs82% reported Good/Fairly Good Health Routine occupations 66% reported Good/Fairly Good Health There was no sub-national analysis to assess socioeconomic health gaps between areas No geographic mapping of estimates to visualise differences Objective of this analysis was to explore differences in health gaps at regional and local authority level

4. Classifying to health status categories Self-assessed general health used to measure health The general health question included in the 2011 Census Individual classified in ‘Good Health’ by combining very good\good responses, and in ‘Not Good Health’ by combining fair\bad\very bad responses These subjective measures have their critics; however, they correlate well with harder measures such as mortality

5. National Statistics Socioeconomic Classification (NS-SEC) Measure of advantage was based on Socioeconomic position using the NS-SEC classification  Based on SOC 2010 and employment status  Measures advantage on the basis of employment relations  7 analytic class version used  Self-assessed health gap measured between  class 1 – higher managerial and professional occupations lawyers, architects, medical doctors, chief executives, economists  class 7 – routine occupations bar staff, cleaners, labourers, bus drivers, lorry drivers

6. NS-SEC Analytic Classes

7. NS-SEC distribution by gender Pictorial representation of relative population sizes of each class

8. Wales’ health gap by NS-SEC: Comparison with England

9. Wales’ health gap by NS-SEC Comparison with English Regions (men)

10. Wales’ health gap by NS-SEC Comparison with English Regions (women)

11. Welsh Unitary Authorities ranked by SII MENWOMEN THIRD OF WELSH UA’s PLACED IN THE FIFTH OF E&W LAs WITH LARGEST SIIs LAs WITH HIGH DENSITY URBAN POPULATIONS HAD LARGEST SIIs IN E&W

12. Info graphics produced for release

13. Digital map: Health Gap by UA (Men)

14. Digital map: Health Gap by UA (Women)

15. Key Findings Health gaps were large and widespread throughout England and Wales North-South divide clearly present in the scale of the health gap in Wales The health gap across regions between classes was mostly larger for women Cardiff’s health gap had greater commonality with inner London than any other Welsh UA It is estimated that an additional 1.6 million men and 1.8 million women in England and Wales as a whole would be assessing their health as ‘Good’ if Class 1 rates prevailed across these countries Variability in not good health between areas was greatest among Routine occupations and least among managerial and professional occupations Local authorities with dense urban populations have the widest health gaps and LAs with largely rural populations narrowest