Life Events and Population Sources Division:
Health Gaps by Socioeconomic Position
Chris White
November 2014
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
Background
• 2001 census analysis showed:
Inverse relationship between SAH and socioeconomic disadvantage
Higher managers\profs
82% 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
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
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
NS-SEC Analytic Classes
NS-SEC distribution by gender
Pictorial representation of relative population sizes of each class
Wales’ health gap by NS-SEC:
Comparison with England
Wales’ health gap by NS-SEC
Comparison with English Regions (men)
Wales’ health gap by NS-SEC
Comparison with English Regions (women)
Welsh Unitary Authorities ranked by SII
MEN
WOMEN
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
Info graphics produced for release
Digital map: Health Gap by UA (Men)
Digital map: Health Gap by UA (Women)
Key Findings
•
•
•
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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