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 StatisticsSocioeconomic 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-SECComparison with English Regions (men)

Wales’ health gap by NS-SECComparison 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

• 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