Understanding health inequalities from a spatial perspective
Collaborative research with Greater Manchester Combined Authority and Tameside & Glossop NHS Foundation Trust
Introduction
Life expectancy for male and Income deprivation, England
Spatial planning is about the management of infrastructure, housing, jobs, recreation and the environment, the very same determinants of public health. The interrelation and cumulative impact of different health determinants of the complex human-environment system have caused the prevalence of chronic illness such as obesity, diabetes, depression, and high blood pressure, which often resulted in lower life expectancy and manifested into variegated spatial landscape of health inequalities.
The COVID-19 Marmot Review once again confirmed the tragic mortality outcomes brought by socio-economic inequalities in Britain, which are often spatially concentrated (Zheng and Wong, 2023). Despite the wide acceptance of the salience of health inequalities in urban policies, there is a lack of systematic effort to establish the effect-modifying interrelations of different health determinants, especially from a spatial perspective (Koksal and Wong, 2022).
To explore our interactive maps, please scroll to the end of the StoryMap or click here .
The Spatial Paradox of Growth
Our work with the UK2070 Commission (Wong and Zheng, 2023) shows that while there has been improvement in labour productivity in some northern combined authority areas, these areas also suffer from very high levels of economic inactivity, unemployment, income deprivation, lower life expectancy and poor health outcomes. This spatial paradox is best illustrated by mapping analysis of the growth in the Greater Manchester Combined Authority (GMCA) area. While many areas in GMCA such as Manchester City Council (4.1%) and Salford MBC (5.35%) experienced relatively high growth in labour productivity, as shown in our maps, these areas also have the lowest male life expectancy in the country.
The broken link between growth and health outcomes for local residents
Of different socio-economic variables, deprivation is one of the major determinants of health outcomes. Income Deprivation is associated with 61% (R=-0.78) of the variations in life expectancy for males and 46% (R=-0.68) of the variations in life expectancy for females in England. Particularly, the correlation coefficients between income deprivation and life expectancy for both males and females in Greater Manchester exceed 0.8, indicating a stronger correlation. The right map illustrates the high association between life expectancy at birth for male and income deprivation across different middle super output areas (MSOAs) of GMCA.
Different forms of deprivation and poverty are found with strong correlations with different types of illness and health outcomes.
The map on the right clearly illustrate the association between poverty/deprivation and deaths that are deemed as preventable in GMCA.
The map on the right clearly illustrate the association between the prevalence of child obesity and child poverty across MSOAs of GMCA.
This shows that improvement in local economic growth has been happening in the same space where major social and health challenges located. This means that there is a missing link between economic growth and success to local residents’ livelihood and wellbeing, which in turn affect the health of the local labour market and labour productivity.
Levelling up requires spatial understanding and targeting
There has been increasing policy awareness of the direct and indirect harmful health effects caused by particulate matter such as PM2.5 and PM 10, as well as by other air pollutants such as Benzene and Sulphur Dioxide. In order to tackle the problem, there is a need to have stronger policy targeting in areas across different policy sectors (planning, housing, transport and public health).
The right map shows the spatial distribution of modelled average PM2.5 level across different MSOAs in GMCA in 2021.
The right map shows the spatial distribution of modelled average benzene level across different MSOAs in GMCA in 2021.
The right map shows the spatial distribution of modelled average PM10 level across different MSOAs in GMCA in 2021.
This map displays the spatial distribution of modelled average NO 2 level across different MSOAs in GMCA in 2021.
This one shows the spatial distribution of modelled average NO x level across different MSOAs in GMCA in 2021.
This one shows the spatial distribution of modelled average SO 2 level across different MSOAs in GMCA in 2021.
To explore hot spots of deaths from respiratory diseases, the right map uses local Moran's I statistics to identify spatial clusters suffering from high level of respiratory disease deaths. It is clear that Northern Manchester, parts of Tameside, Bolton and Wigan are the identified high-high clusters.
The right map displays the varied death rates from respiratory diseases in GMCA, overlaid with the average PM 2.5 level. This suggests a moderate correlation between both variables.
The map below show the spatial clusters by using nine variables relating to deaths from respiratory diseases, air quality and deprivation to perform the classification. It is notable that Manchester city centre is a target cluster (in red, cluster 2), with high level of respiratory disease deaths, high level of air pollutants and high deprivation. However, there are other areas with relatively high level of respiratory disease related deaths, but with medium level of air pollutants (in yellow, cluster 3). It is important to find what other contributory factors e.g. housing stock conditions and occupation types of the local residents that may have contributed to the high level of deaths.
Transport accessibility is critical to the mobility of people and goods to support daily living and the function of the economy. The map on the left displays the varied percentage of disabled residents suffering from limitation of their day-to-day activities in Tameside Metropolitan Borough Council, which is overlaid by the bus routes and stops.
The map on the left displays the varied percentage of disabled residents suffering from limitation of their day-to-day activities in Tameside Metropolitan Borough Council, which is overlaid by GMCA’s public transport accessibility level classification.
The pink area in Stalybridge South stands out as an area with high level of disabled residents with limitation in their day-to-day activities but there is a lack of provision of good level of accessibility and bus service.
Boundary spanning, breaking policy silos
Our analysis aims to demonstrate the importance of adopting a spatial perspective of evidence base (Zheng & Wong, 2023) to address challenging problems spanning across different spatial and policy sectoral boundaries (Koksal & Wong, 2023) to provide more nuanced understanding of the interaction of the complex human-environment system.
Web map of health outcomes in Greater Manchester
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ABOUT THE AUTHORS
Professor Cecilia Wong is a Professor in Spatial Planning and Director of the Spatial Policy & Analysis Lab at the University of Manchester.
Dr Helen Zheng is a Lecturer in Planning and Environmental Management at the University of Manchester.
Both Cecilia and Helen are researching spatial inequalities in the UK and working on projects relating to health inequalities.
References:
- Wong, C. and Zheng, W. (2023) UK2070 Commission Go Local: the Socio-economic landscape of combined and local authority areas in England, Spatial Policy & Analysis Lab of the Manchester Urban Institute. https://uk2070.org.uk/wp-content/uploads/2023/03/UK2070_CA_IAA_3March-1.pdf
- Koksal, C. and Wong, C. (2023) Beyond public health, beyond spatial planning: boundary-spanning policy regime of urban health in England, Built Environment, 49 (2): 166-186.
- Zheng, W. and Wong, C. (2023) Variegated spatial landscape of COVID-19 infection in England, Journal of Public Health, 45 (Supp 1): i45-i5
