Geographical variations in health outcomes in England highlight the need for advanced analytics

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"Recent analysis by our team and the Institute for Public Policy Research (IPPR) revealed strong links between health and a vast array of socio-economic factors such as employment, education and the economy. Longstanding inequalities in health outcomes and in the social determinants of health have also been thrown into sharp relief by the pandemic. The future of the nation’s health will require advanced analytics to facilitate more informed decision making."

There are stark inequalities in health within England

A healthy population is an asset to a nation and its economy. But population health is not distributed evenly in England, and deprived areas tend to have worse overall health than less-deprived areas. The Office for National Statistics Health Index (beta version), launched in 2020, revealed large disparities across numerous indicators of health status, including modifiable lifestyle and clinical risk factors, and the social determinants of health, such as education and employment.

The Chief Medical Officer’s 2021 annual report focused on health disparities between coastal communities and inland cities and towns. Possible drivers for this include higher levels of deprivation and unemployment in coastal towns, along with less diversification in the local economy and lower educational attainment.

Health Index


Chief Medical Officer’s 2021 annual report


Health and socio-economic profiles are inextricably linked

Our recent research with IPPR investigated how levels of health were associated with wealth, education and welfare. We also reviewed whether better or worse outcomes across these domains were geographically clustered. We identified significant inequalities in all indicators, including life expectancy, educational attainment and disposable income levels. Worryingly, the regional disparity in many of these indicators had worsened over the five years preceding the pandemic.

By grouping areas with similar socio-economic profiles, four main clusters were identified:

Cluster 1

Northern cities and surrounding areas, Midland cities, coastal cities

Cluster 2

Rural and coastal rural areas

Cluster 3

Inner-city London boroughs, Bristol, Brighton

Cluster 4

The home counties and wealthier London boroughs

We found that areas and cities in clusters 1 and 2 had significantly worse levels of health...

...along with lower levels of several key socio-economic variables, than those in cluster 4. For example, places in cluster 1 generally had the lowest life expectancy, with lower levels of educational attainment, higher unemployment and lower household income than those in cluster 4, which had the highest life expectancy. This suggests the potential for an ongoing cycle of poor health preventing access to work and education affecting the economy of the area which then may drive health down further. If life expectancy in all clusters improved to match that of cluster 4, the overall life expectancy in England would increase by 2 years.

The combination of Covid-19 and looming public health crises related to living with multiple long-term conditions, obesity, climate change and anti-microbial resistance, means that traditional actuarial projections of pension scheme mortality based on historical trends are no longer sufficient. Additionally, tailored health analytics will be needed to understand how a variety of factors may affect the health trajectories of scheme members.

What does the future of our health look like?

Whether the Covid-19 pandemic should be treated as an outlier, a shift or the start of a new normal in terms of its health and mortality impact is still hotly debated. Directly, the pandemic exacerbated many types of existing inequalities, which may result in worse health and mortality rates later in life. Indirectly, the pandemic could also result in worsening health and mortality due to behavioural changes and pressures on health systems. People may delay seeking medical care, leading to late or ineffective treatment, or not try to access care at all.

Additionally, there are over 5.7 million patients on NHS elective waiting lists (as at October 2021), up from 4.2 million at the beginning of the pandemic. As with other impacts of the pandemic, the number of people awaiting treatment varies geographically and by speciality. For instance, in recent months there have been more than ten times as many patients awaiting treatment under the Hampshire, Southampton and Isle of Wight Clinical Commissioning Groups (CCG) compared to West Lancashire CCG. Areas with the largest waiting lists will have more residents living in poorer health for longer, possibly resulting in higher mortality rates in those areas.

Conversely, the pandemic also accelerated medical research and the roll-out of therapeutics. This, along with the increased concern around the nation’s health post-Covid-19, may prompt greater efforts to tackle inequalities, such as through the government’s levelling up agenda.

It is too early to determine what the long-term impact will be on the nation’s health. However, one certainty is that the variability in health and illness patterns within the population and in the health system’s capability to treat patients is increasing. Advanced analytical approaches can help to evaluate the impact of socio-economic factors on later life health, and to draw out actionable insights to inform decision makers across pensions, healthcare and social care.

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