New insight by data expert CACI reveals vast differences in life expectancy for over-65s across many neighbouring UK postcodes. The new CACI ‘Longevity Acorn’ dataset shows that some people might only expect to live to 80, while people in close-by postcodes are predicted to lead lives that are around 20% longer (living up to the age of 95).
CACI’s data reports life expectancy in 16 different categories for British men and women, using new location insight at postcode level for a more precise prediction. It finds that the average life expectancy for a person at 65 in the UK is 85 years and 7 months (85.6 years), with women expected to live for 86 years and 10 months (86.9 years) and men for 84 years and 3 months (84.3 years). While typical statistical sources on mortality, such as the ONS, only analyse variations in life expectancy at national, country or local authority level in the UK, CACI’s analysis is based on over 1 million records and 3 years’ worth of data, highlighting the value of analysing life expectancy on a more granular level. Longevity Acorn’s categories range from ‘16’ (89.9 years on average) to ‘1’ (average of 81.2 years).
The data uncovers new pockets of category ‘16’ postcodes up and down the country, which have not been identified before.
An example of this is local authority Allerdale (Cumbria), which has an overall life expectancy of around 85.2 years (category 8). However, in postcodes like CA12 4AT, which is located within the Allerdale area, residents are expected to live significantly longer than their neighbours, being predicted to reach the age of 89.9 years (category 16). Another example is local authority East Dunbartonshire in Scotland where people on average reach 85.9 years (category 10), but single postcodes within the East Dunbartonshire area, such as G61 3LR, are again in the highest category ‘16’ with 89.9 years.
Further proving the importance of a more analytical and detailed approach, the distribution of predicted mortality in large UK cities points to some of the most significant differences in the country. In Inner London, the average life expectancy is 86 years, yet from borough to borough this can vary by almost 20% from as little as 80 years in some parts of Southwark and Lewisham to almost 95 years in areas of Camden and Westminster.
Other UK cities, such as Cardiff, represent the diversity in life expectancy along the same lines as the rest of the UK, with the average population living in a ‘category 7’ postcode and being expected to life to 84.7 years. Cities like Manchester and Glasgow, however, are skewed towards the lower categories of CACI’s Longevity Acorn data set, as a large part of their population lives in ‘category 1 to 4’ postcodes.
MONEY MAKES A DIFFERENCE
In collaboration with risk and pensions consultants Hyman Robertson, CACI has also overlaid the new data findings with its existing Acorn location insight, to complement the information with factors such as income and level of education.
Insurance Edge Note:
Much of this data is very interesting and shows how poverty and poor local environment can affect lifespan. Certain UK postcodes do feature more home owners rather than renters, and the value of those bought-and-paid-for homes can also make a difference to life expectancy.
Then there’s the level of medical services, charities and social care in wealthier areas vs poor ones. Again, this really matters more when you’re aged 65 and over, because quite frankly the NHS begins to place you firmly at the back of the queue once you reach that age. The more assistance older people get from other agencies in that situation, the better.
Money can’t buy you happiness, but it might buy you a better standard of health in your latter years.
Kandyce Tester, Vice President at CACI, commented: “There has been a significant amount of theorising around mortality and life expectancy over the decades. However, many of these models only provide very rough approximations which becomes evident when looking at the data at postcode level. With the UK population ageing, the insurance and pensions sectors are crying out for a more granular and analytical approach to the data they use in their modelling. We are now able to deliver this much–needed additional granularity, which will markedly improve accuracy for organisations that need to base their planning around people’s lives.”