Loneliness affects over 1 million older people in the UK, with very high associated health costs. Reducing loneliness among older people can result in fewer visits to the doctors, lower use of medication, fewer days in hospital and fewer admissions to nursing homes. The new data from Age UK helps focus resources to those areas known to have a higher prevalence of loneliness.
This blog is copied from the Community Insight blog which you can access here.
The exciting thing about this prevalence of loneliness indicator is that it shows how a well designed dataset can be used to better target local services. Here we explore what this means for organisations working with older people, and practical ways you can use the data to support your work.
The new dataset on the prevalence of loneliness recently published by Age UK captured the attention of OCSI. Not only because it provides insight on an important social issue at a local level, but also because of the way that the data was constructed (see info box for the tech details, data geeks!). Over the years we have worked a lot with modelling data to produce estimates at small area level, and have seen how using this kind of data can support intelligent and informed service planning decisions. The prevalence of loneliness indicator is the first time that small area predictions regarding loneliness have been made at a national scale in UK. This shows how a well designed dataset can help us to move beyond straight description to be able to estimate more useful statistics using modelling techniques. This data can be used as a tool for evidence based decisions, focusing resources to those areas known to have a higher prevalence of loneliness. Loneliness affects over 1 million older people in the UK and research suggests that prevalence of loneliness in England is far higher than in other developed countries (Scharf and de Jong Gierveld, 2008). The health impacts associated with loneliness are staggering and research shows that low cost approaches to addressing loneliness among older people can result in fewer visits to the doctors, lower use of medication, fewer days in hospital and fewer admissions to nursing homes. Access to data at small area level provides opportunities for local government and community organisations to better understand their local communities and target their resources more effectively and efficiently.
Targeting services for older people
One way in which this data can be used, is to identify and address gaps in services for older people in a local area. Social activities such as day centres, lunch clubs, exercise clubs and creative activities are effective approaches to combating loneliness in older people. Through using the prevalence of loneliness data, organisations can compare the locations of these activities to areas with high prevalence of loneliness, to ensure that residents are able to access services in their local area. The Friends In Actionteam in Wirral have done exactly this and have been able to identify local hotspots and set up a regular meeting place venue in this area. There are wide ranging applications for using this data for more effective targeting of resources. It can be a useful tool for local government communications teams, for example to support with targeting befriending campaigns to the areas most in need, or used by the fire service to identify potentially vulnerable individuals or high risk areas for fires.
Engaging with the issue of loneliness across local partners
Data and the stories that emerge from data can be used as a starting point for cross-partner communication about local issues. For areas where it has proved challenging to keep older people wellbeing high on the agenda, this data can be used to bring partner organisations together to discuss the issues surrounding loneliness in a local area. In Rotherham, the Age UK data has helped to raise awareness of loneliness as a social issue. It has provided a robust evidence base to remind partners of the impacts of loneliness, initiated conversations and engaged individuals and organisations in taking action to tackle loneliness in later life.
Shaping environments to be more inclusive of older people
The loneliness data also has useful implications for transport and urban planning, as these factors have an impact on older people’s ability and willingness to participate socially. Ensuring that accessibility challenges are addressed in areas with a high prevalence of loneliness could help to remove some barriers older people face. The Department for Communities and Local Government (DCLG) 2008 report on Lifetime Neighbourhoods, highlights small changes to neighbourhoods that are needed to ensure communities are fit for an ageing population. The report suggests that the design of neighbourhoods and neighbourhood services can help to prevent social isolation of old people. Although loneliness and isolation are not one and the same, the prevalence of loneliness indicator could be used to prioritise areas and resources to improve communities for older people – such as repairing pavements, ensuring public toilets are open and that anti-social behavior is tackled.
Accessing the data
So, how can you get your hands on this data?
Raw data: The raw data is available through ONS and is the dataset named CT0467_2011 Census – Log odds of loneliness for those aged 65 and over – Local Authorities to Output Areas England and Wales
Age UK heatmaps: Age UK have produced freely available heat maps that show the risk of loneliness at neighbourhood level within a local authority as well as supplying some handy FAQs.
Community Insight: Community Insight is OCSI’s & HACT’s community mapping and reporting tool for the social housing sector. It provides lots of ways to easily map, compare and report on the prevalence of loneliness data (and more than 700 other datasets!). On top of that, you can view data aggregated to any area that you define yourself, by simply drawing an area on a map.
Technical details on the data
The prevalence of loneliness indicator published by Age UK uses data from the English Longitudinal Study of Ageing (ELSA) survey, to identify predictors of loneliness in older age. The results from this modelling were applied to data from Census 2011 to predict the prevalence of loneliness across small area geographies such as Output Areas (OAs), Super Output Areas (LSOAs and MSOAs) and local authorities. Some of the key findings were:
- Household size was found to be inversely related with prevalence of loneliness, with those living alone most likely to feel lonely
- Owning a house outright or renting are both associated with lower probabilities of feeling lonely, compared to those paying a mortgage on a property
- Those reporting worse health are more likely to feel lonely.
- Age, pet ownership, level of income or gender were not found to be significant predictors of loneliness
- Similarly, there was no significant association between loneliness and the rurality or deprivation level of an area.
To read more on the methodology, take a look at the full paper by Professor José Iparraguirre, Chief Economist at Age UK.