Home » Research Review 2020-21 » Research Review: Helping people live well in later life

Helping people live well
in later life

The Office for National Statistics predicts that, by 2030, one in five people in the UK will be aged 65 or over. According to Age UK, many of these people will be living with unmet needs in care and support, poverty, poor housing, loneliness and isolation. 

Researchers from the CDRC are working across projects which aim to enhance access to services and social contact, and increase wellbeing for those in later life. 

Helping policy makers assess the long-term impact of their decisions on the future elderly

The phenomena of population ageing are being seen across all nations of the world, regardless of economic income. There are many knock-on effects, particularly in the management of the healthcare and welfare systems, as well as wider impacts on the economy as a whole. 

Therefore, tools to help policy makers assess the long-term impact of their decisions on the future elderly are increasingly important. CDRC researchers, Dr Nik Lomax and Luke Archer, are working on a collaboration with the University of California Schaeffer Centre to develop an English version of the Future Elderly model (FEM).   

The FEM is a dynamic microsimulation model which simulates demographic change, ageing, disability and mortality, and provides a framework for policy analysis and the assessment of future healthcare need.  

The English FEM is built on longitudinal survey data from the English Longitudinal Study of Ageing and provides insight into how a range of risk factors (e.g. smoking, drinking, exercise, BMI) impact on health outcomes (e.g. cancer, diabetes, lung disease) and on mortality. 

Research is focused on three different scenarios based on (1) a reduction in individual BMI, (2) a reduction in smoking, and (3) a reduction in prevalence of heart disease. All three scenarios are hypothetical and we compare baseline outcomes with interventions which bring about improvements in outcomes. Initial results are promising and demonstrate the utility of the model. A reduction in BMI for obese people in the cohort brings about a reduction in prevalence of diabetes in the future. Stopping people smoking brings about a dramatic reduction in lung disease. For heart disease, reducing prevalence in the model results in increased life expectancy. 

The team have a forthcoming publication in the International Journal of Microsimulation which will provide details of the model and collaboration, and are currently using the FEM to quantify the potential impact of interventions with key risk factors such as drinking and diet. 

Classifying consumer vulnerability in the UK 

Some consumers are more vulnerable to marketing practices due to their personal demographic characteristics such as age, health or household arrangements. While consumer vulnerability has been discussed at length in academic literature and regulatory guidelines, there has not been a comprehensive geographical assessment of consumer vulnerability in the UK. This project, led by Dr Nik Lomax and Dr Stephen Clark, utilised data from the CDRC to create a geodemographic classification of consumer vulnerability at output area level. 
Using 2011 Census outputs, six clusters were identified, each showing distinct characteristics related to consumer vulnerability: 
– Prosperous Professionals 
– Well Established 
– Students and Young Professionals 
– On a Budget 
– Vulnerable Communities 
– Vulnerable Pensioners 
Additional information about these clusters was added using data from commercial partner REaD Group. These cluster results were presented on an interactive map (link below), showing cluster membership of each output area. By assessing the risk of consumer vulnerability at a fine spatial scale, policy makers can identify where practices and policy may need to be adapted to avoid exploiting vulnerable individuals living in these areas, and for identifying areas where consumers may benefit the most from services such as the Telephone Preference Service. The framework developed can also be applied to new data sources to answer questions relating to consumer characteristics at varying geographical scales. 
In February 2021, this research was used to respond to the Competition and Markets Authority’s (CMA) call for information on ‘Algorithms, competition and consumer harm’. It will inform and enhance the CMA’s analysing algorithms programme by helping to define consumer vulnerability with important geospatial modelling.