Labeit, Alexander;
Banerjee, Jay;
Williams, Christopher;
Surinder, Sharma;
Cluley, Victoria;
Pickard, Susan;
Conroy, Simon;
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(2024)
Technical Report: Development of a frailty index using Understanding Society.
Understanding Society: The UK Household Longitudinal Study: London, UK.
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Abstract
A frailty index (FI) is a tool based on surveys to measure the frailty level of individuals at particular points in time (cross-sectionally) and over time (longitudinally). Using population data could help researchers better understand what causes frailty and how it changes over the lifecourse for different people. This working paper outlines how a frailty index has been developed using data from Understanding Society. The FI was constructed using 36 selfreported items across different domains in the dataset, including health conditions, health limitations and disabilities. The FI uses population data from the Great Britain and Northern Ireland, Ethnic Minority Boost and the Immigrant and Ethnic Minority Boost samples. The analysis was restricted to respondents with complete information for all items in a wave. To validate the constructed FI, associations with age and sex were tested. The analysis shows that the FI is a valid measure of frailty in Understanding Society.
Type: | Report |
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Title: | Technical Report: Development of a frailty index using Understanding Society |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.14324/000.rp.10203000 |
Publisher version: | https://www.understandingsociety.ac.uk/documentati... |
Language: | English |
Keywords: | biological ageing, frailty index, measurement tools, older people |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics > Clinical Epidemiology |
URI: | https://discovery.ucl.ac.uk/id/eprint/10203000 |
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