Abstract

This work aimed to classify the elderly according to fall risk factors and to identify the characteristics of the latent classes. Falls mainly occur due to combinations of various risk factors, and each older adult has a different combination of risk factors. This was a secondary data analysis using data from the 2017 National Survey of Older Persons conducted by the Korean Ministry of Health and Welfare. Latent class analysis and multiple logistic regression were performed using data from 1556 older adults who experienced at least one fall during 1 year (1 January 2016 to 31 December 2016). Indicator variables included eight fall risk factors. A 3-class solution was selected according toacceptable goodness of fit. The 'healthy falls risk class' included over half of the cohort, and the comprised older adults did not show typical health problems. The 'complex falls risk class' included older people with physical and mental problems, and the 'musculoskeletal falls risk class' included older people with osteoarthritis and back pain. The results identified combinations of fall risk factors and characteristics among community-dwelling older adults that may contribute to the planning of effective fall prevention programmes.

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