ArticleBMC geriatrics2024
Latent class of multidimensional dependency in community-dwelling older adults: evidence from the longitudinal ageing study in India.
Article in BMC geriatrics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed, 4 citations in OpenAlex.
- How to promote healthy ageing among disabled older adults: from a group difference perspective and function-specific pathway models.International journal for equity in health · 2026Article
- Applications of Artificial Intelligence Technologies in Nursing for Noncommunicable Chronic Diseases: A Scoping Review.Journal of nursing management · 2026Article
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2 authors at 2 institutions in 2 countries.
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Abstract
backgroundExisting studies have used ADL and IADL separately as measures of dependency. However, dependency is a heterogeneous and complex issue, and the dependency of each older adult is a synergistic combination of several functional activities. In this study, we assess the pattern of multidimensional dependency of older adults based on ADL, IADL, visual impairment, difficulty in climbing a flight of stairs, pushing or pulling objects, depressive symptoms, cognitive impairment, marital status, and economic distress. It is important to classify the dependency status of older adults because this will be key to evaluating the needs for care, and plan services that effectively cater for the needs of the older adults. The classification into different latent classes means that older adults within each class have the same needs of dependency but different needs between the latent classes. Our objective is to identify patterns of multidimensional dependency in older adults.
methodsData from the Longitudinal Ageing Study in India (LASI) Wave-1, was used, the analytical sample consisted of 32,827 individuals of age 45 years and above. LCA was used to identify the multidimensional dependency class. LCA was conducted in R statistical package, using the poLCA package. The optimal number of classes was selected based on the comparison of model fit statistics. Independent variables were incorporated to explore the association between these variables and the latent class.
resultsBased on nine indicator variables, three latent classes were identified: "Active Older adults", "Moderately independent" and "Psychological and physically impaired". The "Active older adults" profile is comprised of older adults who have a very low probability of needing help for any ADL, IADL and other activities. The "Moderately independent" class were characterized as those older adults who were visually impaired but less likely to need help for IADL activities. The "Psychological and physically impaired", the smallest of all classes, comprised of older adults with poor dependency status.
conclusionsIn this study, we found that the dependency status of older adults which is based on several domains of functional activity has been classified into three distinct classes. These three classes have distinct physical, psychological, economic, and socio-demographic characteristics in terms of activities in which help is required.
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