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Patterns of instrumental activities of daily living and association with predictors among community-dwelling older women: A latent class analysis

BACKGROUND: The purpose of this study was to classify patterns of instrumental activities of daily living (IADL) among community-dwelling older women, to examine difference in characteristics among the classes, and to explore predictors of class membership. METHODS: This study was a secondary analys...

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Detalles Bibliográficos
Autores principales: Park, Jeongok, Lee, Young Joo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5520369/
https://www.ncbi.nlm.nih.gov/pubmed/28732473
http://dx.doi.org/10.1186/s12877-017-0557-6
Descripción
Sumario:BACKGROUND: The purpose of this study was to classify patterns of instrumental activities of daily living (IADL) among community-dwelling older women, to examine difference in characteristics among the classes, and to explore predictors of class membership. METHODS: This study was a secondary analysis of nationwide data from the 2014 Actual Living Condition of the Elderly and Welfare Need Survey. A total of 10,451 individuals aged 65 years or older were interviewed for the 2014 dataset, but we only selected the female participants (n = 6095) for this study. For statistical analyses, latent class analysis was applied to identify different latent classes of IADL and then the effects of predictors on IADL patterns were analyzed by using multinomial logistic regression. RESULTS: The 5-class model was the best fit for the data. The size of class 1was the biggest (n = 5093, 83.6%), followed by class 5 (n = 401, 6.6%), class 3 (n = 308, 5.1%), class 2 (n = 181, 3.0%), and class 4 (n = 113, 1.8%). The largest class had total independency on all items of IADL. In the multinomial regression, members in the classes 2, 3, 4 and 5 were significantly more likely to have older age and decreased cognitive status compared with the class of total independency on all items of IADL (class1). CONCLUSIONS: The predictors of the classes identified in this study can be used for tailored and targeted interventions to increased old adults’ independency on IADL.