Moon JH. Factors Affecting Activity Limitation in the Elderly: Data Processed from the Korea National Health and Nutrition Examination Survey, 2016.
Osong Public Health Res Perspect 2019;
10:117-122. [PMID:
31263660 PMCID:
PMC6590880 DOI:
10.24171/j.phrp.2019.10.3.02]
[Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
Objectives
The aim of this study was to compare the sociodemographic characteristics, depression, and the health-related quality of life outcome, among the Korean elderly population, with and without activity limitation.
Methods
The data used was drawn from the raw data of the seventh Korea National Health and Nutrition Examination Survey (N = 8,150). There were 1,632 records for individuals aged 65 or older extracted from the seventh Korea National Health and Nutrition Examination Survey database, 199 of those had missing responses (n = 1,433). Differences within the sociodemographic characteristic, the Patient Health Questionnaire-9, and the EuroQol-5 Dimension were analyzed using logistic regression analysis according to the presence or absence of activity limitation.
Results
The prevalence of activity limitation among the elderly individuals surveyed was 19.9%. In the unadjusted regression analysis, the odds ratios of all independent variables (age, gender, education level, type of region, family income, the Patient Health Questionnaire-9, all 5 domains of the EuroQol-5 Dimension) between the elderly individuals with and without activity limitation, were significant. Although, in the adjusted logistic regression analysis, it was observed that the only factors that were significantly associated with activity limitation were the Patient Health Questionnaire-9, EuroQol-5 Dimension, type of region, and family income.
Conclusion
These findings demonstrated that activity limitation in elderly individuals is associated with the sociodemographic characteristics of family income and type of region of residence, as well as depression and the health-related quality of life outcome.
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