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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Application of health concern and activity model on cognition in the elderly
Hyun-Chung Kim1, Kang Soo Lee, Hae-Kwan Cheong
1Department of Psychiatry, National Medical Center, Euljiro 6-ga 18-79, Jung-gu, Seoul 100-799, Republic of Korea.
Abstract:
The aim of this study was to examine the effects of physical, mental, social activity, and health concern on cognition in the elderly by means of the health concern and activity (HCA) model. Data were obtained from 3157 subjects aged 60 years and above. The subjects were divided into four groups according to the HCA model. Cognitive function was assessed by the Korean version of the mini-mental state examination (K-MMSE). A cross-sectional, factorial design was used in which the K-MMSE score was the dependent variable, with physical, mental, and social activity as one factor and health concern as the other. Analysis of covariance revealed significant differences in the K-MMSE score between all four groups after adjusting for age, sex, education, current smoking, and alcohol consumption for all subjects. The results suggest that having health concerns as well as physical, mental, or social activity is associated with cognitive function in the elderly.
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