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KMID : 0613620170370020251
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Health Social Welfare Review
2017 Volume.37 No. 2 p.251 ~ p.286
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Identification and Prediction of Patterns of Health Promoting Behaviors among the Elderly
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Kim Soo-Young
Kim Myoung-Il
Chang Su-Jie
Moon Kyung-Joo
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Abstract
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The major purpose of this study is to find out the general types of health promoting behavior among the elderly. Based on these types, we tried to classify latent group patterns. This research would establish an empirical guideline for health promoting behaviors for the elderly. For this, The National Survey on Living Conditions of the Elderly, 2014 was used. This dataset contained total of 10,281 elderly sample selected from nationwide. Latent class analysis (LCA) was used for identifying types of health promoting behaviors. Based on the Latent class analysis, chi-square (�撮� ) test, ANOVA,
and multinomial logistic regression analysis were performed to find out characteristics and determinants in accordance with the extracted types of health promoting behavior. On the results, latent classes of health promoting behavior for the elderly were turned out as four types: non-smoking and abstinence type, negative health behavior and medical service dependent one, positive health behavior and non-exercise one, and active health behavior practitioner. These four types showed different characteristics in social demographic factors, social institutional conditions, and economic factors.
Moreover, characteristics such as gender, age, educational level, subjective evaluation of health status, spouse satisfaction, social participation, utilizing social service, and participating economic activities were playing a key role in predicting the health promoting behavior types. Based on these findings, we discussed academic and practical implications associated with health promoting behavior types. In addition, several feasible intervention strategies were suggested for improving the health of the elderly.
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KEYWORD
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Health Promoting Behavior, Latent Class Analysis (LCA), Elderly, Multinomial Logistic Regression
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