다층 잠재프로파일링을 통한 심리적 건강 상태 분류와 신체 활동 참여 효과 분석 : 국민노후보장패널 자료를 활용하여

Abstract

The purpose of this study is to analyze the classification of psychological health status and participation in physical activity using multi-level latent profile analysis. In order to achieve the purpose, 5,345 data were used from the 7th data of the Korean Retirement and Income Study (KRelS) released by the National Pension Service. It consisted of 19 questions, and the independent variable was participation of physical activity, and the control variables were gender, age, and household income. Using the multi-level latent profile analysis, the results are as follows. As a result of classifying by one psychological method, as a result of classifying by a parametric method, as a result of classifying by the multi-level latent profile analysis for psychological decisions by a parametric method, it is determined as a parametric optimal model. The high-risk group accounted for 10.98% of the total, the risk group had a total of 33.36%, and the general group had a total of 55.66%. Second, as a result of analyzing the causal relationship between physical activity participation and organizational strength, physical activity participants have an increased probability of belonging to high-risk groups.