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    은퇴 노인의 연령군에 따른 노쇠지수 궤적 유형화와 영향요인 및 삶의 만족도 차이 검증: 성장혼합모형(GMM)의 활용 = Classification of Age-Stratified Frailty Index Trajectories in Retired Elderly: Identifying Influencing Factors and Verifying Differences in Life Satisfaction Using Growth Mixture Modeling

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    https://www.riss.kr/link?id=A109958828

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    This study aimed to explore the age-stratified frailty index trajectories among retired elderly, identify factors influencing trajectory classification, and examine differences in life satisfaction across trajectory types. The research utilized data from the Korean Longitudinal Study of Aging, from waves 5 (2014) through 9 (2022). The study sample comprised 3,067 fully retired elderly who were stratified into three age groups: young-old (65-74), old-old (75-84), and oldest-old (85+). Using growth mixture modeling and three-step approach, we identified heterogeneous frailty trajectories across age groups: young-old with 2 patterns (robust, frail progressing); old-old with 4 patterns (robust, pre-frail progressing, frail accelerated, severely frail); and oldest-old with 4 patterns (pre-frail progressing, frail progressing, frail accelerated, severely frail).
    Analysis of influencing factors demonstrated that social networks exhibited consistent protective effects across all age groups, while gender, residential area, alcohol consumption, and smoking showed differential effects by age group. Life satisfaction varied according to frailty levels.
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    This study aimed to explore the age-stratified frailty index trajectories among retired elderly, identify factors influencing trajectory classification, and examine differences in life satisfaction across trajectory types. The research utilized data f...

    This study aimed to explore the age-stratified frailty index trajectories among retired elderly, identify factors influencing trajectory classification, and examine differences in life satisfaction across trajectory types. The research utilized data from the Korean Longitudinal Study of Aging, from waves 5 (2014) through 9 (2022). The study sample comprised 3,067 fully retired elderly who were stratified into three age groups: young-old (65-74), old-old (75-84), and oldest-old (85+). Using growth mixture modeling and three-step approach, we identified heterogeneous frailty trajectories across age groups: young-old with 2 patterns (robust, frail progressing); old-old with 4 patterns (robust, pre-frail progressing, frail accelerated, severely frail); and oldest-old with 4 patterns (pre-frail progressing, frail progressing, frail accelerated, severely frail).
    Analysis of influencing factors demonstrated that social networks exhibited consistent protective effects across all age groups, while gender, residential area, alcohol consumption, and smoking showed differential effects by age group. Life satisfaction varied according to frailty levels.

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