Objectives: Elderly living alone in South Korea report higher rates of psychological distress compared to the population at large. Using a person-centered approach, the aim of the present study was to identify the latent profiles of South Korean elderly living alone based on self-esteem, life satisfaction, and depression. Method: Latent profile analysis (LPA) was conducted based on data of 1545 older age individuals living alone. In addition, we examined significant factors that differentiate the observed profiles using multinomial logistic regression analysis. Results: We identified five profiles: “extremely depressed (n = 44, 2.9%),” “severely depressed (n = 169, 10.9%),” “mildly depressed (n = 529, 34.2%),” “low life satisfaction (n = 128, 8.3%),” and “positive adaptation (n = 675, 43.7%).” In addition, results of multinomial logistic regression analysis indicated that males (OR: 1.69; 95% CI: 1.02–2.81), and elderly with lower income (OR: 0.86; 95% CI: 0.81–0.91), lower level of physical health (OR: 0.43; 95% CI: 0.33–0.57), and lower social relationship satisfaction (OR: 0.25; 95% CI: 0.18–0.35) were more likely to fall in the “low life satisfaction” rather than the “positive adaptation” profile. In addition, being female (OR: 0.48; 95% CI: 0.30–0.79), of older age (OR: 1.04; 95% CI: 1.01–.1.07), and higher income (OR: 1.14; 95% CI: 1.08–1.20) were related to classification in the “mildly depressed” rather than the “low life satisfaction” profile. The “severely depressed” group was differentiated by older age (OR: 1.05; 95% CI: 1.01–1.08), lower level of physical health (OR: 0.49; 95% CI: 0.34–0.71), and lower satisfaction with social relationship (OR: 0.54; 95% CI: 0.38–0.76). Conclusion: The results highlight the need for welfare policies that secure income and physical health in elderly living alone to enhance their quality of life. Furthermore, interventions that aim to maintain social networks are tantamount in order to prevent isolation in the elderly living alone.
Bibliographical noteFunding Information:
This work was supported by the Yonsei University Research Grant of 2020.
All Science Journal Classification (ASJC) codes
- Public Health, Environmental and Occupational Health