R code using in Psychosocial and cognitive profiles associated with health-related quality of life and healthy aging among community-dwelling older adults: a latent profile analysis.
Citation: Lee, S., Cho, Y. & Song, R. Psychosocial and cognitive profiles associated with health-related quality of life and healthy aging among community-dwelling older adults: a latent profile analysis. BMC Geriatr (2026). https://doi.org/10.1186/s12877-026-07939-0
Background Community-dwelling older adults differ in their social, psychological, and cognitive resources, which may influence health-related quality of life and healthy aging. Variable-centered approaches may not fully capture this heterogeneity. This study aimed to identify psychosocial and cognitive profiles among community-dwelling older adults and examine differences in health-related quality of life and healthy aging across profiles.
Methods This study was a secondary analysis of de-identified data from a nationwide cross-sectional survey of 510 community-dwelling older adults in Korea. Latent profile analysis was conducted using social network, perceived social support, depressive symptoms, and subjective cognitive function as profile indicators. Health-related quality of life, measured by the Physical Component Summary and Mental Component Summary of the 12-item Short Form Health Survey, and healthy aging were examined as distal outcomes. Covariate effects of age, sex, education years, living status, and economic status were removed using linear regression residuals. Welch’s one-way analysis of variance and Games–Howell post hoc tests were used to compare residualized outcomes across profiles.
Results A five-profile solution was selected based on model fit, entropy, minimum profile size, parsimony, and interpretability. The profiles were labeled as the High-Depression Vulnerable Group (n = 29), Moderate-Depression Socially Connected High-Resource Group (n = 53), Low-Depression Socially Constrained Group (n = 129), Elevated-Depression Intermediate-Resource Group (n = 41), and Low-Depression, High-Support, Limited-Network Group (n = 258). Profile membership was significantly associated with the Physical Component Summary, F(4, 107) = 81.66, p < .001; Mental Component Summary, F(4, 107) = 10.27, p < .001; and healthy aging, F(4, 110) = 53.51, p < .001. The Low-Depression, High-Support, Limited-Network Group had the highest healthy aging score, significantly exceeding all other profiles. Physical health-related quality of life was similarly high in the Moderate-Depression Socially Connected High-Resource Group and the Low-Depression, High-Support, Limited-Network Group. The HighDepression Vulnerable Group had the lowest Physical Component Summary and healthy aging scores.
Conclusions Community-dwelling older adults showed distinct psychosocial and cognitive profiles that were differentially associated with health-related quality of life and healthy aging. Healthy aging was most favorable in the group characterized by limited social network resources but high perceived social support, low depressive symptoms, and favorable subjective cognitive function. These findings suggest that healthy aging may depend not only on social network resources, but also on perceived support, depressive symptom burden, and subjective cognitive function. Person-centered assessment may help identify older adults who require tailored strategies to promote quality of life and healthy aging in community settings.