The identified patterns of co-occurring physical and psychosocial symptoms highlight the importance of adopting holistic, tailored strategies to support cognitive health and the importance of adopting holistic, tailored strategies to support cognitive health.
Abstract
Background
Older adults often experience complex, co-occurring physical, psychological, and social health conditions that together characterize their multidimensional health and may have implications for cognitive function. However, the patterns of these multidimensional health conditions and their association with cognitive function in older adults remain poorly understood. This study aims to identify latent profiles of multidimensional health among community-dwelling older adults and examine factors associated with profile membership and corresponding cognitive function.
Methods
In this study, cross-sectional survey data from 1,077 community-dwelling older adults were analyzed. Latent profile analysis was used to classify participants based on pain, fatigue, physical frailty, depressive symptoms, insomnia symptoms, and loneliness. Multinomial logistic regression with the three-step approach (R3STEP) was performed to identify factors associated with latent profile membership. Hierarchical regression analysis was used to examine the associations between latent profiles and cognitive function.
Results
Four distinct latent health profiles were identified: relatively healthy (56.7%), physical symptom (21.5%), physically frail (12.1%), and psychosocial symptom (9.7%) groups. Compared with the relatively healthy group, participants aged ≥ 75 years, with a bachelor's degree or higher, unmarried status, low economic status, chronic diseases, and low engagement in physical activity were more likely to belong to the physical symptom, physically frail, or psychosocial symptom profiles. Participants in all other latent profiles exhibited lower cognitive function than those in the relatively healthy group.
Conclusions
This study highlights the importance of multidimensional health profiles in understanding cognitive vulnerability among older adults. The identified patterns of co-occurring physical and psychosocial symptoms highlight the importance of adopting holistic, tailored strategies to support cognitive health. Developing profile-specific interventions addressing physical function, symptom management, and psychosocial well-being is essential for preventing cognitive decline in this population.
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 High-Depression 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.
Objective To investigate the longitudinal dynamic relationships among frailty, depression, and self-perceptions of aging in community-dwelling older adults, to analyze the mediating role of depression between frailty and aging cognition, and to provide a theoretical basis for physical and mental health interventions for this population. Methods A longitudinal follow-up research design was adopted, involving three waves of surveys (T1, T2, T3) conducted with 286 community-dwelling older adults. Assessments were performed using the Frailty Phenotype, a depression scale, and a brief version of the Self-Perceptions of Aging Scale. SPSS 26.0 was used for descriptive statistics and correlation analysis, while Mplus 8.3 was employed to construct cross-lagged panel models. Covariates such as age, gender, education level, the number of chronic diseases, and cognitive function were controlled. Results The cross-lagged panel model demonstrated good fit indices. With the exception of baseline (T1) self-perceptions of aging not significantly predicting the midterm (T2) level, all other core variables exhibited significant temporal stability. Controlling for autoregressive effects and covariates, significant bidirectional predictive relationships emerged: T1 frailty significantly predicted T2 depression, and T2 depression significantly predicted T3 frailty; T1 depression significantly predicted T2 self-perceptions of aging, and T2 self-perceptions of aging significantly predicted T3 depression. Furthermore, the direct predictive path from frailty to self-perceptions of aging was not significant, suggesting that depression may constitute an indirect pathway linking frailty and self-perceptions of aging. Conclusion This study supports a dynamic psychosomatic interaction pattern among frailty, depression, and self-perceptions of aging in community-dwelling older adults. Depression serves as a core hub connecting physiological frailty and subjective aging cognition. The findings support the Psychosomatic Interaction Theory (PIT) and Stereotype Embodiment Theory (SET). These results suggest that community nursing practice should emphasize early screening and intervention for depressive symptoms. Targeting this potentially important depressive pathway may help interrupt the adverse cycle of “physiological frailty – psychological depression - negative aging cognition” among older adults can be disrupted.
Yongwei Liu, Yuyang Luo, Junjun Sun et al.· Frontiers in Public Health· 0 citations
Key factors contribute to differences in depression and anxiety symptoms among older adults: gender, body mass index, ethnicity, occupation before retirement, marital status, physical disability status, independence in activities of daily living, number of chronic diseases, smoking and drinking habits, dietary habits, recreational activities, physical activity, and sleep quality.
Jing Zhang, Feng Li, Yuntong Yao et al.· Medicine· 0 citations
BACKGROUND
Depression is a leading mental health concern among community dwelling older adults, with childhood trauma and current loneliness identified as critical risk factors. However, existing research has predominantly examined these variables in isolation, obscuring heterogeneity in their co-occurring patterns and differential depression risk across subgroups.
OBJECTIVES
To identify latent profiles based on co-occurrence patterns of childhood trauma and current loneliness and examine differences in depressive symptoms across profiles.
METHODS
A cross-sectional study recruited 740 older adults from three communities. Childhood trauma, loneliness, and depressive symptoms were assessed. Latent profile analysis identified subgroups, and the Bolck-Croon-Hagenaars method examined differences in depressive symptoms across profiles.
RESULTS
Three profiles were identified: "Low Trauma-Low Loneliness", "Low Trauma-High Loneliness", and "High Trauma-High Loneliness". The High Trauma-High Loneliness profile exhibited the highest depressive symptom. Community activity participation, chronic disease, empty-nest status, and marital status were significant predictors of profile membership. .
CONCLUSIONS
Community-dwelling older adults demonstrate heterogeneous co-occurrence patterns of childhood trauma and current loneliness. Individuals in the High Trauma-High Loneliness profile warrant prioritized clinical attention and targeted community-based intervention.
CLINICAL IMPLICATIONS
Screening childhood trauma and loneliness jointly identifies the highest-risk subgroup, for whom trauma-informed care combined with community activity participation is preferable to loneliness-focused intervention alone.
Xiang-Zi Ji, Jiayuan Zhang, Jinping Zhao et al.· Clinical Gerontologist· 0 citations
BACKGROUND
Social determinants of health (SDoH) are increasingly recognized as key contributors to frailty, yet their multidimensional associations remain underexplored. This study examined how multiple SDoH domains and specific variables relate to distinct frailty domains among Chinese community-dwelling older adults.
METHODS
We analyzed 10,654 adults aged ≥ 60 years in the 2020 China Health and Retirement Longitudinal Study. Five SDoH domains, defined by the Healthy People 2030 framework, were assessed: Economic Stability, Education Access and Quality, Health Care Access and Quality, Neighborhood and Built Environment, and Social and Community Context. Latent class analysis was used to operationalize domain-level SDoH groupings. Frailty was measured using a 30-item multidimensional frailty index. Mixed graphical models were applied to estimate domain- and variable-level networks. Centrality and bridge strength identified influential and bridging nodes. Complete-case and post hoc edge removal sensitivity analyses were conducted.
RESULTS
At the domain level, Education Access and Quality and Economic Stability were the main bridge domains linking SDoH to frailty, with the strongest association observed between Education Access and Quality and cognition deficits (edge weight = 0.688). At the variable level, education, access to healthcare, and employment status were key bridging variables linking SDoH to frailty. Cognition consistently showed the highest bridge strength within the frailty community. The strong education-cognition association should, however, be interpreted cautiously.
CONCLUSIONS
Education-, economic-, and healthcare-related disadvantage were key structural links to frailty, with cognition serving as the main frailty bridge. These findings provide insight into important pathways through which social disadvantage may contribute to frailty risk.
CLINICAL TRIAL NUMBER
Not applicable.
Ying Gao, Denise Shuk Ting Cheung, Pui Hing Chau· Journal of general internal...· 0 citations
Previous studies on psychological frailty in older adults have typically examined individual components or assumed population homogeneity, often overlooking latent heterogeneity and complex symptom interrelations. This study aimed to identify latent profiles of psychological frailty and to integrate computational simulation with network analysis to explore patterns of symptom associations. This cross-sectional study included 4,735 adults aged 65 years or older. Psychological distress, cognitive function, physical vulnerability, and memory decline were assessed using established measures from the China Health and Retirement Longitudinal Study. Latent profile analysis was conducted in Mplus to identify subgroups, followed by Gaussian graphical model network analysis in R to examine symptom interrelations within each profile. Additionally, an in silico simulation approach using the NodeIdentifyR algorithm was applied to estimate changes in overall network burden under hypothetical symptom perturbations. Three latent profiles were identified: Relatively Healthy (57.8%), Moderate Distress (32.8%), and Severe Cognitive Deterioration (9.4%). Network structures differed significantly between the Moderate Distress and Severe Cognitive Deterioration profiles. The former showed higher centrality of orientation-related symptoms, whereas the latter was characterized by greater centrality of affective symptoms. In simulation analyses, hypothetical increases in powerlessness, depression, attentional problems, and functional limitations were associated with the largest estimated increases in overall network burden, whereas symptom-response patterns differed across latent profiles. This cross-sectional study identified distinct latent profiles of psychological frailty and demonstrated differences in symptom network organization across profiles. The simulation findings indicate that certain symptoms may be associated with greater model-based changes in network activation. These results provide an exploratory framework for understanding heterogeneity in psychological frailty, but require validation in longitudinal and intervention studies.
Yangjuan Bao, Zhili Jiang, Fangjun Wang et al.· BMC Geriatrics· 0 citations