Aug 2026· Medicine· Vol 105 34, pp.
e50328
· 0 citations
Medicine
TL;DR
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.
Abstract
As the older population grows, depression and anxiety have become common mental health problems that significantly undermine the quality of life of older persons. Improving older people's mental health is vital for their quality of life. Before developing targeted interventions, priority must be given to identifying key factors affecting mental health to address the significant individual differences within this population. The aim was to identify subgroups of depressive/anxiety symptoms in the older population and factors influencing their mental health. Secondary analysis of mental health data of elderly people aged 65 years and older in Guizhou Province, China. Latent Class Modeling was developed using Mplus 8.3 software to examine the factors that influence the occurrence of anxiety and depression in different subgroups of older adults. Chi-square test and unordered multivariate logistic regression were used for detailed analysis from 3 perspectives (demographic characteristics, physical condition and family relationships, and lifestyle). A total of 4 potential category subgroups were identified in this study: the severe depressive and anxiety symptoms group (Class 1, N = 406, 1.46%), the moderate depressive and anxiety symptoms group (Class 2, N = 1834, 6.58%), the mild depressive and anxiety symptoms group (Class 3, N = 3789, 13.59%), and the group without depressive or anxiety symptoms (Class 4, N = 21,851, 78.38%). Significant individual differences in symptoms of depression and anxiety exist among people aged 65 and older. The results of the disordered multiple logistic regression analysis revealed that the following 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. In the context of global aging, the mental health of older adults is paramount. Given significant heterogeneity in their mental health status, health and policy sectors should develop individualized interventions targeting specific subgroups and their risk factors to effectively reduce anxiety and depression.
This study aimed to explore heterogeneous profiles of depression among middle-aged and older adults with disabilities, and the influencing factors associated with the profiles were identified to provide a reference for improving mental health in this population. Data were obtained from the 2020 China Health and Retirement Longitudinal Study (CHARLS). A total of 3019 participants aged ≥45 years with disabilities were included. Latent profile analysis (LPA) was employed to identify profiles of depression. Chi-square tests, one-way ANOVA, and multivariate logistic regression were used to examine the influencing factors associated with different depression profiles among middle-aged and older adults with disabilities. The prevalence of depression among middle-aged and older adults with disabilities was 63.53%. Three depression profiles were identified: 'mild depression' (44.98%), 'severe depression-mild fear' (28.32%), and 'severe depression' (26.70%). Compared to 'mild depression', both severe depression profiles were associated with lower life satisfaction and poorer cognitive function. Other significant factors included gender, age, retirement, sleep hours per night, moderate physical activity, number of chronic diseases, bodily pain, and ADL disability. Depression among middle-aged and older adults with disabilities manifests in distinct latent profiles with varying severity and characteristics. Tailored interventions addressing lifestyle factors, chronic disease management, and functional support are needed to mitigate depression in this vulnerable population.
Li Zeng, Hailong Hou, Li Liu et al.· Psychology, Health & Medicin...· 0 citations
Depression is highly prevalent among older adults, and impairs both mental and physical health. However, whether and how gender influences the development of depressive symptoms in older adults is unclear. The current study systematically examined the gender-specific development of depressive symptoms in national data. Participants were 5683 older adults (47.9% older women; Mage= 66.8 years) from the China Health and Retirement Longitudinal Study. Depressive symptoms were assessed by the center for epidemiological studies depression scale in 2015 (T1) and 2018 (T2). Gaussian graphical model (GGM) networks, Bayesian networks and cross-lagged panel networks (CLPNs) were used to examine the association between depressive symptoms from a comprehensive perspective. Cross-sectional networks (i.e., GGM and Bayesian networks) with T1 data suggested strong connections between loneliness and inability to get going for women while a strong relationship between the everything was an effort and feeling depressed for men. In CLPNs, the feeling bothered at T1 was positively associated with feeling depressed at T2 and the loneliness showed a bidirectional longitudinal association with inability to get going across time for women, while the everything was an effort at T1 was related to feeling depressed at T2 and the feeling depressed at T1 was associated with loneliness at T2 for men. These findings may suggest that older men with depressive symptoms were more likely to experience somatic fatigue, while depressive symptoms in older women were associated with social isolation. Recognizing these gender-specific symptom profiles may inform the development of tailored mental health policies and prevention strategies.
BACKGROUND
The global demographic transition indicates a rapid shift toward an aging population structure. Good mental health in advanced ages is critical for a healthy aging. Problems such as depression reduce life expectancy and impose a societal burden. This study aims to examine, through a multidimensional approach, the sociodemographic, economic, health-related, functional, and psychosocial factors affecting depression levels among individuals aged 65 and over in Türkiye.
METHOD
In this study, microdata from the Türkiye Older Adult Profile Survey conducted by Turkish Statistical Institute (TurkStat) in 2023 was utilized. The analysis included a total of 10,348 individuals aged 65 and over who personally responded to perception-related questions. The dependent variable, depression level, was categorized as "not depressed," "mild," and "severe" according to Geriatric Depression Scale scores. In the analysis of the data, a generalized ordered logit model and marginal effects were employed due to the violation of the parallel lines assumption.
FINDINGS
Depression was common among older adults, with 46.71% exhibiting mild depressive symptoms. Specifically, 34.26% were mildly depressed and 12.45% were severely depressed, while 53.29% were classified as non-depressed. According to the analysis results, female gender, living alone, low-income level, and experiencing financial hardship significantly increase the risk of depression. In terms of health status, poor self-rated general health, sensory impairments (vision/hearing difficulties), history of falls, and the need for home care are the main factors increasing the likelihood of depression. An increase in functional independence (KATZ index) and maintaining a physically active lifestyle exhibit protective effects. Additionally, strong neighbor support, a higher number of support people, and a sense of autonomy in decision-making processes significantly reduce the level of depression.
CONCLUSION
Geriatric depression in Türkiye is a multidimensional phenomenon with complex socioeconomic and environmental determinants, in addition to biological factors. In particular, older women, individuals living alone, and economically disadvantaged groups are at high risk. The findings indicate that, to support healthy aging, clinical interventions alone are insufficient; strengthening social support networks, enhancing urban accessibility, and urgently developing inclusive public health policies that promote older adults'autonomy are required.
Kübranur Çebi̇ Karaaslan, Esra Bayrakçeken, Ö. Alkan et al.· BMC Geriatrics· 0 citations
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.
Background Late-life depression is a growing public health issue in ageing societies, influenced by health, functional, socioeconomic, and psychosocial factors. Evidence integrating health, functional, psychosocial, and healthcare-access determinants using nationally representative data in Turkey remains limited. This study examined determinants of depressive symptoms among adults aged ≥65 years. Methods This study analyzed data from 10,348 participants aged ≥65 years from the nationally representative Turkey Older Persons Profile Survey (TYPA 2023). All analyses incorporated survey sampling weights. Depressive symptoms were defined using the Geriatric Depression Scale-30 (GDS-30) (cut-off ≥10). Hierarchical logistic regression models were constructed in sequential blocks (sociodemographic; health and functional status; psychosocial and healthcare-related factors) to identify independent correlates. Results The weighted mean age was 72.8 years; 55.1% were women, and 46.2% screened positive for depressive symptoms according to the applied screening threshold. In the fully adjusted model, depressive symptoms were associated with female sex, lower education, unmarried status, poorer self-rated health, sensory and functional limitations, perceived age-related restriction, perceived exclusion, and difficulties accessing or communicating with healthcare services. Conclusions Depressive symptoms among older adults in Turkey reflect the combined influence of health decline, functional limitations, negative psychosocial perceptions of ageing, and barriers to healthcare access. Interventions addressing functional decline, financial strain, ageism, and access barriers may support better mental health in later life and inform public health and ageing-related policies.
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.
Myungji Kim, Da Eun Kim· BMC Geriatrics· 0 citations
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