Influencing factors associated with depression among middle-aged and older adults with disabilities: a latent profile analysis.

A cross-sectional latent class analysis of depressive and anxiety symptoms in people aged 65 and older

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.

Multidimensional determinants of depression and non-depression in older adults: evidence from national data.

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.

A Study on the Depressive Symptoms and Life Satisfaction Among Middle-Aged and Older Adults in China Based on CHARLS 2020 Data

Background: Depressive symptoms have become a significant public health issue faced by middle-aged and older adults in China. Although previous studies have primarily focused on demographic and socioeconomic factors, the association between modifiable lifestyle behaviors and depressive symptoms still requires further investigation. Objective: To examine the associations between sleep duration, physical activity, digital participation, social participation, and depressive symptoms as well as life satisfaction among middle-aged and older adults in China. Methods: A cross-sectional analysis was conducted using data from the 2020 China Health and Retirement Longitudinal Survey (CHARLS). Depressive symptoms were defined as CES-D-10 scores ≥10, with 13,576 individuals included in the analysis sample. Adjusted prevalence ratios (aPRs) were estimated using modified Poisson regression, while ordinal logistic regression was employed to analyze life satisfaction. The analysis controlled for covariates such as demographics, socioeconomic status, and health status, and accounted for the complex sampling design. Results: The weighted prevalence of depressive symptoms was 44.5%. Sleep deprivation (<7 h/day) was significantly associated with elevated depressive symptoms (aPR = 1.49, 95% CI: 1.33–1.68); participation in recreational activities was significantly associated with reduced depressive symptoms (aPR = 0.86, 95% CI: 0.77–0.96); adequate physical activity was associated with a higher prevalence of elevated depressive symptoms (aPR = 1.17, 95% CI: 1.04–1.32); watching videos (aPR = 0.87, 95% CI: 0.76–0.99) and playing online games (aPR = 0.65, 95% CI: 0.50–0.83) were significantly associated with reduced depressive symptoms; and overall internet use was correlated with lower life satisfaction (OR = 0.90, 95% CI: 0.81–1.00). Women, rural residents, and low-income groups exhibited higher prevalence of elevated depressive symptoms. Conclusion: Sleep deprivation, as well as different types of social engagement, physical activity, and digital behavior, exhibit distinct associations with depressive symptoms in middle-aged and older adults. Behavioral intervention strategies targeting sleep hygiene, leisure activities, and tailored digital behaviors warrant further attention.

Depression and Functional Disability Among Older Adults in Brazil: Analysis of the 2019 National Health Survey

Latent profile analysis and determinants of social isolation among older adults in China

This study aimed to identify social isolation profiles among older adults in China using latent profile analysis and to explore their associations with demographic and health factors. A cross-sectional study was conducted between July and December 2023 in the Chaoyang and Dongcheng districts of Beijing, China. Participants aged 60 years or older were recruited through convenience sampling from six communities. Latent profile analysis was used to classify social isolation patterns, and multivariate logistic regression models to assess associated factors. 529 participants were included. Three social isolation profiles were identified: the mild social isolation subgroup ( n = 239, 45.2%), the moderate social isolation subgroup ( n = 213, 40.3%), and the severe social isolation subgroup ( n = 77, 14.5%). Comparing mild to severe social isolation, multivariate analysis revealed that older adults living alone without caregiver had significantly higher odds of severe social isolation compared to those living with children (OR = 0.099, 95% CI: 0.034–0.377, P < 0.001). Frailty (OR = 0.141, 95% CI: 0.039–0.588, P = 0.033), severe ADL dependence (OR = 0.249, 95% CI: 0.145–0.454, P = 0.048), and moderate to severe IADL dependence (OR = 0.448 to 0.307, P = 0.046, P = 0.017) were also significantly associated with severe social isolation. Similarly, in the comparison between the moderate and severe subgroups, compared to those living with children, older adults living alone without caregiver were more likely to experience severe social isolation (OR = 0.199, 95% CI: 0.078–0.328, P = 0.001). In terms of functional status, severe ADL dependence (OR = 0.152, 95% CI: 0.061–0.505, P = 0.015) and moderate to severe IADL dependence (OR = 0.231 to 0.128, P = 0.045, P = 0.033) were significantly associated with severe social isolation. Older adults living alone without caregiver, with frailty, and with functional dependence are at significantly higher risk of severe social isolation. Family network integrity emerged as the primary dimension differentiating severe social isolation from mild-to-moderate isolation, which may be linked to a quantitative gradient of overall network restriction. Understanding the specific factors contributing to different profiles could inform tailored support strategies to enhance social engagement and quality of life in this population.

Cognitive status and depressive symptoms among older adults: a SEM analysis study

The increase of age is related with high concerns of cognitive decline and depression which frequently influence each other in both directions. The objective of the current study is the assessment of the cognitive status and the symptoms indicating depression the older adults, in order to evaluate a structural model that subjective cognitive complaints mediate the relationship between objective cognitive performance and depression. The current study, cross-sectional in nature, was carried out with 140 community-dwelling senior adults (63.38 ± 7.22 years). Participants were assessed by using three standardized instruments: Abbreviated Mental Test Score (AMT) for objective cognitive performance, the Persian Cognitive Difficulties Scale (PCDS-26) for subjective cognitive complaints, and the Geriatric Depression Scale (GDS-15) for depressive symptoms. Data were analyzed by the use of SEM (Structural Equation Modeling), together with diagonally weighted least squares (DWLS) estimation to test a partial mediation hypothesis. The finalized model fit was assessed using χ²/df, CFI, TLI, and RMSEA. The structural model resulted in very impressive goodness-of-fit indices (χ²/df = 1.102, CFI = 0.996, RMSEA = 0.027). The analysis revealed that objective cognitive performance has a remarkable direct negative impact on depressive symptoms (β = -0.289, p  = 0.001). Furthermore, a significant indirect pathway was also identified (β = -0.108): higher objective cognitive performance was associated with fewer subjective cognitive complaints (β = -0.201), which in turn strongly predicted lower levels of depressive symptoms (β = 0.534). The total effect of objective cognition on depression was β = -0.397. The findings confirm that better objective cognition is linked to fewer subjective complaints and lower depression, with subjective perceptions partially mediating this relationship. This finding highlights the potential relevance of metacognitive awareness to late-life mental health. Clinically, screening for subjective cognitive complaints may help identify older adults with elevated depressive symptoms who could benefit from further assessment and appropriate interventions, such as cognitive-behavioral therapy. Therefore, clinicians should integrate assessments of subjective cognitive difficulties into routine depression screenings to provide more holistic geriatric care. Not applicable. We clarify that this research employed a cross‑sectional design, with all data gathered and analyzed at one single time point. Therefore, the study does not constitute a clinical trial.