39 research outputs found

    A critical review and development of a conceptual model of exclusion from social relations for older people

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    Social exclusion is complex and dynamic, and it leads to the non-realization of social, economic, political or cultural rights or participation within a society. This critical review takes stock of the literature on exclusion of social relations. Social relations are defined as comprising social resources, social connections and social networks. An evidence review group undertook a critical review which integrates, interprets and synthesizes information across studies to develop a conceptual model of exclusion from social relations. The resulting model is a subjective interpretation of the literature and is intended to be the starting point for further evaluations. The conceptual model identifies individual risks for exclusion from social relations (personal attributes, biological and neurological risk, retirement, socio-economic status, exclusion from material resources and migration). It incorporates the evaluation of social relations, and the influence of psychosocial resources and socioemotional processes, sociocultural, social-structural, environmental and policy contextual influences on exclusion from social relations. It includes distal outcomes of exclusion from social relations, that is, individual well-being, health and functioning, social opportunities and social cohesion. The dynamic relationships between elements of the model are also reported. We conclude that the model provides a subjective interpretation of the data and an excellent starting point for further phases of conceptual development and systematic evaluation(s). Future research needs to consider the use of sophisticated analytical tools and an interdisciplinary approach in order to understand the underlying biological and ecopsychosocial associations that contribute to individual and dynamic differences in the experience of exclusion from social relation

    Social Network Characteristics and Their Associations With Stress in Older Adults: Closure and Balance in a Population-Based Sample

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    Objectives: Integration into social networks reduces stress during adverse life events and improves coping with disability in late life. The aim was to investigate whether social network closure (frequent contact among ties) and balance (positive contact among ties) are associated with perceived stress. We expect lowest stress for older adults with highly closed and balanced networks. Method: Panel data on self-reported egocentric networks stem from the population-based Chicago Health, Aging, and Social Relations Study. Five waves were collected between 2002 and 2006, with 708 observations from 160 participants aged 50-68 years at baseline. Data include information on the participants' social relationships, that is, interaction frequency and relationship quality, for ego-alter ties and alter-alter ties, and participants' perceived stress. The analytical strategy used fixed- and random-effects models. Results: Participants reporting the highest number of balanced relationships (positive ties among alters) experience least stress. This effect holds independently of sociodemographic confounders, loneliness, and network size. Discussion: The absence of a stress-reducing effect from network closure suggests that balance matters more. Future research would benefit from considering balance when examining the characteristics of social networks that impinge on mental health outcomes in older adults

    Neighborhood income and major depressive disorder in a large Dutch population: results from the LifeLines Cohort study

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    Background: Previous studies are inconclusive on whether poor socioeconomic conditions in the neighborhood are associated with major depressive disorder. Furthermore, conceptual models that relate neighborhood conditions to depressive disorder have not been evaluated using empirical data. In this study, we investigated whether neighborhood income is associated with major depressive episodes. We evaluated three conceptual models. Conceptual model 1: The association between neighborhood income and major depressive episodes is explained by diseases, lifestyle factors, stress and social participation. Conceptual model 2: A low individual income relative to the mean income in the neighborhood is associated with major depressive episodes. Conceptual model 3: A high income of the neighborhood buffers the effect of a low individual income on major depressive disorder. Methods: We used adult baseline data from the LifeLines Cohort Study (N = 71,058) linked with data on the participants' neighborhoods from Statistics Netherlands. The current presence of a major depressive episode was assessed using the MINI neuropsychiatric interview. The association between neighborhood income and major depressive episodes was assessed using a mixed effect logistic regression model adjusted for age, sex, marital status, education and individual (equalized) income. This regression model was sequentially adjusted for lifestyle factors, chronic diseases, stress, and social participation to evaluate conceptual model 1. To evaluate conceptual models 2 and 3, an interaction term for neighborhood income*individual income was included. Results: Multivariate regression analysis showed that a low neighborhood income is associated with major depressive episodes (OR (95 % CI): 0.82 (0.73;0.93)). Adjustment for diseases, lifestyle factors, stress, and social participation attenuated this association (ORs (95 % CI): 0.90 (0.79;1.01)). Low individual income was also associated with major depressive episodes (OR (95 % CI): 0.72 (0.68;0.76)). The interaction of individual income*neighborhood income on major depressive episodes was not significant (p = 0.173). Conclusions: Living in a low-income neighborhood is associated with major depressive episodes. Our results suggest that this association is partly explained by chronic diseases, lifestyle factors, stress and poor social participation, and thereby partly confirm conceptual model 1. Our results do not support conceptual model 2 and 3
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