Dynamic Social Network Structures in Aging: A Complex Systems Approach

 描述（由申请人提供）：本项目的总体目标是调查老年人社交网络的结构和动态，以及网络系统相关特征在重要的晚年结局中的作用，包括幸福，认知老化，生存。以前的研究表明，社会关系及其提供的支持是老年人的重要资源，与更好的整体健康和福祉有关。它们还被证明可以降低认知能力下降和死亡率的风险。此外，老年人的社交网络往往随着年龄的增长而大幅萎缩，因为死亡和近亲和朋友之间的搬迁对他们的社交网络系统造成的损失越来越大。然而，人们对老年人的社会弹性和社会关系所嵌入的网络系统知之甚少。也就是说，老年人的社会网络的组成和结构如何影响他们形成新联系的能力，以补偿他们网络中的损失，或者相反，阻碍他们形成新联系的能力，并增加社会孤立？ 此外，目前还不清楚他们的社会网络系统的功能，在其与个人层面的风险和保护因素的相互作用，影响认知老化的速度在这一人群为了解决这些问题，我们建议使用复杂系统的方法，并开发了一系列的模拟模型，以表征社会网络结构的城市人口的老年非西班牙裔白色和非洲裔美国人的成年人，以及这些结构随时间的变化。我们还将使用图形技术来可视化这个群体中的网络结构和动态。其次，我们建议在一系列回归模型中使用网络分析的结果来前瞻性地测试特定网络特征（如聚类程度、密度和中心性）与死亡率以及幸福感和认知结果变化之间的关联。这项研究是由一个大的队列（N > 6,000）的老年人在一段时间内的详细信息的现有数据的可用性促进 他们的社会网络特征和其他心理社会和健康变量与预测福祉，认知能力下降和死亡率。据我们所知，这是第一次应用复杂系统方法来研究与社会网络系统在幸福，认知老化和晚年生存中的作用有关的重要问题。

 DESCRIPTION (provided by applicant): The overall aim of this project is to investigate the structure and dynamics of social networks among older adults, and the role of network system-related characteristics in important late-life outcomes, including well- being, cognitive aging, an survival. Previous research suggests that social relationships and the support they provide are important resources to older adults, and associated with better overall health and well-being. They have also been shown to reduce risk of cognitive decline and mortality. In addition, social networks of older adults tend to shrink substantially as they age, as losses due to death and relocation among close relatives and friends take a growing toll on their social network system. However, much less is known about the social resilience of older adults and the network system in which there social ties are embedded. That is, how do the composition and structure of an older adult's social network affect their ability to form new ties as compensation for losses in their network, or conversely, impede their ability to form new ties, and increase social isolation? In addition, it is unknown how features of their social network system, in its interplay with individual-level risk and protective factors, affect the rate of cognitive aging in this population To address these questions, we propose to use a complex-systems approach and develop a series of simulation models to characterize social network structures of an urban population of older non-Hispanic white and African American adults, as well as the changes in these structures over time. We will also use graphical techniques to visualize the network structure and dynamics in this population. Second, we propose to use the results of the network analysis in a series of regression models to prospectively test the association between specific network features, such as the degree of clustering, density, and centrality, and mortality as well as changes in well-being and cognitive outcomes. This research is facilitated by the availability of existing data on a large cohort (N > 6,000) of older adults with detailed information over a period of about 10 years on their social network characteristics and other psychosocial and health variables relevant to the prediction of well-being, cognitive decline and mortality. To our knowledge, this is the first application of a complex system approach to examine important questions related to the role of social network systems in well-being, cognitive aging and survival in late life.