Objective and Perceived Neighborhood Characteristics and Cognitive Decline

描述（由研究者提供）：社区社会、经济、人口统计学和建筑特征已被证明会影响健康结局，如死亡率、肥胖、心血管疾病和抑郁症，与个体因素无关。最近的文献表明，社区的社会经济地位（NSES）的个人居住的地区是与认知功能，独立的个人因素。然而，迄今为止还没有研究在全国代表性样本中检查纵向关系。此外，研究集中在NSES没有检查其他客观的健康相关的邻里特征和感知的邻里特征，没有考虑其他敏感的晚年认知结果，如认知障碍，并没有解决是否选择到社区，例如基于健康状况，可能会偏见的结果客观。该项目将填补现有研究的空白，开发一个客观邻里特征的国家数据库，将这些数据与健康和退休研究（HRS）中具有全国代表性的老年人样本中评估的认知功能纵向数据联系起来，评估超过22年（1992-2014），并检查客观和感知的邻里特征和认知功能之间的关系随着时间的推移。这项研究还将研究一系列潜在的介质，包括压力的生物标志物，以及血管，行为和心理社会因素，这些因素可能会告知邻里影响认知结果的机制途径。它还将根据社会人口统计学和遗传特征确定最容易受到邻里效应影响的亚组，并测试我们的研究结果对选择偏差方法的敏感性。我们将开发一个客观邻里措施的数据库，包括NSES，种族/民族隔离和组成，城市扩张和食品环境，并将其与HRS的认知功能和主观评级的个人数据以及血管事件临床诊断的医疗保险数据相结合。结构方程模型将检查独立的协会，调解，并影响修改邻里效应。一个创新的统计技术，称为省略变量分析将解决的潜力，个人可能会选择性地移动到不同的社区的健康状况和倾向得分匹配将被用来减少潜在的偏见，在识别社区特征对认知结果的影响。这项研究可以揭示背景特征，可以作为干预措施的可修改的目标，并产生更大规模的变化，努力防止认知能力下降和损害比干预措施，专注于个人因素。调解分析将确定潜在的生物，血管，行为和心理社会机制，以确定更接近的干预目标，以缓冲生活在一个较低质量的社区的影响。查明弱势亚群体将使公共卫生干预措施更有效地侧重于高危群体。

DESCRIPTION (provided by investigator): Neighborhood social, economic, demographic, and built characteristics have been shown to influence health outcomes such as mortality, obesity, cardiovascular disease, and depression, independent of individual factors. Recent literature suggests that the neighborhood socioeconomic status (NSES) of the area in which individuals live is correlated with cognitive functioning, independent of individual factors. However, no studies to date have examined longitudinal relationships in a nationally representative sample. In addition, studies have focused on NSES without examination of other objective health-relevant neighborhood characteristics and perceived neighborhood characteristics, have not considered other sensitive late-life cognitive outcomes such as cognitive impairment, and have not addressed whether selection into neighborhoods, based on health status for example, may bias results Objective. This project will fill gaps in existing research by developing a national database of objective neighborhood characteristics, linking these data with longitudinal data on cognitive function assessed in a nationally representative sample of older adults in the Health and Retirement Study (HRS) assessed over 22 years (1992-2014), and examining the relationship between both objective and perceived neighborhood characteristics and cognitive function over time. This study will also examine a host of potential mediators including biomarkers of stress, and vascular, behavioral, and psychosocial factors that may inform mechanistic pathways by which neighborhoods influence cognitive outcomes. It will also identify subgroups that are most vulnerable to neighborhood effects based on sociodemographic and genetic characteristics, and test the sensitivity of our findings to selection bias Methods. We will develop a database of objective neighborhood measures including NSES, racial/ethnic segregation and composition, urban sprawl, and food environment, and integrate it with individual data on cognitive function and subjective ratings of neighborhoods from the HRS and with Medicare data on clinical diagnoses of vascular events. Structural equation models will examine independent associations, mediation, and effect modification of neighborhood effects. An innovative statistical technique called omitted variable analysis will address the potential that individuals may selectively move into differing neighborhoods by health status and propensity score matching will be used to reduce potential biases in identifying the effects of neighborhood characteristics on cognitive outcomes Implications. This research can shed light on contextual characteristics that may serve as modifiable targets for interventions, and yield larger-scale changes in the effort to prevent cognitive decline and impairment than interventions that focus on individual factors. Mediation analyses will identify underlying biological, vascular, behavioral, and psychosocial mechanisms to pinpoint more proximal intervention targets to buffer against the effects of living in a lower quality neighborhood. Identification of vulnerable subgroups will focus public health interventions more efficiently on at-risk groups.