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.

Public Health Relevance

The proposed research aims to provide clinicians, public health officials, and policymakers with information on whether objective and perceived characteristics of the built, demographic, economic, and social environments in which individuals live are longitudinally related to risk for worse cognitive function, cognitive impairment, and steeper cognitive decline. This research will clarify whether vascular, behavioral, and psychosocial factors and biological markers of stress may explain these relationships and also identify sociodemographic and genetic subgroups that may be most vulnerable to neighborhood influences on cognitive outcomes. As the proportion of older adults at risk for dementia grows, our research can shed light on contextual characteristics that influence this risk, thus identifying modifiable targets for intervention and yielding larger-scale improvements in the effort to prevent cognitive decline and impairment than interventions that focus on individual factors alone.

National Institute of Health (NIH)
National Institute on Aging (NIA)
Research Project (R01)
Project #
Application #
Study Section
Special Emphasis Panel (ZRG1-PSE-B (50))
Program Officer
King, Jonathan W
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Rand Corporation
Santa Monica
United States
Zip Code
Miles, Jeremy N; Weden, Margaret M; Lavery, Diana et al. (2016) Constructing a Time-Invariant Measure of the Socio-economic Status of U.S. Census Tracts. J Urban Health 93:213-32
Sisco, Shannon; Gross, Alden L; Shih, Regina A et al. (2015) The role of early-life educational quality and literacy in explaining racial disparities in cognition in late life. J Gerontol B Psychol Sci Soc Sci 70:557-67
Kovalchik, Stephanie A; Slaughter, Mary E; Miles, Jeremy et al. (2015) Neighbourhood racial/ethnic composition and segregation and trajectories of cognitive decline among US older adults. J Epidemiol Community Health 69:978-84
Gross, Alden L; Benitez, Andreana; Shih, Regina et al. (2015) Predictors of Retest Effects in a Longitudinal Study of Cognitive Aging in a Diverse Community-Based Sample. J Int Neuropsychol Soc 21:506-18
Friedman, Esther M; Shih, Regina A; Langa, Kenneth M et al. (2015) US Prevalence And Predictors Of Informal Caregiving For Dementia. Health Aff (Millwood) 34:1637-41
Weden, Margaret M; Peterson, Christine E; Miles, Jeremy N et al. (2015) Evaluating Linearly Interpolated Intercensal Estimates of Demographic and Socioeconomic Characteristics of U.S. Counties and Census Tracts 2001-2009. Popul Res Policy Rev 34:541-59