Through secure, direct access to IRS tax records, WAM is finalizing the creation of measures of the income and wealth holdings of the entire U.S. population and their linking across generations, extending pioneering work by Raj Chetty and collaborators, Emmanuel Saez and Gabriel Zucman, and others.

WAM will publicly release a large, granular set of statistics based on these measures, both at the national level and across multiple subnational geographies. This new data infrastructure will enable novel analyses of wealth inequality and mobility. WAM also prioritizes user-friendly dissemination to make the data easily accessible to local, state, and federal policymakers, community organizations, journalists, and the broader public.

WAM will analyze the levels, inequality, segregation, and intergenerational mobility of wealth and income across the full U.S. population, in order to answer questions such as:

• How does per-capita wealth vary across the country?
• How do wealth and income disparities differ across states and counties?
• How does residential segregation by wealth compare with segregation by income?
• How strong are the intergenerational correlations in wealth and in income?
• Which U.S. areas exhibit higher and lower rates of intergenerational wealth mobility?

Housing insecurity is a pressing public health problem: U.S. rates are the fastest-growing among older adults, one-third of whom spend more than 30% or 50% of their income on housing. Housing insecurity – defined as limited access to and availability of affordable, stable, safe, and adequate housing and neighborhoods – is a risk factor for numerous adverse health outcomes including chronic conditions, disability, and mortality. Although federal housing assistance is associated with improved health outcomes, current programs support only about one-third of income-eligible, cost-burdened adults aged 50+ who need assistance. Moreover, the relationship between housing assistance, housing insecurity, and adults health and disability trajectories remains poorly understood.

One unexplored area is how housing assistance and multiple dimensions of housing insecurity experienced during emerging adulthood, a critical life course period, relate to midlife and older adult health and disability trajectories. While previous research has examined effects of housing assistance and housing insecurity on health, studies often use cross-sectional or convenience samples, focus on a single rather than combined effects of multiple housing insecurity dimensions, and rarely include income-eligible older adults who do and do not receive housing assistance. Examining how previous housing histories relate to health and disability later in life will enhance our understanding of when housing assistance and housing insecurity matter most, and inform future housing interventions.

This study leverages more than 50 years of nationally representative, prospectively-collected longitudinal life course data from the Panel Study of Income Dynamics to examine how midlife and older adult health and disability trajectories relate to housing assistance and housing insecurity experienced during emerging adulthood, a critical life course period. This project seeks to: (1) develop typologies of housing assistance and housing insecurity life course histories for midlife and older adults; (2) examine how trajectories of health and disability during midlife and older adulthood relate to previous histories of housing assistance and housing insecurity; and (3) assess the extent to which relationships between midlife and older adult health and disability trajectories and housing history typologies vary by neighborhood context.

Complementing this research, a detailed training plan will build on the applicants prior training in environmental psychology and architecture to include (1) aging, gerontology, and life course theory; (2) age-related disability, mobility, and physical function; (3) longitudinal survey data analysis skills, including latent variable modeling; and (4) external grant-writing skills. This integrated training will prepare the applicant for a successful independent research career focused on aging, housing, and neighborhoods.

Findings from this proposal will generate critical insights concerning how and when housing assistance and housing insecurity matter most for midlife and older adults health and disability, inform future housing interventions, and elevate older adults need for housing assistance.

Since its inception in the early 1960s, the Social Environment and Health Program (SEH) has been a leader in the development of theory and research on the major role of psychosocial factors in the etiology and course of both mental and physical health and illness. Founded as a cross-disciplinary program, the program has been home to The Americans’ Changing Lives (ACL) study for over thirty years, which is the oldest ongoing nationally representative longitudinal study of the role of a broad range of social, psychological, and behavioral factors in health and the way health changes with age over the adult life course. Visit the ACL website for more information.

Today, SEH maintains the foundational tenet that health is socially determined by the confluence of factors at the individual, environmental, and societal level over the adult life course. We specialize in integrating knowledge from across multiple disciplines and using innovative & cutting-edge methods to characterize the social and environmental contexts in which people live their lives. Our interdisciplinary faculty includes social, environmental, psychiatric, and infectious disease epidemiologists, as well as gerontologists, climate scientists, and experts in human-centered design. Our work examines interrelated contextual exposures such as the residential neighborhood social and built environment, climate events, housing conditions, and the contexts that shape the distribution of infectious pathogens and their consequences. We do this work with particular attention to issues of health equity. We examine a broad range of health and behavioral outcomes including cognitive function, disability, musculoskeletal health, serious mental illness, sleep, and housing instability.  We also interrogate the factors & processes that may link or modify the relation between the environment and these health & behavioral outcomes, including biomarkers of premature aging and housing modifications. 

How has the home mortgage interest deduction affected White-Black wealth gaps over the past several decades? This project will answer this question by using the NBERs TAXSIM program, which calculates federal and state income tax liabilities from typical survey data, to generate novel estimates of the wealth savings that households in the Panel Study of Income Dynamics have received from the mortgage interest deduction from 1984-2021.

Landscapes of Population Health (“Landscapes”) is an interdisciplinary research collective that includes historians, sociologists, psychologists, epidemiologists, and statisticians who bring their expertise in historical and contemporary racial violence and control, environmental justice, epigenomics, and population health to study the link between structural racism and population health. We bring together critical theories from the humanities and innovative potential biological mechanisms from the bench and medical sciences to better understand the root causes of patterns in population health. Our work includes active data collection, work on existing data sets, and the development and implementation of measures. In addition to our focus on the science itself, we are committed to changing the demography of the scholars who drive our epistemology.

Landscapes Collaborators outside of ISR

• Hedwig Lee
• Michael Esposito
• Dayna Johnson
• Sara Adar
• Kelly Bakulski

A major limitation faced by researchers working within the Internal Revenue Service (IRS) data infrastructure is the absence of any information on race and ethnicity. The same limitation also affects researchers who use tax data in other environments, such as the U.S. Government Accountability Office and the U.S. Department of the Treasury. Additionally, the lack of race and ethnicity measures is an important constraint for researchers using other administrative data—for instance, Social Security Administration information on earnings or state-level information on unemployment insurance income—to carry out research on economic inequalities. This project proposes the application, validation, and extension of a new method that addresses the problem of lack of self-reported race/ethnicity in tax and other administrative data. It will take advantage of a unique opportunity to access restricted data through a new collaboration with researchers at the U.S. Census Bureau. Through an internal Census project, the project will be able to produce gold-standard validation studies of the method’s ability to estimate racial and ethnic inequalities in economic outcomes with data lacking self-reported information on race/ethnicity.

We are only beginning to clarify the ways the COVID-19 pandemic has resulted in substantial changes to American neighborhoods. There has been an excess of permanent business closures, particularly among small neighborhood businesses most vulnerable to social distancing, such as local barbershops and nail salons. COVID-19 outbreaks in late September 2021 caused 2,000 neighborhood schools to close for an average of six days in 39 states.

A burgeoning body of research has tried to understand the forces driving these trends, focusing on infectious disease transmission at the individual level or economic models at the business level. What is not considered is the context in which these changes are taking place. By context, we mean the neighborhood community environment that holds the opportunities, restrictions, risks, and flexibility for post-pandemic growth. The community environment includes:

1. Job opportunities in business sectors robust to social distancing;
2. Comprehensive broadband internet access to facilitate telemedicine, online schooling, remote work, and online grocery shopping;
3. Parks and walkable streets to facilitate socially distanced physical activity and social interaction to mitigate social isolation brought on by the pandemic; and
4. The provision of medical care through the availability of alternate health care providers and pharmacies.

Access to these neighborhood resources is not equally distributed across America, reinforcing risk for vulnerable populations, including older adults, children and adolescents, racial/ethnic minorities, and those in rural areas. However, a lack of national, standardized, longitudinal metrics of the local neighborhood environment has hindered the ability to identify which communities are most vulnerable to the immediate and longer-term consequences of the pandemic for a host of behavioral, psychological, social, and economic outcomes.

To address this limitation in the nation’s data infrastructure, we will augment, curate and disseminate data from our National Neighborhood Data Archive (NaNDA). This dataset includes a wealth of physical, social and economic characteristics of the local neighborhood across the United States (e.g., racial segregation, business density, environmental hazards, broadband internet access, and healthcare availability), in the years both before and since the pandemic. We will participate with the Consortium on Social, Behavioral, and Economic Research on COVID-19 to integrate, share, and analyze spatially referenced neighborhood data that can be readily linked to existing survey data, cohort studies, or electronic health records at various levels of geography. We will work with the COVID-19 Consortium Coordination Center to identify and create key neighborhood metrics that are priorities for research teams in the Consortium, including a set of common data elements (CDEs) on the social, behavioral and economic indicators of the COVID-19 pandemic at the neighborhood level. We will also develop new metrics of longitudinal neighborhood change in the decades preceding the pandemic, which can inform community risk and resilience since the pandemic.

While risk factors for cognitive decline and Alzheimer ’s disease and related dementias (ADRD) have been widely studied, there is still much unknown about the biological pathways that lead to ADRD. This project seeks to improve our understanding of the pathophysiology of cognitive decline and ADRD by examining the role of peripheral immunosenescence in these processes. A major gap in existing research is a lack of longitudinal studies that can establish an etiologic link between peripheral immunosenescence and development of incident ADRD. In addition, there are few population-based studies examining these processes in U.S. representative samples. Population-based studies can evaluate whether clinical findings among ADRD patients are generalizable to the broader population as well as examine the role of social determinants in these processes. Despite consistently observed social inequalities in ADRD, including based on race/ethnicity, sex/gender, and socioeconomic status, we do not yet understand the pathways by which social disadvantage lead to ADRD, limiting population-wide ADRD prevention strategies. Our long-term goal is to elucidate the role of population immunity in predicting ADRD. Our objective for this research is to evaluate the relationship between peripheral immunosenescence and domain-specific cognitive function, decline, and ADRD diagnoses in a nationally representative sample of older US adults, and, to examine the extent to which immunosenescence explains social inequalities in cognitive function, decline, and ADRD. Our central hypothesis is that immunosenescence, characterized by an increased number of senescent immune cells (e.g., CD8+CD45RA-, CD4+CD45RA-) and elevated inflammatory cytokines (C-Reactive Protein (CRP), interleukin (IL)-6, TNF-alpha) will be associated with worse cognitive outcomes, and that immunosenescence will partially explain some of the social inequalities in cognitive outcomes. Our rationale is that immunosenescence may be an important early risk factor for ADRD, potentially representing a biological mechanism explaining population heterogeneity and inequalities in ADRD risk. To investigate these relationships, we will pursue three specific aims:

1. Determine the association between peripheral immunosenescence and cognitive function and decline in the Health and Retirement Study (HRS);
2. Determine the association between peripheral immunosenescence and incident ADRD measured both by HRS cognitive assessment and linked Medicare claim data; and
3. Determine the extent to which immunosenescence explains social inequalities in cognitive function, decline, and ADRD.

This project is the first large-scale population-based study of immunity and cognition. It will yield critical insights to our understanding of the pathophysiology of cognitive decline and ADRD, and inequalities in these processes. This project is significant because the results could point to new diagnostic tools able to discern profiles of immunosenescence predictive of ADRD in the peripheral blood.

The intergenerational persistence of poor health and poverty and the quest to understand underlying processes underscore the importance of rich multigenerational data. Very few existing datasets contain comprehensive information on social, environmental, and biological factors over the life course and across generations; lack of such data has seriously limited attempts to identify the processes shaping health disparities, economic inequalities, and causal linkages between the two. The Fragile Families and Child Wellbeing Study (FF) is the longest running birth-cohort study in the U.S The study is based on a national probability sample and follows parents — both mothers and fathers — and their children who were born in 1998-2000. Based on birth statistics, the children in FF are now having children of their own. We are expanding the FF study by conducting a perinatal survey on the health of this third generation of children, early parenthood experiences of the second generation. We are examining the characteristics of households and families into which the third generation are born, as well as collecting biological specimens from the new children and their non-FF parents. The augmented data will have many unique and valuable features, including:

1. extensive data on three generations of families: children, parents, and grandparents;
2. data on siblings and half-siblings (in the third generation);
3. three generations of exposures and genetic and epigenetic data;
4. genetic data on trios (third generation children and both of their parents); and
5. comprehensive data on perinatal health (pre-pregnancy, prenatal, delivery, neonatal, and postpartum factors including breastfeeding and postpartum depression) and circumstances in the second and third generations.

The Fragile Families Third Generation study will facilitate novel and important analyses of intergenerational transmission of health, intergenerational relationships within families, and gene-environment effects on health. It will also provide an essential foundation for future third generation data collection at subsequent developmental transitions including school readiness and emerging adulthood.