CeASES-ADRD Pilot Project Awardees

2021-2022 Pilot Awardees Have Been Selected

We are delighted to announce the four projects selected for the Center for Advancing Sociodemographic and Economic Study of Alzheimer’s Disease  (CeASES-ADRD) 2021-2022 pilot grant awards. These five projects were selected from a number of competitive applications. Please join us in congratulating our newest cohort of pilot grant recipients. Information about applying for the 2022-2023 CeASES-ADRD Pilot Award can be found here.

Karen Fingerman, PhD, University of Texas

Dr. Fingerman is the Wilson Regents Professor of Human Ecology, the founding Director of the Texas Aging & Longevity Center and Director of Research for the UT Austin Center on Aging and Population Sciences.  She has published over 175 papers and chapters addressing changes in relationships with family members, friends, and acquaintances from young adulthood to old age, with particular attention to emotional qualities of ties and support exchanges. She directed the NIA-funded Family Exchanges Study, a longitudinal study of intergenerational relationships involving middle-aged adults, their romantic partners, grown children and aging parents. She also oversees the NIA-funded Daily Experiences and Well-being in Late Life Study looking at older adults’ social relationships and physical and cognitive functioning using a variety of sensory devices and ecologically valid assessments. She received the Distinguished Mentor in Gerontology Award from the Behavioral and Social Sciences section of the Gerontological Society of America in 2020.

Young Adult Caregivers of Aging Family Members

More than 40 million adults in the U.S. provide caregiving to older adults and 1 in 4 of these caregivers are young adults aged 18 to 34. Research and interventions for Alzheimer’s Disease caregiving have focused on middle aged and older caregivers. Young adults may have distinct experiences in caregiving and providing care for older family members may be detrimental to future goals (e.g., education) with lasting repercussions on well-being throughout the life course. This pilot study will develop survey instruments and research methodologies to examine this under-researched group. Aim 1 Develop research battery to assess young adults’ caregiving experiences. We will assess the frequency and types of tasks young adult caregivers perform, their role in the family caregiving system and cultural beliefs about caregiving. Aim 2 Develop of assessments of young adults’ caregiving burdens and well-being We will assess implications of caregiving (positive and negative), including burden, loss of goal-directed statuses (e.g., educational pursuits) and subjective perceptions of control. Aim 3 Generate methodologies of daily sampling of caregiving. Intensive data collection will provide insights into caregiving close to the time these tasks occur. Across all aims, we will consider race/ethnicity, gender, relationship to care recipient and intergenerational coresidence. We will recruit a sample of 80 Hispanic, African American or Asian young adults (aged 18 to 34) who identify as caregivers for an older relative with ADRD (i.e., aged 65+). They will complete a 30 minute baseline survey to adapt existing measures and develop new ones to assess young adults’ caregiving experiences. Then, participants will complete brief surveys every week for 5 weeks. Our research team has extensive experience analyzing data intensive assessments. The proposed study may fundamentally shift the paradigm for understanding how family caregiving occurs, embedded in cultural and socioeconomic contexts.

Sarah Mawhorter, PhD, University of Groningen

Sarah Mawhorter studies housing inequality. She is an assistant professor of housing in the real estate and planning programs of the University of Groningen Faculty of Spatial Sciences. She holds a Master of Planning and PhD in Urban Planning and Development degrees from the University of Southern California Price School of Public Policy, and completed postdoctoral research at the University of California, Berkeley Terner Center for Housing Innovation and the USC/UCLA Center for Biodemography and Population Health. Sarah’s research involves the connections between population and housing, with implications for planning and development. She interrogates the housing market dynamics and urban development processes that contribute to unequal housing conditions—with special attention to disparities between renters and homeowners—and the downstream links between housing and health. Her recent research topics include housing affordability and residential mobility among older adults, student housing development in university neighborhoods, and housing tenure and health. 

Housing Transitions Associated with Cognitive Decline

While existing research addresses the suitability of various housing alternatives for persons with dementia (PWD), little is known about PWDs’ housing transitions over the course of cognitive decline. This study investigates PWDs’ housing transitions using Health and Retirement study data from 2002 through 2016. We find that over half (56%) of PWD move in the years around dementia onset: 28% move once, and 28% move twice or more. Examining various types of moves, we see that slightly over a third of respondents move to another home at some point during cognitive decline, just under a third move into nursing homes, and around ten percent move in with relatives, with overlap between these categories since some PWD move more than once. We find strong patterns by educational attainment and race/ethnicity: Black and Hispanic PWD and those with lower education levels are less likely to move to another home or enter a nursing home than White and college-educated PWD. This suggests the importance of providing support for PWD and their families to transition into different living arrangements as their housing needs change.

Peter May, PhD, Trinity College of Dublin

Dr. May is a health economist at Trinity College Dublin, Ireland with a focus on palliative and end-of-life care.  He works with a network of collaborators across the United States, United Kingdom and European Union using a range of study designs including multi-country randomized trials, quasi-experiments, prospective cohort studies, longitudinal studies on ageing, and retrospective analysis of routinely collected data.  His particular research interests include heterogeneity of treatment effects, outcome measurement in end-of-life care and medical decision-making under high complexity and uncertainty. 

Dynamic Microsimulation Projections of ADRD in Ireland and the United States 

Projecting the future burden of Alzheimer’s Disease and Related Diseases (ADRD) is of critical importance to understand implications for individuals, families, health systems, and government planning.  Previously, the applicants have developed dynamic microsimulation models in longitudinal panel data to estimate statistical models of aging and predict future outcomes. This pilot has five Aims:  1. Extend and validate the TILDA-based microsimulation to model new outcomes: cognitive function, depressive behavior, functional limitations and time spent in residential care; 2. Extend and validate the HRS-based microsimulation to model the depressive behavioral domain of ADRD; 3. Produce population and subpopulation (gender, education, and race) projections, and compare these projections within and between countries; 4. Recommend best practices for projecting cognition, depressive behavior, functional status, and ADRD to guide other researchers using panel studies similar to HRS and TILDA.  Scope the potential for novel inclusion of biomarkers and laboratory measures in projections; 5. Use the results as a basis for large-scale international study proposal to project future needs, estimate future health and social care costs, and evaluate the effect of different systems and payment models on care, health and economic outcomes. We anticipate three outcomes associated with the pilot aims: (a) Projections of ADRD prevalence, associated depressive symptoms and functional limitations, and associated residential care use in the United States and Ireland, for the population and for subgroups of interest (Aims 1-3); (b) Lessons learned in validating the domains of ADRD will be documented to inform other modelers undertaking similar work, including assessment of how biomarkers and lab data may improve prediction (Aim 4); (c) An R01 proposal for modeling future ADRD prevalence and associated costs in different countries covered by the g2aging family of longitudinal studies (Aim 5).

Leah Richmond-Rakerd, PhD, University of Michigan

Dr. Richmond-Rakerd is an Assistant Professor of Psychology in the Clinical Science area at the University of Michigan. She received her Ph.D. from the University of Missouri; completed her clinical internship at the Durham Veterans Affairs Medical Center; and completed postdoctoral training at Duke University, supported by a fellowship from the NICHD through the Carolina Consortium on Human Development. Dr. Richmond-Rakerd’s research focuses on the origins, mechanisms, and outcomes of emotional and behavioral dysregulation, including the consequences of self-regulation difficulties for processes of aging and neurodegenerative disease. She uses genetically-informative, longitudinal, and nationwide administrative-register study designs in her research. 

Do Mental Disorders Forecast ADRD in Nationwide Administrative Registers?

Neurodegenerative conditions, including Alzheimer’s disease and related dementias (ADRD), have an outsized impact on disability and loss of independence in older adults. As such, there is a growing need to identify modifiable factors that drive variation in ADRD risk at the population level. We propose to investigate mental disorders as a potential preventable risk factor for later-life ADRD. Using three decades of nationwide health-register data on 1.7 million New Zealand citizens aged 21-60 at baseline, we will test whether mental disorders forecast the development of ADRD in the subsequent 30 years. We will test whether these associations hold across sex and age, across different types of mental disorders, within pairs of siblings matched on family-level risk factors, and after controlling for pre-existing physical-health conditions. Through this project, we will (1) quantify the degree to which preventing mental-health problems in young people might reduce the health and social burden of neurodegenerative diseases, and (2) create exportable tools, including a new linked-sibling data resource and a method for ascertaining ADRD across multiple health registers, that can be used by other ADRD researchers employing linked administrative data in their work. If results of the proposed project indicate that mental disorders forecast neurodegenerative diseases, this would also suggest novel hypotheses about mechanisms that underlie the development of ADRD and that may drive variation in ADRD risk across populations (e.g., inflammation, low education, poor health behaviors, social isolation, or psychiatric medications), to be tested in future basic-science and administrative-register studies.

2020-2021 Pilot Awardees

National Longitudinal Study, 1972 (NLS-72) Record Matching to Centers for Medicare and Medicaid Services (CMS) records. Investigator: Chandra Muller, PhD, University of Texas, Austin 

Education is among the most important determinants of later life cognitive health. Over the life course, education leads to better cognitive functioning and healthier aging through access to better jobs, health care, residential neighborhood, wealth accumulation, and economic security. But, research on early-life educational processes that affect cognitive functioning has been severely limited by a lack of prospective longitudinal data. We do not have data sufficient to identify the specific (and potentially manipulability) organizational, curricular, social, or skill aspects of education that shape cognitive functioning. The proposed project will: link information from sample members of the National Longitudinal Study of 1972 NLS-72 cohort to CMS records; use information gained from matching to provide valuable data on health for analysis of educational precursors (adolescence and early adulthood) of health and cognitive aging among individuals in their mid 60’s as they enter old age; and establish a proof of concept and results for potential re-interviewing of the NLS-72 sample members. The proof of concept will involve not only the possibility of locating respondents but also the value of the education data as a resource for understanding cognitive aging. This study would create new data for analysis of the role of education in cognitive aging among individuals currently age 65 and older. It will also make possible comparisons to the HS&B cohort that is approximately a decade younger.

The Impact of Cognitive Screening on Early ADRD Diagnosis, Treatment and Spending. Investigators: Mireille Jacobson, PhD, University of Southern California; Jason Doctor, PhD, University of Southern California 

As part of a new benefit created under the Affordable Care Act (ACA), Medicare now covers an Annual Wellness Visit (AWV) that requires, among other things, an assessment to detect cognitive impairment. In newly collected data on about 1000 seniors ages 65 and over, we find systematic differences by Medicare plan type (traditional fee-for-service vs. commercial Medicare Advantage (MA)) in the likelihood that seniors ever received either an annual wellness visit or a cognitive assessment. Seniors enrolled in MA plans are about 20 percentage points (p<0.001) more likely to have had an annual wellness visit than those in traditional Medicare (traditional group mean = 47%) and about 13 percentage points more likely to have had a cognitive assessment (traditional group mean = 30%). These findings hold even after controlling flexibly for age, gender, race, education, retiree status, general health and mental health status. The specific aims of the broad project are to: (1) Assess whether, consistent with higher self-reported screening rates, MA plan enrollees are more likely to receive an early ADRD diagnosis, where early is captured by age or an MCI diagnosis; (2) Describe health care service use before, during, and after a beneficiary screens positive for cognitive impairment both overall and by plan type (traditional versus MA); (3) Assess the impact of early diagnosis on the trajectory of health care use and spending. In this pilot, we will leverage the difference in MA plan cognitive screening to study the implications for early diagnosis, treatment and spending. Combining both Medicare Fee- for-service claims and MA plan encounter files, we will study how plan type affects the likelihood of an early ADRD diagnosis, where early is defined as prior to and including age 70. As an alternative definition of early diagnosis, we will consider diagnosis of mild cognitive impairment (MCI). Conditional on a diagnosis, we will describe health care utilization and spending and the impact of early diagnosis on them. These aims will help fill an enormous gap in our understanding of the impact of early ADRD diagnosis on health care utilization and spending in both the short and long term.

ADRD Care in New Delivery and Payment Models. Investigator: Alice Chen, PhD, University of Southern California 

Over the last few decades, US health policy has focused on new payment and delivery models to improve the organization and financing of care. Within the Medicare population, there has been a shift away from traditional fee-for-service payments toward alternative payment models that emphasize value-based care. However, there is little empirical evidence on the efficacy of these programs in managing the care of patients with ADRD. In this pilot, we will estimate the impact of new payment and delivery models—including accountable care organization (ACO) models, patient centered medical care homes (PCMH), value-based payment modifiers, and merit-based incentive payments (MIPS)—on the health care and drug use and cost for ADRD patients. Data on health care and drug use will come from Medicare claims data from 2008 to 2019. Data on provider (a) ACO participation will come from the Centers for Medicare and Medicaid Services’ (CMS) Medicare Shared Savings Program Files from 2013 onward and the Next Generation ACO variable in the Carrier Claims data from 2016 onward, (b) PCMH participation will come from the National Committee for Quality Assurance’s PCMH practice location files from 2012 onward; and (c) provider value-based payments from CMS’ Value Modifier NPI-Practice file from 2013-2016. We anticipate that data on MIPS incentives, which affected Medicare Part B reimbursements in 2019, will be available from administrative claims data. For each delivery model, we will employ a differences-in-differences framework that compares providers and beneficiaries participating in the model (treatment) to those unaffected (control), pre- and post-model implementation. We will focus on responses by primary care providers of ADRD patients and consequential changes in ED reliance, hospital lengths of stay, and access to new technologies among ADRD patients. Results from this research will identify which delivery and payment models are most effective in improving dementia care.

Trends and Projections of ADRD in Asia. Investigators: Jay Bhattacharya, MD, PhD, Stanford University; Karen Eggleston, PhD, Stanford University 

Dementia prevalence is increasing at an even faster rate in Asia than many other parts of the world. The study will focus on the social and economic burden of ADRD over the life course in heterogeneous Asian populations, with three specific aims: (1) To develop innovative methods for estimating cognitive decline and dementia incidence and prevalence in Asian economies within pseudo-panel-based microsimulation models such as the Japanese Future Elderly Model (JFEM); (2) To study heterogeneity in the future disability burden associated with dementias and the implications for labor supply, and caregiver burden, using microsimulation models; and (3) To project the implications of cognitive decline and ADRD for health spending and long-term care spending in East Asia. We will work with members of the Japanese Future Elderly Model (JFEM) team to extend the current microsimulation model built from repeated cross-sectional data to include cognitive function and dementia. We will use this expanded JFEM to study the social and economic burden of ADRD in Japan, and compare to other FEM for North America and Europe. Existing Asia microsimulation models include those for South Korea and Singapore, with a model under development for Taiwan, and in the planning stages for Hong Kong, the rest of China, and India. We will project the health and cost implications of cognitive decline and ADRD and implications of long-term care insurance (LTCI) programs in Japan and South Korea. Changing educational attainment within and across countries, is one important element of heterogeneity for understanding cognitive decline and ADRD burden. Our research will be important for understanding these important changes in Asia and their interaction with rapid demographic and economic change.