University of Pennsylvania

PARC supports highly interdisciplinary research on aging by funding pilot projects, hosting a weekly seminar series and a working paper series, and maintaining a secure data enclave for access to sensitive aging-related data. Research associates conduct research on population and individual processes in the areas of aging, including the determinants and effects of population composition and processes. They are also involved in large data collection projects in the U.S. and abroad.

Research Themes
Health disparities in aging; Early life conditions and older adult health; Behavior and well-being; global aging and health; Health care and long-term care in older adults; Cognition and Alzheimer’s Disease and Related Dementia (ADRD); COVID-19 & Aging.

Pilot Projects

  • 2021. C. Boen. Uneven Spillover Effects of Police Violence: Police Shootings and Disparities in Emotional Well-Being.

    In 2018, 992 people were shot and killed by the police in the United States. Black men are at particularly high risk of deadly police violence relative to other groups. In addition to direct consequences of this violence, studies document a host of spill-over effects of police violence, including decreased trust in the police and increased legal cynicism. Given racial disparities in risk of police violence and a broader context of structural racism in the U.S., the collateral consequences of this violence are magnified for Black communities. Now, with the rise of portable video recorders and social media, police violence that was only observed in situ is recorded and broadcast to a global audience, made viral, and viewed repeatedly, broadening the potential reach of these spillover effects. At the same time, forms of social connectivity like Twitter offer individuals platforms for expressing their emotions in real time, offering researchers valuable insight into the effects of widely publicized events, including police violence. A growing body of research aims to identify the spillover effects of police violence, but critical gaps in scientific understanding of the role of police violence in shaping emotional and psychological outcomes—as well as population disparities in well-being—remain. The proposed project improves scientific understanding of the population impacts of police violence by using a corpus of text data from Twitter and computational text analysis to evaluate the emotional spillover effects of police violence and assess racial-ethnic, gender, age, and geographic variation in the associations between police violence and emotional well-being. The project uses longitudinal data, a quasi-natural experiment design, and two cases—the shootings of Michael Brown and Tamir Rice—to assess whether and how police violence affects the emotional well-being of individuals, paying particular attention to the stress-related psychological processes undergirding these links as well as differential vulnerability to these events. This project will expand and shift scholarship on police violence and population disparities in well-being in three key ways. First, this study leverages big data and cutting-edge computational methods to examine the impacts of police violence on population well-being. While most research in this area relies on survey data, our use of Twitter data will allow for improved understanding of how these events shape individual and population well-being in real time. Second, we use a quasi-experimental design and difference-in-difference models to assess the links between police violence and emotional well-being, thereby improving our ability to make causal inferences. Finally, we use a variety of techniques to code sociodemographic characteristics and test for differential vulnerability of exposure to police violence by race, gender, age, and geography, providing new evidence of the role of police violence in shaping inequities in emotional and psychological well-being. Findings from this study will generate new understandings of the spillover effects of police violence, particularly as these events shape individual emotions in ways that relate to individual health and contribute to population health disparities. Results from this project will be inform applications for subsequent extramural funding focused on the links between police violence, emotions, and population disparities in psychological well-being.

    Priority Research Areas: Determinants of Health, Well-Being and Longevity


  • 2021. C. Low. Reproductive Disability: The Link Between Infertility and Economic Well-Being for Women in Zambia.

    It is widely acknowledged that disability results in a permanent downward shift in worker’s incomes, and thus consumption. In other words, workers are not fully insured against these negative shocks in labor market productivity. There is much less attention to another form of disability, that of secondary infertility, which may affect women economically if they are partly dependent on male partners for economic support. In this project, I will test whether infertility materially impacts women’s economic well-being similarly to how worker disability affects their earnings. The long-term plan for this project is to collect longitudinal data over a two-year period on 1,000 women in Zambia to measure how consumption, health, and economic wellbeing co-move with fecundity and spousal expectations of fecundity. The longitudinal data will allow an event study analysis with individual fixed effects to show that the onset of infertility, or “reproductive disability” is associated with a loss of consumption and economic wellbeing. In the initial pilot phase, I will begin enrolling the first 400 women in the survey, as well as analyze existing DHS data in Zambia to demonstrate the connection between infertility and loss of consumption.

    Priority Research Areas: Disability, Health Care and Long-Term Care


  • 2021. R. Greysen. Gamification to Improve Physical Activity in Seniors at Risk for Alzheimer's.

    Increased physical activity by walking further or more vigorously may delay the development of Alzheimer’s Disease and Related Dementias (ADRD) and associated cognitive decline but reaching higher levels of activity and maintaining it as a long-term habit is difficult to do. This project will use concepts from behavioral science to create a mobility game that people at risk for developing ADRD can play in order to increase their levels of activity while having fun doing it. The game is played with a support partner who is a spouse, family member, or close friend who provides feedback and encouragement to help the game-player reach activity goals and maintain them as habits over time. Participants in the game will use their own smartphone and a wristwatch that tracks activity (such as a FitBit, provided by this study) to set goals, get feedback, and play the game for 12 weeks. Participants will be asked to continue wearing the wristwatch for another 6 weeks to track activity after the game is over. To determine the effectiveness of this game, we will randomly assign 50 people to the game and 50 people to only get the wristwatch but no game component. All participants in this study will be recruited from the GeneMatch registry which offers genetic testing on risk for ADRD to all participants. We will recruit participants to our study who have elevated genetic risk as well as those without specific genetic risks to see if either group responds differently to the game. The short-term goal of this study is to determine the feasibility of remotely recruiting and engaging older adults at high risk for developing ADRD from an existing Alzheimer’s cohort study. We hypothesize that we will be able demonstrate the efficacy of gamification to increase physical activity in this pilot population as well as explore differential effects of high-risk genotypes and demonstrate the ability to collect functional and cognitive measures remotely. These results will enable competitive applications for larger studies (NIA R01) immediately after the completion of this pilot. The long-term goal for this project is to launch a successful new line of inquiry into physical activity in patients with ADRD by adapting and applying behavioral economics approaches such as gamification which have been successfully developed for other populations.

    Priority Research Areas: Effects of Interventions on Population Health


  • 2021. W. Roth. How Does Genetic Ancestry Testing Affect Perceptions of Race?.

    The proposed research will evaluate the relative influence of genomic, phenotypic, social attributes, and social context in shaping how individuals perceive other people’s race, to determine how genomic information is influencing societal norms of racial classification. The larger project will conduct a conjoint survey experiment that includes unique morphed photographs, information about genetic ancestry test (GAT) results, and social attributes like racial self-identification before and after testing, to influence the racial classification of others by White, Black, Hispanic, and Asian respondents. The pilot project will develop and test the morphed photographs to be used as the visual stimuli in the experiment. GATs are one of the most common ways that genomic awareness has increased in the public sphere. Many scholars believe GATs will shape individuals’ beliefs about race, including beliefs in essential racial differences and that races are genetically determined. Recent research shows that GATs lead some people to change their racial identity based on the reported genetic information. However, we know little about whether those genetically-influenced identity claims are accepted by others or whether information about an individual’s genetic ancestry influences how their race is perceived. Increased genomic knowledge may be shifting norms of racial classification. This could have significant social implications ranging from demographic shifts and identity-based political mobilization to changing patientprovider interactions and assessments in healthcare settings. In everyday life, people typically rely on phenotype to racially classify others, often using it as a proxy for ancestry. However, we know little about how the perception of phenotype interacts with information about ancestry, which we will test using photographs of human faces and hypothetical GAT results. In addition, an abundant scholarship has shown that race is shaped by social context. Nevertheless, most studies have been observational and may be afflicted by endogeneity. We will provide rigorous experimental evidence for how the social context influences racial classifications: some respondents will be asked to categorize individuals seeking membership in a cultural affinity group; others will be told the individual is applying to college, priming a context of competition for scarce resources; the remainder will be given a neutral context. Last, our nationally representative survey will sample Black, White, Asian, and Hispanic respondents, which will allow us to test how racial perceptions vary across the U.S. and among the nation’s largest ethnoracial groups. This project will develop a research protocol and preliminary data for a larger future study focusing on how genomic information shapes healthcare providers’ racial perceptions and clinical assessments of patients.

    Priority Research Areas: Biology, Genetics and Demography of Aging


  • 2020. I. Kohler. Comparative Cognitive Health Changes in Low-Income Settings.

    This projects overall aim is to lay foundations for a program application to examine for the first time individual variation and age-related changes in cognitive health in mature adults across non-WEIRD (Western, Educated, Industrialized, Rich, Democratic), low-income populations with the ultimate goal to understand if cognitive aging follows universal trajectories and/or is determined by environmentally dependent mechanisms. The project focuses on comparative analysis of longitudinal data on cognition among mature adults using data sets covering substantial segments (at least two decades) of the life-cycle in three very distinct relatively low-income populations in Bolivia, Guatemala, and Malawi.

    Priority Research Areas: Cognitive Aging and the Demography of Dementia


  • 2020. M. Candon. Understanding Nursing Turnover: The Case of Home Health.

    High levels of turnover in professions that rely heavily on skill acquisition is a major source of inefficiency due to productivity loss, termination costs, vacancy, orientation and training, and other spillovers. Turnover among nurses, a bedrock in health care, is a particular concern given the amount of direct care they provide patients – indeed, compromised nursing care has been associated with longer lengths of stay and higher rates of adverse outcomes, including mortality. To date, most studies of nursing turnover have focused on inpatient nurses in hospitals using self-reported survey data and are therefore limited in scope. No projects have been able to cleanly connect nurses to patients, making it impossible to understand the full impact of nursing turnover. This project will leverage a collaborative agreement between the University of Pennsylvania and Encompass Home Health, which is one of the largest home health agencies in the country, currently operating in 30 states. We will acquire a host of different datasets from Encompass to answer two main questions: first, which factors drive nursing turnover in home health; and second, how does nursing turnover in home health affect patient outcomes such as hospitalizations and mortality? Using variables constructed from human resources, payroll, visit logs, and other secondary data sources, we will include a host of potential factors that may drive turnover, e.g., driving time, patient acuity, and outside labor market opportunities, in order to construct an algorithm that can flag nurses at high risk of turnover. This will allow for more tailored personnel interventions to improve retention among home health nurses at Encompass. Next, we will use these unique data to explore the confounded relationship between nursing turnover and patient outcomes. Because home health nurses work alone or in tandem with other provider types, we are able to connect individual nurses to individual patients. That, along with more rigorous statistical approaches, gives us an unprecedented opportunity to pin down the causal pathway between nursing turnover and patient care.

    Priority Research Areas: Disability, Health Care and Long-Term Care


  • 2019. P. Gonalon Pons. The Persistent Feminization and Devaluation of Elder Care.

    Care work, both paid and unpaid, is currently under unprecedented pressure. Population aging and the lengthening of life expectancy are increasing demand for care labor, at the same time that existing social arrangements to meet care needs for the elderly are falling short. The pool of both paid and unpaid caregivers is compressing, in part due to the high economic penalties to specializing in caregiving, either in the family or in the market. This project argues that the feminization and devaluation of caregiving are central to understand shortages in caregiving labor supply and thus central, too, to imagine solutions to the current care crisis. To test this argument, I propose the first comprehensive and comparative analysis about the feminization and devaluation of elder caregiving across countries and care domains –paid and unpaid caregiving. I will use data from the Luxembourg Income Study (LIS) on paid care workers and data from the Multinational Time Use Survey (MTUS) on unpaid caregiving. Both datasets compile and harmonize nationally representative surveys and cover 30 countries and span over 4 decades. These data will be combined with a social policy dataset that will compile policy tools that shape the distribution and penalties of paid and unpaid caregiving (i.e. care leave, care allowances, pension regimes, etc.). This will build an unprecedented map on the political economy of elder care that will serve as a springboard for a novel research agenda on the origins and implications of devaluation and feminization of eldercare. This project contributes to the theme on economics and financing of health and aging by offering a gender and labor perspective that integrates and highlights the interdependency between paid and unpaid caregiving. This perspective will be developed to empirically interrogate how and why the feminization and devaluation persists over time and how it can be undone. This project also fills key gaps in sociological literature about paid and unpaid care work. This project presents the first large-N cross-national study of elder caregiving, it will integrate scholarship on unpaid and paid caregiving, and it will systematically examine the relationship between feminization and devaluation. Taken together, this project will offer a birds’ eye view on the political economy of elder care and why it matters for the future of caregiving, the well-being of the elderly, population health, and the economy at large.

    Priority Research Areas: Disability, Health Care and Long-Term Care


  • 2019. S. Stites. Study Partners: Who are the research partners of persons with Alzheimer's disease and does it matter?.

    Alzheimer’s disease (AD) is the most common cause of dementia, affecting 5 million older adults in United States and causing cognitive and functional impairments that limit the ability to carry out activities of daily living.1 As a result, other individuals usually become involved in the care of persons with AD (PwAD). These individuals serve as “study partners” who report on cognitive function and other outcomes of PwAD in research studies, including clinical trials, and as “caregivers” assisting PwAD with IADLs and BADLs and informing on the functioning and wellbeing of PwAD during medical visits. They have powerful roles in the safety, health, and quality of life of PwAD and in the feasibility and integrity of AD trials. Many prior studies have examined the characteristics and outcomes of caregivers of PwAD but little is known about study partners. Who are they and how does who they are impact how reliably they report on the cognition of PwAD? It is crucial we learn the answers to these questions.  In this proposed study, we focus on characterizing study partners (N=532) of community-dwelling PwAD who were age 70 or older at the time of initial interview in Aging, Demographics, and Memory Study (ADAMS), a subsample of the Health and Retirement Study (HRS) that is nationally representative of older adults 70 and older. The purpose is to characterize study partners in nationally representative samples [specific aim (SA) #1], examine how being a study partner corresponds to caregiving duties (SA#2), and evaluate how characteristics of study partners correspond to how they report on cognition of PwAD (SA#3). Descriptive statistics and 95% confidence intervals will be used to describe and compare the demographic characteristics of study partners. Bivariate and multivariable generalized linear models will be used to examine the cross-sectional and longitudinal associations between study partner characteristics and each their engagement in caregiving duties and how they report on the cognition of PwAD.  This study advances what is known about SPs of PwAD by describing their characteristics in a population-based subsample and how, if all, their characteristics associate with patterns between being an SP and caregiver for PwAD and how they report on the cognitive function of PwAD. What’s discovered will inform design of AD clinical trials and also inform education materials for use in clinical care. The findings from this study will develop important pilot data to be used in submission of multi-site cohort study to NIH NIA that will build upon the existing HRS framework in order to study the experiences of both persons with “preclinical AD” (cognitively unimpaired persons with biomarker evidence of AD) and their study partners.

    Priority Research Areas: Cognitive Aging and the Demography of Dementia


  • 2018. I. Kohler. Social Networks, NCDs and Aging: Leveraging Social Dynamics for Efficient Health Interventions among Older Persons in Low-Income Countries.


  • 2018. K. Lasater. Evaluating A Hospital Intervention to Improve Care for Older Adults at the End of Life.


  • 2017. A. E. Curry, PI. Examination of population-based driver licensing and motor vehicle crash rates among older adults.


  • 2017. C. Boen. Biological Risk, Physical Functioning, and Psychosocial Stress among Older Age Hispanics.


  • 2017. M. Ryerson. Towards an Accessible Healthcare Travel Chain for Elderly Populations Through User-Centered Anthropologic Approach.


  • 2016. M. McHugh. The Effect of Nursing Work Environments on Alzheimer's Disease Patient Outcomes.


  • 2016. S. Preston. The Contribution of Diabetes to Mortality in the US.


  • 2016. HP Kohler. Mental Health, Migration and Mortality among Mature Adults in Malawi.


  • 2016. J.V. Ríos-Rull. Health Status and Consumption Growth.


  • 2015. C. Flippen. Transnational Aging: The Link Between Migration and Aging in Mexico.


  • 2014. L. Aiken/H. Smith. Healthcare Workforce and Quality Outcomes: Lessons from Chile, United States, and Europe.


  • 2014. J. Behrman. Early Life to Mature Adulthood: Guatemalan INCAP Health and Socioeconomic Data.


  • 2014. C. Flippen. Transnational Elder Care and the Financial Security of Low Income Mexican Immigrants in the US: A Case Study of Philadelphia, PA.


  • 2014. A. Starc. Pass-Through in a Highly Regulated Supply Chain - The Who, What, and Where of the US Drug Market.


  • 2013. I. Elo. Health and Well-being of African Migrants in the US and in their Country of Origin.


  • 2013. M Guillot. Study of Adult and Old-Age Mortality among Migrants and Their Descendants in France.


  • 2012. C. Valeggia. Metabolic Profiles of Female Reproductive Aging: A Comparative Study.


  • 2012. E. Fernandez-Duque. Sex Differences in the Life-History and Demography of Socially Monogamous Primates.


  • 2012. I. T. Elo. The Health of Black Immigrants in the United States and Comparisons with Countries of Origin.


  • 2012. IV Kohler/HP Kohler. Mental Health, Cognition and Aging in a Poor High-Risk Disease Environment.


  • 2012. J. Thompson Kolstad. Understanding Health Insurance and Policy Using the Massachusetts Health Reform.


  • 2012. O. Mitchell/K. Peijnenberg. Ambiguity Attitudes and Retirement Preparedness (Japan data).


  • 2012. S. Tishkoff. Biomarkers of Aging in Ethnically Diverse Africans: An Integrative Genomics Analysis.


  • 2011. C. Flippen. Relative Social Position and U.S. Internal Migration: Patterns by Race and Ethnicity.


  • 2011. F. Cunha. Health and Human Capital accumulation.


  • 2011. J. Kable/G. Zauberman. Neural Substrates of Anticipatory Time Perception and Time Discounting.


  • 2010. S. Preston. Sources of Aging in US States.


  • 2010. I. Elo/I.V.Kohler. Do parents in developing countries benefit from their children's education at old age?.


  • 2010. J. Schnittker. The Centrality of Schooling in Gene x Environment Interactions for Health.


  • 2009. C. Valeggia. Hormonal and cultural correlates of physical discomforts during the menopausal transition.


  • 2009. J. Kable/L.W. Chao. Neuroeconomics of Intergenerational Sacrifice: Why Mothers Eat Burnt Toast.


  • 2008. I. T. Elo. Early life conditions and familial correlations in cause-specific mortality.


  • 2008. R. Cnaan. Personal Attributes and the Financial Well-Being of Older Adults: The Effects of Control Beliefs.


  • 2008. S. Cnaan. Personal Attributes and the Financial Well-Being of Older Adults: The Effects of Control Beliefs.


  • 2008. Watkins, S. Aging in a Time of AIDS: The Impact of the Epidemic on Elderly in Rural Malawi.


  • 2007. A. DePaula. An Empirical Study on Behavioral Responses to AIDS.


  • 2007. D. Ewbank. Development of Methods for Applying Demographic Synthesis to Large Genome Scans.


  • 2007. H P Kohler/B. Soldo. Biomarkers in Malawi: Inflammation and CRP.


  • 2007. H. P. Kohler/S. Helleringer. A Population-based Study of the Transmission and Diversification of HIV-1 Using Molecular Genetic and Complete Sexual Network Data.


  • 2007. H. Park. Age Variation in the Relationship between Health Literacy and Self-Rated Health.


  • 2007. H. Park. Age Variation in the Relationship between Health Literacy and Self-Rated Health.


  • 2007. H.P. Kohler/LW Chao. HIV/AIDS and Intergenerational Transfers in Malawi.


  • 2007. K. Jedrziewski. Is Physical Activity a Viable Intervention to Lower the Risk of Dementia.


  • 2007. O. Mitchell/J.L. Ruiz. New Evidence on Annuity Choices in Chile: A Dynamic Programming Approach.


  • 2007. P. Todd. Retirement Savings and Unemployment Insurance.


  • 2007. S. Preston. The Effects of Nutrition and Disease on Child Growth and Adult Health.


  • 2007. S. Preston/R. Margolis. The Effects of Nutrition and Disease on Child Growth and Adult Health.


  • 2007. S. Watkins. Aging in a Time of AIDS: The Impact of the Epidemic on Elderly in Rural Malawi.


  • 2007. Soldo, B/Kohler, HP. Biomarkers in Malawi: Inflammation and CRP.


  • 2006. H. Park. The Literacy Gap between Those with High Levels and Low Levels of Educational Attainment among Older Adults: A Comparative Study of 20 Countries.


  • 2006. K. Volpp. Financial Incentives for Weight Loss.


  • 2006. C. Valeggia. Demographic Changes in Toba Villages in Transition.


  • 2006. H.P. Kohler/L.W. Chao. Trust and Transfers in South Africa: Linking Surveys.


  • 2006. I. T. Elo. Race/Ethnic and Immigrant Differences in Disability: What Can We Learn From the 2000 Census of Population?.


  • 2006. L. W. Chao. Does Poor Health Induce Myopia? An Investigation of Mortality, Morbidity, Aging, and Time Preference.


  • 2006. O. Mitchell. Contribution Patterns Under the Chilean Retirement Survey.


  • 2006. O. Mitchell. The Efficiency and Characteristics of Investment Choices Offered by 401(k) Pension Plans.


  • 2006. S. Preston/I.V. Kohler. The Muslim Mortality Puzzle in Bulgaria.


  • 2005. H.P. Kohler/S. Helleringer. HIV/AIDS and Complete Sexual and Social Networks in Rural Malawi.


  • 2005. O. Mitchell. Understanding Pension Literacy.


  • 2005. S. Preston. Factors Responsible for the Changing Sex Differentials in Mortality at Older Ages in US.


  • 2005. J. Behrman. Resource Flows Among Three Generations in Guatemala: Supplementary Analysis and Data Collection to (R01 HD 045627).



Center-Supported Publications


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