Global literature underscores that certain children and families are more likely to experience persistent social and economic disadvantages often determined by their race, ethnicity, social group, or other socio- demographic characteristics. Simultaneously, studies from diverse settings demonstrate unequal burdens of disease and unequal access to timely, quality health services in early childhood, contributing to lifelong health disparities. However, few studies have available data to examine the distinct ways that intergenerational disadvantage contributes to disparities in illness burden and healthcare utilization among children under five when morbidity and mortality risk are high. We address a critical gap in the research by estimating the association of persistent intergenerational disadvantage and diarrheal disease and acute respiratory infection (ARI), with attention to the role of persistent disadvantage in determining the likelihood and type of healthcare received, and potential modification by spatial remoteness. We use data from a longitudinal study of households that includes data on young children and their parents, households, and communities. The availability of detailed, high-frequency measures of the incidence and duration of diarrheal disease and ARI in combination with data on household and community context and health services over time provides a unique opportunity to study these questions with three specific aims. The first aim uses newly collected data about experiences of diarrheal disease and ARI among children under five years of age to estimate the association between persistent disadvantage and children’s illness burden. The second aim estimates the association between the burden of diarrheal disease and ARI and the likelihood and characteristics of healthcare utilized. This aim also tests whether this association is modified by persistent household disadvantage. The third aim investigates the roles of spatial remoteness, distance to health ser- vices, and persistent household disadvantage as modifiers of the association between the burden of diarrheal disease and ARI, and the likelihood and type of healthcare facility utilized. We will archive and disseminate all data collected to facilitate innovative research on social and structural determinants of child health and healthcare utilization outcomes, and inform child health and health equity programs globally. The effects of persistent, intergenerational social and economic disadvantage are increasingly important considerations for providers and policymakers seeking to improve children’s health and health service utilization, and to reduce health disparities that emerge in early childhood. This research will enhance our understanding of the mechanisms through which exposure to persistent disadvantage shapes the health and illness burden among young children; identify promising avenues for future research in this area; and generate rigorous evidence for effective child health policies and interventions.

This project seeks to document the frequency and duration of diarrheal disease and acute respiratory infection in early childhood, and assess how intergenerational disadvantage and household and community circumstances shape disparities in children’s health, illness, and healthcare utilization. The results of this project will allow child health programs and health systems to better address health disparities in illness and healthcare utilization among young children, and inform our understanding of the consequences of intergenerational disadvantage for children globally.

Spearheaded by U-M Economics Professor Amanda Kowalski, the research team featuring U-M Sociology’s Sarah Burgard secured nearly $2M in financial support from U-M’s College of Literature, Science, and the Arts for research examining health inequity exacerbated by the COVID-19 pandemic. This study will examine early access to COVID-19 vaccination data from Michigan Medicine to evaluate various health inequities faced by marginalized communities. This research project seeks to inform future health policy guidance. 

Kowalaski’s multidisciplinary team includes Sarah Burgard (Sociology), Yanna Krupnikov (Communication & Media), and Abram Wagner (Public Health). With the support of LSA, this project joins a growing list of Meet the Moment-funded research endeavors aimed at creating progressive change.

The COVID-19 pandemic has exacerbated already severe inequities in health and economic hardship by race, ethnicity, social vulnerability, and health. Although new life-saving technologies can reduce inequities, certain factors determine their real-world effectiveness, making policy guidance difficult. This project will examine early access to COVID-19 vaccination data from Michigan Medicine to evaluate those inequities, how they came to be, and their impact on individuals’ health and financial hardships with the aim to inform future policy guidance.  

Project Team: Amanda Kowalski, Sarah Burgard, Yanna Krupnikov, Abram Wagner

Total Award: $1,999,782

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

I am a population health scientist. Broadly, this means I research the interplay between human societies, health, and aging. Most of my work focuses specifically on explaining why certain groups of people live shorter and sicker lives than others. I also investigate how people cope with chronic stress using religion and other social support mechanisms.

Kristi Gamarel’s (she/her) program of research focuses on addressing health inequities among LGBTQ+ communities within the context of HIV, mental health, substance, use, and healthcare access. Her research is largely focused using CBPR principles in the development and evaluation of community-engaged interventions.  She is founding member of the “Love Her Collective” which is a community-academic partnership with the Trans Sistas of Color Project (TSoCP). Through qualitative research, survey research, and intervention studies, the “Love Her Collective” is engaged in a number of research projects designed to address social determinants of HIV, including violence, gender affirmation, economic vulnerability, and health-harming legal needs. She also works closely with her mentees on the development of their independent programs of research, often focused on understanding the structural drivers of health inequities. An additional area of her research focuses on dissemination and implementation science, including peer-delivered and digital health interventions. She has been actively involved with the Adolescent Medicine Trials Network for HIV Interventions (ATN) since 2014, including serving as a Protocol Chair for the ATN 157 and ATN 167 research protocols. She co-created and currently directs the ATN Communication-Dissemination Hub, which focuses on expediting the gap between research, practice, and policy and ensuring youth engagement throughout the ATN. 

She serves an Associate Editor for Annals of Behavioral Medicine and is a member of the HIV/AIDS Intra- and Inter-personal Determinants and Behavioral Interventions (HIBI) study section for the National Institutes of Health. She is the Health Behavior and Health Equity Doctoral Curriculum Committee Chai and is a Research Associate Professor in the Population Studies Center, working closely with its pre- and post-doctoral training programs. She prioritizes cultural humility in her research, teaching, and mentoring.

Trained in environmental psychology and architecture, Dr. Rollings’ research examines effects of the built and natural environment on physical and mental health, particularly among vulnerable populations at higher risk of poor health (low-income, children, seniors, unstably housed) within housing and neighborhood settings. Current work focuses on affordable and permanent supportive housing design and health. She was the inaugural Health and Design Research Fellow at the University of Michigan’s Medical School and Institute for Healthcare Policy and Innovation, and previously served as an Assistant Professor at the University of Notre Dame School of Architecture and Department of Psychology. Dr. Rollings received her M.S. and Ph.D. in Human Behavior and Design from Cornell University’s Department of Design and Environmental Analysis (now Human-Centered Design). She also holds a B. Architecture from the University of Notre Dame.

Lizbeth ‘Libby’ Benson, PhD, is a Research Assistant Professor in the Data Science for Dynamic Intervention Decision Making Center (d3c) at the University of Michigan’s Survey Research Center and Institute for Social Research. Before moving to Michigan, Libby completed a Postdoctoral Fellowship at the TSET Health Promotion Research Center within the NCI-designated Stephenson Cancer Center and University of Oklahoma Health Sciences Center. She received her PhD from the Pennsylvania State University in the department of Human Development and Family Studies and her BA in Psychology from the University of Wisconsin-Madison.

Libby’s research program is focused on intensive longitudinal, computational, and machine learning methods for examining temporal dynamics of affective, social and health behavior experiences using ecological momentary assessment and sensor-based data collected from individuals in their daily lives. Her goals are to understand how behavioral processes unfold across multiple time-scales and contexts, and how this knowledge can be used to build personalized interventions to facilitate health behavior change. Data visualization is also an important component of her work as a way to better understand complex behavioral processes, to generate new ideas, and to use as a tool for scientific communication. Currently, Libby is writing a NIH K01 focused on developing a reinforcement learning algorithm for personalizing intervention content in a smoking cessation just-in-time adaptive intervention.

The overall purpose of this project is to identify modifiable risk factors for Alzheimer’s disease and related dementias that influence DNA methylation and dementia status among groups at increased risk for dementia including women, minorities, rural inhabitants, and those with low educational attainment. Our results may provide an opportunity to identify epigenetic components that contribute to the prevalence and risk of dementia that could lead to a mechanistic understanding or targeted interventions that may substantially decrease the burden of Alzheimer’s disease and related dementias in the US population.

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.

The Child Development Supplement (CDS) is an integral and on-going component of the Panel Study of Income Dynamics (PSID), a longitudinal survey of a nationally representative sample of U.S. families that began in 1968. With data collected on the same families and their descendants for 41 waves over 52 years (as of 2020), PSID is a cornerstone for empirical social science research in the U.S. Through its long-term measures of economic and social wellbeing, and based on its weighted representative sample of U.S. families that now includes two major immigrant refresher samples, the study has advanced research on the dynamics of social, economic, demographic, and health processes and their interrelationships. Five waves of CDS have been conducted: three on the original cohort of children born between 1985 and 1997 (in 1997, 2002/2003, and 2007/2008) and two waves (in 2014 and 2019) on the next generation of PSID children who were born between 1997 and 2019.

This project has two specific aims. The first is to design and field a follow-up wave of CDS in 2021, collecting re-interview data on children aged 2-17 years who participated in CDS-19, through interviews with primary caregivers and older children aged 12-17 years. The second specific aim is to process, document, and distribute the new CDS-21 data, with scale composites, generated variables, and individual-level links to detailed school data from the National Center for Education Statistics. The 2021 wave of CDS will, in conjunction with data from CDS-14 and CDS-19, provide unique and valuable prospective panel data to study the effects of the Covid-19 pandemic, lockdown, and recession. The study will provide comprehensive and rich information on a large, nationally representative sample of children that includes an over-sample of African Americans and a new refresher sample of children in immigrant families. These data will be available free of charge through the PSID Online Data Center, which provides customized extracts and codebooks, detailed study documentation, and comprehensive user education and support.

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