About

Barbara Entwisle is a Kenan Distinguished Professor in the Department of Sociology at the University of North Carolina at Chapel Hill. Her areas of interest include Social Demography, Migration, Life Course, Quantitative Methods, and Population and Environment. She earned her Ph.D. from Brown University in 1980. Her professional background encompasses research and teaching in social demography, migration, life course studies, and quantitative methods, with a focus on population and environmental issues.

Research topics

• Sociology
• Geography
• Political Science
• Social Science
• Computer Science
• Psychology
• Economic geography
• Biology
• Ecology
• Genetics
• Nursing
• Medicine
• Gerontology
• Environmental health
• Developmental psychology

Selected publications

• Data Management and Sharing Plan for: Network on Life Course Health Dynamics and Disparities in 21st Century America

  UNC Dataverse · 2026-03-16

  datasetOpen access1st authorCorresponding

  The Data Management and Sharing Plan describes the scientific data to be generated and/or used in the research and outlines a strategy for managing and sharing project data.

  PublisherDOI

• Accelerating real‐world prediction and research in Alzheimer's: The M3AD study

  Alzheimer s & Dementia · 2026-03-01

  articleOpen access

  Chronic diseases, including Alzheimer's disease (AD) and related dementia (ADRD), do not exist solely as isolated entities. Instead, they weave concomitant trajectories of multiple diseases, conditions, behaviors, and risks, mutually influencing each other's course and natural history, in ways yet unexplored. Electronic health records (EHRs) provide us with a unique opportunity to look at related and unrelated clinical trajectories over time, thus potentially providing insight into unrecognized prodromes, while incorporating the complexities of patients' lives. We harmonize and federate a three-city EHR metaplatform of nearly 10 million patients (∼60,000 with AD/ADRD), which we further embed within census tracts, to contextualize these health trajectories. Our multidisciplinary approach ambitions a unique dynamic platform to inform strategies to tailor risk prediction, complex clinical management, and real-world evaluation of future treatments of AD/ADRD. We present the rationale for and design of the Multimorbidity Three-City Alzheimer's Disease EHR (M3AD) Study and real-world data metaplatform, progress and demonstration of feasibility, its expected singular and complementary contributions to the field. HIGHLIGHTS: Our success in living longer lives often brings chronic conditions and multimorbidity. Alzheimer's research should comprise life trajectories' complexity in multimorbidity. New real-world analytical approaches allow integrated prediction of Alzheimer's disease. We are building a three-city electronic health record (EHR) metaplatform for prediction, prevention, and impact We further embed EHR within census tracts to contextualize Alzheimer's trajectories.

  PublisherDOI

• Caring for Communities: Comparing Health Care System Patient Populations to Regional Populations

  Journal of General Internal Medicine · 2025-09-17

  articleOpen accessSenior author

  BACKGROUND: Recent years have seen an increase in the number and size of integrated health care delivery systems in the USA. The size and sophistication of these systems afford a greater focus on population health, leading to a fundamental question: How do the patients of these systems compare to the underlying regional populations that the systems serve? OBJECTIVE: To demonstrate an approach to answering this question for a large public integrated delivery system, with a particular focus on neighborhood social determinants of health (SDOH). DESIGN: We present a descriptive, graphical comparison of the neighborhood characteristics of UNC Health patients and the overall population of North Carolina (NC). SUBJECTS: We leveraged electronic health record data from a 5-year period for patients at UNC Health, an integrated health care delivery system focused on serving the NC population. Estimates for the NC population were obtained from the American Community Survey (ACS). MAIN MEASURES: Measures included neighborhood SDOH indices for NC census tracts derived from ACS data as well as race and ethnicity. KEY RESULTS: Overall, patients were more concentrated in neighborhoods with the least and greatest disadvantage. However, the density patterns of specific racial and ethnic groups across neighborhood SDOH scores were similar between the patients and NC population. CONCLUSIONS: Using a large, public integrated health care delivery system, we illustrate an approach for comparing the demographic and neighborhood characteristics of the patients of such a system and its underlying regional population using freely available data and open-source software. Our findings indicate many similar patterns between the health care system patients and regional population, but overall higher concentrations of patients in neighborhoods with the least and greatest disadvantage.

  PublisherOA PDFDOI

• Race and Ethnicity Data in the Electronic Health Records: New Insights Through Comparison with American Community Survey Microdata

  Journal of Racial and Ethnic Health Disparities · 2025-04-22 · 2 citations

  articleOpen accessSenior author
  PublisherOA PDFDOI

• Climate Change and Migration: New Insights from a Dynamic Model of Out-Migration and Return Migration.

  UNC Libraries · 2025-07-15

  articleOpen accessSenior author

  In popular accounts, stories of environmental refugees convey a bleak picture of the impacts of climate change on migration. Scholarly research is less conclusive, with studies finding varying effects. This paper uses an agent-based model (ABM) of land use, social networks, and household dynamics to examine how extreme floods and droughts affect migration in Northeast Thailand. The ABM explicitly models the dynamic and interactive pathways through which climate-migration relationships might operate, including coupled out and return streams. Results suggest minimal effects on out-migration but marked negative effects on return. Social networks play a pivotal role in producing these patterns. In all, the portrait of climate change and migration painted by focusing only on environmental refugees is too simple. Climate change operates on already established migration processes that are part and parcel of the life course, embedded in dynamic social networks, and incorporated in larger interactive systems where out- and return migration are integrally connected.

  PublisherDOI

• Assessing Electronic Health Records for Describing Racial and Ethnic Health Disparities: A Research Note

  Demography · 2024-09-27 · 2 citations

  articleOpen accessSenior author

  The use of data derived from electronic health records (EHRs) to describe racial and ethnic health disparities is increasingly common, but there are challenges. While the number of patients covered by EHRs can be quite large, such patients may not be representative of a source population. One way to evaluate the extent of this limitation is by linking EHRs to an external source, in this case with the American Community Survey (ACS). Relying on a stratified random sample of about 200,000 patient records from a large, public, integrated health delivery system in North Carolina (2016-2019), we assess linkages to restricted ACS microdata (2001-2017) by race and ethnicity to understand the strengths and weaknesses of EHR-derived data for describing disparities. The results in this research note suggest that Black-White comparisons will benefit from standard adjustments (e.g., weighting procedures) but that misestimation of health disparities may arise for Hispanic patients because of differential coverage rates for this group.

  PublisherOA PDFDOI

• The PhenX Toolkit: Measurement Protocols for Assessment of Social Determinants of Health

  American Journal of Preventive Medicine · 2023 · 33 citations

  • Political Science
  • Sociology
  • Social Science

  INTRODUCTION: Social determinants are structures and conditions in the biological, physical, built, and social environments that affect health, social and physical functioning, health risk, quality of life, and health outcomes. The adoption of recommended, standard measurement protocols for social determinants of health will advance the science of minority health and health disparities research and provide standard social determinants of health protocols for inclusion in all studies with human participants. METHODS: A PhenX (consensus measures for Phenotypes and eXposures) Working Group of social determinants of health experts was convened from October 2018 to May 2020 and followed a well-established consensus process to identify and recommend social determinants of health measurement protocols. The PhenX Toolkit contains data collection protocols suitable for inclusion in a wide range of research studies. The recommended social determinants of health protocols were shared with the broader scientific community to invite review and feedback before being added to the Toolkit. RESULTS: Nineteen social determinants of health protocols were released in the PhenX Toolkit (https://www.phenxtoolkit.org) in May 2020 to provide measures at the individual and structural levels for built and natural environments, structural racism, economic resources, employment status, occupational health and safety, education, environmental exposures, food environment, health and health care, and sociocultural community context. CONCLUSIONS: Promoting the adoption of well-established social determinants of health protocols can enable consistent data collection and facilitate comparing and combining studies, with the potential to increase their scientific impact.

  PublisherOA PDFDOI

• Linking Electronic Health Records to the American Community Survey: Feasibility and Process

  American Journal of Public Health · 2022-04-21 · 10 citations

  articleOpen accessSenior author

  Objectives. To assess linkages of patient data from a health care system in the southeastern United States to microdata from the American Community Survey (ACS) with the goal of better understanding health disparities and social determinants of health in the population. Methods. Once a data use agreement was in place, a stratified random sample of approximately 200 000 was drawn of patients aged 25 to 74 years with at least 2 visits between January 1, 2016, and December 31, 2019. Information from the sampled electronic health records (EHRs) was transferred securely to the Census Bureau, put through the Census Person Identification Validation System to assign Protected Identification Keys (PIKs) as unique identifiers wherever possible. EHRs with PIKs assigned were then linked to 2001–2017 ACS records with a PIK. Results. PIKs were assigned to 94% of the sampled patients. Of patients with PIKs, 15.5% matched to persons sampled in the ACS. Conclusions. Linking data from EHRs to ACS records is feasible and, with adjustments for differential coverage, will advance understanding of social determinants and enhance the ability of integrated delivery systems to reflect and affect the health of the populations served. (Am J Public Health. 2022;112(6):923–930. https://doi.org/10.2105/AJPH.2022.306783 )

  PublisherOA PDFDOI

• The Social Forces that Shape Families: Reflections on 100 Years of Publications in <i>Social Forces</i>

  Social Forces · 2022-10-19 · 2 citations

  articleOpen accessSenior author
  PublisherOA PDFDOI

• Reflections on the Past, Present, and Future of Population-Environment Research

  International handbooks of population · 2022-01-01 · 1 citations

  book-chapter1st authorCorresponding
  PublisherDOI

Recent grants

• IGERT: Integrative Graduate Education, Research, and Training in Population and Environment

  NSF · $2.8M · 2003–2012

• NIH Grant R03HD050217

  NIH · $144k · 2009

• NIH Grant R21HD051776

  NIH · $346k · 2010

• NIH Grant R01HD037896

  NIH · $744k · 2004

• NIH Grant R24HD050924

  NIH · $10.0M · 2015

Frequent coauthors

• Ronald R. Rindfuss

  51 shared

• Stephen J. Walsh

  University of North Carolina at Chapel Hill

  20 shared

• Paul C. Stern

  Social and Environmental Research Institute

  13 shared

• Leah K. VanWey

  12 shared

• George P. Malanson

  University of Iowa

  12 shared

• Myron P. Gutmann

  10 shared

• Yothin Sawangdee

  Mahidol University

  10 shared

• Ashton M. Verdery

  Pennsylvania State University

  9 shared