Biography and Research Interests

Biography

I received my Ph.D. degree in Sociology and Demography in 2005 and M.S. degree in Statistical and Decision Sciences in 2004 from Duke University. I began my first academic appointment in 2005 as Assistant Professor at the University of Chicago in the Department of Sociology, the Population Research Center, and Center of Demography and Economics of Aging. I joined University of North Carolina (UNC)-Chapel Hill in 2010, where I am now Alan Shapiro Distinguished Professor of Sociology, Fellow of the Carolina Population Center and Carolina Center for Population Aging and Health. I am also a joint faculty member at the Lineberger Comprehensive Cancer Center in the School of Medicine. I have 95 publications in 43 peer-reviewed journals across disciplines. My research accomplishments and intellectual leadership in bridging social, population, and health sciences have been recognized by major career awards such as the Ruth & Phillip Hettleman Prize for Artistic & Scientific Achievement at the University of North Carolina at Chapel Hill and the Early Achievement Award at the Population Association of America (PAA) as well as invited lectureship at the National Institutes of Health Behavioral and Social Science Research, Center for Disease Control and Prevention, National Institute on Aging, the National Academies of Sciences, Engineering, and Medicine (NAS), and Max Plank Institute for Demographic Research. I am a member of the honorary Sociological Research Association. I was elected to the Board of Directors of the PAA, the Councils of the Methodology Section, Aging and the Life Course Section, and Population Section of the American Sociological Association. I have contributed editorial services in the flagship journals in sociology and demography, including the Deputy Editor of the American Sociological Review (2014 – 2015) and Editorial Board member of the American Journal of Sociology (2005 – 2010), Social Forces (2010 – present), Sociological Methodology (2011 – 2013), Journal of Health and Social Behavior (2017 – present), and Demography (2007 – 2010). My research has been featured in national media such as Reuters, Washington Post, Los Angeles Times, CNN news, Chicago Tribune, and press releases of prestigious research agencies such as National Science Foundation, NAS, and Population Reference Bureau.

Research Interests

I am a sociologist conducting transdisciplinary research on population health and aging that crosscuts a range of areas in demography, medical sociology, aging and the life course, and quantitative methodology. I have established an innovative and proliferative program of scholarship across these areas. My overarching goal is to understand how social factors affect health across the human life span. My research aims to reveal complex patterns of social disparities in health, explicate the life course processes shaping these disparities, and test demographic, behavioral, and biological mechanisms underlying health disparities. My research agenda pushes new boundaries and combines advances in sociological, psychological, developmental, and biological sciences in an integrative life-course framework to advance our understanding of how social exposures and life experiences “get under the skin” to manifest in health differences. I use a comprehensive life course exposome approach to: 1) bring demographic and sociological theoretical perspectives to bear on the analyses of diverse forms of big health data (e.g., vital statistics, large-scale surveys, biomarkers, and administrative records); 2) develop new statistical models and methods for integrative analyses of these data across the full life course from birth to old age; and 3) construct a multisystem explanatory framework across levels (cellular, individual, and structural) for investigating life course origins of and changes in social disparities in health.

My contributions to science lie in five areas:

• Biodemography of aging, chronic disease, and mortality: Previous theories of aging, survival, and longevity have not been fully tested by accounting for population heterogeneity or social historical forces and contexts. I employed population-level data on chronic diseases and mortality rates and advanced mathematical modeling techniques to test and extend previous theories of dynamics of aging and survival and assess the influences of population heterogeneity (by gender, race/ethnicity, and socioeconomic status) and social historical and demographic contexts on these dynamics. These studies led to the refinement or modification of conventional models that improved our understanding of temporal trends, social patterns, and population mechanisms of chronic disease and mortality risks.
• Social disparities and cohort differences in health and aging over the life course: In tandem of my research in biodemography of trends and patterns of population health disparities, I have invested heavily in social epidemiology focusing on structural and behavioral drivers of such disparities. This line of research has used a wide variety of population-based sample surveys to reveal social status and cohort variations in aging-related health outcomes across the life course as a result of differential exposures to social life experiences and historical societal contexts. This body of work has tested and extended life course theories of aging and broadened the sociological, demographic, and epidemiologic discussions around the impact of social change on individual well-being.
• Social biology of health and aging: socioeconomic status, social relationships, and biological stress process: I have long-standing interests in data and methodological challenges of measuring and modeling the impact of social factors on health outcomes over the full life span. This line of research aims to develop an integrative theoretical and empirical framework that jointly examines social and biological explanations for social gradients in aging-related disease and survival. It breaks new ground with an innovative life-course research design integrating multiple large-scale NIH population-based longitudinal cohort studies that collectively cover the full life span. It focuses on the explication of the interconnections between social stress (socioeconomic disadvantages, social relationships) and biomarkers of stress response (e.g., inflammation, infection, metabolic disorders, biological aging) as interactive pathways underlying social disparities in health over the life course.
• Life course process of Alzheimer’s disease and related dementia (ADRD) and biosocial mechanisms: Most recently, I have developed an NIA funded research program to address major gaps in biomedical research on ADRD based on small clinical studies to examine social disparities in cognitive decline with aging and the interplay of social and biological pathways that generate and sustain these disparities. My team has developed and applied novel statistical methods to model longitudinal age trajectories of cognitive functioning from adolescence to late adulthood and age profiles of dementia risk in old age. We have also produced novel biomarkers of inflammation and infection using archived blood spots from the Add Health Wave IV data and are integrating them with biomarkers from other cohort studies to examine social and biological mechanisms influencing cognitive aging trajectories and associated ADRD risk.
• New methodologies for aging and cohort analysis: I have been continuously engaged in the development of new statistical methodologies for studying time-related changes, particularly in the form of age-period-cohort (APC) or cohort analysis, for the past 20 years in various directions. The utility of APC analysis has been widely recognized across disciplines in social, demographic, epidemiologic, and biomedical sciences, but has also been largely limited by the lack of adequate data and analytic strategies. The innovative models and methods I have developed with collaborators over the years address these problems in conventional research based on cross-sectional data and descriptive analysis or simple linear models. United by a generalized linear mixed effects models framework, these new methods have been applied across different research and study designs for cohort analysis. The most recent development moves beyond conventional analysis of a single dataset toward methods of data linkages for life course and aging research. Drawing on recent advances in psychometrics on complex coordinated analysis of multiple datasets, I introduce the longitudinal integrative data analysis (IDA) as a methodological framework to combine and synthesize separate datasets for enhanced inferences for testing life course hypotheses. Illustrative examples from my book on APC analysis and a recent NIA R01 project using the IDA are provided on this website with sample codes for conducting cohort analysis and public-use source codes for creating integrated datasets for longitudinal IDA.

(Last updated in September, 2025)