Y. Claire Yang, Ph.D., Professor, Sociology
Lineberger Cancer Center Faculty Fellow
I study complex patterns and biosocial mechanisms of population health disparities and their changes over the life course.
Yang conducts transdisciplinary research focusing on social disparities in health and aging that crosscuts life course sociology, biodemography, social epidemiology, and statistical methods. She has established an innovative and proliferative program of scholarship on this topic. Her overarching goal is to discover complex patterns and mechanisms of population health disparities and their changes over the life course. Specifically, her research aims to explicate the life course process by which social stress contributes to aging related diseases and mortality and the underlying biological pathways, to uncover how it is that exposures and experiences "get under the skin" to manifest in health differences, and to understand and find solutions to problems arising from reciprocal interactions between individuals' social and physical worlds. Her general approaches are to 1) bring integrative biosocial theoretical perspectives to bear on the analyses of diverse forms of big health data (e.g., vital statistics, sample surveys, and clinical biomarkers); 2) to develop new statistical models and methods for integrative data analyses of the full spectrum of the life course from birth to old age; and 3) to construct a multisystem explanatory framework across levels (cellular, organ, organism, developmental, and behavioral) for understanding mechanisms of health and aging jointly affected by social contexts and biological processes over the life course.
Yang's contributions to science lie in three areas: 1) Biodemography of aging, chronic disease, and mortality: She employed population level data on mortality rates and chronic conditions (e.g., obesity, disability, depression, cancer, and frailty) and advanced modeling techniques (e.g., age-period-cohort, Strehler and Mildvan, and two-mortality models) to test and extend theories of dynamics of aging and survival, and assess the influences of social historical contexts on these dynamics as well as patterns of population heterogeneity (by gender, race/ethnicity, and socioeconomic status) therein. 2) Integrative biosocial explanatory framework of social differentials in health over the life course: This line of work breaks new ground with an innovative life-course research design that combines prospective cohort data from multiple large-scale NIH longitudinal studies that collectively cover the entire life span. She used this design integrating novel biomarkers for population-based studies (e.g., C-reactive protein) to jointly examined social and biological explanations for social gradients in health not possible before in studies using a single dataset confined to only one life period (childhood or old age). The body of empirical studies she published made two contributions to the literature on health disparities: the explication of interconnections between social stress (e.g., low SES and social isolation) and physiological stress responses (e.g., inflammation and metabolic syndrome) as mechanisms underlying health disparities, and the life-course variation in such interconnections that shape the early-life influences on late-life health. 3) New methodological developments in aging and cohort analysis: originating from her dissertation, her methodological studies focus on modeling time related change and its applications in demographic and health research. She has been continuously engaged in developing and testing new statistical models and methods for studying cohort changes in various directions well beyond her earlier work. These new models and methods are united by a generalized linear mixed models framework that can be flexibly applied across different data structures and study designs and are increasingly used in a wide range of disciplines.
Last Updated: 2020-08-04