Event
Biography and Research Interests
Yang Claire Yang was born and grew up in Chengdu, Sichuan Province, China. She did her undergraduate work in Beijing University and received the B.A. in Chinese Language and Literature in 1998. A change of scholarly interest from humanities to quantitative social sciences led her to graduate studies at the Ohio State University, where she received the M.A. in Sociology in 2000. Yang Claire Yang continued her graduate education at Duke University and received the M.S. in Statistics in 2004 and Ph.D. in Sociology in 2005. Before coming to UNC-CH in 2010, she was Assistant Professor at the Sociology Department and Research Associate at the Population Research Center and Center on Aging at NORC at the University of Chicago. Yang Claire Yang is now Alan Shapiro Distinguished Professor at the Sociology Department and the Lineberger Comprehensive Cancer Center and Faculty Fellow of the Carolina Population Center. She has many other interests such as ballroom dancing, swimming, hiking, power yoga, music, and reading (especially when raining).
Research Interests and Goals
I conduct transdisciplinary research focusing on social disparities in health and aging that crosscuts a range of areas in demography, medical sociology, life course sociology, social epidemiology, and quantitative methodology. My overarching goal is to discover complex patterns and mechanisms of population health disparities and their temporal dynamics and life course variations. In addition, my 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. My 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.