Getting to Know ISR: Combining Social and Biological Data
In recent years a substantial number of population-based and social science studies have begun adding biological data. These data can include genetic and epigenetic measures, telomere length, hormones, brain scans, clinical and inflammation markers, just to name a few. Including biological data expands the reach and potential of social science studies by adding richer health-related content to the survey measures we collect. Researchers using biological data can identify early biomarkers of health conditions and disease, elucidate the consequences of potentially harmful environmental exposures, and discover the mechanisms by which the social context and our life experiences change us on a cellular level. The union of social and biological sciences helps build a stronger case for the importance of social science research.
All Welcome. Presented by the ISR DACCD Perspectives Committee.
Tuesday, February 26, 2019
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Dr. Faul received her Ph.D. in Epidemiology from the University of Michigan. She is currently a Research Associate Scientist in the Survey Research Center, a Co-PI of the Health and Retirement Study, and is affiliated with the Michigan Center on the Demography of Aging (MiCDA), the Population Studies Center, and the University of Michigan BioSocial Methods Collaborative. Her research focuses on socioeconomic predictors of health and health disparities across the life course, specifically on dementia and cognitive decline in older age. She is interested in research and methods that integrate genetic and other biomarkers into social science research, especially the interaction between genetics, biomarkers and social environments on measures of health and well-being.
Dr. Mitchell is a Research Assistant Professor in the Survey Research Center, the co-Director of the ISR Biospecimen Lab and the NIA course Genomics for Social Scientists (both with Dr. Faul), Associate Director of the Biosocial Methods Collaborative, and research affiliate of the Population Studies Center and MiCDA. He leads the collection and analysis of the biological data for the Fragile Families and Child Wellbeing project. He has a broad background in sociology, demography, statistics, genetics, and molecular biology. His research utilizes population-based studies to examine how social contextual factors such as family instability, poverty, incarceration, childhood trauma, neighborhood characteristics, and parenting interact with and influence genetic, epigenetic, neurodevelopment, and telomere data and how those in turn predict later life health and wellbeing. He also has a line of research on the collection and analyses of biosocial data.