Member Database

Jennifer Smith

Associate Professor
Epidemiology
Public Health

PhD, Epidemiology, University of Michigan
MA, Statistics, University of Michigan
MPH, Health Management and Policy, University of Michigan
BS, Biological Sciences, Cornell University

Dr. Smith studies the ways that genetic factors influence age-related chronic diseases, subclinical phenotypes, and their risk factors. Her work encompasses a broad range of phenotypes, including cardiovascular traits, hypertension, chronic kidney disease, subclinical phenotypes for dementia and cognition, obesity and body mass index, diabetes and glucose metabolism, metabolic syndrome, inflammation, and health behaviors. She is particularly interested in the interaction between genetic and non-genetic determinants of health (such as demographic, social, and psychosocial factors) in shaping disease risk. Her research also includes biological markers that may lend insight into disease etiology and molecular mechanisms, including epigenetics, gene expression, and telomere length. Dr. Smith holds appointments in the Department of Epidemiolgy (School of Public Health) and the Survey Research Center (Institute for Social Research) at the University of Michigan. She is affiliated with the Center for Social Epidemiology and Public Health (CSEPH), the Michigan Center on the Demography of Aging (MiCDA), and the Center for Midlife Science.


Projects:

Genetics and Epigenetics of Cardiovascular Disease and Dementia, workgroup leader-cohort development

Community and Professional Affiliation(s)

American Heart Association | American Society of Human Genetics | International Genetic Epidemiology Society

Research Area(s)

Genetics / Genomics / other OMICS | Health disparities

Grants

  • Principal investigator of: Role of Diet in Heart Failure Genesis, Progression and Biochemical and Epigenetic Biomarkers
  • Co-investigator of: Integrative Approaches to Population Health Disparities: Healthy Communities=Healthy People
  • Principal investigator of: A Multi-Disease Study of PRS Dynamics in the Age of Data Science
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