Anusha Vable, ScD, MPH

Assistant Professor
School of Medicine
1001 Potrero Avenue
San Francisco, CA 94110
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Education and Training

Grinnell College, Grinnell, Iowa, BA - 2004 Chemistry

University of Michigan, Ann Arbor, Michigan, MPH - 2007 Epidemiology

Harvard T.H. Chan School of Public Health, Boston, Massachusetts, ScD - 2015 Social Epidemiology

Harvard T.H. Chan School of Public Health, Boston, Massachusetts, Postdoctoral fellow - 2016 Social Epidemiology

Stanford Center for Population Health Sciences, Stanford, California, Postdoctoral fellow - 2018 Social Epidemiology

Awards and Honors

Travel Scholarship, Society for Epidemiologic Research, 2014

Finalist for the Erickson Foundation Award for Excellence in Research on Positive Aging, American Public Health Association, 2016

"Good Ideas" Contest Winner, University of California San Francisco, Department of Epidemiology and Biostatistics, 2018

Poster Winner, Society for Epidemiologic Research, 2018

Incentive Scholarship, Grinnell College, 2000-2004

Mitchell L. & Robin LaFoley Dong Scholarship, Harvard T.H. Chan School of Public Health, 2010-2012

Harvey V. Fineberg Fellowship in Cancer Prevention, Harvard T.H. Chan School of Public Health, 2013-2014

Health Disparities Loan Repayment Program Recipient, National Institutes of Health, 2019-2021
I am a Social Epidemiologist and my research agenda focuses on identifying scalable, population-level solutions to racial and socioeconomic health disparities. In particular, I focus on education and educational interventions and how they impact dementia, cognition, and other diseases of aging. I found that the Korean War GI Bill, which subsidized college education for qualifying veterans, predicted smaller socioeconomic disparities in markers of mental, physical and cognitive health among veterans compared to non-veterans, and that structurally marginalized groups (women, racial minoritized people, and those from lower socioeconomic backgrounds) seem to benefit more from each year of education than structurally advantaged groups (e.g. high socioeconomic status White men). My work to date suggests programs and policies to increase educational attainment could be powerful mechanism to reduce racial and socioeconomic health inequities.

Methodologically, I employ methods from basic linear regression to more sophisticated approaches for identifying causal effects using methods from modern epidemiology, econometrics, and psychometrics. I am especially interested in novel approaches for identifying heterogenous treatment effects (HTEs) such as quantile regression, distributional decomposition, and causal forests (a machine learning technique). HTEs are important for reducing disparities, e.g. when the structurally marginalized group benefits more from the exposure than the advantaged group. I additionally have expertise in matching methods and the measurement of childhood socioeconomic status.

I am especially interested in training the next generation of Social Science researchers and welcome research interns with a range of statistical skills from new learners to those with advanced quantitative skills interested in making a quantitative argument for social change and a more equitable society.

I also organize a monthly happy hour for Bay Area Population Health Researchers, typically on first Fridays; you can add yourself to the listserv here: https://bit.ly/2GlXpyX