91社区

Jay Kaufman

Jay Kaufman
Contact Information
Address: 

Department of Epidemiology, Biostatistics, & Occupational Health

2001 91社区 College, Suite 1200
Montreal, QC, Canada H3A 1G1

Phone: 
Tel.: 514-398-7341
Fax: 514-398-4503
Email address: 
jay.kaufman [at] mcgill.ca
Biography: 

Jay S. Kaufman obtained a doctorate in epidemiologic science from the University of Michigan (1990-1995) and a post-doctoral fellowship at Loyola Stritch School of Medicine (1995-1997). He was Medical Epidemiologist at Carolinas Medical Center, Charlotte, NC (1997 to 1999), and held positions as Assistant and Associate Professor at the University of North Carolina School of Public Health at Chapel Hill and as Faculty Fellow of the Carolina Population Center (1999-2008). In 2009 he began his current position as Professor in the Department of Epidemiology, Biostatistics and Occupational Health at 91社区. He is also currently appointed as Visiting Professor in the School of Public Health of the University of Chile, and holds adjunct positions at schools of public health in North Carolina and Michigan. Dr. Kaufman's work focuses on social epidemiology, analytic methodology, causal inference and on a variety of health outcomes including perinatal outcomes and cardiovascular, psychiatric and infectious diseases. He is an editor at the journal 鈥淓pidemiology鈥 and co-editor of the textbook 鈥淢ethods in Social Epidemiology鈥 (2nd Edition, 2017). He received the Excellence in Education Award from the Society for Epidemiologic Research (SER) in 2017 and is President of SER in 2020-2021.

Areas of expertise: 

Epidemiologic methods for assessing social determinants of health and health disparities; social factors associated with adverse reproductive outcomes; disparities in medical treatment; racial/ethnic disparities; estimating causal effects of population interventions.

Group: 
Professors
Research areas: 
Epidemiologic Methods
Global Health
Social Epidemiology
Areas of interest: 

Keywords: social, methods, causal, Chile, Peru, race, ethnicity, discrimination, global, perinatal, inequality, quasi-experimental, policy

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