SER-ISEE Collaboration – Society for Epidemiologic Research

Join the Society for Epidemiologic Research (SER) and International Society for Environmental Epidemiology (ISEE) for a joint webinar! Members of all organizations are welcome to participate!

Thanks to working group members Jessie Buckley, Joan Casey, Beate Ritz, Jeanette Stingone, and Marianthi-Anna Kioumourtzoglou for planning the events!

Register

March 15, 2023 at 12:00 PM EST

“Thoughts on meaningful and interpretable data science for environmental epidemiology”

The proliferation of high-dimensional environmental health data and the emergence of paradigms such as the exposome have led to increased interest in the use of technologies and techniques from the broader field of data science. However, the ability of these methods to generate new knowledge in epidemiologic research and practice is often debated.

Moderator

Jessie Buckley
Johns Hopkins University

BIO

Jessie Buckley, PhD, MPH is an Associate Professor of Environmental Health & Engineering and Epidemiology (joint) at the Johns Hopkins Bloomberg School of Public Health. Her research aims to characterize exposure and health effects of environmental chemicals to inform policies to improve lifelong health. As a recipient of an NIEHS Outstanding New Environmental Scientist (ONES) Award, she is studying the impacts of endocrine disrupting chemical mixtures on bone health during adolescence. In addition, Dr. Buckley serves as Director of Chemical Exposure Methodology for the Environmental influences on Child Health Outcomes (ECHO) Data Analysis Center at Johns Hopkins and is co-chair of ECHO’s Chemical Exposures Working Group. Dr. Buckley earned her MPH in Environmental and Occupational Health from the George Washington University and PhD in Epidemiology from the University of North Carolina at Chapel Hill.

Moderator

Joan Casey
University of Washington

BIO

Joan A. Casey received her doctoral degree from the Department of Environmental Health Sciences at Johns Hopkins Bloomberg School of Public Health in 2014. Dr. Casey is an environmental epidemiologist who focuses on environmental health, environmental justice, and sustainability. Her research uses large secondary health datasets, such as electronic health records, to study the relationship between emerging environmental exposures and population health across the lifecourse. She also considers vulnerable populations, joint social and environmental exposures, and health disparities, particularly in an era of climate change. Dr. Casey investigates a range of exposures, including wildfires, power outages, ambient temperature, the built environment, fossil fuel infrastructure, and concentrated animal feeding operations.

Presenter

Tarik Benmarhnia
University of California, San Diego

BIO

Tarik Benmarhnia is an associate professor in epidemiology with a joint appointment at the University of California San Diego’s Scripps institution of Oceanography and the Herbert Wertheim School of Public Health. He finished his PhD in epidemiology jointly from the University of Montreal and Paris Sud and a post-doctoral position at McGill University with the Institute for Health and Social Policy. His work is combining epidemiological methods with environmental and econometric models with a specific focus on health policies and environmental justice.

Presenter

Jeanette A. Stingone
Columbia University

Presenter

Ellen Eisen
University of California, Berkeley

BIO

I am an occupational epidemiologist with decades of experience analyzing cohort data on chronic health outcomes in relation to long-term workplace exposures in large populations of industrial workers. My training in biostatistics and occupational health provided the foundation for my longstanding interest in addressing healthy worker survivor effect – a ubiquitous potential bias in longitudinal studies of chronic disease in workers. That bias arises because susceptible workers leave work earlier than workers less susceptible to health effects of exposures. This leads to a structural problem where leaving work is a time varying confounder that is also on the causal pathway. Standard survival methods cannot address this data structure, but an array of causal inference g-methods developed over the past few decades can. We have applied g-estimation, IPW, and parametric g-formula to study workplace chemical exposures in relation to cancer, heart disease, and lung disease in complex longitudinal datasets from iconic occupational cohorts of autoworkers, underground miners, and aluminum manufacturing workers in .

Presenter

Youssef Oulhote
University of Massachusetts, Amherst

BIO

Dr. Oulhote is an Assistant professor of Epidemiology at the department of Biostatistics and Epidemiology at the University of Massachusetts Amherst School of Public Health and Health Sciences. He received his Engineering degree in Food Industrial processes from the National Institute of Veterinary and Agricultural Sciences in Morocco, a Master’s degree in Risk assessment from the AgroParisTech Engineering School in Paris, and a PhD from the French National School of Public Health. Before joining UMASS, He worked as a researcher within the Environmental and Occupational Medicine & Epidemiology program at Harvard T. H. Chan School of Public Health where he investigated health effects of chemicals. As an epidemiologist, Dr. Oulhote’s research focuses on the health effects of early life exposures to metals (e.g. mercury, lead, and manganese) and endocrine disruptors (e.g. PBDEs, PFAS, and phthalates), with an emphasis on children’s cognitive and behavioral functions. Dr. Oulhote also investigates the interplay of environmental, nutritional, and social factors, and how these exposures interact to impact population health. He received an outstanding environmental scientist award from NIEHS in 2022.