Environmental Mixtures Workshop: Applications in Environmental Health Studies

 

Environmental Mixtures training workshopThe next Environmental Mixtures Workshop in NYC is August 19-20, 2021. Join the email list below to hear about registration opening!

The Environmental Mixtures Workshop is a two-day intensive training of seminars and hands-on analytical sessions to provide an overview of environmental mixtures concepts, techniques, and data analysis methods used in health studies.   

 

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MIXTURES WORKSHOP OVERVIEW

Summer 2021 dates: Live-stream, online training August 19-20, 2021; 10:00am - ~5:00pm EDT

Traditionally, environmental health studies have focused on assessing risks related to a single pollutant at a time. This, however, does not reflect reality, since we are constantly exposed to multiple pollutants at once. Recently, there has been an increased interest in methods that allow researchers to assess exposures to many pollutants at a time. These methods are able to accommodate the high dimension of the exposure matrix, as well as the usually high correlation across exposures of interest.

This two-day intensive workshop will provide a rigorous introduction to multiple different techniques to analyze exposure to mixtures in environmental health. Led by a team of world experts in environmental health, epidemiology and statistics, many of whom have developed their own methods to analyze exposure to mixtures, the workshop will integrate seminar lectures with hands-on computer lab sessions to put concepts into practice. Emphasis will be given to supervised and unsupervised methods. Since the choice of method depends on the research question at hand, the workshop will conclude with a panel discussion on when each method presented is appropriate for use and for which research questions. 

By the end of the workshop, participants will be familiar with the following topics:

  • Principle Component Analysis (PCA)
  • Factor Analysis (FA)
  • Clustering
  • Variable Selection (Lasso, elastic net)
  • Bayesian Kernel (BKMR)
  • Weighted Quantile Sum Regression (WQS)
  • Emerging mixtures topics and novel extensions

Investigators at all career stages are welcome to attend, and we particularly encourage trainees and early-stage investigators to participate.

PREREQUISITES AND REQUIREMENTS

There are three prerequisites to attend this workshop:

  1. Each participant must have an introductory background in statistics.
  2. Each participant must be familiar with R.
  3. Each participant must bring a laptop with R downloaded and installed prior to the first day of the workshop. R is available for free download and installation on Mac, PC, and Linux devices.   

INSTRUCTORS

Brent Coull, PhD, Harvard T.H. Chan School of Public Health, Harvard University.

Chris Gennings, PhD, Research Professor and Biostatistics Division Director, Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai. Dr. Gennings’ research program includes the development of Weighted Quantile Sum (WQS) regression, joint work with a dissertation student, a method that is robust to confounding concerns based on complex correlations among exposure to environmental mixtures. She is currently developing methods for nutritional and environmental exposures that estimate and evaluate regulatory guideline values for mixtures.

Jeff Goldsmith, PhD, Assistant Professor, Department of Biostatistics, Columbia University Mailman School of Public Health. Dr. Goldsmith's statistical research focuses on high-dimensional data, with particular emphasis on dimension reduction methods, and modeling health outcomes. In addition to environmental health, he works on physical activity quantification using accelerometers, and on motor control experiments involving kinematic data. 

Marianthi-Anna Kioumourtzoglou, ScD, Assistant Professor, Department of Environmental Health Sciences, Columbia University Mailman School of Public Health. Dr. Kioumourtzoglou is an environmental engineer and environmental epidemiologist by training, with a research emphasis on air pollution exposures. Her research focuses on statistical issues related to environmental epidemiology, such as assessing exposure to environmental mixtures (chemical and non-chemical) in health studies, and quantifying and correcting exposure measurement error.

SCHOLARSHIPS

Training scholarships are available for the Environmental Mixtures Workshop.

LOCATIONS

COVID-19 Update: Our hope and plan is for the Mixtures Workshop to take place in person in summer 2021. The course will take place at the Mailman School of Public Health at 722 W. 168th Street, New York, NY 10032. We are closely monitoring the Covid-19 pandemic and will make adjustments as needed. 

TESTIMONIALS

"The workshop was appropriately intense and packed with loads of information and skills to take home for months of practice!" - Faculty member at Emory University, 2020.

"Excellent introduction to tools for analyzing chemical mixtures or other high dimensional data." - Program Officer at NIH, 2020.

"This workshop focused on common methods used in environmental health for understanding mixtures of pollutants. It was a good grounding in the techniques and I learned many things I can use in my current work." - Postdoc at Michigan State University, 2020.

"The workshop presented well-organized and detailed reviews of several mixtures methods using real dataset as an example. Lecturers were all very experienced and materials provided were very useful!" - Student at Emory University, 2020.

"This was an excellent overview of a number of different methods to address mixtures of exposures. The instructors not only explained how the methods work, but also gave interactive examples of which methods might be preferred in specific applications." - Non-profit staff member, 2020.

"I enjoyed hearing from each mixture expert. I feel up-to-date on current mixture methods and enjoyed the 'rapid' overview of many different methods which I can now explore further according to my data and research aims." - Research analyst at NIH, 2020.

​"The mixtures workshop was really well done, and I came out of it with an abundance of new knowledge and resources. I really appreciate all of the speakers, as I thought they did a really nice job presenting the material. I can tell how much work was put into this, and I was impressed at how smooth the transitions were from presentation to R lab. I thought it was useful to have a presentation overview and then the hands on lab to view how to conduct the analyses. I thought this was especially well done, considering the necessary quick transition from in-person to virtual. Thanks so much for all your work and for developing this workshop!" - Student at University of California, Berkeley, 2020.

"The Environmental Mixtures workshop is very efficient in covering multiple models for environmental mixtures data. Excellent lectures and hands-on practices!" - Postdoc at Columbia University, 2020.

"This workshop is a really nice overview of the major mixtures methods currently being used in environmental health. Even as an individual with no prior mixtures methods experience, I was able to gain a solid foundation in these mixtures methods to apply to my own research." - Student at Michigan State University, 2020.

"Great workshop and would recommend to anyone in the field of environmental health." - Faculty member at Maine Medical Center, 2020.

"A fantastic primer to enter the field of mixtures research- helpful briefings on the theory but a great emphasis on practical application including useful example code." - Student at the University of North Carolina, Chapel Hill, 2020.

"Excellent workshop taught by experts in cutting-edge methods for parsing and analyzing the combined effects of mixtures of environmental pollutants on health outcomes. The methods are extensible for other applications, such as reducing the dimensionality of outcome data and/or for investigating other non-environmental exposures. All materials and code are provided." - Health scientist attendee, 2019.

"The quality of the teaching is incredible -- the lectures are worth it even if you have no intention of using these methods. The instructors are that good. The matched lecture-lab sequence is a great way to introduce and apply these topics, and makes them relevant to a broad audience. And, thank you for using a standard data set and lab example across all methods. That makes so much sense." - Postdoc at NIEHS, 2019.

"Excellent workshop! I am just learning R, and did not feel debilitated at all. I greatly appreciated the html code where I could follow along and takes notes. Wonderful experience. Thank you!" - Postdoc at the University of Toronto, 2019.

"Amazing workshop with instructors that were very knowledgeable and open about the techniques uses and limitations. Support staff was really helpful, and I learned a lot from this short training - thank you!" - PhD student from Oregon State University, 2019.

"Fantastic opportunity to learn state of the art mixtures methodologies." - Postdoc at Dartmouth College, 2018.

"Great job! I learned a lot about the methods I will be using in my research. It was a perfect mix of theory and practical applications (R code)." - Postdoc at Icahn School of Medicine at Mount Sinai, 2018.

"Interesting, informing and interactive." - Student at Northeastern University, 2018.

"It's a great primer/workshop that is accessible to all epidemiologist/statisticians working on related fields. I think it's supremely helpful for anyone trying to get started on this." - Postdoc at Columbia University, 2018.

"This was an excellent distillation of incredibly challenging concepts. The resources provided were fantastic." - Student attendee, 2018.

"Excellent overview of range of different methods to use when studying environmental mixtures. It was very helpful to use the R code during lab sections and get a taste of what running the code will be like."  Postdoc at University of California, San Francisco, 2018.

 

REGISTRATION FEES

  Early-Bird Rate (through 6/15/21) Regular Rate (6/16/21 - 8/12/21) Columbia Discount*
Student/Postdoc/Trainee  $875  $975 10% off
Faculty/Academic Staff/Non-Profit Organizations $975 $1,175 10% off
Corporate/For-Profit Organizations $1,175 $1,375 NA

 

*Columbia Discount: This discount is valid for any active student, postdoc, staff, or faculty at Columbia University. To access the Columbia discount, email Columbia.Mixtures@gmail.com for instructions and specify if you are paying by credit card, or internal transfer within Columbia.

Invoice Payment and Group Registrations: If you would prefer to pay by invoice/check, or would like to pay for a group of registrants, please email Columbia.Mixtures@gmail.com with details.

Registration Fee: This fee includes course material, which will be provided to all participants after the workshop. 

Cancellations: Cancellation notices must be received via email at least 30 days prior to the training start date in order to receive a full refund, minus a $75 administrative fee. Cancellation notices received via email 14-29 days prior to the training will receive a 75% refund, minus a $75 administrative fee. Please email your cancellation notice to Columbia.Mixtures@gmail.com. Due to workshop capacity and preparation, we regret that we are unable to refund registration fees for cancellations after these dates. 

If you are unable to attend the training, we encourage you to send a substitute within the same registration category. Please inform us of the substitute via email at least one week prior to the training to include them on attendee communications, updated registration forms, and materials. Should the substitute fall within a different registration category your credit card will be credited/charged respectively. Please email substitute inquiries to Columbia.Mixtures@gmail.com. In the event Columbia must cancel the event, your registration fee will be fully refunded. 

 

ADDITIONAL INFORMATION

 

 

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Questions? Email the Mixtures team here.

The Mixtures Workshop is hosted by Columbia University's Department of Environmental Health Sciences in the Mailman School of Public Health. 

 

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