Causal Inference in Obesity Research

Welcome!

 

Overview of this Webinar Series

STRENGTHENING CAUSAL INFERENCE IN BEHAVIORAL OBESITY RESEARCH

The identification of causal relations is fundamental to a science of intervention and prevention. Obesity is a major problem for which much progress in understanding, treatment, and prevention remains to be made. Understanding which social and behavioral factors cause variations in adiposity and which other factors cause variations is vital to producing, evaluating, and selecting among intervention and prevention strategies as well as to understanding obesity’s root causes, requiring input from disciplines including statistics, economics, psychology, epidemiology, mathematics, philosophy, and in some cases behavioral or statistical genetics. This webinar features: Key underlying and fundamental principles of causal inference in obesity research Applying a broad range of techniques in obesity research Tailored approaches to specific and varying situations in obesity research

The objectives of this webinar are to:

  • expose researchers from the mathematical sciences and obesity to the language and methodology at the interface of both disciplines,
  • facilitate collaborations between the two groups through effective contact, and
  • guide early investigators interested in conducting research at the interface of the mathematical sciences in obesity on the next career step.

Meet the Hosts

David B. Allison, Ph.D.

Dean and Provost Professor, Indiana University School of Public Health-Bloomington

Dr. Allison became Dean and Provost Professor at the Indiana University-Bloomington School of Public Health in August of 2017. Prior he was Distinguished Professor, Quetelet Endowed Professor, and Director of the NIH-funded Nutrition Obesity Research Center (NORC) at the University of Alabama at Birmingham. He holds several NIH grants, including an NIH Director's Transformative Research Award entitled "Energetics, Disparities, & Lifespan A unified hypothesis." In 2012 he was elected to the National Academy of Medicine of the National Academies. His research interests include obesity and nutrition, clinical trials, statistical and research methodology, and research rigor and integrity.

 

Kevin R. Fontaine, PhD

Professor and Chair, The University of Alabama at Birmingham School of Public Health-Bloomington

Kevin Fontaine is a Professor and Chair of the Department of Health Behavior, School of Public Health at the University of Alabama at Birmingham. He is also the Antoine Lavoisier Endowed Professor of Energetics and Health Lifestyles and serves as Adjunct Faculty in the Division of Rheumatology at the Johns Hopkins University School of Medicine, Baltimore, Maryland. His current research interests include obesity, non-deceptive placebo responses, resistant exercise, neuro-dynamic strain in Chronic Fatigue Syndrome, and the effects of ketogenic diets on metabolism, inflammation and chronic disease, including cancer.

 

Andrew W. Brown, PhD

Assistant Professor, Indiana University School of Public Health-Bloomington

Andrew Brown is an Assistant Professor with the Department of Applied Health Science in the School of Public Health-Bloomington at Indiana University. Formally trained in nutrition, biochemistry, and statistics, he brings practical, basic science experience to evaluating how nutrition and obesity research is conducted and communicated. His recent work involved investigating myths and presumptions in nutrition and obesity literature, meta-analyzing studies about nutritional influences on obesity, characterizing reporting practices that may perpetuate nutrition misinformation, and crowdsourcing the synthesis of public research. Dr. Brown has received local, regional, and national awards and spoken internationally about integrity in research reporting and science communication with respect to nutrition and obesity research.

Webinar Archives

Webinar series is organized into 9 modules. Below you can find the following modules on this course site. You can also access Modules from the navigation menu on the left at the top of the module list on the Home page

Module 1: Introduction to Basic Language, Terms, and Concepts in Statistics and Design

Module 2: Conventional Observational Studies: Advantages, Limits, and Best Practices

Module 3: Randomized Controlled Experiments, Part I

Module 4: Randomized Controlled Experiments, Part II

Module 5: Quasi Experiments

Module 6: Natural Experiments

Module 7: Genetically Informed Designs – Unmeasured Genotype Approaches

Module 8: Genetically Informed Designs – Measured Genotype Approaches

Module 9: Mediating and Moderating Variables

 

This course is an archive of the 2019 academic year. 

We would like to thank our sponsors for their support:  NIH National Institute of Diabetes and Digestive and Kidney Diseases

NIH Disclaimer:
This material is based upon work supported by the National Institutes of Health under Grant No. (R25HL124208). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Institutes of Health.