Course recordings provide rigorous exposure to fundamental principles of obesity research. A broad array of techniques for applying these principles in research are addressed by experts in their fields. These annual short courses better position scientists — and clinician researchers — to help identify ways of reducing the burden of obesity.

The Obesity Short Courses are jointly hosted by the Indiana University-Bloomington and the University of Alabama at Birmingham.

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. A burgeoning array of research techniques exists to help scientists make more informed conclusions about causal effects, but many obesity researchers are unfamiliar with these techniques. 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.

The Strengthening Causal Inference in Behavioral Obesity Research course provides rigorous exposure to the key fundamental principles of causal inference in behavioral obesity research. The nine modules in the 2019 webinar series cover:

• key underlying and fundamental principles of causal inference in obesity research
• application of a broad range of techniques in obesity research
• tailored approaches to specific and varying situations in obesity research

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

• Intro to Statistical Inference
  with Dr. Evan Mayo-Wilson of Indiana University-Bloomington
• Intro to Energy Balance and Laws of Thermodynamics
  with Dr. Greg Demas of Indiana University-Bloomington
• Study Designs & Quantifying Effect and Association Size
  with Dr. Keith Haddock of Hope Health Research Institute

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

• Best practices
  with Dr. Douglas Weed of DLW Consulting
• Advantages
  with Dr. Yiqing Song of Indiana University-Purdue University Indianapolis
• Limits I – Theory: Bias and Confounding
  with Dr. Dominik Alexander of Meta Method Health
• Limits II – Empirical: Evidence & Case Studies of Confirmation and Non-Confirmation of Observational Study-Generated Hypotheses
  with Dr. Andrew Brown of Indiana University-Bloomington

Module 3: Randomized Controlled Experiments, Part I

• Theory: Potential Outcomes
  with Dean David B. Allison of Indiana University-Bloomington
• Methods for Randomization (Including Cluster Randomization, Stratifies, Choice of Allocation Rations, Adaptive, Etc.)
  with Dr. Scarlett Bellamy of the University of Pennsylvania
• Power & Sample Size Calculation
  with Dr. Michael Oakes of the University of Minnesota
• Choice of Control Condition Based on Hypothesis and Anticipated Claims
  with Dr. Kevin Fontaine of the University of Alabama at Birmingham
• Controlling for Expectancy and Not-Specific Effects
  with Dr. Jack Raglin of Indiana University-Bloomington

Module 4: Randomized Controlled Experiments, Part II

• Identifying and Guarding Against Inferential Errors and Exaggerated Claims
  with Dr. Andrew Brown of Indiana University-Bloomington
• Practical Challenges: Measurement Error, Missing Data, Assumption Violations, Etc.
  with Dr. Carmen Tekwe of Indiana University-Bloomington
• Ethical Issues in RCEs
  with Dr. Theodore Kyle of ConscienHealth
• Procedural Elements: Trail Registration, Reporting Guidelines
  with Dr. Samuel Field of the Center for Open Science
• Large Simple Trials & Cluster Randomized Trials
  with Dr. Michael Oakes of the University of Minnesota

Module 5: Quasi Experiments

• Importance in Evaluating Changes that Occur
  with Dr. Kosali Simon of Indiana University-Bloomington
• Design & Analysis
  with Dr. Coady Wing of Indiana University-Bloomington
• Ethical Issues
  with Dr. Greg Pavela of the University of Alabama at Birmingham
• Quasi-Experiments – Real World Case Studies
  with Dr. Nir Menachemi of Indiana University-Bloomington

Module 6: Natural Experiments

• The Role of Natural Experiments in Public Health Decision Making
  with Dr. Christina Ludema of Indiana University-Bloomington
• Study Design and Practical Applications of Natural Experiments in Public Health
  with Dr. David Redden of the University of Alabama at Birmingham
• Analysis
  with Dr. Bisakha Sen of the University of Alabama at Birmingham
• Packet Randomized Experiments: Adoption Example
  with Dr. Greg Pavela of the University of Alabama at Birmingham

Module 7: Genetically Informed Designs – Unmeasured Genotype Approaches

• Co-Twin and Sibling Control Designs
  with Dr. Matt McGue of the University of Minnesota
• Structural Equation Modeling of Twin and Family Data to Assess Causal Effects
  with Dr. Michael Neale of the Virginia of Commonwealth University
• Ethical Considerations: Studying Behavioral Phenotypes in Weight-Discordant Siblings
  with Dr. Tanja Kral of the University of Pennsylvania

Module 8: Genetically Informed Designs – Measured Genotype Approaches

• Causal Inference from Mendelian Randomization
  with Dr. Kaitlin Wade of the University of Bristol
• Methodological Issues in Testing for Gene by Environment or Gene by Behavior Interaction
  with Dr. Ruth Loos of Icahn School of Medicine at Mount Sinai
• Social, Behavioral, and Ethical Issues
  with Dr. Jody Madeira of Indiana University-Bloomington
• Real World Case Studies – Causal Inference and Counterfactuals in Obesity Research: Obesity and the Gut Microbiome
  with Dr. Lee Kaplan of Harvard University

Module 9: Mediating and Moderating Variables

• Conceptual Models (the Mediator-Moderator Distinction, Environmental, Behavioral, Psychological, and Molecular Mediators and Moderators)
  with Dr. David Redden of the University of Alabama at Birmingham
• Testing in General Linear Models
  with Dr. Amanda Fairchild of the University of South Carolina
• Testing in Structural Equation Models
  with Dr. Michael Neale of the Virginia of Commonwealth University
• Real Life Examples & Ethical Issues
  with Dr. Amanda Fairchild of the University of South Carolina

This short course 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.