Course Introduction

This is an archive of the in-person course held from June 26, 2023, to June 30, 2023.

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 short course features: (1) Key underlying and fundamental principles of causal inference in obesity research; (2) Applying a broad range of techniques in obesity research; (3) Tailored approaches to specific and varying situations in obesity research.

The learning objectives of this course 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.

Course Modules

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