# Strengthening Causal Inference in Behavioral Obesity Research

> **NIH NIH R25** · TRUSTEES OF INDIANA UNIVERSITY · 2020 · $213,719

## Abstract

Project Summary/Abstract
Identifying 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. Behavior is a vital
contributor to variations in energy balance and body composition, the final common pathways of obesity. Social,
environmental and physiological factors are also key influences on behaviors which affect energy balance.
Evidence for causation of these hypothesized factors exists on a continuum from weakest to strongest. Yet, most
obesity research does not consider the evidence continuum between ordinary association tests (OATs)
(observational, non-intervention studies among unrelated individuals), which do not offer strong evidence of
causal effects, and randomized controlled trials (RCTs), which do offer strong evidence, but cannot be done in
all circumstances. In contrast, there are techniques that lie intermediary between OATs and RCTs, including but
not limited to quasi-experimental studies and natural experiments. Such designs are increasingly used,
especially in the disciplines of economics and genetics, but are used by obesity researchers less often than
seems warranted. Our ability to draw causal inferences in obesity research could be strengthened by using such
approaches. In-depth understanding and appropriate use of the full continuum of these methods requires input
from disciplines including statistics, economics, psychology, epidemiology, mathematics, philosophy, and
behavioral or statistical genetics. Applying these techniques, however, does not involve routine ‘cookbook’
approaches but requires understanding of underlying principles, so the investigator can tailor approaches to
specific and varying situations. Yet, other than our annual 5-day short course, no resource provides such training,
particularly for behavioral and social science researchers. Our short course on methods for causal inference in
obesity research, which features some of the world’s finest scientists, has been consistently evaluated by
attendees as essential for their research and teaching. The course provides rigorous exposure to the key
fundamental principles underlying a broad array of techniques and experience in application through guided
discussion using real examples. The course is dynamic in that we refine and modify its content and delivery
methods based on feedback from stakeholders. In this renewal application, we propose to continue to offer this
course, alternating its location between Indiana University and the University of Alabama at Birmingham. Given
the prevalence of obesity and its related health problems, training behavioral and social science researchers to
better assess causal effects is more important than ever.

## Key facts

- **NIH application ID:** 9853989
- **Project number:** 2R25HL124208-06
- **Recipient organization:** TRUSTEES OF INDIANA UNIVERSITY
- **Principal Investigator:** DAVID B ALLISON
- **Activity code:** R25 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $213,719
- **Award type:** 2
- **Project period:** 2014-08-15 → 2024-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9853989

## Citation

> US National Institutes of Health, RePORTER application 9853989, Strengthening Causal Inference in Behavioral Obesity Research (2R25HL124208-06). Retrieved via AI Analytics 2026-05-21 from https://api.ai-analytics.org/grant/nih/9853989. Licensed CC0.

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