Causes and Interventions for Childhood Obesity: Innovative Systems Analysis

Research Question
Obesity has become a public health crisis in the United States. Obesity is believed as the result of a complex interplay between biological, behavioral, cultural, social, environmental and economic dynamics operating at multiple levels. Studying such complex dynamics is a challenge using traditional analytical approaches. Our study aims to study how complex factors may affect childhood obesity and test potential intervention options Using integrated conceptual framework, innovative statistical analysis approaches, and rich data from multiple sources. Our central hypothesis is that the determinants of individuals' energy balance related behaviors (EBRB) and body weight outcomes involve complex, dynamic processes including various feedback loops across multi-level factors.

Modeling Approach
Our study have four specific aims and our systematic analysis will be conducted using a set of innovative, sophisticated methods including multilevel models (MLM), and systems analysis models for analyses of empirical and simulation data. Data collected from national surveys including cohort studies linked with contextual measures from other data sources will be used. Our multidisciplinary team has extensive related experiences and a solid track record. Our related methodological products will benefit future studies, and our empirical findings will help clarify a number of controversies surrounding the causes of the childhood obesity epidemic and help direct future interventions. four specific aims are:

Aim 1: Using innovative, integrated conceptual framework and mutlilevel statistical analysis approaches, to examine the influences and interactions between individual, family and environmental factors on childhood obesity.

Aim 2: To determine the key contextual drivers of the childhood obesity epidemic at the population level (i.e., time trends), using a novel combination of systems analysis methods and nationally representative data sets linked with contextual measures. This will help us to develop and calibrate systems dynamics models (SDM) that can accurately replicate the time-course of the obesity epidemic and help project future obesity trends and impact of intervention options.

Aim 3: Using agent-based models (ABM) to test simple rules (eg, how children may interact with their social and build environments) that help explain individuals' EBRB and obesity risk and the changes in population level prevalence of these outcomes.

Aim 4: To identify and characterize promising intervention/policy strategies based our results of aims 1-3, taking into account non-linearities, feedback loops and recursive causal relations, and those in the literature; and to project/simulate impacts of these strategies on obesity rates using SDM and ABM models we developed and calibrated in Aims 2-3. We will also conduct sensitivity analyses based on various specifications of models.


Principal Investigator

Youfa Wang, MD MS PhD
Associate Professor of International Health and Epidemiology
Center for Human Nutrition
Department of International Health
Johns Hopkins Bloomberg School of Public Health (JHBSPH)


Benjamin Caballero, MD PhD
Professor of International Health at JHBSPH and of Pediatrics
at the Johns Hopkins University (JHU) School of Medicine

Joshua M. Epstein, PhD
Center for Advanced Modeling in the Social, Behavioral and Health Sciences (CAM) at Johns Hopkins
Emergency Medicine
Joint appointments: Departments of Economics, Biostatistics, and Environmental Health at JHU

Thomas A. Glass, PhD
Associate Professor
Department of Epidemiology at JHBSPH

Ross A. Hammond, PhD
Fellow in Economics Studies
The Brookings Institution

Benjamin F. Hobbs, PhD, Theodore and Kay Schad
Environmental Management and Professor (Joint) of Applied Mathematics and Statistics, Whiting School of Engineering, JHU
Johns Hopkins Environment, Sustainability & Health Institute

Takeru Igusa, PhD
Civil Engineering, Whiting School of Engineering, JHU
Associate Director
Johns Hopkins Systems Institute

Shiriki Kumanyika, PhD MPH
Epidemiology, Department of Biostatistics and Epidemiology and Department of Pediatrics
University of Pennsylvania School of Medicine

William Pan, DrPH
Assistant Professor at Department of International Health at JHBSPH

Qi Zhang, PhD
Health Economist, Assistant Professor
School of Community and Environmental Health
Old Dominion University