Combined-Survey Estimation and Markov-Chain Simulation of Childhood Obesity

Research Question
To understand childhood obesity and design effective interventions to address the public health problem, two major research needs emerge from the literature:

  • a need for a joint understanding of biological and social determinants and their interactions
  • a need to develop a better understanding of childhood obesity as a longitudinal trajectory of weight status.

Unfortunately, modeling multiple (more than three) levels of biological and social influence simultaneously is beyond the feasibility of current methods and data. A single survey may have some, but not all, of the variables need to estimate these effects, nor will a single survey have a sufficient sample size for estimation of these multiple effects in a longitudinal model.

To meet these needs, our project will develop methods that combine two longitudinal survey datasets to estimate and simulate trajectories of weight status from birth to adolescence. We will use the simulated childhood life paths to address questions on the absolute and relative impacts on childhood obesity of biological, behavioral and socio-economic variables, and of potential policy interventions.

Modeling Approach
Our solution to the problem of how to include more than three levels of influence entails the following modeling approach:

  1. the use of existing statistical modeling methods for up to two or three levels of influence in any one equation;
  2. the use of multiple imputation from one survey to another to allow pooling of child observations across two surveys and greatly increase effective sample sizes in this model estimation; and
  3. the use of Markov-chain simulation models to allow for more than three levels of influences to be accumulated across four separate equations describing the childhood weight-status trajectory.

Principal Investigator

Michael S. Rendall, PhD
Senior Social Scientist and Director of the Population Research Center
RAND Corporation


Margaret M. Weden, PhD
Social Scientist
RAND Corporation

Zafar E. Nazarov, PhD
Research Associate
Cornell University

Bonnie Ghosh-Dastidar, PhD
RAND Corporation

Meena Fernandes, PhD
Senior Analyst
Abt Associates Inc.

Peter Brownell, PhD
Assistant Social Scientist
RAND Corporation