Xiao Chen is the associate director and senior statistician of the Center's Health Economics Evaluation Research (HEER) Program. She is a co-evaluator of nutrition and obesity prevention programs in Metropolitan and South Los Angeles.
In this brief interview, Chen discusses the methodology and challenges in evaluating the multifaceted Nutrition Education and Obesity Prevention (NEOP-LA) Program.
Q: What are the challenges in evaluating a program like NEOP-LA?
Three important factors come to my mind. One of the goals of this evaluation is to assess the long-term effect of NEOP-LA. Lack of longitudinal data makes it very difficult to estimate or predict what would happen 10 or 20 years ahead. It is also important to take into account the impact family members and coworkers have on a person's health behavior. This social network component is usually not directly observed. Last but not least is that NEOP is not a single intervention program; it has multiple components built-in. We would like to be able to compare the impact of these different components.
Q: Why an agent-based model for this particular evaluation project?
An agent-based model is a type of simulation model and it allows researchers to simulate relationships, interactions among individuals and to synthesize information from different sources, such as individual data, program data and literature review. The idea is to construct computational models that will mimic the real world and allow researchers to test different hypotheses and scenarios.
In a simulation model, we can easily formulate and test a hypothesis related to time, such as how long it takes for an intervention to have a long-term effect. We are able to model a scenario with only a single intervention and also model multiple interventions simultaneously.
Q: Why are you only studying adults?
NEOP-LA programs touch both children and adults. Nevertheless, many of the programs have been targeted more to adults. We created a cohort of individuals and will follow them in the simulation model over many years. In our simulation system, we need to account for population change, such as birth, death and migration. To focus only on adults makes our model more manageable and the results easier to understand.
Additional Information
The UCLA Center for Health Policy Research (CHPR) is one of the nation’s leading health policy research centers and the premier source of health policy information for California. UCLA CHPR improves the public’s health through high quality, objective, and evidence-based research and data that informs effective policymaking. UCLA CHPR is the home of the California Health Interview Survey (CHIS) and is part of the UCLA Fielding School of Public Health and affiliated with the UCLA Luskin School of Public Affairs.