Methods for Evaluating Natural Experiments in Obesity

Workshop Materials

Background

Obesity is a major contributor to serious health conditions in children and adults. The prevalence of obesity in the United States and globally has grown rapidly in the last three decades; thus, there is a pressing need to help people achieve and maintain a healthy weight.

In adults, obesity is commonly defined as having a body mass index (BMI) greater than or equal to 30, and in children, as a BMI above the 95th percentile of a population growth chart (Centers of Disease Control and Prevention [CDC] growth charts are commonly used in the United States). In 2014, more than one-third (37.7%) of U.S. adults (Flegal, 2016 ) and 17% of U.S. children and young adults under the age of 20 (Ogden, 2016 ) met the definition of obesity. There are also persistent disparities among socioeconomic and racial/ethnic groups in the prevalence of obesity and its health consequences.

Obesity and obesity-related conditions such as type 2 diabetes and certain types of cancers contribute to increased morbidity and mortality across the lifespan, resulting in a significant public health and economic burden. In 2008, the medical costs in the United States for individuals with obesity were $1,429 higher than for those with normal weight, resulting in an estimated annual medical cost of $147 billion (CDC).

Much is already known about obesity, including many of its proximate causes:

  • Poor-quality diet
  • Overconsumption of calories
  • Lack of physical activity
  • Excessive sedentary time

However, because multiple factors (lifestyle, socioeconomics, the environment, etc.) contribute to obesity, it remains an exceedingly complex condition to study.

Challenges

Major gaps exist in our understanding of appropriate and effective societal and systems changes to achieve a healthier energy balance (intake [calories] vs. output [activity]) for individuals. In part, these gaps are related to the amount of research completed to date and to methodological challenges, which range from measuring environmental influences on the causes of obesity to designing and implementing practical and rigorous evaluations of natural experiments. Studies of natural experiments can allow insights into the effects that programs, interventions, or policies have on health-related outcomes including obesity. In obesity prevention research, these include:

  • Effects of investments in transportation infrastructure such as light rail or bike share programs
  • Changes in the food environment, such as construction of new food retail outlets in food deserts or support for farmers’ markets
  • Consequences of economic policies such as taxes and subsidies, particularly those addressing low-income and at-risk populations
  • Changes within organizations such as schools or workplaces
  • Changes in health care systems related to prevention of obesity.

Workshop Goals

The workshop assessed the available scientific evidence to better understand appropriate, high-quality natural experiment research designs in the field of obesity prevention and control, specifically addressing the following questions:

  1. What population-based data sources have been used in studies of how programs, policies, or built environment changes affect or are associated with obesity prevention and control outcomes?
  2. What methods have been used to link different population-based data sources?
  3. What obesity measures, dietary and physical behaviors, and other outcomes have been assessed in studies of how programs, policies, or built environment changes affect or are associated with obesity prevention and control?
  4. Which experimental and non-experimental methods have been used in studies of how programs, policies, or built environment changes affect or are associated with obesity prevention and control outcomes?
  5. What are the risks of bias in studies of how programs, policies, or built environment changes affect or are associated with obesity prevention and control outcomes?
  6. What methodological/analytic advances (e.g., data system features, approaches to linking data sources, or analytic methods) would help to strengthen efforts to estimate the effect of programs, policies, or built environment changes on obesity prevention and control?

Sponsoring Institutes, Centers, and Offices