Behavior Analysis in the Prevention and Treatment of Obesity

A staggering 34% of adults and 20% of children and adolescents in the U.S. are obese (Mitchell et al., 2011), and it has been projected that half of adults in the U.S. will be considered obese by 2030 (Wang et al., 2011). According to the U.S. Department of Health and Human Services (2017), 28% of Americans age 6 and older were physically inactive and 27% of young Americans would not meet the requirements to serve in the military. Obesity is not only unhealthy (correlated with, e.g., hypertension, diabetes, heart disease, stroke, sleep apnea, and death; “Adult Obesity Causes & Consequences,” 2019), but costly as well. The U.S. Department of Health and Human Services estimated that obesity-related illnesses (i.e., chronic disease, disability, and death) costs the United States $190.2 billion annually (“Facts & Statistics,” 2017) with Medicare and Medicaid absorbing most of the cost (Glickman, 2012). Indirect costs of the obesity epidemic also include $3 – $6 billion worth of productivity costs due to obesity-related absenteeism (Centers for Disease Control and Prevention, 2019).

The topic of behavioral interventions targeting obesity began appearing as early as the 1970s in the Journal of Applied Behavior Analysis (Wooley et al., 1979). Such interventions include contingency management (including group contingencies; Aragona et al., 1975; Galbraith & Normand, 2017; Hirsch et al., 2016), prompts and cues (Dubbert et al., 1984; Sigurdsson et al., 2014; Stark et al., 1986), and stimulus equivalence paradigms (i.e., accuracy of portion size; Hausman et al., 2014). Basic behavioral approaches to obesity interventions include two main components: ensuring a calorie deficit (i.e., decreasing food consumption) and increased activity (i.e., exercise; Pinto et al., 2007). Other behavioral components of standard weight-loss treatments include self-monitoring (e.g., food journal, counting calories), stimulus control (e.g., only eating at the dinner table), and goal setting (Pinto et al., 2007). Common environmental modifications that facilitate weight loss and maintenance consist of using a smaller plate, eating more fruits and vegetables, increasing sleep duration, and drinking more water (Cardel, 2013).

Overweight adolescents have a 70% chance of maintaining obesity into adulthood, therefore focusing efforts to target obesity proactively (i.e., childhood) is warranted (“Facts & Statistics,” 2017). Again, targeting food consumption (both the amount and type) and increasing physical activity are integral components to weight loss interventions (Pinto et al., 2007). Children and adolescents spend a large portion of their day at school, creating a convenient setting for intervention (Galbraith & Normand, 2017). There are many interventions targeting physical activity (De Luca & Holborn, 1992; Fogel et al., 2010; Galbraith & Normand, 2017; Patel et al., 2019; Zerger et al., 2016) and healthy food choices (Blom-Hoffman et al., 2004; Hanks et al., 2012; Hoffman et al., 2009; Jones et al., 2014; Lowe et al., 2004 ) in school settings.

While token reinforcement (Patel et al., 2019), adult attention (Zerger et al., 2016), and exergaming (Fogel et al., 2014) have all been effective to increase physical activity among students, the Good Behavior Game (GBG), an intervention easily implemented by teachers (Barrish et al., 1969), is an efficient way to target physical activity among children and adolescents (Galbraith & Normand, 2017). Divided into two groups, 20 third-grade general-education students’ steps were tracked during recess periods using pedometers, with the winning team (i.e., the team that took the most steps), were rewarded with raffle tickets associated with a school wide lottery already in place (Galbraith & Normand, 2017). It was found that participants took more steps during GBG phases than when the game was not being played (Galbraith & Normand, 2017). Because of the time spent at school and the accessibility of teachers, utilizing the GBG to increase physical activity would be beneficial not only with targeting childhood obesity, but could be used to reinforce healthy behavior that could maintain into adulthood (Galbraith & Normand, 2017).

However, increasing physical activity alone is not enough to prevent and reverse childhood obesity; teaching healthy eating is also imperative (Jones et al., 2014). While the Centers for Disease Control and Prevention recommended schools focus on providing healthy food options and teaching healthy food choices (“School Nutrition,” 2019) and nutritionally balanced meals in schools are federally funded and provided (“National School Lunch Program,” 2017), this facilitates only the offering and taking of nutritious food, not the actual consumption (Jones et al., 2014). To tackle this issue, researchers implemented a gamified intervention with elementary school students to increase students’ fruit and vegetable intake (Jones et al., 2014). In what was called the FIT game, increased consumption (i.e., the weight of prepared fruits and vegetables minus unserved fruits and vegetables minus weight of fruit and vegetable waste) led to winning in-game currency that could be used to “purchase” in-game equipment that would aid in ultimately winning the FIT game (Jones et al., 2014). Because the rewards are non-tangible (i.e., in-game), the FIT game is a low-cost intervention making it viable and attractive to schools (Jones et al., 2014).

If the first issue surrounding the obesity epidemic is prevention (i.e., a proactive approach preventing and targeting obesity in children, hoping the behavior change will maintain into adulthood), the second issue would be what to do with the 34% of adults already considered obese (Mitchell et al., 2011). Treatment for obesity ranges from medical solutions (e.g., bariatric surgery, gastric balloons, and medicines) to environmental solutions (e.g., special diets, exercise programs, and self-management programs; “Treatment for Overweight and Obesity,” 2018). While medical solutions are considered a quick and relatively “easy” fix (e.g., a one-time surgery that makes one’s stomach physically smaller, thus restricting overeating), they are expensive (contributing to the $190.2 billion in healthcare costs; “Facts & Statistics,” 2017) and can be a short-term solution if eating and exercise behavior are not targeted for change (i.e., lifestyle changes; Yeager et al., 2008). Existing self-management solutions for obesity typically use a combination of food diaries, regular weigh-ins, tracking exercises, and self-monitoring equipment such as pedometers and fitness watches that help facilitate behavior change (Yeager et al., 2008). Technology has made these  “Skinnerian weight loss programs,” so labeled because of their use of behavioral principles, convenient, as many self-management programs can be found online or downloaded onto a smartphone (e.g., “Lose It,” “Noom,” “Weight Watchers,” “My Fitness Pal,” etc.; Freedman, 2012; Timmons, 2019).

While commercial weight loss programs are abundant, obesity rates in the U.S. remain high (Mitchell et al., 2001; Noguchi, 2019), justifying the need for a different approach. For example, the University of Vermont offered a one-credit course designed to target eating and exercise behaviors in undergraduate students enrolled in the course who were interested in managing their weight and making lifestyle changes through the use of behavioral strategies (e.g., self-monitoring, stimulus control, and goal setting; Harvey-Berino et al., 2012). Over 12 weeks, those enrolled in the course who were of a healthy weight reported losing an average of one to three pounds, with those considered overweight reporting a loss of five to six pounds (Harvey-Berino et al., 2012).

Another example of a successful weight loss program is the MOVE! (Managing Overweight/Obesity for Veterans Everywhere) Weight Management Program for Veterans, an intervention created and implemented by the U.S. Department of Veteran Affairs (VA), consisting of handouts about nutrition, physical activity, and behavior change, goal setting, diet and activity logs, pedometers, self-management, and staff-patient contact (i.e., individual or group meetings; Kinsinger et al., 2009). While treatment effects were evident (i.e., weights increased preintervention and decreased postintervention), maintenance of weight loss was not evaluated, a necessary next step regarding obesity research (Dahn et al., 2011). MOVE! Weight Management Program is promoted by health insurance (i.e., VA medical benefits), perhaps an effective way to provide weight loss interventions to a wide range of people. Another example, Blue Cross Blue Shield of Massachusetts offers reimbursements for participating in certain fitness and weight loss programs (Fitness and Weight Loss Reimbursements, 2020).

It appears as though we have the tools to manage the country’s obesity epidemic (Dahn et al., 2011; Harvey-Berino et al., 2012; Kinsinger et al., 2009), and implementation is crucial (Colbert & Jangi, 2013). Perhaps these tools are best in the hands of our nation’s physicians, as they are the ones faced with treating and managing obesity and obesity-related illnesses (Colbert & Jangi, 2013). Primary care physicians will most often come into contact with the epidemic, therefore their thorough understanding of the “science of obesity” paired with a “mastery of behavioral medicine” is a starting point (Colbert & Jangi, 2013). The dissemination of behavior analytic treatments among physicians to target obesity will help to foster not only the relationship between physician knowledge and practice but might also help facilitate the use of behavior analytic treatments for other issues within the medical field. Colbert and Jangi (2013) stated that effective management of obesity requires a functioning, collaborative interdisciplinary team, specifically noting behavior analysts as being a part of that team; the time is now to begin this necessary collaboration.

Photo by Renee Fisher on Unsplash

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