Why Is America Fatter Than Ever?

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By Adam Eckart, MS, CSCS, FDN-P

Summary

Obesity has reached epidemic proportions affecting more than 36% of all Americans. The health implications of obesity include risk factors for all other metabolic syndrome conditions including type 2 diabetes and heart disease. These risk factors lead to the most common causes of death including stroke, heart disease, and cancer. These chronic conditions also represent the most preventable illnesses through lifestyle modification including regular exercise and healthy eating. Healthcare spending allocated toward these lifestyle diseases is astronomically high and places undue burden on healthcare funding and the health insurance policy holder. Despite the preventability of these illnesses, the U.S. has created a culture of obesity due to availability of addictive foods, over-medicalization of the health care system, unhinged food industry marketing, failing school physical education and nutrition programs, and lacking obesity awareness.  To add to the issue, evidence suggests food may be used as a coping mechanism for societal pressure experienced by teens during influential school years. With such an overwhelming number of American citizens affected by this illness, governmental policy reform is greatly needed to reverse the deleterious effects of obesity. A health in all policies (HiAP) approach to legislation and federal and state attorneys general intervention would drastically improve the state of health in America. Local government policy implementation and community outreach would provide adult education and health programs and bridge gaps in the continuum of care. Alliances between medical and local health-promoting businesses would accelerate patient behavioral modification and build community health culture.

Keywords: obesity, public health, behavior modification, health in all policies

Population Health Resolution: Obesity

Obesity is a population health issue defined as having a body mass index of 30 kg/m2 or greater (CDC, 2016). Currently, more than 36% of the U.S. adult population is considered obese. Obesity presents risk factors for other chronic illnesses such as heart disease, stroke, type 2 diabetes, and some forms of cancer rise dramatically (CDC, 2016). These comorbidities are also the leading causes of preventable death making obesity a true health crisis. As a population health issue, it is important to acknowledge that obesity affects specific populations more than others. Black and Hispanics have the highest rate of obesity, followed by whites and Asians. Citizens over the age of 40 years are most affected, regardless of race. Socioeconomic status also plays a role with higher incomes linked to higher rates of obesity among most demographic groups (CDC, 2016). In fact, most obese adults are 130% above the poverty line (CDC, 2016). Overall obesity rates have increased across all income and education levels since 1988, yet, there appears to be slightly lower rates of obesity in men and women with a college education. While the specific cause of obesity is at the center of much debate, the availability of calorie-dense foods and reduction in physical activity are undeniably mechanistic. It would be logically assumed that higher economic status and education level would be associated with lower rates of obesity, yet, this is not the case. The fact that childhood obesity is strongly associated with adult obesity gives clues to the underlying cause (Harvard Chan, 2017). Children, as well as adults, have adopted nutritional and physical activity behaviors to accommodate an over-industrialized nation. To make matters worse, the nation’s food industry has profited from our obesity problem and undoubtedly influenced it. Added to the irresponsibility of large food companies, there is evidence that inumerous environmental toxins found in common items could be the cause of childhood obesity (Hyman, 2010). Hyman (2010) states that many toxins found in foods and the lining of food and beverage containers increases risk for diabetes, heart disease, and abnormal liver function due to the deleterious effect these toxins have on metabolic function. Finally, nutrition and physical activity education is greatly lacking from both parental and early educational institutions. Given the myriad of confounding factors affecting this population health crisis, the health culture of the United States must be revolutionized. To that end, broad and local governmental policy must be transformed to reverse the devastating effects of obesity. Therefore, the purpose of this paper is to examine cause and effect nature and propose population health policy reform to address the nation’s obesity crisis.

The Obesity Mentality

There is no single cause of obesity, rather, this illness seems to be a manifestation of U.S. culture. Over medicalization of the health care system, unhinged food industry marketing, failing school physical education programs, unsatisfactory nutrition education, and lacking obesity awareness have established obesity as the norm. Ultimately, behaviors conducive to great health and fitness have been dramatically altered to reflect lifestyles of abundance.

Capitalizing on the wealth of the nation are food companies who are, ultimately, responsible for the choices given consumers. Large food companies with massive marketing budgets, such as Nestle, are advertising food products that are “super-palatable” . These super-palatable foods, containing high amount of salt, sugar, and fat, have been shown to stimulate neurological circuits akin to cases of drug addiction (Tempels, Verweij, & Blok, 2017).  Worse still, these companies market and gamify their products to kids who are unable to distinguish fact from marketing gimmicks. In fact, many food companies direct their marketing towards parents emphasising the health benefits and omitting the consequences (Harris, LoDolce, & Schwartz, 2015).  The large profits realized from overconsumption has enabled these companies to lobby against public health efforts to hold these companies accountable. For example, Pepsico and Coca-Cola gave millions of dollars to health researchers while simultaneously lobbied against health legislation to limit soda consumption in cities like New York City (O’Connor, 2016). It is for this reason, companies involved in corporate social responsibility programs (CSP) receive scrutiny about their motives to participate (Tempels, Verweij, & Blok, 2017).

Despite food big food’s maleficence, U.S. citizens must be accountable for their own health. Yet, many young Americans are unaware of the link between lifestyle behaviors such as physical activity,  health eating and obesity (Sylvetsky et al., 2013). In a study conducted by Alasmari, Al-Shehri, Aljuaid, Alzaidi, and Alswat (2017), only 25% of the over 500 participating students were able to identify obesity as a disease. Evidence by McDavid, Cox, and Amorose (2012) supports the notion that physical educators play a significant role in the away-from-school health behaviors of adolescents. Yet, physical activity participation has been on the decline due to pressure imposed by the No Child Left Behind mandate (Reed, 2013). School administrations have opted to increase classroom time in lieu of physical education minutes and nutrition education. Though, this appears to be counterproductive given physical fitness has been positively associated with reading and math scores, while obesity is linked to a decline in cognitive abilities (Rubens et al., 2016; Srikanth, Petrie, Greenleaf, and Martin, 2015).  The driving force appears to involve the overt prioritization of social status and increased social pressures on our youth. In fact, Lemaitre (2016) theorizes that obesity may be the result of the social bias which causes stress and leads to visceral fat accumulation. Lemaitre adds an increase in society’s narcissistic tendencies, which are the product of materialism and self-promotion, may result in added pressure to achieve higher social status. In cases of under performance or perceived failure, overeating may be used as a coping mechanism. While physical and nutrition education are vital to lowering obesity risk in school-aged children, parental influence on a child’s habits can have long-term effects. Usually, if the parents are overweight, specifically the mother, there is a high probability the children will be overweight (Muthuri, 2016). Additionally, Muthuri (2016) found that maternal education was negatively associated with children meeting the physical activity recommendation. While it is difficult to establish a cause and effect relationship between societal pressure and obesity, abundance and industrialization have been the environment in which obesity has flourished.

Conflicting Interests

While our healthcare system has been dominated by medical interventions, pharmaceuticals have shown meager ability to resolve the obesity (Curry, 2017). In fact, most medications for obesity come with an extensive list of side effects and contraindications, only providing up to 5% weight loss after 12 months. Given 47% of healthcare spending is allocated towards chronic illnesses and up to 40% off all illness are preventable, it appears logical addressing health behaviors would, both, lower premature death and health care spending (Conway, Goodrich, Machlin, Sasse, & Cohen, 2011). Yet only 5% of all health care funding is allocated toward prevention efforts. The reason for this may be controversial, but it is hard to ignore. The Food and Drug Administration receives roughly $2.3 million per drug application submitted for FDA approval. In 2016, the FDA collected almost $8 billion in drug application fees (Wollett & Jackson, 2016).  Drug manufacturing is big business, but efforts to eliminate pharmaceutical profit for up to 40% of all people with chronic illnesses will, most likely, be met with staunch opposition.

The Obesity Solution

Obesity accounts for up to $210 billion in annual medical expenses and $4.3 billion in annual job absenteeism (CDC, 2009). Additionally, obesity is a risk factor for chronic conditions such as type 2 diabetes, heart disease, and stroke. Due to these facts, obesity has become a serious epidemic, one needing government intervention to help resolve. The cause of obesity appears to be multifactorial and includes the availability of addictive super-palatable foods, exposure to neurotoxins during early childhood,  food being used as a coping mechanism for societal pressures, lack of parental education regarding physical activity and healthy eating, and education system primary focus on academic scores. In order to reverse the spread of obesity, both federal and local policy reform is necessary.

Legislative mentality regarding health policy should shift to a health in all policies (HiAP) approach. The HiAP approach to public health is broad-based health care reform where policy-makers consider the impact of all policies on the health of the population (Hardcastle, Record, Jacobson, & Gostin, 2011). Historically, health care and public health sectors have been treated as separate entities with differing goals by policy-makers. While the healthcare sector has been largely concerned with the delivery of health care services, the public health sector has been mostly concerned with preventative and other behavioral interventions that affect the broader population.

One major reform using the HiAP approach should involve elimination of super-palatable food ingredients such as high fructose corn syrup (HFCS) and environmental toxins found on common household items. HFCS has been found to be one of the causes related to childhood obesity and should be banned similarly to the banning of trans fats (Morgan, 2013). Further EPA investigation regarding the over 200 neurotoxins found in the umbilical cords of infants should be highly considered. In addition to reducing the amount of environmental toxins and sugar exposure in children, marketing tactics by large food companies should be mandated for transparency. This regulation would bring about healthier ingredient formulations and more truthful marketing.

Obesity solutions must also involve state and local government policy reform and community outreach. Schools must foster a culture of health by providing better access to comprehensive physical and nutrition education, enforce strict rules on physical activity participation and ensure school lunch options are healthy. Community outreach programs providing access to physical activity, nutrition, and health promoting behavior education and programs to adults across socioeconomic lines would advance health disparity attenuation. Better health behavior education for healthcare professionals would increase continuity of care and hasten the initiation of healthy behaviors in patients. Finally, an alliance among the local medical community and health promoting businesses would provide referral systems and accelerate behavioral modification.

State attorneys general recommendations, historically, have been successful in achieving nationwide health behavior reform as evidenced by recent initiatives in smoking and food and drug labeling  (Pomeranz, & Brownell, 2011). Attorneys general use the doctrine of parens patriae to make protect consumer interests, enact rules and regulations, work together across the states, engage in consumer education, and drafting opinions (Pomeranz, & Brownell, 2011). Using state attorneys general to implement HiAP reform would be a transformative first step in reducing America’s obesity crisis.

Conclusion

Obesity in America has remained at epidemic proportions and continues to worsen year over year. Pharmaceutical interventions have little to offer the obesity crisis. The availability of addictive unhealthy foods and the unethical marketing strategies of large food companies make it difficult for consumers to be informed about healthy foods. The allowance and unregulated use of toxic agents in foods and food products contribute to obesity and illness. The combination of lacking parental education and reduced equity in school health education has created a culture of unhealthy and overweight children. Governments at all levels have a responsibility to protect it’s citizens from unethical or harmful behavior as the result of misinformation or lacking transparency. Health in all policies reform and attorneys general intervention appears to be the most logical and efficient response to reverse the epidemic of obesity.

About The Author

When he’s not working with clients to achieve their health and wellness goals, Adam can be found teaching at Kean University, where he is a professor in their Global Fitness and Wellness Program. He co-designed the concept and practice of Critical Mass Training Systems, employing innovative coaching and training strategies. His expertise in Motor Learning and Control form the basis for his cutting-edge preventive and corrective exercise program. 

Adam also attended Kean University, where he earned a Bachelors Degree in Adult Fitness and a Masters Degree in Exercise Science. He is a Certified USA Weightlifting (USAW) instructor, Certified Strength and Conditioning Specialist (CSCS) and a highly sought after Russian Kettlebell expert.

With over 10 years of experience in the industry – combined with his wide-ranging expertise – Adam is an asset for clients from all walks of life.

 

Do Activity Trackers Really Help?

img_5597By Adam Eckart, MS, CSCS, FDN-P     

     In recent years, wearable activity tracking devices have gained widespread popularity. Research by Bravada et al. (2007) and Cadmus-Bertram, Bess, Patterson, Parker, and Morey (2015) has shown that the use of wearable activity trackers increases short-term activity levels above previous levels in some individuals. Consolvo et al. (2008) and Lin, Mamykina, Lindtner, Delajoux, and Strub (2006) suggest wearing activity tracking devices increases self awareness and provides feedback prompting a user to modify behaviors to increase activity levels. Despite the evidence showing the benefits, new research has shown that measuring activity undermines intrinsic motivation, thus, decreases the enjoyment of the physical activity performed and may lead to cessation of activity (Etkin, 2016). Additionally, a recent study by Jakicic et al. (2016) found activity tracker users lost less weight than those on a standard weight loss intervention.  Research by Clawson, Pater, Miller, Mynatt, and Mamykina (2015) and Li, Dey, and Forlezzi (2010) has shown discontinued or decreased usage of wearable activity trackers is attributable to several factors including device limitations, technological complexity, and incompatibility with changing goals.

      The study of persuasive technology for the purposes of improving health through daily tracking and feedback began in the early 2000s. Devices are considered persuasive if new goals are encouraged and goal achievement is rewarded. Since inception of wearable activity trackers, researchers have failed to show clear associations between use of activity trackers and long-term health behavior. However, researchers have shown short-term increases in activity levels with the use of activity trackers (Bravata et al., 2007). While some researchers have reported long-term tracker usage among participants, study design limitations make it difficult to draw clear associations between tracker usage and long-term behavioral change (Fritz, Huang, Murphy, & Zimmermann, 2014). The researchers of the interview study by Fritz, Huang, Murphy, and Zimmermann (2014) did not question former tracker users to gain clarity on the individual reasons for discontinued use. Similarly, other studies by Day (2016) and Li, Dey, and Forlezzi (2010) using behavioral constructs to determine the efficacy of activity tracking devices utilized qualitative analysis due to small sample sizes and yielded inconclusive data.  Though there exists a substantial body of knowledge in self-quantification theory and technology, it is not quite clear why the evidence for long-term adoption remains inadequate. A deeper look into the literature reveals that behavioral change presents a multifactorial affair and that the current state of activity tracking technology may be limiting people from long-term healthy physical activity habits. Therefore, the purpose of this paper is to analyze the efficacy of current wearable activity tracking technology on long-term behavioral change.  

The Current State of Activity Tracking May Not Contribute to Long Term Behavioral Change

      A recent Internet survey revealed that nearly one in 10 adults owns an activity tracker (Ledger & McCaffery, 2014). Despite the popularity of wearable activity tracker usage, more than 50% of consumers no longer use their device and a third stop using their device after just six months of purchase (Ledger & McCaffery, 2014). Li, Dey, and Forlezzi (2010) proposed that tracker users progress through five stages of self-quantification. These stages are preparation, collection, integration, reflection, and action.  The authors advised that a device must allow the user control in each stage and facilitate the user experience to ensure long-term usage and user success. In other words, the device must adapt to the user’s specific needs by collecting the appropriate information and providing feedback that motivates the user until goals are met. This process starts over when new goals are set by the user. Li et al. (2010) added that this process either becomes iterative or stops if barriers become too high. A recent study by Clawson, Pater, Miller, Mynatt, and Mamykina (2015) shared the sentiments of Li et al. (2010). Clawson et al. (2015) investigated the many reasons former tracker users listed their device for sale on Craigslist. Though no clear conclusions were made, the authors remarked that the following reasons were the most common: changing goals, initiation of new exercise programs, changes in domestic situations, socially-driven device switches, and device limitations. Yet, the Clawson et al. (2015) did not indict activity trackers for the failure of long-term usage by consumers. Instead, the authors proposed that the creators of the technology lack the full understanding of how personal informatics influences behavioral outcomes. Thus, the Clawson et al. (2015) concluded that the technology fell short of meeting the long-term needs of the consumer.  Other theories associated with the complexity of self-quantification models classify users based on the type of motivation and the user’s specific purpose of tracking their activities (Gimpel & Niβen, 2013; Rooksby, Rost, Morrison, & Chalmers, 2014). Yet, Jakacic et al. (2016) showed that individuals wearing activity trackers to track exercise during a weight loss program lost less weight than participants who did not use them. Participants in Jakacic et al. (2016) study were given diet and exercise recommendations, access to weekly support groups, and follow ups calls. The group that received a wearable activity tracker only lost 7.7 pounds on average compared to 13 pounds for the group that did not use a wearable device. The authors proposed that tracking exercise may have lead the group to assume that it earned the opportunity to eat more food.

      Because activity trackers attempt to affect human behavior, a number of constructs have been used to determine the efficacy of the technology. Day (2016) proposed a research model derived from established human behavior constructs to examine positive attitudes displayed by long-term Fitbit users including

  • performance expectancy, which determines the user’s perception of the usefulness of the technology;
  • effort expectancy, which determines the ease of use experienced by the user and the ubiquity of the technology;
  • social influence, which determines the influence of friends or family on usage of the activity tracker;
  • attitude, which determines the degree of motivation derived from the device;
  • and Goal Determination, which determines how a user sets goals, receives feedback, understands their progress, and how this information influences the user to set longer term goals.

      Using the previous constructs and conducting interviews,  Day (2016) revealed how some Fitbit users change the way they use their device. While 93% of participants claimed they intended to use a device in the future, users’ attitudes toward how the device shaped behavior were mixed. For users utilizing their device from one to three months, 63% indicated that usage had not changed and, for some, excitement abated. For longer term users (three to twelve months), usage shifted towards maintaining initial goals and setting new ones. It appears that these results may support Li et al. (2010) stages of useage model, yet, limitations such as self-reported usage and qualitative analysis make it difficult to draw clear associations.

      To further understand human behavior regarding self-quantification, Etkin (2016) examined how individuals felt when their activity was being measured. Etkin (2016) found that when students’ activity level was measured, students increased step count, yet, enjoyed the activity less than when the activity was not measured. These findings are supported by Kruglanski, Friedman, and Zeevi (1971) and Laran and Janiszewski (2010) establishing that activities are extrinsically motivated when output is quantified and that self-quantification tends to make common activities feel like work (Kruglanski, Friedman & Zeevi, 1971; Laran & Janiszewski, 2010). Etkin (2016) displayed that self-quantification could ultimately lead to a reduction in the activity measured and a decrease in subjective well-being. However, it should be noted that some of Etkin’s (2016) results suggested that when measurement is associated with an individual’s goal, it may not decrease enjoyment, especially when measurement is an integral part of the activity.

Activity Tracking Technology Shows Promise for the Future

      The literature regarding the influence of activity trackers on long-term activity behavior appears inconclusive. However, there is strong evidence to suggest activity trackers are consequential for helping users change short term activity levels. For example, Bravada et al. (2007) found pedometers increased activity levels by over 26% when users set a step goal. While several other studies corroborate these findings, researchers have recognized the need for long term studies to evaluate the effectiveness of prevailing activity tracking technology (Barua, Kay, & Paris, 2013). Thus far, research has focused on how the behaviors of adopters have changed due to tracking with various devices (Day, 2016; Fritz, Huang, Murphy, & Zimmermann, 2014). For example, Fritz et al. (2014) and Day (2016) learned that users made durable behavioral changes, especially individuals that used persuasive technology, such as Fitbit.

      Though these studies are limited by sample size and provide only contextual information, activity tracker developers are using similar research to improve tracking technologies. Endeavour Partners, a think tank for digital business and technologies, recognizes the need for tracking devices to manipulate the governing mechanisms of human behavior. Endeavour Partners members, Ledger and McCaffery (2014), have proposed that a wearable activity tracker must involve three factors to ensure long-term engagement and the success of the device in the market. These factors include habit formation, social motivation, and goal reinforcement. Habit formation includes cuing a behavior and rewarding the user after completion. Social motivation involves sharing goals and building a social support network. Goal reinforcement requires continuous objective feedback about progress. Currently, there are several devices on the market incorporating all three components including Polar Flow and Nike FuelBand. Interview studies by Day (2016) and Fritz et al. (2014) support the notion that long-term activity tracker users utilize social media to stay motivated. Bandura (1986) introduced social cognitive theory, a behavioral construct proposing that people make decisions about their behaviors by evaluating the behaviors of others. This theory continues to guide activity tracker makers toward improvement of social media interfaces (Ledger & McCaffery, 2014).

Wearable Activity Trackers of Tomorrow

      Despite short-term improvement in activity levels, the current state of wearable activity tracker technology appears to lack the complexity to align with factors influencing long-term behavioral change. Activity tracker makers are using behavioral constructs such as social cognitive theory and goal setting theory to improve the effectiveness of their devices (Ledger & McCaffery, 2014). Yet, these constructs do not fully explain why many people abandon a device within the first few months of purchase. One proposed solution involves the stages of change model. This theory suggests that people move through five stages change, from not perceiving the need for change to recognizing a problem, developing a solution, taking action, and maintaining progress (Velicer, Prochaska, Fava, Norman, & Redding, 1998). It is important to consider that in order for tracking devices to be effective, an individual must have a strong belief in their need for change. For progress to continue, so must the belief that progress is needed. Activity tracking devices must be part of the solution and the maintenance of progress. Research has shown that activity tracking devices can become a barrier if the device is too difficult to use, does not help the user set new goals, does not provide appropriate feedback, or does not allow social sharing as users advance their progress (Clawson, Pater, Miller, Mynatt, & Mamykina, 2015; Day, 2016; Fritz, Huang, Murphy, & Zimmermann, 2014; Li, Dey, & Forlezzi, 2010).  More research is needed to understand correlations between readiness for change and success for activity tracker users.

      Goal setting and social support are important determinants of long term use which is mediated by self-efficacy (Locke & Latham, 2002). The wearable activity tracker of tomorrow should be able to predict the behavior of the individual and help set and track new goals based on user information such as personality traits, special interests, geographical location, and social network. It appears that the more autonomously the device operates, the more effective it may be to help users achieve long-term behavioral change.

 

 

Adam Eckart, MS, CSCS, FDN-P

Co-Founder, Critical MASS Training Systems