Currently, many nations across the globe experience several socio-economic and health challenges. Opocher and Steedman (2009) note that people in the US encounter challenges like increasing unemployment, rising costs for education, increasing poverty levels, homeliness, obesity, and drug and substance abuse. In 2014, obesity constitutes not only a health problem, but also a social problem due to its association with failing to take control of one’s eating habits. Indeed, it is a dominant issue in social, print, and other forms of media. For example, in an article appearing on the New York Times on 21 February 2014, Hoyt and Burnette (2014) argue that there is a high prevalence rate for childhood obesity, which progresses into adulthood. The Centers for Disease Control and Prevention (2014) observes that 78.6 million or a 1/3 of the total adults in the US are obese. This paper extends the public debate developed by Hoyt and Burnette (2014) on whether obesity should be considered as a moral failing disease.
Discussion of the authors’ claims
Hoyt and Burnette (2014) posit that during the month of June 2013, millions of the American people acquired a disease unrelated to pathogens or illnesses. However, they reckon that the American Medical Association arrived at a decision to tag obesity as “multi-metabolic and hormonal disease state” (Hoyt and Burnette, 2014, par.8). This move gives rise to the main public debate on the appropriateness of labeling obesity as a disease, especially given its causation. Hoyt and Burnette (2014, par.12) point out that calling obesity a disease has the impact of creating a warning on its health risks. Mixed reactions on perceiving obesity as a disease emerged, thus prompting intensive medical research to provide medical remedies to it.
Apart from concerns of the causation of obesity, Hoyt and Burnette (2014) are concerned with the public psychological implication of tagging obesity as a disease. Can such a move have implications on people’s body image, especially feeling shameful about their body overweight? Can the move lead to empowerment of people and increase the acceptance of their body image? While Hoyt and Burnette (2014) provide a direct response to these queries, the questions posed above are critical for further research. The authors hypothesize that labeling obesity as a disease has the implication of making people seek mechanisms of avoiding it. However, their research findings confirmed the opposite.
Deploying a sample of 700 people divided into two groups, they randomly assigned the participants reading material with different health messages. One group read newspaper detailing the American Medical Association’s decision. The controlled group read weight-loss messages in a standard public health format or any other article arguing that obesity does not constitute a disease. Finally, both groups filled questionnaires on their eating behaviors and altitudes towards obesity. Arguably, this aspect entangles an attempt to study the causation of obesity coupled with how it shapes public opinion on health challenges facing the Americans.
Hoyt and Burnette (2014) found that labeling obesity as a disease had two implications. Firstly, their hypothesis that messages presenting obesity as a disease would lead to self-body image satisfaction was confirmed.
They explain this finding by theoretical assumption that the message eliminates shame associated with overweight and the perception of moral failing. Secondly, the message had the implication of creating the perception that one’s weight constitutes a fixed state or long-term illness (Hoyt & Burnette, 2014). This assumption lowers focus on good eating habits and worries over getting overweight. For instance, as compared to the control group, the other group selected foods having more than 7% calories. To this extent, obesity correlates with people’s altitudes and perceptions towards it. In this relationship, body weight acts as the dependent variable while perception on whether obesity is a disease or not acts as the independent variable.
Scholarly and governmental sources indicate that over the last two decades, incidences of obesity in the US have been on the rise. The Centers for Disease Control and Prevention (2008) reckons that 19.5 percent of the American population was obese in 1997. This figure rose to 24.5 percent in 2004 then to 26.6 percent in 2007 and finally to 33.8 percent among adults, and 17 percent amongst children in 2008 (Shalikashvili & Shelton, 2010).
The Centers for Disease Control and Prevention (2014) reported escalated figures for obesity, viz. 35.7 percent of the American adults coupled with17 percent of children were obese. Data from NHANES confirm the trend of increased obesity among the American children. Hartocollis (2010) echoes the NHANES’ survey in 1976 to 1980 and in 2003 to 2006 for children aged 2 to 5 years. The prevalence of obesity hiked from 5 percent to 12.4 percent while for children aged 6 to 11 it moved from 6.5 percent to 19.6 percent (Hartocollis, 2010, p.16). From these statistics, it is evident that obesity in the US is on the rise amongst the general population. However, what is causing the rise?
Hoyt and Burnette (2014) relate the increasing number of overweight Americans to their perceptions about the condition. Alternatively, the problem of obesity can be explained from the perception of eating habits and fast foods’ mainstream culture. Various scholars have argued that fast foods have close associations with higher calories intakes, fats, poorer nutrients intakes, higher sodium intakes, higher BMI, and hence rising obesity (Bowman, Gortmaker, Ebbeling, Pereira, & Ludwig, 2004). Niemeier, Raynor, Lloyd-Richardson, Rogers, and Wing (2006) attribute higher weight gain amongst American children to increased fast foods intake during the transition age from adolescence to adulthood (p.843). Freedman et al. (2005) note that obesity tracks people from their childhood to adulthood.
The above arguments imply that obesity relates to poor eating habits and food choices. However, these two determinants are modifiable by contextual and environmental factors. These factors entails making healthy foods available and ensuring that only convenient and appealing healthy foods are promoted coupled with price variations. Freedman et al. (2005) posit, “Food prices have been shown as key determinants of consumption of fast foods” (p.25).
If price can influence the rate of consumption of foods leading to obesity, then it is an independent variable in the causal relationship for fast foods and obesity. Chou, Rashad, and Grossman (2008) argue that fast food prices are negatively associated with obesity. A research by Beydoun, Powell, Chen, and Wang (2011) deploying 1994 to 1998 data on food intake surveys conducted by CSFII (Continuing Survey of Food Consumption by Individuals) studied the roles of price and fast foods consumption amongst the US youngsters. It concluded that higher fast food prices lead to lower consumption by children aged 2-9 years coupled with 10-18 year old adolescents.
However, the association proved not significant statistically for the adolescents considered (Beydoun et al., 2011). From deductions of another study using high school cafeteria data, increasing prices of food possessing high fats contents, viz. cookies, cheese sauce, and French fries by 10% does not change significantly the revenue generated by fast food store (French, 2003).
This trend does not change even after lowering the price for low-fat content foods, viz. fresh fruits, low fat French fries and cookies and the cereal bars, by 25%. This realization implies that price adjustment, which is an independent variable, can shift people’s consumption of high calories foods to healthy foods with the ramification of reducing obesity (the dependent variable).
A study conducted on prices of vending machines indicated that reducing the prices of snacks containing low fats by 10 and 25 percent led to 9 and 39 percent increase in sales among adults and adolescents respectively (French, Jeffery & Story, 2001). From this study, the consumption of foods containing high fat contents and energies are related to prices of the fast foods. However, does this pattern only apply within certain geographical regions or can it be extended into larger geographical regions and reflect the actual scenario happening in the US? In the equation of demand and supply, price is a significant parameter that determines quantities produced and consumed in the market.
Therefore, it is possible to hypothesize that increased cost of foods, for instance, pork would lead to increased cost of production of pork-related products, and thus fewer sausages would reach the consumers. Economically speaking, decreased costs would arguably lead to the converse result. In economic terms, it is then anticipated that other products such as poultry, rice, bread, milk, dairy products, fruits, vegetables, fast foods, and beef would have similar relationship with price as pork. This aspect means that obesity can be related to low cost of foods containing high fats and high energy levels.
Statement of research hypothesis
Borrowing from Hoyt and Burnette (2014), public ideologies on overweight can explain the prevalence rates of the problem. Additionally, changes in prices of unhealthy foods can potentially induce positive healthy foods’ eating culture. In support of these theoretical propositions, it can also be hypothesized that media profiling of fast foods helps in reinforcing attitudes favoring increased consumption of unhealthy foods leading to obesity.
Studying the hypothesis
Research can be designed to unveil correlations, associations, differences, or relationships. In a bid to prove or disapprove the hypotheses that media, through advertisement, help to profile positively and encourage the consumption of high calories foods, it is important to design the research as that seeking to unveil an association. Thus, the role of media and advertising in encouraging the consumption of fast foods can be studied through experimental research design. Such a design makes it possible to address the association, temporal ordering, and elimination of alternative explanation criteria for causality. Two main approaches can be used to complete the task.
Firstly, a researcher may analyze data on traffic flow within fast food organization before and after initiation of marketing campaigns promoting food with high calories. The data for this research can be obtained from archives of organizations selling fast foods. In this kind of research, an assumption is made that huge sales for foods with high calories in fast foods stores directly correlate with increased obesity. Secondly, an experimental research through studying a sample size representative of the clientele for fast foods may reveal the association of media with repeated purchase of high calories’ foods.
The assumption here is that higher frequencies for purchasing foods with high calories increase the risks for acquiring obesity. In the two types of research, it is also important to assume that people depend largely on information flow in making their purchasing decisions so that without product communication, an organization makes insignificant amount sales.
In a bid to operationalize variables in the first case, the number of times a fast food advert runs constitutes the independent variable. The resulting amount of sales comprises the dependent variable. To indentify a relationship between these two variables, it important to consider data from different fast food organizations and focus on similar types of products in different organizations. In the second case, the number of times an advert runs still comprises the independent variable. However, the dependent variable is the reports on repeated sales on watching promotional material for fast foods. In both cases, statistical and qualitative analysis is necessary to arrive at research findings and conclusions.
Finding supporting the models
Media is an important force for driving sales and inducing positive perceptions about a given product. In most instances, potential customers receive information about the need to shun or embrace the consumption of fast foods from traditional media, the Internet, and social media (Chou, Rashad & Grossman, 2008). Through new media, it is possible to reach a large number of people globally with minimal expenditure of an organization’s financial resources (Shalikashvili & Shelton, 2010). This assertion holds true especially for social media. Customers share promotional information among themselves with some promotions going viral (Maktoba & Sonny, 2011). Therefore, it is not coincidental that new and traditional media may be responsible for the escalation of the problem of obesity in the US.
Research on association of media with increased obesity in the US suffers some drawbacks. The first approach depends on data retrieved from the fast foods organizations’ archives. In the US, there is increasingly public sensitization on the need to shun unhealthy fast foods.
Hence, the willingness of the organizations to provide necessary data is unwarranted. Consequently, the accuracy and reliability of the data is questionable. In the second type of research, some promotional campaigns through the media may yield impacts in some organizations and fail in others. Thus, an unbiased research would need studying all fast food organizations. However, this proposition is practically impossible in some situations due constraints in human resources and financial requirements for conducting such research in all states across the US. This aspect poses the challenge of generalization. The finding may not apply to all the States in the US.
Beydoun, M., Powell, L., Chen, X., & Wang, Y. (2011). Food prices are associated with dietary quality, fast food consumption, and body mass index among U.S. children and adolescents. Journal of Nutrition, 141(2), 304–311. Web.
Bowman, A., Gortmaker, S., Ebbeling, B., Pereira M., & Ludwig, D. (2004). Effects of Fast-Food Consumption on Energy Intake and Diet Quality among Children in a National Household Survey. Pediatrics, 113(1), 112–118. Web.
Centers for Disease Control and Prevention. (2008). Early Released of Selected Estimates Based on Data From 2004 National Health Interview Survey. New York, NY: Centers for Disease Control and Prevention. Web.
Centers for Disease Control and Prevention. (2014). Overweight and Obesity: Adult Obesity Facts. New York, NY: Centers for Disease Control and Prevention. Web.
Chou, S., Rashad, I., & Grossman, M. (2008). Fast-food restaurant advertising on television and its influence on childhood obesity. Journal of Law and Economics, 51(4), 599–618. Web.
Freedman, D., Khan, L., Serdula, M., Dietz, W., Srinivasan, R., & Berenson, G. (2005). The relation of childhood BMI to adult adiposity: the Bogalusa heart study. Pediatrics, 115(1), 22–27. Web.
French, A. (2003). Pricing effects on food choices. Journal of Nutrition, 133(3), 841–843. Web.
French, A., Jeffery, W., & Story M. (2001). Pricing and promotion effects on low-fat vending snack purchases: the CHIPS study. American Journal of Public Health, 91(1), 112–117. Web.
Hartocollis, A. (2010). Growing obesity increases peril of child bearing. The New York Times, p. 16. Web.
Hoyt, C., & Burnette, J. (2014). Should obesity be a disease? The New York Times. Web.
Maktoba, I., & Sonny, N. (2011). Internet marketing and customer satisfaction in emerging markets: the case of Chinese online shoppers, Competitiveness Review. An International Business Journal incorporating Journal of Global Competitiveness, 21(2), 224-237. Web.
Niemeier, H., Raynor, A., Lloyd-Richardson, E., Rogers, L., & Wing, R. (2006). Fast food consumption and breakfast skipping: predictors of weight gain from adolescence to adulthood in a nationally representative sample. Journal of Adolescent Health, 39(6), 842–849. Web.
Opocher, A., & Steedman, I. (2009). Input Price-Input Quantity Relations and the Numeraire. Cambridge Journal of Economics, 3(2), 937-948. Web.
Shalikashvili, J., & Shelton, H. (2010). The latest national Security threat: Obesity. The Washington Post, p. 37. Web.