UTILIZING THE ATTRIBUTION THEORY TO PREDICT HEALTH BELIEFS AND BEHAVIORS ASSOCIATED WITH BMI. Laura Figge. Schmid College of Science

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1 Running Head: UTILIZING THE ATTRIBUTION THEORY TO PREDICT HEALTH BELIEFS AND 1 UTILIZING THE ATTRIBUTION THEORY TO PREDICT HEALTH BELIEFS AND Laura Figge Schmid College of Science Chapman University

2 2 Introduction The prevalence of overweight and obesity is present in more than 68% of US adults, and the rate is rapidly increasing (National Institute of Diabetes and Digestive and Kidney Diseases, 2010). Being overweight is defined as a body mass index (BMI) of 25.0 to 29.9, while obesity is defined as a BMI of 30.0 or higher (Flegal, Carroll, Ogden, & Curtin, 2010). Classified as a public health crisis, nationally representative data shows that the prevalence of obesity has increased at a steady rate for the past 30 years and will continue to remain on the rise (Wang, Beydoun, Liang, Caballero, & Kumanyika, 2008). If the frequency of overweight and obese individuals does indeed continue to increase, it has been estimated that more than 86% of adults will be overweight or obese by 2030; 51% of adults will also be classified as obese (Wang, et al ). Furthermore, it has been estimated that the current US generation may have a shorter life expectancy than their parents if the obesity epidemic cannot be controlled (Wang, Beydoun, Liang, Caballero, & Kumanyika, 2008). The implications of this obesity epidemic are quite substantial on many accounts. Obesity is a risk factor for a variety of chronic illnesses; heart disease, hypertension, stroke, type 2 diabetes, gallbladder disease, osteoarthritis, sleep apnea, asthma, respiratory problems, and cancers such as endometrial, breast, and colon cancer can all be caused by obesity (Leslie, Hughes, & Braun, 2010). These chronic illnesses, such as heart disease, diabetes, and cancer, are among the most frequent causes of death in the United States and worldwide (Yach, Hawkes, Gould, and Hofman, 2004). In addition to the severity of medical implications associated with obesity, the cost of obesity-related care has skyrocketed since the late 1980 s (Wyatt, Winters, & Dubbert, 2006).

3 3 The financial burden of obesity in the US is two to three times greater than in other developed countries; in 2008, the overall cost for overweight and obesity combined was $147 billion. (Tsai, Williamson, Glick, 2011). Evidently, obesity is a problem of national concern, and should be addressed on many fronts (Flegal, Carroll, Ogden, & Curtin, 2010). In order to alleviate the national obesity issue, health professionals must begin by understanding what causes it. For example, is it commonly understood that lack of exercise, overeating, and other environmental factors can cause weight gain. Although obesity may be a multifactor condition, genetics can play a role (Boutin & Froguel, 2001). In fact, recent research suggests that several genetic variants are associated with obesity (Wang & Coups, 2010). Although uncovering the genetic proportions relating to obesity is important in the advance of biomedical research, it has been argued that promoting this information may decrease motivation of obese individuals to engage in healthy lifestyle behaviors such as dieting and exercise (Wang & Coups, 2010). Some research goes as far to argue that even labeling obesity as a public health issue promotes the notion that it is unacceptable and that these bodies are undesirable (Schwartz & Henderson, 2009). It is important that public health messages about obesity be consistent (Schwartz & Henderson, 2009). Aside from understanding the many causes of obesity and tailoring public health campaigns to address preventative behaviors, it also is essential to understand what these obese individuals believe to be the cause of obesity and how this motivates them to address their health. Feelings of stigmatization are common among obese individuals, contributing to poor mental health and judgment (Friedman et al., 2005).

4 4 According to the Health Information National Trends Survey (2007), 20% of the US population believes the extent to which obesity is inherited is a lot. The following chart provides a categorical breakdown of responses: HINTS (2007) QUESTION: To what extent do you believe that obesity is inherited? Would you say? Response Number Percentage Sample Responses Sample Percentage 1 A lot 44,878, % 1, % 2 Some 101,995, % 3, % 3 A little 49,328, % 1, % 4 Not at all 20,122, % % 98 Refused 20, % 2 0.0% 99 Don't know 1,141, % % Total - 100% 7, % As previously noted, research suggests that promoting the possible genetic link to obesity may decrease motivation to exercise among obese individuals. This relationship is worth researching and is the primary purpose of this study. It is interesting to note that in the US, more women than men (35.5% versus 32.2%) are classified as obese (Flegal, Carroll, Ogden, & Curtin, 2010). For these overweight and obese

5 5 women, determining if there is a correlation to their beliefs about whether obesity is genetic is important to understanding the behavioral patterns of this population. If health communication professionals understand the beliefs and motivations of this overweight and obese population, targeted health interventions and campaigns that effectively resonate with this population can be created and implemented. Furthermore, physicians can adapt their communication techniques to uncover this possibly subconscious barrier within their overweight or obese patients, and overweight or obese individuals can successfully maneuver through their internal obstacles to achieve balanced health. Applying a Theoretical Framework: The Attribution Theory A wide range of health literature has shown that using theory in developing health interventions can lead to more powerful effects that interventions not based on theory (Glanz, Rimer, Viswanath, 2008). According to Weiner s (1980) Attribution Theory, people are motivated by the sense of feeling good about themselves. How individuals currently view themselves strongly influences the way they interpret the success or failure of their efforts and their further tendency to repeat the same behavior. Specifically, explanations that people make to attribute success or failure can be analyzed by three sets of characteristics, which for the purpose of this study will be applied to an obesity construct. According to Weiner (1980), the first set of characteristics states that the cause of the success or failure (obesity) may be internal (genetic) or external (environmental). The second characteristic states that the cause of the success or failure (obesity) may be stable (will remain obese because it is internally genetic) or unstable. For example, if an individual believes the cause is stable (genetic), then the outcome is likely to be the same if they perform the same behavior (exercise) on another occasion. An obese individual in this situation

6 6 might think, Exercise and dieting will be ineffective in reducing my weight because obesity is an inherent factor. No matter how often I try to exercise, I will remain obese. The third characteristic states that cause of the success or failure (obesity) may be controllable (environmental) or uncontrollable (genetics). A controllable factor is one which we believe we ourselves can alter if we wish to do so. In this case, one could choose to reduce their weight through exercising more. An uncontrollable factor is one that we do not believe we can easily alter. In this case, the uncontrollable factor would be having a genetic predisposition to obesity. By applying the Attribution Theory to this scenario, I can suggest that for those obese individuals who believe that obesity is inherited (internal), it therefore cannot be controlled by exercise. This conclusion can be illustrated by the following suggested thought pattern of an obese individual: I am obese because it is an internal, genetic predisposition. Because it is internal, it is also stable and will unlikely be affected by exercise. Because my obesity is uncontrollable, there is no point in trying to exercise. Therefore, I present the following research hypotheses: H1: As one s BMI increases, the effect to which one believes obesity is inherited will also increase. H2: Believing that obesity is inherited will have a negative effect on exercise, especially if one is an obese female. Methods & Procedures By using data derived from the United States 2007 Health Information National Trends Survey, a national health information survey among U.S. adults, I set out to document the correlates of the beliefs about the genetic link to obesity. Additionally, I sought to uncover a

7 7 relationship between this belief and the self-reported amount of exercise a person engaged in during the past month. The objective of building the study in this methodological fashion was to uncover possible correlations on whether belief in the genetic link to obesity might cause obese individuals to exercise less or not at all, especially for women; determining such a connection would be an important discovery and predictor for future obesity prevention campaigns. The HINTS (2007) data set contains a total of 7,674. After cleaning the data, which involved selecting only the variables to study, the remaining N=2,034. Measures Participants were selected by focusing on fourteen demographic variables such as BMI, weight, height, age, gender, education level, income level, ethnicity, and smoking status. By using R software, a program used for statistical analysis, the data was cleaned to remove missing or unimportant information. For example, if one were to answer do not know to the question, what is your weight? they would be removed entirely from the data set. The objective of this methodological approach to cleaning the response is to ensure that a full measureable dataset is available. Furthermore, categories within responses were coded to increase compatibility with the R software. For example, responses to what is your gender? would be coded as either a 1 (male) or 2 (female). In order to determine if there were any correlations to the aforementioned variables and the effect to which one believed if obesity was inherited, I used linear regression analysis. Through using this type of analysis, I efficiently analyzed if there was a statistically significant correlation between one s weight and the effect to which they believed obesity was genetic, for example. Upon running statistical summaries for each variable in correlation to the obesity inheritance question, I determined which were significant and which were insignificant by their

8 C o e f f i c i e n t s : E s t i m a t e S t d. E r r o r I n t e r c e p t f a c t o r ( l a u r a 1 2 $ g e n d e r n ) l a u r a 1 2 $ b m i UTILIZING THE ATTRIBUTION THEORY TO PREDICT HEALTH BELIEFS AND 8 p-value. I chose to remain generous in order to be absolutely sure about any correlations and kept those with a p-value less than or equal to 0.1. After removing insignificant variables, I began to build a model by combining such variables to see if significance increased or decreased when doing so. The objective of this process was to determine if by adding variables together, the effect to which one believed obesity is inherited increased. Forward and backward elimination was employed to ensure a process of checks and balances. When this process was complete, the variables were then checked for interactions. No interactions appeared with the demographic variables, the obesity inheritance questions, and whether or not one engaged in any moderate exercise within the past month. Results Although there were no significant interactions among the variables within the dataset, there was a statistically significant correlation between one s BMI, especially a female s, and the effect to which they believed if obesity was genetic. This is illustrated in the final model below: MODEL: lm(formula = laura12$br22genesdetermineweight ~ factor(laura12$gendern) + laura12$bmi) Residuals: Min: , 1Q: , Median: , 3Q: , Max: Multiple R-squared: , Adjusted R-squared: F-statistic: on 2 and 2029 DF, p-value: 3.649e-08 Looking at the intercept (row 1), one can tell that it represents a person who is male with a BMI of zero. This particular person would believe that the extent to which obesity is inherited is a little or some, because those are the lowest choice other than not at all on the scale of choices provided to respondents when asked to what extent they believe obesity is inherited.

9 9 When holding the baseline individual s (a male with a BMI of zero) characteristics constant except for gender a women actually agrees with the dependent variable statement, obesity is genetic, more ( , ). Although this represents a slight correlation, it is a significant correlation of women versus men to the dependent variable. When looking specifically at BMI and holding the baseline individual s characteristics constant except for BMI as the baseline individual s BMI increases, they more strongly agree with the dependent variable statement, obesity is genetic ( , ). For the example of an obese individual, one with a BMI of 30, this would be illustrated by looking at the baseline individual with BMI of 30, there average response would be illustrated by the following equation: ((-0.019) ) * 30 = I can therefore conclude that as one s BMI increases the more strongly they agree with the dependent variable, obesity is genetic. Discussion Although there seemed to be no correlation between one s beliefs that obesity was inherited and whether or not one exercised moderately within the past month, several other significant findings were uncovered in this study that can contribute to obesity related literature and how certain factors such as gender, BMI, and health communication techniques can influence proactive health behavior among the obese population. The outcomes of this study support H1. As previously discussed, as the baseline individual s BMI increases, the more strongly agree they will agree with the dependent variable statement, obesity is genetic. This could suggest that for individuals who continue to gain weight, or are of overweight or obese status, their beleifs are associated with the notion that obesity is a condition, something that has happened to them, rather than something that they can control. Whether or not this has implications on certain behaviors should be further researched.

10 10 Research suggests that social desireability is associated with overreporting of activity, resulting in an overestimation of physical activity; this is especially true for surveys administered over the phone such as the Health Information National Trend Survey used in this study (Adams et al., 2005). This suggests that a follow-up study can be done that uses alternative methods to survey obese individuals on their beliefs about obesity and genetics and their exercise behaviors. Alternative methods that have proven to be more reliable in terms of self-reporting are Internet or even face-to-face qualitative methods. The fact that the data used in this study was gathered through telephone methods is a potential limitation. Additionally, this study found that women are more likely than men to have a correlation to believing the effect to which obesity is inherited is a lot. Although this had no implication on exercise patterns, it did reveal that there was a gender association correlated to this belief. Research supports the fact that obese women tend to reveal more genetic attributions to obesity than obese men (Hilbert et al., 2009). Additional research through qualitative analysis should be done to gather more in depth knowledge as to what leads to a stronger female correlation. Further research is also needed to discover if these correlations, or beliefs, can be modified. In addition, health communication scholars have the opportunity to determine if through altering these beliefs, positive health behaviors can be instilled in the obese population.

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