Relationship between Obesity and Depression - Research Proposal Example

?Running head: OBESITY AND DEPRESSION The Relationship between Obesity and Depression: Co-morbidity of the Physical and the Mental Affiliation Abstract Obesity and depression pose a definite problem to developing and developed regions, both in terms of their physical and their mental health threats at an individual level. Obese individuals are more likely to report stronger depressive symptoms, and depressed individuals are less likely to adhere to high nutritional standards and physical activity. Given the scope of the obesity and depression problems, this study hopes to establish a significant correlation between the two variables in a general context by utilizing a new method of measuring obese body types and comparing that to a standardized measurement of depressive symptoms. Ultimately, it is hoped a significant relationship between these physical and mental symptoms can increase the reliability of depression diagnoses so that depressive symptoms may be addressed earlier in their onset. The Relationship between Obesity and Depression: Co-morbidity of the Physical and the Mental The term “epidemic” is often fashionably applied to a range of perceived health problems facing specific parts of the world. For years, scientists have known that rapid increasing rates of obesity in the United States are creating a problem for governments in terms of healthcare costs and food resources (Mokdad, Serdula, Dietz, Bowman, Marks, & Koplan, 1999). In addition, obesity is a source of decreased life satisfaction and contentment, which does not bode well for a country’s mean happiness levels as it becomes increasingly overweight. However, as recent research has shown, the so-called “epidemic” obesity is not limited per se to one or even multiple nations, particularly in the developed world (Caballero, 2007). Even in the developing world, where food resources are perceived as being scarce, obesity is becoming an increasingly apparent problem, along with the other co-morbid conditions that follow being overweight. As obesity rates increase on a worldwide scale, the problem is not so much an epidemic, but a pandemic. Perhaps coincidentally, rates of depression around the world are on the rise. Within developed countries where data is obtainable, cohort studies reveal several sharp spikes in rates of depression throughout the 20th century (Klerman & Weissman, 1989). This is particularly noteworthy following macroeconomic declines and traumatic national crises, such as World War II and the 1973 oil crisis. The connection between declining economic prosperity and increasing rates of obesity are well-established (Ludwig & Pollack, 2009). However, there is possibly a third variable at work in those studies of obesity and the economy. Major depressive disorder and its symptoms seem to emerge out of worsening economic conditions, with growing concerns about one’s financial well-being tied to one’s subjective well-being and overall happiness. Lower levels of well-being might conceivably lead to lower nutritional standards and less time devoted to physical activity—both risk factors for obesity. In addition to a possible link through studies of the economy, major depressive disorder and obesity may be otherwise connected on an individual level. In a study of depressive and suicidal patients, Lester, Iliceto, Pompili and Girardi (2011) noted a statistically significant link between not only a patient’s obesity and his depressive symptoms, but also his risk for suicide and other self-destructive behaviors. Among young people, suicide rates are traditionally very high; however, with the added risk factor of obesity, the link becomes troublesome for preventing and addressing suicide concerns. In addition, suicide rates among young people (particularly males) have been on the rise for a number of years, which is correlated with rising rates of obesity in the countries studied (Wasserman, Cheng, & Jiang, 2005). As was mentioned previously, all of these associations between different variables such as rate of suicide, rate of obesity in a population, rate of depressive disorder in a population, macroeconomic prosperity, and so on may be coincidental. Regardless, they offer some rational basis for wanting a clearer picture of how related each of these factors is to each other. Other recent developments in the field point to a link between obesity and depression in the population. For instance, one recent study confirmed the link between depressive disorders and obesity that was influenced by lower social and physical activities among the depressed (de Wit, Fokkema, van Straten, Lamers, Cuijpers, & Penninx, 2010). This kind of evidence also indicates a third variable operating in the mix between obesity and depression, leading to the overall impression that the relationship between the two variables is not a simple one-to-one correlation. The authors also postulate that obesity is related (as an effect) with depression (as a cause), while there is no direct evidence pointing to that as the correct directionality of causation. Perhaps obesity is a cause more often of depression than depression is of obesity. These kinds of causality questions are important for treatment and classifying mental illnesses. Evidence from recent studies of obese depressives indicates also a different kind of experience of depression symptoms. For one, depression symptoms among obese patients tends to be more severe than depression in non-obese patients, and according to the authors, gaining weight while depressed is a marker of their depression’s severity (Murphy, et al., 2009). Thus, depression’s role as a cause of obesity is highlighted in another study. Secondly, the authors indicate that additional research is necessary in establishing a better knowledge of “sequences and outcomes of depression,” which is taken to mean an understanding of both how depression sequentially develops and how it is corrected among obese patients. Further work in the area of depression and obesity should seek to better understand the directionality of causation based on current work attempting to establish a firm link between the two variables. This involves proving that the link is statistically more likely than chance, or due to coincidence. The present study seeks to further our understanding of how obesity and depression are related through a measurement of co-morbidity in study participants. Lastly, it is important to note that a significant correlation (or co-morbidity) between obesity and depression would indicate an important link between a physical illness and a mental illness, which is methodologically important because outward symptoms of a mental illness provide a surer and more certain way of diagnosing those mental illnesses. The present study seeks to add to that diagnostic ability through establishing a definite link between depression and its physical correlates. Based on the results of previous studies such as Lester et al. (2011) and Murphy et al. (2009), we hypothesize that obesity is statistically significant in its correlational relationship to major depressive symptoms as measured by a questionnaire. The expected results of this study and their possible implications to the field of research are discussed in subsequent sections of this paper. Methods In terms of participants, we anticipate recruiting a number large enough to ensure a statistically significant relationship between the variables. In their study of suicidality’s relationship to body weight, Lester et al. (2011) took responses from 70 obese patients. In this study, we expect to recruit a similar number of participants to give responses to the measuring instruments. Seventy participants is a reasonable number because (a) it is a realistic and attainable goal for running this experiment and (b) that number replicates similar kinds of studies, such as Lester et al. (2011). This n=70 estimate does not include the participants who will be initially screened for the study. Since this study is looking to question only an obese sample, underweight, normal weight, and overweight individuals will be excluded from participation. Demographically, we expect that this sample will be primarily white, have an age mean between 18 and 22, and have a relatively low income. Anyone younger than 18 years of age will be automatically ineligible. An important consideration to note is possible ethical challenges to this study. Since obesity and depression are both heavily tied to an individual’s self-concept, there is potential for the questions asked by the survey to be personally upsetting to participants if they are especially sensitive about their weight and others’ perceptions of them. For that reason, explicit consent to participate in the study—highlighting both its benefits and its potential costs to the individual—should be given even before a potential participant answers the screening questions about his or her weight. Some surveys may be administered in person rather than over the computer; in those cases, researchers should be instructed on how to treat individual participants with respect and to not deviate in their interactions with participants beyond explaining the content of the consent form. Each participant will be asked to sign the consent form (entering their first and last name if conducted digitally), stating that he understands the purpose and methods of the study. Outside of the consent form, no personally identifying information is collected from participants. In terms of the measuring instrument, this study does not incorporate the body mass index for evaluating whether an individual is obese. The body mass index is an easy instrument for a general idea of whether a person is underweight, normal weight, overweight, or obese, with values greater than 30 representing obesity (Dalton, et al., 2003). However, criticisms have cast doubt on the ability of BMI measurements to accurately assess an individual’s cardiovascular risk factors, which play a part in negative physiological health of excess body fat (Dalton, et al., 2003). Instead, hip-to-waist ratio is taken to be a better predictor of cardiovascular risk factors and obesity in general. Hip-to-waist ratio explains a greater amount of variance in health risk than body mass index alone. Accordingly, for the purposes of this study, participants are screened based on their waste circumference. As part of screening for participation, individuals are asked to use a conventional tape-measuring device. To find hip circumference, participants must be wearing light clothing only and wrap the tape around their hips (at the widest point over the buttocks) to obtain a measurement in centimeters. Afterward, participants apply the same procedure to their waist to obtain a measurement in centimeters. Two measurements for both hip and waist are completed, the mean of which constitutes the measurement for each participant. In line with WHO (1998), waist-to-hip ratio is obtained by dividing the mean waist circumference by the mean hip-circumference. Men with a WHR 0.90 to 0.99 and women with a WHR 0.80 to 0.84 are cataloged as overweight, while men with a WHR greater than 1.00 and women with a WHR greater than 0.85 are cataloged as obese. These measurements are taken to be a more reliable computation of obesity than BMI because BMI does not incorporate information about muscle to fat mass on a person’s body. Waist-to-hip ratio implicitly incorporates that information in where it measures and how the ratio is derived. After this initial screening, the WHR data for each participant is retained. Those who are screened and deemed overweight or obese by the WHR scaling technique move on to a second round of participation, which is a measure of depressive symptoms. The Major Depression Inventory (MDI) is a self-report mood questionnaire originally developed by the World Health Organization (Bech, Rasmussen, Olsen, Noerholm, & Abildgaard, 2001). Not only does the MDI provide an affirmative diagnosis of depression, but it also gives some idea of the severity of those depressive symptoms. On a scale of 0 to 50, the severity of symptoms is rated either as moderate or severe. This questionnaire is completed either online or on the computer, depending on what is more convenient for participants. In addition to being accurate, the survey is brief and non-invasive, which adds to its appeal as a quick method of gauging a respondent’s depressive symptoms. The survey tests participants on nine recognized symptoms of major depressive disorder, in addition to feelings of guilt. Each question is constructed on a ratio scale, with either a presence (n=1) or an absence (n=0) of major depressive symptoms. Moderate to severe (major) depression is diagnosed in the presence of at least two of the three core symptoms (depressed mood, lack of interests, and lack of energy) and at least four of the other seven items. After completing the questionnaire, the participant’s WHR measurements are paired with the MDI scaled responses in preparation for a correlational analysis. As was mentioned previously, the procedure for this study occurs in two stages, with the first stage consisting of a pre-screening obesity measurement and the second stage consisting of a depression measurement. Participants are made aware of the fact that their responses will only be considered in the aggregate of all responses collected from each participant. Proposed Data Analysis Given the presence of two variables, both of which are expressed on ratio scales, it is expected that a Pearson’s r correlation will be computed to measure the statistical significance of their relationship. Pearson’s r is a measure of linear dependence between two variables that seeks only to answer questions about whether two variables are dependent on one another, not about which variable is dependent on which. Therefore, this initial data analysis will reveal only whether there is a statistically significant relationship between depressive symptoms as rated by the MDI scaled test and obesity as measured by the WHR given by the World Health Organization (1998). The criterion of significance in this case will be a standard 0.05 measurement (significant if P < 0.05, meaning “significant” if there is less than a 1/20 chance that the variation is due to chance). If the alpha level in this case is greater than 0.05, the chances of a Type I error (that is, rejecting a true null hypothesis that obesity is unrelated to depression) are too high. Clearly, the possibility of making a Type I error with only a 1/20 chance of a statistically significant correlation being due to chance exists; however, a statistically significant rejection of the null hypothesis is safely assumed to be the rejection of a false hypothesis. With the alternative hypothesis being that there is a relationship between depressive symptoms and obesity, we expect to find a statistically significant positive correlation between the two variables. For the purposes of this data analysis, any Pearson r correlation between -0.09 and 0.09 is rated as “no correlation.” Any positive correlation between 0.10 and 0.30, 0.31 and 0.50, 0.51 and 1.00 are taken to be “small,” “medium,” and “large” respectively. Lester et al. (2011), for instance, computed an r = 0.32 correlation between suicide rate and depressive symptoms in the patients in their study. On the scale proposed above, this would rank as a “small” but significant (P < 0.001) correlation. Discussion Even after conducting a correlational study of 70 obese people, how does one interpret a statistically significant relationship between obesity and depression? The primary facet of an interpretation of that result is predictive ability: now that we know there is a definite, very likely relationship between the two variables, we can identify that the likely presence of one factor indicates the likely presence of the other factor. In depressive individuals who are underweight or normal weight, this does not mean weight gain will inevitably follow. But for depressive individuals who are overweight and obese, this seems to indicate that depressive symptoms will be more severe and less likely to dissipate with existing treatment modalities, which is in line with the results of Murphy et al. (2009). In addition, other mediating factors (such as proclivity to suicidal thoughts and macroeconomic conditions) play a role in these relationships, which are not addressed in this correlational study. A positive relationship between obesity and depression produces application-oriented question sets tied up with concerns about how we treat and alleviate depressive symptoms. As was mentioned previously, the results of this study (if obtained) will provide a foundation for taking the first step in any diagnostic process: identifying that there is a problem. Knowing that there is a positive correlation between obesity and depression provides psychiatrists the diagnostic tool of being able to recognize and predict the presence of one problem based on the presence of another. One of these problems happens to be a very visible outward manifestation of a mental problem that individuals can sometimes hide to the outside world because of shame or guilt. In addition, given the role that obesity plays in strengthening and perhaps worsening depressive symptoms, treatments may address those mental illnesses by directly addressing their physical co-morbid correlates. Limitations of this research focus primarily on the fact that the relationship between obesity and depression is so tremendously complex that establishing a correlation between the two variables does not address all of the mediating variables at play. However, the purpose of this study was not to categorize and rate the effects of third variables. Rather, this study seeks to establish the generality of the relationship. This limitation remains an indicator of a possible direction for further research, one that is gaining interest as obesity and depression become greater epidemics (Caballero, 2007). An additional limitation of this research is that it does not establish causal directionality between the two variables: that, like most other studies in the literature, neither obesity nor depressive symptoms are found to be definitively linked causally to the other. Again, the purpose of this study was to establish the connection between the two variables, not to define the causal relationship between them. In part, this is because the connection between the two variables is context-dependent and relative to circumstances. It is doubtful, in fact, that a psychiatrist will ever have the methodological capability to diagnose a person’s depression as definitively caused by his or her obesity and vice versa. Previously, we surveyed the growing problem that obesity and depression both pose to a global society, as opposed to simply developed countries. Growing attention is needed to examine the complex relationship between obesity and depression: research that will build on the conclusion that there is a definite correlation between the two variables. With increased knowledge about how obesity increases the severity of depression and how depression increases one’s risk factors for obesity, better treatments can be produced to mitigate the physical and mental harms of these co-morbid conditions. Part of this effort will consist of developing and improving how we measure obesity, depression, and related conditions, which is an effort briefly addressed and continued in this study. References Bech, P., Rasmussen, N., Olsen, L., Noerholm, V., & Abildgaard, W. (2001). The sensitivity and specificity of the Major Depression Inventory, using the Present State Examination as the index of diagnostic validity. Journal of Affective Disorders, 66 , 159-164. Caballero, B. (2007). The global epidemic of obesity: An overview. Epidemiologic Reviews, 29 , 1-5. Dalton, M., Cameron, A., Zimmet, P., Shaw, J., Jolley, D., Dunstan, D., et al. (2003). Waist circumference, waist–hip ratio and body mass index and their correlation with cardiovascular disease risk factors in Australian adults. Journal of Internal Medicine, 254 , 555-563. de Wit, L., Fokkema, M., van Straten, A., Lamers, F., Cuijpers, P., & Penninx, B. (2010). Depressive and anxiety disorders and the association with obesity, physical, and social activities. Depression and Anxiety, 27 , 1057–1065. Klerman, G., & Weissman, M. (1989). Increasing rates of depression. The Journal of the American Medical Association, 261 , 2229-2235. Lester, D., Iliceto, P., Pompili, M., & Girardi, P. (2011). Depression and suicidality in obese patients. Psychological Reports, 108 , 367-368. Ludwig, D., & Pollack, H. (2009). Obesity and the economy: From crisis to opportunity. The Journal of the American Medical Association, 301 , 533-535. Mokdad, A., Serdula, M., Dietz, W., Bowman, B., Marks, J., & Koplan, J. (1999). The spread of the obesity epidemic in the United States, 1991-1998. The Journal of the American Medical Association, 282 , 1519-1522. Murphy, J., Horton, N., Burke, J., Monson, R., Laird, N., Lesage, A., et al. (2009). Obesity and weight gain in relation to depression: findings from the Stirling County Study. International Journal of Obesity, 33 , 335-341. Wasserman, D., Cheng, Q., & Jiang, G. (2005). Global suicide rates among young people aged 15-19. World Psychiatry, 4 , 114-120. World Health Organization. (1998). Obesity – preventing and managing the global epidemic: Report of a WHO consultation on obesity. Geneva: World Health Organization. Read More