Relationship Between Obesity and Depression

Relationship between obesity and depression

PICO question:  In patients ≥ 18 years with a BMI≥ 29.9, does incorporating psychiatric evaluation in their comprehensive care plan reduce the risk of depression by about 50% compared with those not integrating psychiatric evaluation in their comprehensive care plan?

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P: Patient Population– ≥ 18 years obese patients (B.M.I.≥ 29.9)

I: Intervention– Incorporating psychiatric evaluation such as Multidimensional Body-Self Relations Questionnaire – Appearance Scales (MBSRQ-AS) in the comprehensive care plan of obese patients

C: Comparison– Obese patients whose comprehensive care plan does not include psychiatric evaluation

O: Outcomes– Lower risk of depression by about 50%

 

This PICO was done by the previous writer, pls kindly rewrite as per comment highlighted.

Yes, there is a relationship between obesity and depression. However, let the body/content of this work be guided by the pico question, which is basically asking how can incorporating psychiatric evaluation into comprehensive care plan of obese patient reduce the prevalence of depression among this population. Therefore, I am expected to do my research on one or two psychiatric evaluation tool that has been proven to reduce the prevalence of depression among obese patient. When I say obese patient, I mean male and female ≥ 18 years with B.M.I.≥ 29.9.

This is a literature review assignment. For this work, I please need a PICO question, an Abstract, Introduction, Background and significance, Method, Review of Literature, Discussion, Conclusion, Reference (15-18, should be fine. Pls include at least 2 practice guidelines, as part of the references). Then Evaluative Bibliography.

Instruction for Evaluative Bibliography

An “evaluative” annotated bibliography includes an appropriately cited reference along with a short paragraph (3-5 sentence summary of the author’s main idea along with the addition of the reader’s detailed judgements (either positive or negative) about the source material and its quality.

For this assignment you are asked to select a reference that pertains to the topic of your research. You are permitted to choose one of the references that you included on your reference page provided you add a short paragraph (3-5 sentences) that summarizes the author(s) main idea along with your detailed judgements (either positive or negative) about the source, the author’s approach, and the quality of the writing. Your paper should include a title page which is separate from the body of your paper.

 

Assignment Rubric

The main body of a research paper is the largest section, in it you collect and arrange evidence that will persuade the reader of your argument.  It should have logical organization, building your writing around the points you want to make versus letting your sources guide you.  Integrate your sources into your discussion. Summarize, analyze, explain, and evaluate published work. However, please add an appropriate title for your work and running head if you have not done so already.

As always, be sure to submit work written according to APA-7  guidelines, free from spelling and grammatical errors!

 

Category Unacceptable (Below Standards) Acceptable

(Meets Standards)

Good

(Occasionally Exceeds)

Excellent

(Exceeds Standards)

 

 

SCORE
Title Page

 

 

Includes <= 3 elements of a title page Includes <= 4 elements of a title page Includes most elements of the title page <=5 Includes all 6 elements of title page:  title of paper, author’s name, institutional affiliation, course name/#, instructor name, and due date 20 points
Body of Paper/Focus & Sequencing

 

 

Little evidence material is logically organized into topic, subtopics or related to topics. Many transitions are unclear or nonexistent. Most material clearly related to subtopic, main topic.  Material may not be organized within subtopics.  Attempts to provide variety of transitions. All material clearly related to subtopic, main topic and logically organized within subtopics.  Clear, varied transitions linking subtopics, and main topic. All material clearly related to subtopic, main topic.  Strong organization and integration of material within subtopics. Strong transitions linking subtopics, and main topic. 20 points
Support

 

Few sources supporting thesis.  Sources insignificant or unsubstantiated. Sources generally acceptable but not peer-reviewed research (evidence) based. Sources well selected to support thesis with some research in support of thesis. Provides 8, strong peer-reviewed research-based support for thesis. 10 points
Grammar & Mechanics

 

Grammatical errors or spelling & punctuation substantially detract from the paper. Very few grammatical, spelling, or punctuation errors interfere with reading the paper. Grammatical errors or spelling & punctuation are rare and do not detract from the paper. The paper is free of grammatical errors, spelling, and punctuation. 10 points
APA Style & Communication

 

 

Errors in APA style detract substantially from the paper.  Word choice is informal in tone.  Writing is choppy, with many awkward or unclear passages. Errors in APA style are noticeable.  Word choice occasionally informal in tone.  Writing has a few awkward or unclear passages. Rare errors in APA style that do not detract from the paper.  Scholarly style. Writing has minimal awkward unclear passages. No errors in APA style.  Scholarly style.  Writing is flowing and easy to follow.

 

-Double-spaced

-1” margins on all sides

-Running head

 

20 points
Citations & References

 

 

Reference and citation errors detract significantly from the paper. Two references or citations missing or incorrectly written. One reference or citations missing or incorrectly written. All references and citations are correctly written and present. 20 points
Total Points         100

 

Sample Answer

Psychiatric Evaluation in Obese Patients

PICOT Question: In patients ≥ 18 years with a B.M.I.≥ 29.9, does incorporating psychiatric evaluation tools such as PHQ-9 Depression-Screening Test, Hospital Anxiety and Depression Scale, and Beck’s Depression Inventory in their comprehensive care plan reduce the risk of depression compared with those that do not integrate psychiatric evaluation in their comprehensive care plan?

P: Patient Population – ≥ 18 years obese patients (B.M.I.≥ 29.9)

I: Intervention – incorporation of psychiatric evaluation tools such as PHQ-9 Depression-Screening Test, Hospital anxiety and depression scale (HADS), and Beck’s Depression Inventory in the comprehensive care plan of obese patients.

C: Comparison – Obese patients whose care plans do not include the use of depression assessment tools.

O: Outcome – Lower the risk of depression by about 50%

T: Time – Within a period of 4 to 6 months

Abstract

Obesity has been a notorious health concern in the U.S.A. due to its associated health concerns, linked mortality and morbidity rates. Of importance is the high risk of depression among obese patients due to excessive cellular inflammation and dysregulation of the pathways of the hypothalamus, pituitary, and adrenal glands leading to an increase in insulin, glucocorticoids, and leptin. These effects of obesity in the body result in mood disturbance and significant development of obesity in such patients (Milaneschi et al., 2019). This paper seeks to reveal the need for incorporating psychiatry evaluation tools such as Beck’s Depression Inventory (B.D.I.), PHQ-9 Depression-Screening Test, and HADS in the patients’ care plan (Schutt et al. 2016). A systematic review of published and peer-reviewed articles shows a side-by-side comparison of the level of depression in patients whose management incorporates evaluation tools and those whose management lacks thereof. It is noted that the incorporation of these evaluative tools lowers the risk of development of depression in obese patients and thus lowering mortality and morbidity.

Introduction

Obesity is a body mass index of more than 29.9, which results from excessive accumulation of fats in the body. These fats deposit in the adipose tissue due to high calory intake than the rate of their burning through exercise and activities of normal day-to-day life. Obesity is closely associated with depression, a low-mood psychiatry disorder (Barbuti et al., 2021). Blasco et al. (2020) identify that obesity, on the one hand, is a causative factor for depression and that the independent existence of depression in the body also causes obesity. In a study by Yosaee et al. (2018), depression causes obesity due to increased pituitary and adrenal hormones. These include a rise in cortisol levels and dysregulation of the body’s response to adrenocorticotropic hormone (Weinberger et al., 2018). Associated with this is the inflammatory state during obesity that releases C-reactive protein and inflammatory cytokines (Barbuti et al., 2021). The synergic actions of the described factors result in the interruption of the metabolic system, as described by (Schutt et al. 2016). This results in high insulin levels, resistance to inulin by body cells, and hyperplasia of the beta cells in the pancreas resulting in obesity.

In a similar study, McCombie et al. (2019) identify the high prevalence of depression in obese patients. According to this study, obese patients are likely to be depressed five times more than normal patients. This is attributable to high inflammation and deregulated hypothalamus-pituitary-adrenal axis (Blasco et al., 2020). As this may lead to serious mortality rates in obese patients, there is a need for timely identification and management of depression in these patients. This is only achieved through psychiatric evaluation tools (Schutt et al., 2016). An example of this tool is Beck’s depression inventory. These tools help the patients and clinicians assess the depression states and assume timely measures for managing identified symptoms.

Background and Significance

In a study, 55% of those who develop obesity were at risk of depression (Barbuti et al., 2021). Another study shows that an obese adult is five times at risk of having depression symptoms than an adult of normal weight (Inoue et al., 2018). In the U.S.A., one in every three adult men has obesity, while more than one woman in every four women is obese (“U.S. data and statistics,” 2020). Among these figures, 2 out of every five adults have obesity ranging from mild to severe obesity. In the period between 2017 to 2020, a statistic shows that the prevalence of obesity increased from 30% to 41.9% of the general population (“U.S. data and statistics,” 2020). This means that more than 99 million individuals are overweight. Out of this number, 70 million are adults, which means that more than 40 million are at risk of developing depression symptoms. Among these figures, an estimated 300,000 deaths are associated with obesity every year in the U.S.A. (“U.S. data and statistics,” 2020). Significantly, many obese patients are at a high risk of death due to depressive symptoms (Silva et al., 2020). Thus, a patient-centered approach that takes into recognition of depressive symptoms during the management of obese patients would help in avoiding preventable deaths and sustaining the well-being of obese patients (Schutt et al. 2016). This wholesome approach can be achieved through the timeliness assessment and recognition of depression symptoms in obese patients through the use of psychiatry evaluation tools (Inoue et al., 2018). The benefits of these tools can be exalted by a closer investigation of peer-reviewed articles on interventions in which obese patients were managed with their incorporation.

Methodology

The evidence presented in this paper was gathered through systematic identification of peer-reviewed articles from Google scholar, PubMed, Research gate, the National library of medicine, and Springer. I carefully identified useful literature published between 2012 and 2022 using various search words typed in the search engine. In google scholar, I typed the words “obesity and depression,” “causes of depression in obese patients,” “management of obese patients,” and “assessment of obese patients.” Through this search, I could identify eight articles that have provided vital information in answer to my PICOT question. In Research gate, I typed the words “Assessment of obesity” and “use of depression assessment tools.” This search helped in identifying two literature materials. Next, I searched for various assessment tools for the diagnosis of depression in the National Library of medicine. In Springer, I used the keywords “Obesity and depression” and “managing depression in obese patients.” A careful literature review of the identified material helped identify the usefulness of incorporating evaluative tools in the management of obese patients.

Review of Literature

In a study by Stidham (2017), depression and anxiety were screened in patients admitted to a bariatric weight loss clinic. This also aimed at equipping nurses with sufficient tools and skills that would be aidful in screening patients in the wards. This is targeted at offering better health care to obese patients who develop depressive and anxiety symptoms during their course of care. I focused on the assessment of depressive symptoms that were evaluated through the application of the patient help questionnaire – 9 (PHQ-9). This study applied the PHQ-9 scale on 300 patients who were reporting for weight management. Out of this, 175 patients had a score of over 5 on the PHQ-9 scale which means that they had symptoms of depression (Stidham, 2017). These results assisted the clinicians to manage and promptly respond to these patients to manage these symptoms of depression.

In a similar study in 2019, researchers sought to improve the quality of health delivery in an urgent care setting. Before the roll-out of this study, patients reporting at this urgent care facility were routinely assessed and managed for obesity without assessment of depression (Michelle et al., 2019). In the study period, 50% of obese patients reporting for care were assessed for depression using the PHQ-9 scale, and those who tested positive were referred for psychiatric exams and management. Out of the 73 patients between the age of 18 and 69 who were admitted for the study, 18 tested positive for depression and admitted to not having been on antidepressants before (Michelle et al., 2019). 6 had no history of depression while the rest had a history of depression and had been on antidepressants. The positive patients were linked to a psychiatrist for medical attention and management. Prior to the start of this study, the patients previously managed for obesity without the evaluation of obesity showed poor outcomes (Michelle et al., 2019). The intervention to evaluate depression during the care plan of the patients resulted in better health care and better health outcome for the patients reporting to the urgent care facility for weight management.

In a different study to assess depression in obese women through the examination of two commonly used psychiatry evaluation tools, the B.D.I. and HADS, 355 women were admitted into a randomized controlled trial. In this study, the researchers first sought to understand if there were reported cases of higher weight loss in obese patients with major depression and if a lifestyle intervention was introduced after behavioral activation for management of depression was elicited (Schneider et al., 2013). Secondly, they compared this with health education attention control interventions applied together with lifestyle changes. To arrive at their conclusions, researchers took three samples, starting with general measures for depression for the 355 individuals using B.D.I. and HADS. The second sample included those who had recovered from depression after treatment and this involved 115 participants (Schneider et al., 2013). The third samples were those who were subjected to behavioral intervention and had recovered from depression after treatment.

The 355 participants were then randomized into either of the weight intervention strategies after their baseline measures were evaluated using the B.D.I. and the H.D.S. The first group was then taken through a 10-week behavioral therapy followed by 16 weeks of group lifestyle intervention therapy. Throughout this period of weight management, their depression symptoms were monitored using the two evaluative scales. The second group was taken through 16 visits for health assessment over 6 months. At each visit, depression symptoms were determined that pointed toward an appropriate intervention for weight loss (Schneider et al., 2013). At the end of the study, the measurements on both the evaluation scales showed consistency in improvement over time. This meant that as more interventions were put in place to manage the depressive symptoms of each group, the health situation of each individual was improved. However, the B.D.I. scale showed more consistency and sensitivity than the HADS.

Discussion

In the investigated literature above, three evaluative scales are identified. First is the PHQ-9 scale, a multipurpose scale developed for screening and diagnosing depression in individuals. This scale has 9 points of personal reflection corresponding to a total of 27 scores for all the items on the scale. It can classify depression as either none-minimal, mild, moderate, severe, or severe (Patrick & Connick, 2019). No minimal depression corresponds to a score less than four on the scale. Scores of 5 to 9 correspond to mild depression, 10-14 to moderate depression, 15-19 to moderately severe depression, and 20-27 to severe depression. This scale has a wide array in the assessment of depression symptoms in obese patients (Patrick & Connick, 2019). Most clinicians prefer this scale because it can be useful in tracking symptoms by the patient, it exclusively focuses on the 9 diagnostic criteria for depression in the DSM-V, and it is more reliable and valid (Drew, Morgan & Young, 2022).

The second psychiatric evaluation tool is Beck’s depression inventory. This is a 21-item scale that is self-reporting the symptoms of depression (von Glischinski, von Brachel & Hirschfeld, 2019). This scale can score up to 63 points and is easily filled by patients within ten minutes. Scores 0f between 17-20 are considered borderline for clinical depression, while those above 40 are considered severe depression (Alabi et al., 2018). The third scale is the HADS which focuses on the nonphysical symptoms to diagnose anxiety and depression in the health care setting. It has 14 questions, 7 for anxiety and 7 for depression (Wu et al., 2021). Each of these items has a score which ranges from zero to three relating to low level of or highest level of depression and anxiety respectively. The maximum score on this scale for anxiety or depression symptoms is 21, while a score of 8 for either of the symptoms is considered minimal (Wu et al., 2021). As anxiety and depression have been shown to coexist where anxiety can be described as a minimal response to stressors than depression, this scale can be easily used to diagnose depression where other scales cannot be used.

In the three intervention plans above, the measurement scales are described to be used in the evaluation of depression symptoms during the management of obesity. These two disorders are highly comorbid with obese patients being at high risk of developing depression. These scales show excellent results on the number of patients found to be depressed in each study. Of importance is the positive outcome in each study where the patients were keenly monitored for depressive symptoms. Clinicians easily intervened in the first study to manage depression symptoms and thus improve the health outcomes of the patients (Borgland, 2021). Out of the 300 patients admitted for the study, 175 had depression which could have been easily overlooked had there been no screening tool (Stidham, 2017). This was a similar case in the second study where quality improvement in health outcomes at the urgent care unit was increased through the incorporation of these scales. 18 adults who were recognized to have depression symptoms were connected to psychiatrists for timely management of their symptoms.

These scales have been noted to provide accurate, reliable, and timely information on depression in obese patients. As depression can also worsen depression, prompt treatment of these symptoms leads to better health outcomes for the patients (Yosaee et al., 2018). Similarly, the HADS and B.D.I. were useful in determining necessary interventions for improved weight loss in the third article. In the second study, there were poor health outcomes for patients who were managed for obesity without the assessment of depression. This is attributable to the bidirectional relationship of these comorbid symptoms (Borgland, 2021). Obesity causes inflammation in the body cells which leads to a rise in C-reactive protein in the body. Additionally, it dysregulates the hormonal axis of the hypothalamus, pituitary, and adrenal glands which interferes with the mood in the body (Weinberger et al., 2018). Thus, these pieces of evidence are sufficient to conclude that the incorporation of psychiatry evaluation scales in the care plan can lower the risk of depression in obese patients.

Conclusion

In conclusion, it has been identified that obesity is a major risk factor for the development of depression due to the dysregulation of the hypothalamus-pituitary-adrenal axis and inflammation that dysregulates mood. Failure to identify these symptoms has been associated with lower positive health outcomes in obese patients due to the bidirectional relationship between these two comorbid conditions. For clinicians, identification of these symptoms can be made easy through the incorporation of psychiatry evaluation scales in the care plans of these obese patients. This was shown to improve patient outcomes in an urgent care center in a study in 2019. Some of these psychiatry evaluation tools include Beck’s depression inventory, hospital anxiety and depression scale, and patient health questionnaire-9.

 

 

References

Alabi, F., Guilbert, L., Villalobos, G., Mendoza, K., Hinojosa, R., Melgarejo, J. C., … & Zerrweck, C. (2018). Depression before and after bariatric surgery in low-income patients: The utility of the beck depression inventory. Obesity surgery28(11), 3492-3498. https://doi.org/10.1007/s11695-018-3371-0

Barbuti, M., Carignani, G., Weiss, F., Calderone, A., Santini, F., & Perugi, G. (2021). Mood disorders comorbidity in obese bariatric patients: the role of the emotional dysregulation. Journal of Affective Disorders, 279, 46-52. https://doi.org/10.1016/j.jad.2020.09.128

Blasco, B. V., García-Jiménez, J., Bodoano, I., & Gutiérrez-Rojas, L. (2020). Obesity and depression: Its prevalence and influence as a prognostic factor: A systematic review. Psychiatry investigation17(8), 715. https://doi.org/10.30773/pi.2020.0099

Borgland, S. L. (2021). Can treatment of obesity reduce depression or vice versa? Journal of Psychiatry & Neuroscience: J.P.N., 46(2), E313. https://doi.org/10.1503/jpn.210036

Drew, R. J., Morgan, P. J., & Young, M. D. (2022). Mechanisms of an eHealth program targeting depression in men with overweight or obesity: A randomized trial. Journal of affective disorders299, 309-317. https://doi.org/10.1016/j.jad.2021.12.001

Inoue, Y., Qin, B., Poti, J., Sokol, R., & Gordon-Larsen, P. (2018). Epidemiology of obesity in adults: latest trends. Current obesity reports7(4), 276-288. https://doi.org/10.1007/s13679-018-0317-8

Janssen, F., Bardoutsos, A., & Vidra, N. (2020). Obesity prevalence in the long-term future in 18 European countries and in the U.S.A. Obesity facts13(5), 514-527. https://doi.org/10.1159/000511023

McCombie, L., Brosnahan, N., Ross, H., Bell‐Higgs, A., Govan, L., & Lean, M. E. J. (2019). Filling the intervention gap: service evaluation of an intensive nonsurgical weight management program for severe and complex obesity. Journal of Human Nutrition and Dietetics32(3), 329-337.

Michelle, J, Shannon. H., John, G., & Rebecca, G. (2019). Depression screening in obesity: A quality improvement project. Clinical Advisor.

Milaneschi, Y., Simmons, W. K., van Rossum, E. F., & Penninx, B. W. (2019). Depression and obesity: evidence of shared biological mechanisms. Molecular psychiatry24(1), 18-33. https://doi.org/10.1038/s41380-018-0017-5

Patrick, S., & Connick, P. (2019). Psychometric properties of the PHQ-9 depression scale in people with multiple sclerosis: a systematic review. PloS one14(2), e0197943. https://doi.org/10.1371/journal.pone.0197943

Schneider, K. L., Busch, A. M., Whited, M. C., Appelhans, B. M., Waring, M. E., & Pagoto, S. L. (2013). Assessing depression in obese women: An examination of two commonly-used measures. Journal of psychosomatic research75(5), 425-430. https://doi.org/10.1016/j.jpsychores.2013.08.015

Schutt, P. E., Kung, S., Clark, M. M., Koball, A. M., & Grothe, K. B. (2016). Comparing the Beck Depression Inventory-II (BDI-II) and Patient Health Questionnaire (PHQ-9) depression measures in an outpatient bariatric clinic. Obesity surgery26(6), 1274-1278. https://doi.org/10.1007/s11695-015-1877-2

Silva, D. A., Coutinho, E. D. S. F., Ferriani, L. O., & Viana, M. C. (2020). Depression subtypes and obesity in adults: a systematic review and meta‐analysis. Obesity Reviews21(3), e12966. https://doi.org/10.1111/obr.12966

Stidham, C. T. (2017). Screening to Identify Depression and Anxiety in Obese Patients. Surgery for Obesity and Related Diseases, 13(10), S152. https://doi.org/10.1016/j.soard.2017.09.334

U.S. data and statistics (2020, December 7). Official Guide to Government Information and Services | USAGov. https://www.usa.gov/statistics

von Glischinski, M., von Brachel, R., & Hirschfeld, G. (2019). How depressed is “depressed”? A systematic review and diagnostic meta-analysis of optimal cut points for the Beck Depression Inventory revised (BDI-II). Quality of Life Research28(5), 1111-1118. https://doi.org/10.1007/s11136-018-2050-x

Weinberger, N. A., Kersting, A., Riedel-Heller, S., & Luck-Sikorski, C. (2018). The Relationship between Weight Status and Depressive Symptoms in a Population Sample with Obesity: The Mediating Role of Appearance Evaluation. Obesity Facts, 11(6), 514–523. https://doi.org/10.1159/000492000

Wu, Y., Levis, B., Sun, Y., He, C., Krishnan, A., Neupane, D., … & Thombs, B. D. (2021). Accuracy of the Hospital Anxiety and Depression Scale Depression subscale (HADS-D) to screen for major depression: systematic review and individual participant data meta-analysis. bmj373. https://doi.org/10.1136/bmj.n972

Yosaee, S., Djafarian, K., Esteghamati, A., Motevalian, A., Shidfar, F., Tehrani-Doost, M., & Jazayeri, S. (2018). Depressive symptoms among metabolically healthy and unhealthy overweight/obese individuals: a comparative study. Medical journal of the Islamic Republic of Iran32, 95. https://doi.org/10.14196/mjiri.32.95

 

 

Annotated Bibliography

Schneider, K. L., Busch, A. M., Whited, M. C., Appelhans, B. M., Waring, M. E., & Pagoto, S. L. (2013). Assessing depression in obese women: An examination of two commonly-used measures. Journal of psychosomatic research75(5), 425-430. https://doi.org/10.1016/j.jpsychores.2013.08.015

Schneider et al., (2013) conducted a study to determine the effectiveness of the use of B.D.I. and HADS in the measurement and evaluation of obesity during weight management in obese patients. In this study, 355 obese individuals were admitted and taken through a randomized control trial. At the start, baseline depression signs and B.M.I. values were measured. The group was then randomly divided into two, the first for behavioral depression therapy followed by group lifestyle change intervention while the second was randomized for group lifestyle intervention followed by health education attention control. At each visit, depression symptoms were measured which guided the mode of action for intervention toward weight loss. In the end, both scales showed a consistent reduction in obesity as depression symptoms were managed. Also, the researchers identified that the B.D.I. scale was more consistent and sensitive to obesity changes than the HADS. I believe the results and conclusions of the authors as per their research question were appropriate and helpful in determining the usefulness of the psychiatry evaluation tool in managing depression in obese patients.

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