Prepare for Final Paper Topic: Ethical Conduct of Research (Outcomes 1,6): 20 hours • Select a healthcare related research study. Identify the sample population. Analyze and critique the study to identify if sampling method reflects ethical principles in

Prepare for Final Paper Topic: Ethical Conduct of Research (Outcomes 1,6): 20 hours • Select a healthcare related research study. Identify the sample population. Analyze and critique the study to identify if sampling method reflects ethical principles in

American Journal of Epidemiology © The Author 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. Vol. 185, No. 9 DOI: 10.1093/aje/kwx030 Advance Access publication: March 22, 2017 Original Contribution Depressive Disorder Subtypes as Predictors of Incident Obesity in US Adults: Moderation by Race/Ethnicity * Correspondence to Dr. Jesse C. Stewart, Department of Psychology, Indiana University-Purdue University Indianapolis, 402 North Blackford Street, LD 100E, Indianapolis, IN 46202 (e-mail: jstew@iupui.edu). Initially submitted April 15, 2016; accepted for publication July 12, 2016. We compared the relative importance of atypical major depressive disorder (MDD), nonatypical MDD, and dysthymic disorder in predicting 3-year obesity incidence and change in body mass index and determined whether race/ethnicity moderated these relationships. We examined data from 17,787 initially nonobese adults in the National Epidemiologic Survey on Alcohol and Related Conditions waves 1 (2001–2002) and 2 (2004–2005) who were representative of the US population. Lifetime subtypes of depressive disorders were determined using a structured interview, and obesity outcomes were computed from self-reported height and weight. Atypical MDD (odds ratio (OR) = 1.68, 95% confidence interval (CI): 1.43, 1.97; P < 0.001) and dysthymic disorder (OR = 1.66, 95% CI: 1.29, 2.12; P < 0.001) were stronger predictors of incident obesity than were nonatypical MDD (OR = 1.11, 95% CI: 1.01, 1.22; P = 0.027) and no history of depressive disorder

Don't use plagiarized sources. Get Your Custom Essay on
Prepare for Final Paper Topic: Ethical Conduct of Research (Outcomes 1,6): 20 hours • Select a healthcare related research study. Identify the sample population. Analyze and critique the study to identify if sampling method reflects ethical principles in
Just from $13/Page
Order Essay

ORDER A PLAGIARISM FREE PAPER NOW

. Atypical MDD (B = 0.41 (standard error, 0.15); P = 0.007) was a stronger predictor of increases in body mass index than were dysthymic disorder (B = −0.31 (standard error, 0.21); P = 0.142), nonatypical MDD (B = 0.007 (standard error, 0.06); P = 0.911), and no history of depressive disorder. Race/ethnicity was a moderator; atypical MDD was a stronger predictor of incident obesity in Hispanics/Latinos (OR = 1.97, 95% CI: 1.73, 2.24; P < 0.001) than in non-Hispanic whites (OR = 1.54, 95% CI: 1.25, 1.91; P < 0.001) and blacks (OR = 1.72, 95% CI: 1.31, 2.26; P < 0.001). US adults with atypical MDD are at particularly high risk of weight gain and obesity, and Hispanics/Latinos may be especially vulnerable to the obesogenic consequences of depressions. body mass index; depressive disorders; ethnicity; obesity; prospective study; race Abbreviations: BMI, body mass index; MDD, major depressive disorder; NESARC, National Epidemiologic Survey on Alcohol and Related Conditions. In contrast to the episodic nature of MDD, dysthymic disorder is a chronic condition characterized by low-grade depressive symptoms that last at least 2 years (2). Emerging evidence has suggested that obesity risk may vary across subtypes of depressive disorders, with atypical MDD likely conferring the greatest risk. First, the hyperphagia that accompanies atypical MDD could lead to increased energy intake, and the hypersomnia could result in decreased energy expenditure. Second, atypical MDD has been linked with other obesity-promoting biological and behavioral changes. At the biological level, atypical MDD has been associated with increased systemic inflammation and metabolic dysregulation (5–9). At the behavioral level, atypical MDD Substantial research has suggested that depression is a risk factor for obesity (1); however, little is known about whether the strength of this relationship differs across depressive disorder subtypes. In the present study, we examined the subtypes of atypical major depressive disorder (MDD), nonatypical MDD, and dysthymic disorder. MDD is characterized by a discrete episode of moderate to severe depressive symptoms that lasts at least 2 weeks (2). Key features of atypical MDD are reversed somatic-vegetative symptoms of hyperphagia (increased appetite/weight gain) and hypersomnia (excessive sleep), whereas nonatypical MDD is a heterogeneous group that includes MDD with other features, such as feeling anxious or melancholic (2–4). 734 Am J Epidemiol. 2017;185(9):734–742 Downloaded from https://academic.oup.com/aje/article-abstract/185/9/734/3076989 by guest on 29 January 2019 Brittanny M. Polanka, Elizabeth A. Vrany, Jay Patel, and Jesse C. Stewart* Depression Subtypes as Predictors of Obesity 735 METHODS Study design and sample NESARC is a prospective cohort study designed by the National Institute on Alcohol Abuse and Alcoholism to determine the prevalence of alcohol use disorders and associated disabilities in the US civilian noninstitutionalized population who are 18 years of age or older. NESARC sampling and interview methods have been described previously (15–17). At wave 1 (2001–2002), 43,093 respondents (81.0% response rate) underwent home interviews in which substance use and psychiatric disorders, medical conditions, and other factors were assessed. At wave 2 (2004–2005), which was approximately 3 years later (mean = 36.6 months), 34,653 (86.7% response rate) of the eligible wave-1 respondents underwent a second home interview. The NESARC protocol received ethical approval from the US Census Bureau and the US Office of Management and Budget. From the wave-2 cohort, we excluded 9,432 respondents with a wave-1 BMI of 30 or higher. We then excluded 589 respondents with BMIs that were potentially indicative of anorexia ( 0.34 for all). Because there was no evidence of moderation by race/ethnicity, we did not run stratified models. DISCUSSION In a large sample representative of the US population, we found that lifetime atypical MDD and lifetime dysthymic disorder were stronger predictors of 3-year incidence of obesity than were lifetime nonatypical MDD and no depressive disorder history. Atypical MDD was also a stronger predictor of 3-year increases in BMI than were dysthymic disorder, nonatypical MDD, and no depressive disorder history. To illustrate, adults with atypical MDD had a 68% greater odds of incident obesity and exhibited a 0.41 greater increase in BMI than did those without a depression history. In addition, adults with atypical MDD had 51% greater odds of incident obesity and displayed a 0.40 greater increase in BMI than did those with nonatypical MDD. We detected evidence of moderation by race/ethnicity for incident obesity but not for BMI change. Although atypical MDD predicted incident obesity in all 3 racial/ethnic groups, it was a stronger predictor in Hispanics/Latinos than in non-Hispanic whites and non-Hispanic Table 3. Linear Regression Models Examining Depressive Disorder Subtypes in Wave 1 (2001–2002) as Predictors of 3-Year Change in Body Mass Index in Wave 2 (2004–2005) (n = 17,787), National Epidemiologic Survey on Alcohol and Related Conditions Disorder No depressive disorder Dysthymic disorder only Nonatypical MDD Atypical MDD Demographic Characteristics– Adjusted Modela Total Cases B Fully Adjusted Modelb No. % 14,570 81.9 143 0.8 −0.32 0.21 2,546 14.3 −0.003 0.06 0.007 0.06 528 3.0 0.40c 0.15 0.41c 0.15 0 SE Referent B 0 −0.31 SE Referent 0.21 Abbreviations: B, unstandardized regression coefficient; MDD, major depressive disorder; SE, standard error. Adjusted for age, sex, race/ethnicity, education level, wave-1 body mass index, and study sampling design. b Adjusted for age, sex, race/ethnicity, education level, wave-1 body mass index, lifetime alcohol use disorders, lifetime tobacco use, lifetime antidepressant use, cardiovascular disease, liver disease, arthritis, and study sampling design. c P < 0.01. a Am J Epidemiol. 2017;185(9):734–742 Downloaded from https://academic.oup.com/aje/article-abstract/185/9/734/3076989 by guest on 29 January 2019 groups revealed that both dysthymic disorder only (odds ratio = 1.49, 95% confidence interval: 1.15, 1.94; P = 0.003) and atypical MDD (odds ratio = 1.51, 95% confidence interval: 1.26, 1.81; P < 0.001) were stronger predictors of incident obesity than was nonatypical MDD. These models also showed that dysthymic disorder only and atypical MDD did not differ in the odds of incident obesity (odds ratio = 0.99, 95% confidence interval: 0.76, 1.28; P = 0.930). The linear regression models (Table 3) yielded some complementary results, as atypical MDD predicted increases in BMI in the demographic characteristic–adjusted (P = 0.010) and fully adjusted (P = 0.007) models. After adjustment for all covariates, the average BMI of respondents with atypical MDD increased 0.41 more over the 3-year period than did that that of respondents with no depressive disorder. In contrast to incident obesity, dysthymic disorder only (P = 0.134 and P = 0.142) and nonatypical MDD (P = 0.961 and P = 0.911) did not predict BMI change in the demographic characteristic–adjusted or fully adjusted models. Models in which we used different reference groups indicated that atypical MDD was a stronger predictor of BMI change than were dysthymic disorder only (B = 0.73 (standard error, 0.25); P = 0.004) and nonatypical MDD (B = 0.40 (standard error, 0.15); P = 0.009). These models also showed that there was no difference in BMI change between dysthymic disorder only and nonatypical MDD groups (B = −0.32, (standard error, 0.21); P = 0.130). 740 Polanka et al. Race and Depressive Disorder Subtype OR (95% CI) Non-Hispanic White Nonatypical MDD 1.09 (0.95, 1.24) Atypical MDD 1.54 (1.25, 1.91) Non-Hispanic Black 1.01 (0.87, 1.17) Atypical MDD 1.72 (1.31, 2.26) Hispanic/Latino Nonatypical MDD 1.36 (1.21, 1.53) Atypical MDD 1.97 (1.73, 2.24) 0.80 1.00 1.20 1.40 Odds Ratio 1.60 1.80 2.00 2.20 2.40 Figure 1. Logistic regression models examining major depressive disorder (MDD) subtypes in wave 1 (2001–2002) as predictors of 3-year incidence of obesity in wave 2 (2004–2005), stratified by racial/ethnic group (n = 16,724), National Epidemiologic Survey on Alcohol and Related Conditions. The reduced sample size was due to the removal of persons in the “other” race/ethnicity category and in the dysthymic disorder only category. Models were adjusted for age, sex, educational level, wave-1 body mass index, lifetime alcohol use disorders, lifetime tobacco use, lifetime antidepressant use, cardiovascular disease, liver disease, arthritis, and study sampling design. CI, confidence interval; OR, odds ratio. blacks (97% greater odds versus 54% and 72%, respectively). Nonatypical MDD predicted incident obesity only in Hispanics/Latinos. Our findings indicate that 1) those with atypical MDD are a subgroup of depressed adults with a particularly elevated risk of gaining weight and developing obesity and 2) Hispanics/Latinos may be especially vulnerable to the obesogenic consequences of depression. Our results agree with 1 of 2 existing prospective studies in which researchers compared the predictive utilities of depressive disorder subtypes. In a Swiss sample, Lasserre et al. (11) found that current atypical MDD, but not other MDD subtypes, predicted incident obesity and increases in BMI, waist circumference, and fat mass over 5.5 years. In the present study, we extended their findings to the US population. Our results, however, do not agree with those of Lamers et al. (12), who found that BMI trajectories over the 6-year follow-up period did not differ between adults with atypical MDD and nondepressed controls. In addition, results from the analysis by Pickering et al. (36) of the NESARC data conflict with ours, because they found that MDD did not predict changes in BMI class over time. However, Pickering et al. did not examine MDD subtypes, which likely obscured relationships. Although a link between atypical MDD and obesity-related variables has been detected in a few cross-sectional studies (29, 37, 38), the potential for reverse causality (1) limits their usefulness. Atypical MDD may be a stronger predictor of obesity outcomes for several reasons. First, it is plausible that the symptoms of hyperphagia and hypersomnia lead to increased energy intake and decreased energy expenditure, respectively. Second, patients with atypical MDD have poorer diet quality than do those with melancholic MDD (10), which could result in higher energy intake. Third, adults with atypical MDD report higher rates of disability days and restricted activity days than do those with nonatypical MDD (4), which could lead to lower energy expenditure. Fourth, atypical MDD is characterized by earlier age of onset, more severe symptoms, and a greater number of episodes (4, 30, 39). Thus, people with atypical MDD have greater exposure to depression and its obesogenic consequences. Fifth, compared with persons with nonatypical depression, those with atypical depression are also more likely to be taking an antidepressant (4), some of which have been linked to weight gain (40). Sixth, increased systemic inflammation and metabolic dysregulation have been observed in atypical MDD (5–9); however, it is unclear whether these changes are causes or consequences of weight gain. Finally, shared genetic factors could contribute to both future atypical MDD and obesity. As an example, a fat mass and obesity-associated protein (FTO) gene variant was found to be related to greater odds of having atypical MDD (41). To our knowledge, we are the first to report that the strength of associations between depressive disorder subtypes and obesity outcomes depends on race/ethnicity, with the strongest relationship found in Hispanics/Latinos. These findings conflict with those from prior prospective studies, in which depression was found to be a more consistent or stronger predictor of obesity outcomes in non-Hispanic whites (42, 43). A key methodological difference is that our Am J Epidemiol. 2017;185(9):734–742 Downloaded from https://academic.oup.com/aje/article-abstract/185/9/734/3076989 by guest on 29 January 2019 Nonatypical MDD Depression Subtypes as Predictors of Obesity 741 ACKNOWLEDGMENTS Author affiliation: Department of Psychology, Indiana University-Purdue University Indianapolis, Indianapolis, Indiana (Brittanny M. Polanka, Elizabeth A. Vrany, Jay Patel, Jesse C. Stewart). The National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) is funded by the National Institute on Alcohol Abuse and Alcoholism, with supplemental support from the National Institute on Drug Abuse. J.C.S. was supported in part by the National Heart, Am J Epidemiol. 2017;185(9):734–742 Lung, and Blood Institute of the National Institutes of Health under award number R01HL122245. The sponsors designed and conducted NESARC and collected and managed the study data. The sponsors had no involvement in the analysis, interpretation of results, or preparation, review, or approval of this manuscript. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Conflict of interest: none declared. REFERENCES 1. Luppino FS, de Wit LM, Bouvy PF, et al. Overweight, obesity, and depression: a systematic review and meta-analysis of longitudinal studies. Arch Gen Psychiatry. 2010;67(3):220–229. 2. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, 5th Edition. Arlington, VA: American Psychiatric Association; 2013. 3. Quitkin FM. Depression with atypical features: diagnostic validity, prevalence, and treatment. Prim Care Companion J Clin Psychiatry. 2002;4(3):94–99. 4. Matza LS, Revicki DA, Davidson JR, et al. Depression with atypical features in the national comorbidity survey: classification, description, and consequences. Arch Gen Psychiatry. 2003;60(8):817–826. 5. Penninx BW, Milaneschi Y, Lamers F, et al. Understanding the somatic consequences of depression: biological mechanisms and the role of depression symptom profile. BMC Med. 2013;11:129. 6. Hickman RJ, Khambaty T, Stewart JC. C-reactive protein is elevated in atypical but not nonatypical depression: data from the National Health and Nutrition Examination Survey (NHANES) 1999-2004. J Behav Med. 2014;37(4):621–629. 7. Lamers F, Vogelzangs N, Merikangas KR, et al. Evidence for a differential role of HPA-axis function, inflammation and metabolic syndrome in melancholic versus atypical depression. Mol Psychiatry. 2013;18(6):692–699. 8. Rudolf S, Greggersen W, Kahl KG, et al. Elevated IL-6 levels in patients with atypical depression but not in patients with typical depression. Psychiatry Res. 2014;217(1-2):34–38. 9. Takeuchi T, Nakao M, Kachi Y, et al. Association of metabolic syndrome with atypical features of depression in Japanese people. Psychiatry Clin Neurosci. 2013;67(7): 532–539. 10. Rahe C, Baune BT, Unrath M, et al. Associations between depression subtypes, depression severity and diet quality: cross-sectional findings from the BiDirect Study. BMC Psychiatry. 2015;15:38. 11. Lasserre AM, Glaus J, Vandeleur CL, et al. Depression with atypical features and increase in obesity, body mass index, waist circumference, and fat mass: a prospective, population-based study. JAMA Psychiatry. 2014;71(8): 880–888. 12. Lamers F, Beekman AT, van Hemert AM, et al. Six-year longitudinal course and outcomes of subtypes of depression. Br J Psychiatry. 2016;208(1):62–68. 13. Case SM, Stewart JC. Race/ethnicity moderates the relationship between depressive symptom severity and C-reactive protein: 2005-2010 NHANES data. Brain Behav Immun. 2014;41:101–108. Downloaded from https://academic.oup.com/aje/article-abstract/185/9/734/3076989 by guest on 29 January 2019 study utilized a US population–based sample, whereas past studies utilized samples of adolescents (42) and older adults (43), possibly limiting generalizability. Although the mechanisms underlying the stronger relationship in Hispanics/Latinos are unknown, evidence has suggested that depressed Hispanics/Latinos are less likely to engage in physical activity than are depressed non-Hispanic whites (44), which could promote obesity. Despite limited knowledge about underlying mechanisms, our race/ ethnicity findings are of high potential significance, because the stronger obesogenic consequences of depressive disorders in Hispanics/Latinos could in part explain the health disparity in obesity rates between Mexican Americans (40%) and other Hispanics (39%) compared with non-Hispanic whites (34%) (45). Our study has limitations. First, BMI was calculated from self-reported height and weight. Although correlations between measured and self-reported BMI are high, relying on selfreports could result in an overestimation of height and underestimation of weight (31), leading to missed cases of incident obesity. Such misclassification, however, would reduce power and bias results toward the null hypothesis. Second, although we adjusted for lifetime antidepressant use, we could not examine specific medications. Some antidepressants (e.g., selective serotonin reuptake inhibitors) (46, 47) are more likely to promote weight gain. Third, we attempted to exclude respondents with a BMI that was potentially indicative of anorexia (
Purchase answer to see full attachment