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Metabolic syndrome and metabolic abnormalities in patients with major depressive disorder: a meta-analysis of prevalences and moderating variables

Published online by Cambridge University Press:  21 November 2013

D. Vancampfort*
Affiliation:
University Psychiatric Centre KU Leuven, Kortenberg, Belgium Department of Rehabilitation Sciences, KU Leuven, Belgium
C. U. Correll
Affiliation:
The Zucker Hillside Hospital, Glen Oaks, NY, USA Albert Einstein College of Medicine, Bronx, NY, USA
M. Wampers
Affiliation:
University Psychiatric Centre KU Leuven, Kortenberg, Belgium
P. Sienaert
Affiliation:
University Psychiatric Centre KU Leuven, Kortenberg, Belgium
A. J. Mitchell
Affiliation:
Department of Psycho-oncology, Leicestershire Partnership Trust, Leicester, UK Department of Cancer and Molecular Medicine, University of Leicester, UK
A. De Herdt
Affiliation:
Department of Rehabilitation Sciences, KU Leuven, Belgium
M. Probst
Affiliation:
University Psychiatric Centre KU Leuven, Kortenberg, Belgium Department of Rehabilitation Sciences, KU Leuven, Belgium
T. W. Scheewe
Affiliation:
Windesheim University of Applied Sciences, Zwolle, The Netherlands
M. De Hert
Affiliation:
University Psychiatric Centre KU Leuven, Kortenberg, Belgium
*
*Address for correspondence: Dr D. Vancampfort, University Psychiatric Centre KU Leuven, Campus Kortenberg, Leuvensesteenweg 517, 3070 Kortenberg, Belgium. (Email: [email protected])

Abstract

Background

Individuals with depression have an elevated risk of cardiovascular disease (CVD) and metabolic syndrome (MetS) is an important risk factor for CVD. We aimed to clarify the prevalence and correlates of MetS in persons with robustly defined major depressive disorder (MDD).

Method

We searched Medline, PsycINFO, EMBASE and CINAHL up until June 2013 for studies reporting MetS prevalences in individuals with MDD. Medical subject headings ‘metabolic’ OR ‘diabetes’ or ‘cardiovascular’ or ‘blood pressure’ or ‘glucose’ or ‘lipid’ AND ‘depression’ OR ‘depressive’ were used in the title, abstract or index term fields. Manual searches were conducted using reference lists from identified articles.

Results

The initial electronic database search resulted in 91 valid hits. From candidate publications following exclusions, our search generated 18 studies with interview-defined depression (n = 5531, 38.9% male, mean age = 45.5 years). The overall proportion with MetS was 30.5% [95% confidence interval (CI) 26.3–35.1] using any standardized MetS criteria. Compared with age- and gender-matched control groups, individuals with MDD had a higher MetS prevalence [odds ratio (OR) 1.54, 95% CI 1.21–1.97, p = 0.001]. They also had a higher risk for hyperglycemia (OR 1.33, 95% CI 1.03–1.73, p = 0.03) and hypertriglyceridemia (OR 1.17, 95% CI 1.04–1.30, p = 0.008). Antipsychotic use (p < 0.05) significantly explained higher MetS prevalence estimates in MDD. Differences in MetS prevalences were not moderated by age, gender, geographical area, smoking, antidepressant use, presence of psychiatric co-morbidity, and median year of data collection.

Conclusions

The present findings strongly indicate that persons with MDD are a high-risk group for MetS and related cardiovascular morbidity and mortality. MetS risk may be highest in those prescribed antipsychotics.

Type
Review Article
Copyright
Copyright © Cambridge University Press 2013 

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References

Alberti, KG, Eckel, RH, Grundy, SM, Zimmet, PZ, Cleeman, JI, Donato, KA, Fruchart, JC, James, WP, Loria, CM, Smith, SC Jr. (2009). A joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation 120, 16401645.CrossRefGoogle Scholar
Alberti, KG, Zimmet, P, Shaw, P (2006). The metabolic syndrome – a new world-wide definition. A consensus statement from the International Diabetes Federation. Diabetes Medicine 23, 469480.CrossRefGoogle ScholarPubMed
APA (2000). Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision. DSM-IV-TR. American Psychiatric Association: Washington, DC.Google Scholar
Atlantis, E, Shi, Z, Penninx, BJ, Wittert, GA, Taylor, A, Almeida, OP (2012). Chronic medical conditions mediate the association between depression and cardiovascular disease mortality. Social Psychiatry and Psychiatric Epidemiology 47, 615625.Google Scholar
Barth, J, Schumacher, M, Herrmann-Lingen, C (2004). Depression as a risk factor for mortality in patients with coronary heart disease: a meta-analysis. Psychosomatic Medicine 66, 802813.Google Scholar
Bayturan, O, Tuzcu, EM, Lavoie, A, Hu, T, Wolski, K, Schoenhagen, P, Kapadia, S, Nissen, SE, Nicholls, SJ (2010). The metabolic syndrome, its component risk factors, and progression of coronary atherosclerosis. Archives of Internal Medicine 170, 478484.CrossRefGoogle ScholarPubMed
Begg, CB, Mazumdar, M (1994). Operating characteristics of a rank correlation test for publication bias. Biometrics 50, 10881101.CrossRefGoogle Scholar
Brown, AD, Barton, DA, Lambert, GW (2009). Cardiovascular abnormalities in patients with major depressive disorder: autonomic mechanisms and implications for treatment. CNS Drugs 23, 583602.Google Scholar
Correll, CU, Lencz, T, Malhotra, AK (2011). Antipsychotic drugs and obesity. Trends in Molecular Medicine 17, 97107.Google Scholar
Davidson, JR (2010). Major depressive disorder treatment guidelines in America and Europe. Journal of Clinical Psychiatry 71 (Suppl. E1), e04.Google ScholarPubMed
De Hert, M, Cohen, D, Bobes, J, Cetkovich-Bakmas, M, Leucht, S, Ndetei, DM, Möller, HJ, Gautam, S, Detraux, J, Correll, CU (2011 a). Physical illness in patients with severe mental disorders. II. Barriers to care, monitoring and treatment guidelines, and recommendations at the system and individual levels. World Psychiatry 10, 138151.Google Scholar
De Hert, M, Correll, CU, Bobes, J, Cetkovich-Bakmas, M, Cohen, D, Asai, I, Detraux, J, Gautam, S, Möller, HJ, Ndetei, DM, Newcomer, JW, Uwakwe, R, Leucht, S (2011 b). Physical illness in patients with severe mental disorders. I. Prevalence, impact of medications and disparities in health care. World Psychiatry 10, 5277.Google Scholar
De Hert, M, Dekker, J, Wood, D, Kahl, K, Holt, R, Möller, H (2009). Cardiovascular disease and diabetes is people with severe mental illness position statement from the European Psychiatric Association (EPA), supported by the European Association for the Study of Diabetes (EASD) and the European Society of Cardiology (ESC). European Psychiatry 24, 412424.Google Scholar
De Hert, M, Detraux, J, van Winkel, R, Yu, W, Correll, CU (2011 c). Metabolic and cardiovascular adverse effects associated with antipsychotic drugs. Nature Reviews. Endocrinology 8, 114126.Google Scholar
De Hert, M, Vancampfort, D, Correll, C, Mercken, V, Peuskens, J, Sweers, K, van Winkel, R, Mitchell, AJ (2011 d). Guidelines for screening and monitoring of cardiometabolic risk in schizophrenia: systematic evaluation. British Journal of Psychiatry 199, 99105.Google Scholar
Duvall, S, Tweedie, R (2000). A non-parametric ‘trim and fill’ method for assessing publication bias in meta-analysis. Journal of the American Statistical Association 95, 8998.Google Scholar
Egger, M, Davey, SG, Schneider, M, Minder, C (1997). Bias in meta-analysis detected by a simple, graphical test. British Medical Journal 315, 629634.Google Scholar
Expert Panel (2001). Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. Executive Summary of The Third Report of The National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol In Adults (Adult Treatment Panel III). Journal of the American Medical Association 285, 24862497.CrossRefGoogle Scholar
Farahani, A, Correll, CU (2012). Are antipsychotics or antidepressants needed for psychotic depression? A systematic review and meta-analysis of trials comparing antidepressant or antipsychotic monotherapy with combination treatment. Journal of Clinical Psychiatry 73, 486496.Google Scholar
Ford, ES, Giles, WH, Dietz, WH (2002). Prevalence of the metabolic syndrome among US adults: findings from the third National Health and Nutrition Examination Survey. Journal of the American Medical Association 287, 356359.Google Scholar
Galassi, A, Reynolds, K, He, J (2006). Metabolic syndrome and risk of cardiovascular disease: a meta-analysis. American Journal of Medicine 119, 812819.Google Scholar
Gami, AS, Witt, BJ, Howard, DE, Erwin, PJ, Gami, LA, Somers, VK, Montori, VM (2007). Metabolic syndrome and risk of incident cardiovascular events and death: a systematic review and meta-analysis of longitudinal studies. Journal of the American College of Cardiology 49, 403414.Google Scholar
Gartlehner, G, Hansen, RA, Morgan, LC, Thaler, K, Lux, L, Van Noord, M, Mager, U, Thieda, P, Gaynes, BN, Wilkins, T, Strobelberger, M, Lloyd, S, Reichenpfader, U, Lohr, KN (2011). Comparative benefits and harms of second-generation antidepressants for treating major depressive disorder: an updated meta-analysis. Annals of Internal Medicine 155, 772785.Google Scholar
Grundy, SM, Cleeman, JI, Daniels, RS, Donato, KA, Eckel, RH, Franklin, BA, Gordon, DJ, Krauss, RM, Savage, PJ, Smith, SC Jr., Spertus, JA, Costa, F (2005). Diagnosis and management of the metabolic syndrome: an American Heart/National Heart, Lung, and Blood Institute Scientific Statement. Circulation 112, 27352752.Google Scholar
Hedges, LV, Olkin, I (1985). Statistical Models for Meta-Analysis. Academic Press: New York.Google Scholar
Hennings, JM, Schaaf, L, Fulda, S (2012). Glucose metabolism and antidepressant medication. Current Pharmaceutical Design 18, 59005919.Google Scholar
Hwang, LC, Bai, CH, Chen, CJ (2006). Prevalence of obesity and metabolic syndrome in Taiwan. Journal of the Formosan Medical Association 105, 626635.CrossRefGoogle ScholarPubMed
Knol, MJ, Derijks, HJ, Geerlings, MI, Heerdink, ER, Souverein, PC, Gorter, KJ, Grobbee, DE, Egberts, AC (2008). Influence of antidepressants on glycaemic control in patients with diabetes mellitus. Pharmacoepidemiology and Drug Safety 17, 577586.CrossRefGoogle ScholarPubMed
Lamers, F, Vogelzangs, N, Merikangas, KR, de Jonge, P, Beekman, AT, Penninx, BW (2013). Evidence for a differential role of HPA-axis function, inflammation and metabolic syndrome in melancholic versus atypical depression. Molecular Psychiatry 18, 692699.Google Scholar
Lipsey, MW, Wilson, DB (2001). Practical Meta-Analysis. Sage: Thousand Oaks, CA.Google Scholar
Lord, O, Malone, D, Mitchell, AJ (2010). Receipt of preventive medical care and medical screening for patients with mental illness: a comparative analysis. General Hospital Psychiatry 32, 519543.CrossRefGoogle ScholarPubMed
Luppino, FS, de Wit, LM, Bouvy, PF, Stijnen, T, Cuijpers, P, Penninx, BWJH, Zitman, FG (2010). Overweight, obesity, and depression: a systematic review and meta-analysis of longitudinal studies. Archives of General Psychiatry 67, 220229.Google Scholar
Maayan, L, Vakhrusheva, J, Correll, CU (2010). Effectiveness of medications used to reduce antipsychotic-related weight gain and metabolic abnormalities: a systematic review and meta-analysis. Neuropsychopharmacology 35, 15201530.CrossRefGoogle Scholar
Manu, P, Correll, CU, van Winkel, R, Wampers, M, De Hert, M (2012). Prediabetes in patients treated with antipsychotic drugs. Journal of Clinical Psychiatry 73, 460466.CrossRefGoogle ScholarPubMed
Manu, P, Correll, CU, Wampers, M, van Winkel, R, Yu, W, Mitchell, A, De Hert, M (2013). Prediabetic increase in hemoglobin A1c compared with impaired fasting glucose in patients receiving antipsychotic drugs. European Neuropsychopharmacology 23, 205211.Google Scholar
McIntyre, RS, Alsuwaidan, M, Goldstein, BI, Taylor, VH, Schaffer, A, Beaulieu, S, Kemp, DE (2012). The Canadian Network for Mood and Anxiety Treatments (CANMAT) task force recommendations for the management of patients with mood disorders and comorbid metabolic disorders. Annals of Clinical Psychiatry 24, 6981.Google Scholar
McIntyre, RS, Park, KY, Law, CW, Sultan, F, Adams, A, Lourenco, MT, Lo, AK, Soczynska, JK, Woldeyohannes, H, Alsuwaidan, M, Yoon, J, Kennedy, SH (2010). The association between conventional antidepressants and the metabolic syndrome: a review of the evidence and clinical implications. CNS Drugs 24, 741753.CrossRefGoogle ScholarPubMed
McIntyre, RS, Rasgon, NL, Kemp, DE, Nguyen, HT, Law, CW, Taylor, VH, Woldeyohannes, HO, Alsuwaidan, MT, Soczynska, JK, Kim, B, Lourenco, MT, Kahn, LS, Goldstein, BI (2009). Metabolic syndrome and major depressive disorder: co-occurrence and pathophysiologic overlap. Currents Diabetes Reports 9, 5159.Google Scholar
McIntyre, RS, Soczynska, JK, Konarski, JZ, Kennedy, SH (2006). The effect of antidepressants on glucose homeostasis and insulin sensitivity: synthesis and mechanisms. Expert Opinion on Drug Safety 5, 157168.Google Scholar
McIntyre, RS, Soczynska, JK, Konarski, JZ, Woldeyohannes, HO, Law, CW, Miranda, A, Fulgosi, D, Kennedy, SH (2007). Should depressive syndromes be reclassified as ‘metabolic syndrome type II’? Annals of Clinical Psychiatry 19, 257264.CrossRefGoogle ScholarPubMed
Meng, L, Chen, D, Yang, Y, Zheng, Y, Hui, R (2012). Depression increases the risk of hypertension incidence: a meta-analysis of prospective cohort studies. Journal of Hypertension 30, 842851.Google Scholar
Mitchell, AJ, Malone, D, Doebbeling, CC (2009). Quality of medical care for people with and without comorbid mental illness and substance misuse: systematic review of comparative studies. British Journal of Psychiatry 194, 491499.Google Scholar
Mitchell, AJ, Vancampfort, D, De Herdt, A, Yu, W, De Hert, M (2013 a). Is the prevalence of metabolic syndrome and metabolic abnormalities increased in early schizophrenia? A comparative meta-analysis of first episode, untreated and treated patients. Schizophrenia Bulletin 39, 295305.Google Scholar
Mitchell, AJ, Vancampfort, D, Sweers, K, van Winkel, R, Yu, W, De Hert, M (2013 b). Prevalence of metabolic syndrome and metabolic abnormalities in schizophrenia and related disorders – a systematic review and meta-analysis. Schizophrenia Bulletin 39, 306318.Google Scholar
Moher, D, Liberati, A, Tetzlaff, J, Altman, DG; PRISMA Group (2009). Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Medicine 6, e1000097.CrossRefGoogle ScholarPubMed
Mojtabai, R (2013). Antidepressant use and glycemic control. Psychopharmacologia 227, 467477.Google Scholar
Mottillo, S, Filion, KB, Genest, J, Joseph, L, Pilote, L, Poirier, P, Rinfret, S, Schiffrin, EL, Eisenberg, MJ (2010). The metabolic syndrome and cardiovascular risk: a systematic review and meta-analysis. Journal of the American College of Cardiology 56, 11131132.Google Scholar
Nicholson, A, Kuper, H, Hemingway, H (2006). Depression as an aetiologic and prognostic factor in coronary heart disease: a meta-analysis of 6362 events among 146 538 participants in 54 observational studies. European Heart Journal 27, 27632774.CrossRefGoogle Scholar
Niranjan, A, Corujo, A, Ziegelstein, RC, Nwulia, E (2012). Depression and heart disease in US adults. General Hospital Psychiatry 34, 254261.Google Scholar
North, BJ, Sinclair, DA (2012). The intersection between aging and cardiovascular disease. Circulation Research 110, 10971108.Google Scholar
Pan, A, Keum, N, Okereke, OI, Sun, Q, Kivimaki, M, Rubin, RR, Hu, FB (2012). Bidirectional association between depression and metabolic syndrome: a systematic review and meta-analysis of epidemiological studies. Diabetes Care 35, 11711180.CrossRefGoogle ScholarPubMed
Pan, A, Sun, Q, Okereke, OI, Rexrode, KM, Hu, FB (2011). Depression and risk of stroke morbidity and mortality: a meta-analysis and systematic review. Journal of the American Medical Association 306, 12411249.Google Scholar
Patten, SB, Williams, JVA, Lavorato, DH, Eliasziw, MA (2009). Longitudinal community study of major depression and physical activity. General Hospital Psychiatry 31, 571575.Google Scholar
Patton, GC, Carlin, JB, Coffey, C, Wolfe, R, Hibbert, M, Bowes, G (1998). Depression, anxiety, and smoking initiation: a prospective study over 3 years. American Journal of Public Health 88, 15181522.Google Scholar
Penninx, BW, Beekman, AT, Honig, A, Deeg, DJ, Schoevers, RA, van Eijk, JT, van Tilburg, W (2001). Depression and cardiac mortality: results from a community-based longitudinal study. Archives of General Psychiatry 58, 221227.CrossRefGoogle ScholarPubMed
Rugulies, R (2002). Depression as a predictor for coronary heart disease. A review and meta-analysis. American Journal of Preventive Medicine 23, 5161.Google Scholar
Smith, M, Hopkins, D, Peveler, RC, Holt, RI, Woodward, M, Ismail, K (2008). First- v. second-generation antipsychotics and risk for diabetes in schizophrenia: systematic review and meta-analysis. British Journal of Psychiatry 192, 406411.Google Scholar
Swardfager, W, Herrmann, N, Marzolini, S, Saleem, M, Farber, SB, Kiss, A, Lanctôt, KL (2011). Major depressive disorder predicts completion, adherence, and outcomes in cardiac rehabilitation: a prospective cohort study of 195 patients with coronary artery disease. Journal of Clinical Psychiatry 72, 11811188.Google Scholar
Tillin, T, Forouhi, N, Johnston, DG, McKeigue, PM, Chaturvedi, N, Godsland, IF (2005). Metabolic syndrome and coronary heart disease in South Asians, African-Caribbeans and white Europeans: a UK population-based cross-sectional study. Diabetologia 48, 649656.Google Scholar
Valkanova, V, Ebmeier, KP (2013). Vascular risk factors and depression in later life: a systematic review and meta-analysis. Biological Psychiatry 73, 406413.Google Scholar
Vancampfort, D, Vansteelandt, K, Correll, CU, Mitchell, AJ, De Herdt, A, Sienaert, P, Probst, M, De Hert, M (2013). Metabolic syndrome and metabolic abnormalities in bipolar disorder: a meta-analysis of prevalence rates and moderators. American Journal of Psychiatry 170, 265274.Google Scholar
Van der Kooy, K, van Hout, H, Marwijk, H, Marten, H, Stehouwer, C, Beekman, A (2007). Depression and the risk for cardiovascular diseases: systematic review and meta analysis. International Journal of Geriatric Psychiatry 22, 613626.Google Scholar
Whang, W, Kubzansky, LD, Kawachi, I, Rexrode, KM, Kroenke, CH, Glynn, RJ, Garan, H, Albert, CM (2009). Depression and risk of sudden cardiac death and coronary heart disease in women. Journal of the American College of Cardiology 53, 950958.CrossRefGoogle ScholarPubMed
WHO (1993). The ICD-10 Classification of Mental and Behavioural Disorders – Diagnostic Criteria for Research. World Health Organization: Geneva.Google Scholar
WHO Consultation (1999). Definition, Diagnosis and Classification of Diabetes Mellitus and its Complications. Part 1: Diagnosis and Classification of Diabetes Mellitus. World Health Organization: Geneva.Google Scholar
Whooley, MA, de Jonge, P, Vittinghoff, E, Otte, C, Moos, R, Carney, RM, Ali, S, Dowray, S, Na, B, Feldman, MD, Schiller, NB, Browner, WS (2008). Depressive symptoms, health behaviors, and risk of cardiovascular events in patients with coronary heart disease. Journal of the American Medical Association 300, 23792388.Google Scholar
Wulsin, LR, Singal, BM (2003). Do depressive symptoms increase the risk for the onset of coronary disease? A systematic quantitative review. Psychosomatic Medicine 65, 201210.Google Scholar
Wulsin, LR, Vaillant, GE, Wells, VE (1999). A systematic review of the mortality of depression. Psychosomatic Medicine 61, 617.Google Scholar
Ziegelstein, RC, Fauerbach, JA, Stevens, SS, Romanelli, J, Richter, DP, Bush, DE (2000). Patients with depression are less likely to follow recommendations to reduce cardiac risk during recovery from a myocardial infarction. Archives of Internal Medicine 160, 18181823.Google Scholar
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