Depression and risk of type 2 diabetes: The potential role of metabolic factors

Molecular Psychiatry

Volumn 21, Issue 12, 2016, Pages 1726-1732

  Schmitz, N ^a,b,c   Deschenes S S ^a,b   Burns, R J ^a,b   Smith, K J ^d   Lesage, A ^e   Strychar, I ^c,f,g   Rabasa Lhoret, R ^c,f,g,h   Freitas, C ^a,b   Graham, E ^a,b   Awadalla, P ^f   Wang, J L ⁱ  

^a MCGILL UNIVERSITY   (Canada)

^b DOUGLAS MENTAL HEALTH UNIVERSITY INSTITUTE   (Canada)

^c Montreal Diabetes Research Centre   (Canada)

^d BRUNEL UNIVERSITY   (United Kingdom)

^e CENTRE DE RECHERCHE FERNAND SEGUIN   (Canada)

^f UNIVERSITÉ DE MONTRÉAL   (Canada)

^g CENTRE HOSPITALIER DE L UNIVERSITÉ DE MONTRÉAL   (Canada)

^h CLIN RESEARCH INSTITUTE OF MONTREAL   (Canada)

ⁱ UNIVERSITY OF CALGARY   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ANTIDEPRESSANT AGENT; HEMOGLOBIN A1C; HIGH DENSITY LIPOPROTEIN CHOLESTEROL; TRIACYLGLYCEROL; GLUCOSE BLOOD LEVEL;

ADULT; AGED; ARTICLE; DEPRESSION; FEMALE; FOLLOW UP; GLUCOSE BLOOD LEVEL; GLYCEMIC CONTROL; HUMAN; HYPERGLYCEMIA; HYPERTENSION; MAJOR CLINICAL STUDY; MALE; METABOLIC DISORDER; NON INSULIN DEPENDENT DIABETES MELLITUS; OBESITY; PRIORITY JOURNAL; PROSPECTIVE STUDY; RISK FACTOR; STUDY; BLOOD; CANADA; COMPLICATION; DIABETES MELLITUS, TYPE 2; LONGITUDINAL STUDY; METABOLISM; MIDDLE AGED; ODDS RATIO; PATHOPHYSIOLOGY; PHYSIOLOGY;

ADULT; BLOOD GLUCOSE; CANADA; DEPRESSION; DEPRESSIVE DISORDER; DIABETES MELLITUS, TYPE 2; FEMALE; HUMANS; LONGITUDINAL STUDIES; MALE; METABOLISM; MIDDLE AGED; OBESITY; ODDS RATIO; RISK FACTORS; TRIGLYCERIDES;

EID: 84959167667     PISSN: 13594184     EISSN: 14765578     Source Type: Journal    
DOI: 10.1038/mp.2016.7     Document Type: Article

References (45)

1. Collaborators GBoDS. Global, regional, and national incidence, prevalence, and years lived with disability for 301 acute and chronic diseases and injuries in 188 countries, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet 2015; 386: 743-800
2. Ducat L, Philipson LH, Anderson BJ. The Mental Health Comorbidities of Diabetes. JAMA 2014; 312: 691-692
3. Knol MJ, Twisk JWR, Beekman ATF, Heine RJ, Snoek FJ, Pouwer F. Depression as a risk factor for the onset of type 2 diabetes mellitus. A meta-analysis. Diabetologia 2006; 49: 837-845
4. Mezuk B, Eaton WW, Albrecht S, Golden SH. Depression and type 2 diabetes over the lifespan a meta-analysis. Diabetes Care 2008; 31: 2383-2390
5. Rotella F, Mannucci E. Depression as a risk factor for diabetes: a meta-analysis of longitudinal studies. J Clin Psychiatry 2013; 74: 32-38
6. Renn BN, Feliciano L, Segal DL. The bidirectional relationship of depression and diabetes: A systematic review. Clin Psychol Rev 2011; 31: 1239-1246
7. Schulze MB, Hoffmann K, Boeing H, Linseisen J, Rohrmann S, Mohlig M, et al. An accurate risk score based on anthropometric, dietary, and lifestyle factors to predict the development of type 2 diabetes. Diabetes Care 2007; 30: 510-515
8. Lindstrom J, Tuomilehto J. The diabetes risk score -A practical tool to predict type 2 diabetes risk. Diabetes Care 2003; 26: 725-731
9. Rahman M, Simmons RK, Harding AH, Wareham NJ, Griffin SJ. A simple risk score identifies individuals at high risk of developing Type 2 diabetes: a prospective cohort study. Fam Pract 2008; 25: 191-196
10. Joseph J, Svartberg J, Njolstad I, Schirmer H. Incidence of and risk factors for type-2 diabetes in a general population: The Tromso Study. Scand J Public Health 2010; 38: 768-775
11. Shin JA, Lee JH, Lim SY, Ha HS, Kwon HS, Park YM, et al. Metabolic syndrome as a predictor of type2 diabetes, and its clinical interpretations and usefulness. J Diabetes Investig 2013; 4: 334-343
12. McIntyre RS, Rasgon NL, Kemp DE, Nguyen HT, Law CWY, Taylor VH, et al. Metabolic syndrome and major depressive disorder: Co-occurrence and pathophysiologic overlap. Curr Diabetes Rep 2009; 9: 51-59
13. Vancampfort D, Correll CU, Wampers M, Sienaert P, Mitchell AJ, De Herdt A, et al. Metabolic syndrome and metabolic abnormalities in patients with major depressive disorder: a meta-analysis of prevalences and moderating variables. Psychol Med 2014; 44: 2017-2028
14. Vogelzangs N, Beekman AT, Boelhouwer IG, Bandinelli S, Milaneschi Y, Ferrucci L, et al. Metabolic depression: a chronic depressive subtype? Findings from the InCHIANTI study of older persons. J Clin Psychiatry 2011; 72: 598-604
15. Liu CS, Carvalho AF, McIntyre RS. Towards a 'metabolic' subtype of major depressive disorder: shared pathophysiological mechanisms may contribute to cognitive dysfunction. CNS Neurol Disord Drug Targets 2014; 13: 1693-1707
16. DiMatteo MR, Lepper HS, Croghan TW. Depression is a risk factor for noncompliance with medical treatment -Meta-analysis of the effects of anxiety and depression on patient adherence. Arch Inter Med 2000; 160: 2101-2107
17. Awadalla P, Boileau C, Payette Y, Idaghdour Y, Goulet JP, Knoppers B, et al. Cohort profile of the CARTaGENE study: Quebec's population-based biobank for public health and personalized genomics. Int J Epidemiol 2013; 42: 1285-1299
18. Lamers F, Jonkers CCM, Bosma H, Penninx B, Knottnerus JA, van Eijk JTM. Summed score of the Patient Health Questionnaire-9 was a reliable and valid method for depression screening in chronically ill elderly patients. J Clin Epidemiol 2008; 61: 679-687
19. Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, et al. Harmonizing the metabolic syndrome 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 2009; 120: 1640-1645
20. Kessler RC, Ustun TB. The World Mental Health (WMH) Survey Initiative Version of the World Health Organization (WHO) Composite International Diagnostic Interview (CIDI). Int J Methods Psychiatr Res 2004; 13: 93-121
21. American Psychiatric Association APATFoDSMIV. Diagnostic and Statistical Manual of Mental Disorders: DSM-IV-TR. American Psychiatric Association: Washington, DC 2000
22. Craig CL, Marshall AL, Sjostrom M, Bauman AE, Booth ML, Ainsworth BE, et al. International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc 2003; 35: 1381-1395
23. Guidelines for data processing and analysis of the International Physical Activity Questionnaire (IPAQ)-short and long forms https://sites.google.com/site/theipaq/scoring-protocol2005, Accessed Date
24. Eyre H, Kahn R, Robertson RM, Writing AAAC. American Cancer Society, the American Diabetes Association, and the American Heart Association.Collaborative Writing Committee. Preventing cancer, cardiovascular disease, and diabetes -A common agenda for the American Cancer Society, the American Diabetes Association, and the American Heart Association. Diabetes Care 2004; 27: 1812-1824
25. Andersson T, Alfredsson L, Kallberg H, Zdravkovic S, Ahlbom A. Calculating measures of biological interaction. Eur J Epidemiol 2005; 20: 575-579
26. Bollen KA. Structural Equations with Latent Variables. Wiley: New York, NY 1989
27. Byrne B. Structural Equation Modeling with Mplus: Basic Concepts, Applications, and Programming. Routledge Academic Publishers: New York
28. Muthén LK, Muthén BO. Mplus User's Guide. Seventh Edition Muthén & Muthén: Los Angeles, CA 2012
29. Knol MJ, VanderWeele TJ. Recommendations for presenting analyses of effect modification and interaction. Int J Epidemiol 2012; 41: 514-520
30. Qin L, Knol MJ, Corpeleijn E, Stolk RP. Does physical activity modify the risk of obesity for type 2 diabetes: a review of epidemiological data. Eur J Epidemiol 2010; 25: 5-12
31. Tisnado DM, Adams JL, Liu HH, Damberg CL, Chen WP, Hu FA, et al. What is the concordance between the medical record and patient self-report as data sources for ambulatory care? Medical Care 2006; 44: 132-140
32. Skinner KM, Miller DR, Lincoln E, Lee A, Kazis LE. Concordance between respondent self-reports and medical records for chronic conditions: experience from the Veterans Health Study. J Ambul Care Manage 2005; 28: 102-110
33. Margolis KL, Qi LH, Brzyski R, Bonds DE, Howard BV, Kempoinen S, et al. Validity of diabetes self-reports in the Women's Health Initiative: comparison with medication inventories and fasting glucose measurements. Clinical Trials 2008; 5: 240-247
34. Grenard JL, Munjas BA, Adams JL, Suttorp M, Maglione M, McGlynn EA, et al. Depression and medication adherence in the treatment of chronic diseases in the United States: a meta-analysis. J Gen Intern Med 2011; 26: 1175-1182
35. Schmitz N, Gariepy G, Smith KJ, Clyde M, Malla A, Boyer R, et al. Recurrent subthreshold depression in type 2 diabetes: an important risk factor for poor health outcomes. Diabetes Care 2014; 37: 970-978
36. Marazziti D, Rutigliano G, Baroni S, Landi P, Dell'Osso L. Metabolic syndrome and major depression. CNS Spectr 2014; 19: 293-304
37. Musselman DL, Evans DL, Nemeroff CB. The relationship of depression to cardiovascular disease -Epidemiology, biology, and treatment. Arch Gen Psychiatry 1998; 55: 580-592
38. Pan A, Sun Q, Okereke OI, Rexrode KM, Rubin RR, Lucas M, et al. Use of antidepressant medication and risk of type 2 diabetes: results from three cohorts of US adults. Diabetologia 2012; 55: 63-72
39. Eckel RH, Alberti K, Grundy SM, Zimmet PZ. The metabolic syndrome. Lancet 2010; 375: 181-183
40. Vogelzangs N, Beekman ATF, Dortland A, Schoevers RA, Giltay EJ, de Jonge P, et al. Inflammatory and metabolic dysregulation and the 2-year course of depressive disorders in antidepressant users. Neuropsychopharmacology 2014; 39: 1624-1634
41. McEwen BS. Mood disorders and allostatic load. Biol Psychiatry 2003; 54: 200-207
42. Lesage A. Heuristic model of depressive disorders as systemic chronic disease. Epidemiol Psychiatr Sci 2015; 24: 309-311
43. Penninx BW, Milaneschi Y, Lamers F, Vogelzangs N. Understanding the somatic consequences of depression: biological mechanisms and the role of depression symptom profile. BMC Med 2013; 11: 129
44. Lamers F, de Jonge P, Nolen WA, Smit JH, Zitman FG, Beekman ATF, et al. Identifying depressive subtypes in a large cohort study: results from the Netherlands Study of Depression and Anxiety (NESDA). J Clin Psychiatry 2010; 71: 1582-1589
45. Cizza G, Ronsaville DS, Kleitz H, Eskandari F, Mistry S, Torvik S, et al. Clinical subtypes of depression are associated with specific metabolic parameters and circadian endocrine profiles in women: The Power Study. PLoS One 2012; 7: 9