Hostname: page-component-745bb68f8f-kw2vx Total loading time: 0 Render date: 2025-01-31T13:44:59.723Z Has data issue: false hasContentIssue false
  • English
  • Français

The association between cognitive function and subsequent depression: a systematic review and meta-analysis

Published online by Cambridge University Press:  14 September 2016

M. A. Scult ,
A. R. Paulli ,
E. S. Mazure ,
T. E. Moffitt ,
A. R. Hariri  and
T. J. Strauman
M. A. Scult*
Affiliation:
Department of Psychology & Neuroscience, Duke University, Durham, NC, USA
A. R. Paulli
Affiliation:
Department of Psychology & Neuroscience, Duke University, Durham, NC, USA
E. S. Mazure
Affiliation:
Duke University Medical Center Library & Archives, Duke University Medical Center, Durham, NC, USA
T. E. Moffitt
Affiliation:
Department of Psychology & Neuroscience, Duke University, Durham, NC, USA
A. R. Hariri
Affiliation:
Department of Psychology & Neuroscience, Duke University, Durham, NC, USA
T. J. Strauman
Affiliation:
Department of Psychology & Neuroscience, Duke University, Durham, NC, USA
*
*Address for correspondence: Dr M. A. Scult, Department of Psychology & Neuroscience, Duke University, Durham, NC 27708, USA. (Email: [email protected])
Get access Rights & Permissions [Opens in a new window]

Abstract

Despite a growing interest in understanding the cognitive deficits associated with major depressive disorder (MDD), it is largely unknown whether such deficits exist before disorder onset or how they might influence the severity of subsequent illness. The purpose of the present study was to conduct a systematic review and meta-analysis of longitudinal datasets to determine whether cognitive function acts as a predictor of later MDD diagnosis or change in depression symptoms. Eligible studies included longitudinal designs with baseline measures of cognitive functioning, and later unipolar MDD diagnosis or symptom assessment. The systematic review identified 29 publications, representing 34 unique samples, and 121 749 participants, that met the inclusion/exclusion criteria. Quantitative meta-analysis demonstrated that higher cognitive function was associated with decreased levels of subsequent depression (r = −0.088, 95% confidence interval. −0.121 to −0.054, p < 0.001). However, sensitivity analyses revealed that this association is likely driven by concurrent depression symptoms at the time of cognitive assessment. Our review and meta-analysis indicate that the association between lower cognitive function and later depression is confounded by the presence of contemporaneous depression symptoms at the time of cognitive assessment. Thus, cognitive deficits predicting MDD likely represent deleterious effects of subclinical depression symptoms on performance rather than premorbid risk factors for disorder.

Keywords

Cognitive functiondepressionintelligencelongitudinalpremorbidrisk
Type
Review Article
Information
Psychological Medicine , Volume 47 , Issue 1 , January 2017 , pp. 1 - 17
Copyright
Copyright © Cambridge University Press 2016 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Aarts, E, van Holstein, M, Cools, R (2011). Striatal dopamine and the interface between motivation and cognition. Frontiers in Psychology 2, 163.Google Scholar
Atkinson, KM, Koenka, AC, Sanchez, CE, Moshontz, H, Cooper, H (2014). Reporting standards for literature searches and report inclusion criteria: making research syntheses more transparent and easy to replicate. Research Synthesis Methods 6, 87–95.Google Scholar
Baer, LH, Tabri, N, Blair, M, Bye, D, Li, KZH, Pushkar, D (2013). Longitudinal associations of need for cognition, cognitive activity, and depressive symptomatology with cognitive function in recent retirees. Journals of Gerontology. Series B, Psychological Sciences and Social Sciences 68, 655–664.CrossRefGoogle ScholarPubMed
Barbey, AK, Colom, R, Solomon, J, Krueger, F, Forbes, C, Grafman, J (2012). An integrative architecture for general intelligence and executive function revealed by lesion mapping. Brain 135, 1154–1164.Google Scholar
Barnett, JH, Salmond, CH, Jones, PB, Sahakian, BJ (2006). Cognitive reserve in neuropsychiatry. Psychological Medicine 36, 1053–1064.Google Scholar
Beaujean, AA, Parker, S, Qiu, X (2013). The relationship between cognitive ability and depression: a longitudinal data analysis. Social Psychiatry and Psychiatric Epidemiology 48, 1983–1992.Google Scholar
Belsky, DW, Caspi, A, Arseneault, L, Bleidorn, W, Fonagy, P, Goodman, M, Houts, R, Moffitt, TE (2012). Etiological features of borderline personality related characteristics in a birth cohort of 12-year-old children. Development and Psychopathology 24, 251–265.CrossRefGoogle Scholar
Betts, KS, Williams, GM, Najman, JM, Alati, R (2016). Predicting spectrums of adult mania, psychosis and depression by prospectively ascertained childhood neurodevelopment. Journal of Psychiatric Research 72, 22–29.Google Scholar
Bora, E, Harrison, BJ, Yücel, M, Pantelis, C (2013). Cognitive impairment in euthymic major depressive disorder: a meta-analysis. Psychological Medicine 43, 2017–2026.CrossRefGoogle ScholarPubMed
Borenstein, M, Hedges, LV, Higgins, JPT, Rothstein, HR (2011). Introduction to Meta-Analysis. John Wiley & Sons: West Sussex, UK.Google Scholar
Canals, J, Domènech-Llaberia, E, Fernández-Ballart, J, Martí-Henneberg, C (2002). Predictors of depression at eighteen. A 7-year follow-up study in a Spanish nonclinical population. European Child & Adolescent Psychiatry 11, 226–233.Google Scholar
Christensen, H, Griffiths, K, Mackinnon, A (1997). A quantitative review of cognitive deficits in depression and Alzheimer-type dementia. Selection of Studies 3, 631–651.Google ScholarPubMed
Connolly, SL, Wagner, Ca, Shapero, BG, Pendergast, LL, Abramson, LY, Alloy, LB (2014). Rumination prospectively predicts executive functioning impairments in adolescents. Journal of Behavior Therapy and Experimental Psychiatry 45, 46–56.Google Scholar
Cooper, HM (1979). Statistically combining independent studies: a meta-analysis of sex differences in conformity research. Journal of Personality and Social Psychology 37, 131–146.CrossRefGoogle Scholar
Cooper, HM (2010). Research Synthesis and Meta-Analysis: A Step-by-Step Approach, 4th edn. SAGE Publications: Washington (DC), USA.Google Scholar
Cuijpers, P, de Graaf, R, van Dorsselaer, S (2004). Minor depression: risk profiles, functional disability, health care use and risk of developing major depression. Journal of Affective Disorders 79, 71–79.CrossRefGoogle ScholarPubMed
Cuthbert, BN, Kozak, MJ (2013). Constructing constructs for psychopathology: the NIMH research domain criteria. Journal of Abnormal Psychology 122, 928–937.CrossRefGoogle ScholarPubMed
Der, G, Batty, GD, Deary, IJ (2009). The association between IQ in adolescence and a range of health outcomes at 40 in the 1979 US National Longitudinal Study of Youth. Intelligence 37, 573–580.Google Scholar
Dubow, EF, Boxer, P, Huesmann, LR (2008). Childhood and adolescent predictors of early and middle adulthood alcohol use and problem drinking: the Columbia County Longitudinal Study. Addiction 103, 36–47.CrossRefGoogle ScholarPubMed
Duval, S, Tweedie, R (2000). Trim and fill: a simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis. Biometrics 56, 455–463.CrossRefGoogle ScholarPubMed
Evans, LD, Kouros, CD, Samanez-Larkin, S, Garber, J (2015). Concurrent and short-term prospective relations among neurocognitive functioning, coping, and depressive symptoms in youth. Journal of Clinical Child and Adolescent Psychology 53, 1–15.Google Scholar
Franz, CE, Lyons, MJ, O'Brien, R, Panizzon, MS, Kim, K, Bhat, R, Grant, MD, Toomey, R, Eisen, S, Xian, H, Kremen, WS (2011). A 35-year longitudinal assessment of cognition and midlife depression symptoms: the Vietnam Era Twin Study of Aging. American Association for Geriatric Psychiatry American Journal of Geriatric Psychiatry 19, 559–570.Google Scholar
Gale, CR, Batty, GD, Tynelius, P, Deary, IJ, Rasmussen, F (2010). Intelligence in early adulthood and subsequent hospitalization for mental disorders. Epidemiology 21, 70–77.Google Scholar
Gale, CR, Deary, IJ, Boyle, SH, Barefoot, J, Mortensen, LH, Batty, GD (2008). Cognitive ability in early adulthood and risk of 5 specific psychiatric disorders in middle age: the Vietnam experience study. Archives of General Psychiatry 65, 1410–1418.Google Scholar
Gale, CR, Hatch, SL, Batty, GD, Deary, IJ (2009). Intelligence in childhood and risk of psychological distress in adulthood: the 1958 National Child Development Survey and the 1970 British Cohort Study. Intelligence 37, 592–599.Google Scholar
Gjerde, PF (1995). Alternative pathways to chronic depressive symptoms in young adults: gender differences in developmental trajectories. Child Development 66, 1277–1300.CrossRefGoogle ScholarPubMed
Gottfredson, LS (1997). Mainstream science on intelligence: an editorial with 52 signatories, history, and bibliography. Intelligence 24, 13–23.CrossRefGoogle Scholar
Guyer, AE, Choate, VR, Grimm, KJ, Pine, DS, Keenan, K (2011). Emerging depression is associated with face memory deficits in adolescent girls. Elsevier Inc. Journal of the American Academy of Child and Adolescent Psychiatry 50, 180–190.Google Scholar
Gyurak, A, Patenaude, B, Korgaonkar, MS, Grieve, SM, Williams, LM, Etkin, A (2015). Frontoparietal activation during response inhibition predicts remission to antidepressants in patients with major depression. Biological Psychiatry 79, 1–8.Google Scholar
Hagenaars, SP, Harris, SE, Davies, G, Hill, WD, Liewald, DCM, Ritchie, SJ, Marioni, RE, Fawns-Ritchie, C, Cullen, B, Malik, R, METASTROKE Consortium IC for BPG, SpiroMeta Consortium, CHARGE Consortium Pulmonary Group CCA and LG, Worrall, BB, Sudlow, CLM, Wardlaw, JM, Gallacher, J, Pell, J, McIntosh, AM, Smith, DJ, Gale, CR, Deary, IJ (2016). Shared genetic aetiology between cognitive functions and physical and mental health in UK Biobank (N = 112 151) and 24 GWAS consortia. Molecular Psychiatry. Published online: 26 January 2016. doi:10.1038/mp.2015.225.CrossRefGoogle ScholarPubMed
Hatch, SL, Jones, PB, Kuh, D, Hardy, R, Wadsworth, MEJ, Richards, M (2007). Childhood cognitive ability and adult mental health in the British 1946 birth cohort. Social Science & Medicine (1982) 64, 2285–2296.CrossRefGoogle ScholarPubMed
Hipwell, AE, Sapotichne, B, Klostermann, S, Battista, D, Keenan, K (2011). Autobiographical memory as a predictor of depression vulnerability in girls. Journal of Clinical Child and Adolescent Psychology 40, 254–265.Google Scholar
Horowitz, JL, Garber, J (2003). Relation of intelligence and religiosity to depressive disorders in offspring of depressed and nondepressed mothers. The American Academy of Child and Adolescent Psychiatry Journal of the American Academy of Child and Adolescent Psychiatry 42, 578–586.Google Scholar
Johnson, W, Bouchard, TJ, Krueger, RF, McGue, M, Gottesman, II (2004). Just one g: consistent results from three test batteries. Intelligence 32, 95–107.Google Scholar
Keedwell, PA, Andrew, C, Williams, SCR, Brammer, MJ, Phillips, ML (2005). The neural correlates of anhedonia in major depressive disorder. Biological Psychiatry 58, 843–853.Google Scholar
Kessler, RC, Berglund, P, Demler, O, Jin, R, Koretz, D, Merikangas, KR, Rush, AJ, Walters, EE, Wang, PS (2003). The epidemiology of major depressive disorder: results from the National Comorbidity Survey Replication (NCS-R). Journal of the American Medical Association 289, 3095–3105.Google Scholar
Koenen, KC, Moffitt, TE, Roberts, AL, Martin, LT, Kubzansky, L, Harrington, H, Poulton, R, Caspi, A (2009). Childhood IQ and adult mental disorders: a test of the cognitive reserve hypothesis. American Journal of Psychiatry 166, 50–57.Google Scholar
Lewinsohn, PM, Solomon, A, Seeley, JR, Zeiss, A (2000). Clinical implications of ‘subthreshold’ depressive symptoms. Journal of Abnormal Psychology 109, 345–351.Google Scholar
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, 220–229.Google Scholar
McCord, J, Ensminger, ME (1997). Multiple risks and comorbidity in an African-American population. Criminal Behaviour and Mental Health 7, 339–352.CrossRefGoogle Scholar
McDermott, LM, Ebmeier, KP (2009). A meta-analysis of depression severity and cognitive function. Elsevier B.V. Journal of Affective Disorders 119, 1–8.Google Scholar
Melartin, TK, Rytsälä, HJ, Leskelä, US, Lestelä-Mielonen, PS, Sokero, TP, Isometsä, ET (2002). Current comorbidity of psychiatric disorders among DSM-IV major depressive disorder patients in psychiatric care in the Vantaa Depression Study. Journal of Clinical Psychiatry 63, 126–134.Google Scholar
Meyer, SE, Carlson, GA, Wiggs, EA, Martinez, PE, Ronsaville, DS, Klimes–Dougan, B, Gold, PW, Radke–Yarrow, M (2004). A prospective study of the association among impaired executive functioning, childhood attentional problems, and the development of bipolar disorder. Development and Psychopathology 16, 461–476.Google Scholar
Miyake, A, Friedman, NP, Emerson, MJ, Witzki, aH, Howerter, A, Wager, TD (2000). The unity and diversity of executive functions and their contributions to complex ‘Frontal Lobe’ tasks: a latent variable analysis. Cognitive Psychology 41, 49–100.CrossRefGoogle ScholarPubMed
Moher, D, Liberati, A (2009). Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Annals of Internal Medicine 151, 264–269.CrossRefGoogle ScholarPubMed
Papmeyer, M, Sussmann, JE, Hall, J, McKirdy, J, Peel, A, Macdonald, A, Lawrie, SM, Whalley, HC, McIntosh, AM (2015). Neurocognition in individuals at high familial risk of mood disorders with or without subsequent onset of depression. Psychological Medicine 45, 1–11.Google Scholar
Peterson, RA, Brown, SP (2005). On the use of beta coefficients in meta-analysis. Journal of Applied Psychology 90, 175–181.Google Scholar
Pine, DS, Cohen, P, Brook, J, Coplan, JD (1997). Psychiatric symptoms in adolescence as predictors of obesity in early adulthood: a longitudinal study. American Journal of Public Health 87, 1303–1310.Google Scholar
Quinn, ME, Joormann, J (2015). Control when it counts: change in executive control under stress predicts depression symptoms. Emotion Junio 22, 1–10.Google Scholar
Rawal, A, Rice, F (2012). Examining overgeneral autobiographical memory as a risk factor for adolescent depression. Elsevier Inc. Journal of the American Academy of Child and Adolescent Psychiatry 51, 518–527.CrossRefGoogle ScholarPubMed
Ree, MJ, Earles, JA (1991). The stability of g across different methods of estimation. Intelligence 15, 271–278.Google Scholar
Rock, PL, Roiser, JP, Riedel, WJ, Blackwell, AD (2014). Cognitive impairment in depression: a systematic review and meta-analysis. Psychological Medicine 44, 2029–2040.Google Scholar
Rogers, MA, Kasai, K, Koji, M, Fukuda, R, Iwanami, A, Nakagome, K, Fukuda, M, Kato, N (2004). Executive and prefrontal dysfunction in unipolar depression: a review of neuropsychological and imaging evidence. Neuroscience Research 50, 1–11.Google Scholar
Scult, MA, Knodt, AR, Swartz, JR, Brigidi, BD, Hariri, AR (2016). Thinking and feeling: individual differences in habitual emotion regulation and stress-related mood are associated with prefrontal executive control. Clinical Psychological Science. doi:10.1177/2167702616654688.Google Scholar
Sharp, C, Petersen, N, Goodyer, I (2008). Emotional reactivity and the emergence of conduct problems and emotional symptoms in 7- to 11-year-olds: a 1-year follow-up study. Journal of the American Academy of Child and Adolescent Psychiatry 47, 565–573.CrossRefGoogle ScholarPubMed
Siegel, LS (1999). Issues in the definition and diagnosis of learning disabilities: a perspective on Guckenberger v. Boston University. Journal of Learning Disabilities 32, 304–319.Google Scholar
Simons, CJP, Jacobs, N, Derom, C, Thiery, E, Jolles, J, van Os, J, Krabbendam, L (2009). Cognition as predictor of current and follow-up depressive symptoms in the general population. Acta Psychiatrica Scandinavica 120, 45–52.Google Scholar
Slykerman, RF, Thompson, J, Waldie, K, Murphy, R, Wall, C, Mitchell, EA (2015). Maternal stress during pregnancy is associated with moderate to severe depression in 11-year-old children. Acta Paediatrica 104, 68–74.Google Scholar
Snyder, HR (2013). Major depressive disorder is associated with broad impairments on neuropsychological measures of executive function: a meta-analysis and review. Psychological Bulletin 139, 81–132.CrossRefGoogle ScholarPubMed
Sørensen, HJ, Sæbye, D, Urfer-Parnas, A, Mortensen, EL, Parnas, J (2012). Premorbid intelligence and educational level in bipolar and unipolar disorders: a Danish draft board study. Journal of Affective Disorders 136, 1188–1191.Google Scholar
Spearman, C (1904). ‘General intelligence,’ objectively determined and measured. American Journal of Psychology 15, 201.Google Scholar
Stern, Y (2003). The concept of cognitive reserve: a catalyst for research. Journal of Clinical and Experimental Neuropsychology (Neuropsychology, Development and Cognition: Section A) 25, 589–593.CrossRefGoogle ScholarPubMed
Stroup, D, Berlin, J, Morton, S, Olkin, I, Williamson, GD, Rennie, D, Moher, D, Becker, BJ, Sipe, TA, Thacker, SB (2000). Meta-analysis of Observational Studies in Epidemiology: a proposal for reporting. Journal of the American Medical Association 283, 2008.Google Scholar
Vinberg, M, Miskowiak, KW, Kessing, LV (2013). Impairment of executive function and attention predicts onset of affective disorder in healthy high-risk twins. Journal of Clinical Psychiatry 74, e747–e753.Google Scholar
Zammit, S, Allebeck, P, David, AS, Dalman, C, Hemmingsson, T, Lundberg, I, Lewis, G (2004). A longitudinal study of premorbid IQ Score and risk of developing schizophrenia, bipolar disorder, severe depression, and other nonaffective psychoses. Archives of General Psychiatry 61, 354–360.Google Scholar
Supplementary material: File

Scult supplementary material

Scult supplementary material

Download Scult supplementary material(File)
File 355.2 KB