Hostname: page-component-669899f699-g7b4s Total loading time: 0 Render date: 2025-04-28T07:46:44.294Z Has data issue: false hasContentIssue false
  • English
  • Français

The network structure of major depressive disorder, generalized anxiety disorder and somatic symptomatology

Published online by Cambridge University Press:  15 August 2016

E. Bekhuis ,
R. A. Schoevers ,
C. D. van Borkulo ,
J. G. M. Rosmalen  and
L. Boschloo
E. Bekhuis*
Affiliation:
Department of Psychiatry, University of Groningen, University Medical Center Groningen, Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), Groningen, The Netherlands
R. A. Schoevers
Affiliation:
Department of Psychiatry, University of Groningen, University Medical Center Groningen, Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), Groningen, The Netherlands
C. D. van Borkulo
Affiliation:
Department of Psychiatry, University of Groningen, University Medical Center Groningen, Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), Groningen, The Netherlands Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands
J. G. M. Rosmalen
Affiliation:
Department of Psychiatry, University of Groningen, University Medical Center Groningen, Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), Groningen, The Netherlands
L. Boschloo
Affiliation:
Department of Psychiatry, University of Groningen, University Medical Center Groningen, Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), Groningen, The Netherlands
*
*Address for correspondence: E. Bekhuis, B.Sc., Department of Psychiatry, University Medical Center Groningen, PO Box 30.001, 9700 RB Groningen, The Netherlands. (Email: e.bekhuis@umcg.nl)
Get access Rights & Permissions [Opens in a new window]

Abstract

Background

Major depressive disorder (MDD) and generalized anxiety disorder (GAD) often co-occur with somatic symptomatology. Little is known about the contributions of individual symptoms to this association and more insight into their relationships could help to identify symptoms that are central in the processes behind the co-occurrence. This study explores associations between individual MDD/GAD symptoms and somatic symptoms by using the network approach.

Method

MDD/GAD symptoms were assessed in 2704 participants (mean age 41.7 years, 66.1% female) from the Netherlands Study of Depression and Anxiety using the Inventory of Depressive Symptomatology. Somatic symptoms were assessed with the somatization scale of the Four-Dimensional Symptom Questionnaire. The technique eLasso was used to estimate the network of MDD/GAD and somatic symptoms.

Results

The network structure showed numerous associations between MDD/GAD and somatic symptoms. In general, neurovegetative and cognitive/affective MDD/GAD symptoms showed a similar strength of connections to the somatic domain. However, associations varied substantially across individual symptoms. MDD/GAD symptoms with many and strong associations to the somatic domain included anxiety and fatigue, whereas hypersomnia and insomnia showed no connections to somatic symptoms. Among somatic symptoms, excessive perspiration and pressure/tight feeling in chest were associated with the MDD/GAD domain, while muscle pain and tingling in fingers showed only a few weak associations.

Conclusions

Individual symptoms show differential associations in the co-occurrence of MDD/GAD with somatic symptomatology. Strongly interconnected symptoms are important in furthering our understanding of the interaction between the symptom domains, and may be valuable targets for future research and treatment.

Keywords

Co-morbiditygeneralized anxiety disordermajor depressive disordernetwork analysessomatic symptoms
Type
Original Articles
Information
Psychological Medicine , Volume 46 , Issue 14 , October 2016 , pp. 2989 - 2998
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.)

Article purchase

Temporarily unavailable

References

Abelson, JL, Khan, S, Liberzon, I, Young, EA (2007). HPA axis activity in patients with panic disorder: review and synthesis of four studies. Depression and Anxiety 24, 66–76.CrossRefGoogle ScholarPubMed
American Psychiatric Association (1994). Diagnostic and Statistical Manual of Mental Disorders. American Psychiatric Association: Washington, DC.Google Scholar
American Psychiatric Association (2013). Diagnostic and Statistical Manual of Mental Disorders. American Psychiatric Association: Arlington, VA.Google Scholar
Barrat, A, Barthelemy, M, Pastor-Satorras, R, Vespignani, A (2004). The architecture of complex weighted networks. Proceedings of the National Academy of Sciences of the USA 101, 3747–3752.Google Scholar
Bekhuis, E, Boschloo, L, Rosmalen, JG, Schoevers, RA (2015). Differential associations of specific depressive and anxiety disorders with somatic symptoms. Journal of Psychosomatic Research 78, 116–122.Google Scholar
Borsboom, D, Cramer, AO (2013). Network analysis: an integrative approach to the structure of psychopathology. Annual Review of Clinical Psychology 9, 91–121.CrossRefGoogle Scholar
Boschloo, L, Schoevers, RA, van Borkulo, CD, Borsboom, D, Oldehinkel, AJ (2016 a). The network structure of psychopathology in a community sample of preadolescents. Journal of Abnormal Psychology 125, 599–606.Google Scholar
Boschloo, L, van Borkulo, CD, Borsboom, D, Schoevers, RA (2016 b). A prospective study on how symptoms in a network predict the onset of depression. Psychotherapy and Psychosomatics 85, 183–184.CrossRefGoogle Scholar
Bringmann, LF, Lemmens, LH, Huibers, MJ, Borsboom, D, Tuerlinckx, F (2015). Revealing the dynamic network structure of the Beck Depression Inventory-II. Psychological Medicine 45, 747–757.Google Scholar
Chakraborty, K, Avasthi, A, Kumar, S, Grover, S (2012). Psychological and clinical correlates of functional somatic complaints in depression. International Journal of Social Psychiatry 58, 87–95.Google Scholar
Chen, J, Chen, Z (2008). Extended Bayesian information criteria for model selection with large model spaces. Biometrika 95, 759–771.CrossRefGoogle Scholar
Cramer, AO, Waldorp, LJ, van der Maas, HL, Borsboom, D (2010). Comorbidity: a network perspective. Behavioral and Brain Sciences 33, 137–150; discussion 150–193.CrossRefGoogle ScholarPubMed
Duivis, HE, Vogelzangs, N, Kupper, N, de Jonge, P, Penninx, BW (2013). Differential association of somatic and cognitive symptoms of depression and anxiety with inflammation: findings from the Netherlands Study of Depression and Anxiety (NESDA). Psychoneuroendocrinology 38, 1573–1585.Google Scholar
Epskamp, S, Cramer, AOJ, Waldorp, LJ, Schmittmann, VD, Borsboom, D (2012). qgraph: Network visualizations of relationships in psychometric data. Journal of Statistical Software 48, 1–18.Google Scholar
Fava, M (2002). Somatic symptoms, depression, and antidepressant treatment. Journal of Clinical Psychiatry 63, 305–307.Google Scholar
Fried, EI, Epskamp, S, Nesse, RM, Tuerlinckx, F, Borsboom, D (2016). What are ‘good’ depression symptoms? Comparing the centrality of DSM and non-DSM symptoms of depression in a network analysis. Journal of Affective Disorders 189, 314–320.Google Scholar
Fried, EI, Nesse, RM (2015). Depression sum-scores don't add up: why analyzing specific depression symptoms is essential. BMC Medicine 13, 72.CrossRefGoogle ScholarPubMed
Fruchterman, TM, Reingold, EM (1991). Graph drawing by force-directed placement. Software: Practice and Experience 21, 1129–1164.Google Scholar
Haug, TT, Mykletun, A, Dahl, AA (2004). The association between anxiety, depression, and somatic symptoms in a large population: the HUNT-II study. Psychosomatic Medicine 66, 845–851.Google Scholar
Henningsen, P, Zimmermann, T, Sattel, H (2003). Medically unexplained physical symptoms, anxiety, and depression: a meta-analytic review. Psychosomatic Medicine 65, 528–533.CrossRefGoogle ScholarPubMed
Hettema, JM (2008). The nosologic relationship between generalized anxiety disorder and major depression. Depression and Anxiety 25, 300–316.Google Scholar
Hong, J, Novick, D, Montgomery, W, Aguado, J, Duenas, H, Peng, X, Haro, JM (2015). Should unexplained painful physical symptoms be considered within the spectrum of depressive symptoms? Clinical Practice and Epidemiology in Mental Health: CP & EMH 11, 130–139.CrossRefGoogle ScholarPubMed
Kapfhammer, HP (2006). Somatic symptoms in depression. Dialogues in Clinical Neuroscience 8, 227–239.Google Scholar
Kessler, RC, Andrews, G, Colpe, LJ, Hiripi, E, Mroczek, DK, Normand, SL, Walters, EE, Zaslavsky, AM (2002). Short screening scales to monitor population prevalences and trends in non-specific psychological distress. Psychological Medicine 32, 959–976.Google Scholar
Kessler, RC, Chiu, WT, Demler, O, Merikangas, KR, Walters, EE (2005). Prevalence, severity, and comorbidity of 12-month DSM-IV disorders in the National Comorbidity Survey Replication. Archives of General Psychiatry 62, 617–627.CrossRefGoogle ScholarPubMed
Kolaczyk, E (2009). Statistical Analysis of Network Data. Springer: New York.CrossRefGoogle Scholar
Krueger, RF (1999). The structure of common mental disorders. Archives of General Psychiatry 56, 921–926.Google Scholar
Lux, V, Kendler, KS (2010). Deconstructing major depression: a validation study of the DSM-IV symptomatic criteria. Psychological Medicine 40, 1679–1690.CrossRefGoogle ScholarPubMed
Manian, N, Schmidt, E, Bornstein, MH, Martinez, P (2013). Factor structure and clinical utility of BDI-II factor scores in postpartum women. Journal of Affective Disorders 149, 259–268.Google Scholar
Penninx, BW, Beekman, AT, Smit, JH, Zitman, FG, Nolen, WA, Spinhoven, P, Cuijpers, P, De Jong, PJ, Van Marwijk, HW, Assendelft, WJ, Van Der Meer, K, Verhaak, P, Wensing, M, De Graaf, R, Hoogendijk, WJ, Ormel, J, Van Dyck, R, NESDA Research Consortium (2008). The Netherlands Study of Depression and Anxiety (NESDA): rationale, objectives and methods. International Journal of Methods in Psychiatric Research 17, 121–140.Google Scholar
Rosmalen, JG, Tak, LM, de Jonge, P (2011). Empirical foundations for the diagnosis of somatization: implications for DSM-5. Psychological Medicine 41, 1133–1142.Google Scholar
Rush, AJ, Giles, DE, Schlesser, MA, Fulton, CL, Weissenburger, J, Burns, C (1986). The Inventory for Depressive Symptomatology (IDS): preliminary findings. Psychiatry Research 18, 65–87.Google Scholar
Rush, AJ, Gullion, CM, Basco, MR, Jarrett, RB, Trivedi, MH (1996). The Inventory of Depressive Symptomatology (IDS): psychometric properties. Psychological Medicine 26, 477–486.CrossRefGoogle ScholarPubMed
Smith, SM, Vale, WW (2006). The role of the hypothalamic–pituitary–adrenal axis in neuroendocrine responses to stress. Dialogues in Clinical Neuroscience 8, 383–395.Google Scholar
Terluin, B, van Marwijk, HW, Ader, HJ, de Vet, HC, Penninx, BW, Hermens, ML, van Boeijen, CA, van Balkom, AJ, van der Klink, JJ, Stalman, WA (2006). The Four-Dimensional Symptom Questionnaire (4DSQ): a validation study of a multidimensional self-report questionnaire to assess distress, depression, anxiety and somatization. BMC Psychiatry 6, 34.Google Scholar
Tibshirani, R (1996). Regression shrinkage and selection via the lasso. Journal of the Royal Statistical Society. Series B (Methodological) 58, 267–288.Google Scholar
Uhlig, BL, Engstrom, M, Odegard, SS, Hagen, KK, Sand, T (2014). Headache and insomnia in population-based epidemiological studies. Cephalalgia: An International Journal of Headache 34, 745–751.CrossRefGoogle ScholarPubMed
van Borkulo, C, Boschloo, L, Borsboom, D, Penninx, BW, Waldorp, LJ, Schoevers, RA (2015). Association of symptom network structure with the course of longitudinal depression. JAMA Psychiatry 72, 1219–1226.Google Scholar
van Borkulo, CD, Borsboom, D, Epskamp, S, Blanken, TF, Boschloo, L, Schoevers, RA, Waldorp, LJ (2014). A new method for constructing networks from binary data. Scientific Reports 4, 5918.Google Scholar
Wardenaar, KJ, van Veen, T, Giltay, EJ, den Hollander-Gijsman, M, Penninx, BW, Zitman, FG (2010). The structure and dimensionality of the inventory of depressive symptomatology self report (IDS-SR) in patients with depressive disorders and healthy controls. Journal of Affective Disorders 125, 146–154.Google Scholar
Wesley, AL, Gatchel, RJ, Polatin, PB, Kinney, RK, Mayer, TG (1991). Differentiation between somatic and cognitive/affective components in commonly used measurements of depression in patients with chronic low-back pain. Let's not mix apples and oranges. Spine 16, S213–S215.Google Scholar
Whisman, MA, Perez, JE, Ramel, W (2000). Factor structure of the Beck Depression Inventory-second edition (BDI-II) in a student sample. Journal of Clinical Psychology 56, 545–551.Google Scholar
Wittchen, HU, Jacobi, F, Rehm, J, Gustavsson, A, Svensson, M, Jonsson, B, Olesen, J, Allgulander, C, Alonso, J, Faravelli, C, Fratiglioni, L, Jennum, P, Lieb, R, Maercker, A, van Os, J, Preisig, M, Salvador-Carulla, L, Simon, R, Steinhausen, HC (2011). The size and burden of mental disorders and other disorders of the brain in Europe 2010. European Neuropsychopharmacology: The Journal of the European College of Neuropsychopharmacology 21, 655–679.Google Scholar
Wittchen, HU, Robins, LN, Cottler, LB, Sartorius, N, Burke, JD, Regier, D (1991). Cross-cultural feasibility, reliability and sources of variance of the Composite International Diagnostic Interview (CIDI). The Multicentre WHO/ADAMHA Field Trials. British Journal of Psychiatry: The Journal of Mental Science 159, 645–653, 658.Google Scholar
Supplementary material: PDF

Bekhuis supplementary material

Figure S1

Download Bekhuis supplementary material(PDF)
PDF 27 KB
Supplementary material: File

Bekhuis supplementary material

Table S3

Download Bekhuis supplementary material(File)
File 19.9 KB
Supplementary material: File

Bekhuis supplementary material

Tables S1-S2

Download Bekhuis supplementary material(File)
File 51.7 KB