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Sex similarities and differences in risk factors for recurrence of major depression

Published online by Cambridge University Press:  27 November 2017

Hanna M. van Loo ,
Steven H. Aggen ,
Charles O. Gardner  and
Kenneth S. Kendler
Hanna M. van Loo*
Affiliation:
Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
Steven H. Aggen
Affiliation:
Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
Charles O. Gardner
Affiliation:
Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
Kenneth S. Kendler
Affiliation:
Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USA
*
Author for correspondence: Hanna M. van Loo, E-mail: h.van.loo@umcg.nl
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Abstract

Background

Major depression (MD) occurs about twice as often in women as in men, but it is unclear whether sex differences subsist after disease onset. This study aims to elucidate potential sex differences in rates and risk factors for MD recurrence, in order to improve prediction of course of illness and understanding of its underlying mechanisms.

Methods

We used prospective data from a general population sample (n = 653) that experienced a recent episode of MD. A diverse set of potential risk factors for recurrence of MD was analyzed using Cox models subject to elastic net regularization for males and females separately. Accuracy of the prediction models was tested in same-sex and opposite-sex test data. Additionally, interactions between sex and each of the risk factors were investigated to identify potential sex differences.

Results

Recurrence rates and the impact of most risk factors were similar for men and women. For both sexes, prediction models were highly multifactorial including risk factors such as comorbid anxiety, early traumas, and family history. Some subtle sex differences were detected: for men, prediction models included more risk factors concerning characteristics of the depressive episode and family history of MD and generalized anxiety, whereas for women, models included more risk factors concerning early and recent adverse life events and socioeconomic problems.

Conclusions

No prominent sex differences in risk factors for recurrence of MD were found, potentially indicating similar disease maintaining mechanisms for both sexes. Course of MD is a multifactorial phenomenon for both males and females.

Keywords

Major depressive disorderrecurrencecourse of illnesssex differencesprediction
Type
Original Articles
Information
Psychological Medicine , Volume 48 , Issue 10 , July 2018 , pp. 1685 - 1693
Copyright
Copyright © Cambridge University Press 2017 

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References

Boschloo, L, Schoevers, RA, Beekman, AT, Smit, JH, van Hemert, AM and Penninx, BW (2014) The four-year course of major depressive disorder: the role of staging and risk factor determination. Psychotherapy and Psychosomatics 83(5), 279–288.CrossRefGoogle ScholarPubMed
Bracke, P (1998) Sex differences in the course of depression: evidence from a longitudinal study of a representative sample of the Belgian population. Social Psychiatry and Psychiatric Epidemiology 33(9), 420–429.CrossRefGoogle ScholarPubMed
de Graaf, R, ten Have, M, Tuithof, M and van Dorsselaer, S (2013) First-incidence of DSM-IV mood, anxiety and substance use disorders and its determinants: results from the Netherlands Mental Health Survey and Incidence Study-2. Journal of Affective Disorders 149(1–3), 100–107.CrossRefGoogle ScholarPubMed
Eaton, WW, Shao, H, Nestadt, G, Lee, BH, Bienvenu, OJ and Zandi, P (2008) Population-based study of first onset and chronicity in major depressive disorder. Archives of General Psychiatry 65(5), 513–520.CrossRefGoogle ScholarPubMed
Frank, E, Prien, RF, Jarrett, RB, Keller, MB, Kupfer, DJ, Lavori, PW, Rush, AJ and Weissman, MM (1991) Conceptualization and rationale for consensus definitions of terms in major depressive disorder. Remission, recovery, relapse, and recurrence. Archives of General Psychiatry 48(9), 851–855.CrossRefGoogle ScholarPubMed
Friedman, J, Hastie, T and Tibshirani, R (2010) Regularization paths for generalized linear models via coordinate descent. Journal of Statistical Software 33(1), 1–22.CrossRefGoogle ScholarPubMed
Gerrits, MM, van Oppen, P, van Marwijk, HW, van der Horst, H and Penninx, BW (2013) The impact of chronic somatic diseases on the course of depressive and anxiety disorders. Psychotherapy and Psychosomatics 82(1), 64–66.CrossRefGoogle ScholarPubMed
Gopinath, S, Katon, WJ, Russo, JE and Ludman, EJ (2007) Clinical factors associated with relapse in primary care patients with chronic or recurrent depression. Journal of Affective Disorders 101(1–3), 57–63.CrossRefGoogle ScholarPubMed
Hardeveld, F, Spijker, J, De Graaf, R, Hendriks, SM, Licht, CM, Nolen, WA, Penninx, BW and Beekman, AT (2013a) Recurrence of major depressive disorder across different treatment settings: results from the NESDA study. Journal of Affective Disorders 147(1–3), 225–231.CrossRefGoogle ScholarPubMed
Hardeveld, F, Spijker, J, De Graaf, R, Nolen, WA and Beekman, AT (2013b) Recurrence of major depressive disorder and its predictors in the general population: results from the Netherlands Mental Health Survey and Incidence Study (NEMESIS). Psychological Medicine 43(1), 39–48.CrossRefGoogle ScholarPubMed
Hastie, T, Tibshirani, R and Friedman, J (2009) The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd edn. New York, NY: Springer.CrossRefGoogle Scholar
Heagerty, PJ and Saha-Chaudhuri, P (2013) survivalROC: Time-dependent ROC curve estimation from censured survival data.1.0.3 edn. Available at http://CRAN.R-project.org/package=survivalROC.Google Scholar
Holma, KM, Holma, IAK, Melartin, TK, Rytsälä, HJ and Isometsä, ET (2008) Long-term outcome of major depressive disorder in psychiatric patients is variable. Journal of Clinical Psychiatry 69(2), 196–205.CrossRefGoogle ScholarPubMed
James, G, Witten, D, Hastie, T and Tibshirani, R (2013) An Introduction to Statistical Learning with Applications in R. New York: Springer.Google Scholar
Kendler, KS (2014) The structure of psychiatric science. The American Journal of Psychiatry 171(9), 931–938.CrossRefGoogle ScholarPubMed
Kendler, KS and Gardner, CO (2014) Sex differences in the pathways to major depression: a study of opposite-sex twin pairs. The American Journal of Psychiatry 171(4), 426–435.CrossRefGoogle ScholarPubMed
Kendler, KS and Prescott, CA (2006) Genes, Environment and Psychopathology: Understanding the Causes of Psychiatric and Substance use Disorders. New York: Guilford Press.Google Scholar
Kendler, KS, Thornton, LM and Gardner, CO (2000) Stressful life events and previous episodes in the etiology of major depression in women: an evaluation of the “kindling” hypothesis. The American Journal of Psychiatry 157(8), 1243–1251.CrossRefGoogle ScholarPubMed
Kessing, LV (1998) Recurrence in affective disorder. II. Effect of age and gender. The British Journal of Psychiatry: The Journal of Mental Science 172, 29–34.CrossRefGoogle ScholarPubMed
Kessing, LV, Andersen, PK and Mortensen, PB (1998) Predictors of recurrence in affective disorder. A case register study. Journal of Affective Disorders 49(2), 101–108.CrossRefGoogle ScholarPubMed
Kessler, RC (2003) Epidemiology of women and depression. Journal of Affective Disorders 74(1), 5–13.CrossRefGoogle ScholarPubMed
Kessler, RC, McGonagle, KA, Swartz, M, Blazer, DG and Nelson, CB (1993) Sex and depression in the National Comorbidity Survey. I: Lifetime prevalence, chronicity and recurrence. Journal of Affective Disorders 29(2–3), 85–96.CrossRefGoogle ScholarPubMed
Kuehner, C (2017) Why is depression more common among women than among men?. The Lancet Psychiatry 4, 146–158.CrossRefGoogle ScholarPubMed
Mattisson, C, Bogren, M, Horstmann, V, Munk-Jorgensen, P and Nettelbladt, P (2007) The long-term course of depressive disorders in the Lundby Study. Psychological Medicine 37(6), 883–891.CrossRefGoogle ScholarPubMed
Mueller, TI, Leon, AC, Keller, MB, Solomon, DA, Endicott, J, Coryell, W, Warshaw, M and Maser, JD (1999) Recurrence after recovery from major depressive disorder during 15 years of observational follow-up. The American Journal of Psychiatry 156(7), 1000–1006.CrossRefGoogle ScholarPubMed
Musliner, KL, Munk-Olsen, T, Laursen, TM, Eaton, WW, Zandi, PP and Mortensen, PB (2016) Heterogeneity in 10-year course trajectories of moderate to severe major depressive disorder: a Danish National Register-Based Study. JAMA Psychiatry 73(4), 346–353.CrossRefGoogle ScholarPubMed
Oldehinkel, AJ and Bouma, EM (2011) Sensitivity to the depressogenic effect of stress and HPA-axis reactivity in adolescence: a review of gender differences. Neuroscience and Biobehavioral Reviews 35(8), 1757–1770.CrossRefGoogle Scholar
Patten, SB, Wang, JL, Williams, JV, Lavorato, DH, Khaled, SM and Bulloch, AG (2010) Predictors of the longitudinal course of major depression in a Canadian population sample. Canadian Journal of Psychiatry. Revue canadienne de psychiatrie 55(10), 669–676.CrossRefGoogle Scholar
Piccinelli, M and Wilkinson, G (2000) Gender differences in depression. Critical review. The British Journal of Psychiatry: The Journal of Mental Science 177, 486–492.CrossRefGoogle ScholarPubMed
R Core Team (2014) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org/.Google Scholar
Royston, P and Altman, DG (2013) External validation of a Cox prognostic model: principles and methods. BMC Medical Research Methodology 13, 33.CrossRefGoogle ScholarPubMed
Rutter, M, Caspi, A and Moffitt, TE (2003) Using sex differences in psychopathology to study causal mechanisms: unifying issues and research strategies. Journal of Child Psychology and Psychiatry, and Allied Disciplines 44(8), 1092–1115.CrossRefGoogle ScholarPubMed
Schloerke, B, Crowley, J, Cook, D, Hofmann, H, Wickham, H, Briatte, F, Marbach, M and Thoen, E (2014) GGally: Extension to ggplot2., R package version 0.4.7 edn.Google Scholar
Simon, N, Friedman, J, Hastie, T and Tibshirani, R (2011) Regularization paths for cox's proportional hazards model via coordinate descent. Journal of Statistical Software 39(5), 1–13.CrossRefGoogle ScholarPubMed
Steyerberg, EW, Vickers, AJ, Cook, NR, Gerds, T, Gonen, M, Obuchowski, N, Pencina, MJ and Kattan, MW (2010) Assessing the performance of prediction models: a framework for traditional and novel measures. Epidemiology (Cambridge, Mass.) 21(1), 128–138.CrossRefGoogle ScholarPubMed
Stroud, CB, Davila, J and Moyer, A (2008) The relationship between stress and depression in first onsets versus recurrences: a meta-analytic review. Journal of Abnormal Psychology 117(1), 206–213.CrossRefGoogle ScholarPubMed
Thernau, T (2014) A Package for Survival Analysis in S. R package. 2.37-7 edn. Available at http://CRAN.R-project.org/package=survival.Google Scholar
van Buuren, S and Groothuis-Oudshoorn, K (2011) Mice: multivariate imputation by chained equations in R. Journal of Statistical Software 45(3), 1–67.Google Scholar
van Loo, HM, Aggen, SA, Chardner, CO and Kendler, KS (2015) Multiple risk factors predict recurrence of major depressive disorder in women. Journal of Affective Disorders 180, 52–61.CrossRefGoogle ScholarPubMed
van Loo, HM, van den Heuvel, ER, Schoevers, RA, Anselmino, M, Carney, RM, Denollet, J, Doyle, F, Freedland, KE, Grace, SL, Hosseini, SH, Parakh, K, Pilote, L, Rafanelli, C, Roest, AM, Sato, H, Steeds, RP, Kessler, RC and de Jonge, P (2014) Sex dependent risk factors for mortality after myocardial infarction: individual patient data meta-analysis. BMC Medicine 12(1), 242.CrossRefGoogle ScholarPubMed
Wang, JL, Patten, SB, Currie, S, Sareen, J and Schmitz, N (2012) Predictors of 1-year outcomes of major depressive disorder among individuals with a lifetime diagnosis: a population-based study. Psychological Medicine 42(2), 327–334.CrossRefGoogle ScholarPubMed
Wichers, M, Geschwind, N, van Os, J and Peeters, F (2010) Scars in depression: is a conceptual shift necessary to solve the puzzle? Psychological Medicine 40(3), 359–365.CrossRefGoogle ScholarPubMed
Wu, TT, Chen, YF, Hastie, T, Sobel, E and Lange, K (2009) Genome-wide association analysis by lasso penalized logistic regression. Bioinformatics (Oxford, England) 25(6), 714–721.Google ScholarPubMed
Xu, H, Caramanis, C and Mannor, S (2012) Sparse algorithms are not stable: a no-free-lunch theorem. IEEE Transactions on Pattern Analysis and Machine Intelligence 34(1), 187–193.Google Scholar
Zou, H and Hastie, T (2005) Regularization and variable selection via the elastic net. Journal of the Royal Statistical Society, Series B 67, 301–320.CrossRefGoogle Scholar
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