Hostname: page-component-78c5997874-4rdpn Total loading time: 0 Render date: 2024-11-13T01:54:00.276Z Has data issue: false hasContentIssue false

Lifetime prevalence and co-morbidity of externalizing disorders and depression in prospective assessment

Published online by Cambridge University Press:  16 April 2013

N. R. Hamdi*
Affiliation:
Department of Psychology, University of Minnesota, Minneapolis, MN, USA
W. G. Iacono
Affiliation:
Department of Psychology, University of Minnesota, Minneapolis, MN, USA
*
* Address for correspondence: N. R. Hamdi, S462 Elliott Hall, Department of Psychology, University of Minnesota, 75 East River Road, Minneapolis, MN 55455, USA.

Abstract

Background

Epidemiological research is believed to underestimate the lifetime prevalence of mental illness due to recall failure and a lack of rapport between researchers and participants.

Method

In this prospective study, we examined lifetime prevalence and co-morbidity rates of substance use disorders, antisocial personality disorder (ASPD) and major depressive disorder (MDD) in a representative, statewide Minnesota sample (n = 1252) assessed four times between the ages of 17 and 29 years with very low attrition.

Results

Lifetime prevalence rates of all disorders more than doubled between the ages of 17 and 29 years in both men and women, and our prospective rates at the age of 29 years were consistently higher than rates from leading epidemiological surveys. Although there was some variation, the general trend was for lifetime co-morbidity to increase between the ages of 17 and 29 years, and this trend was significant for MDD–alcohol dependence, MDD–nicotine dependence, and ASPD–nicotine dependence.

Conclusions

Overall, our results show that emerging adulthood is a high-risk period for the development of mental illness, with increases in the lifetime prevalence and co-morbidity of mental disorders during this time. More than a quarter of individuals had met criteria for MDD and over a fifth had experienced alcohol dependence by the age of 29 years, indicating that mental illness is more common than is estimated in cross-sectional mental health surveys. These findings have important implications for the measurement of economic burden, resource allocation toward mental health services and research, advocacy organizations for the mentally ill, and etiological theories of mental disorders.

Type
Original Articles
Copyright
Copyright © Cambridge University Press 2013 

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

Angst, J, Gamma, A, Neuenschwander, M, Ajdacic-Gross, V, Eich, D, Rossler, W, Merikangas, KR (2005). Prevalence of mental disorders in the Zurich Cohort Study: a twenty year prospective study. Epidemiologia e Psichiatria Sociale 14, 6876.CrossRefGoogle ScholarPubMed
APA (1987). Diagnostic and Statistical Manual of Mental Disorders, 3rd edn, revised. American Psychiatric Association: Washington, DC.Google Scholar
APA (1994). Diagnostic and Statistical Manual of Mental Disorders, 4th edn, revised. Washington, DC: American Psychiatric Association.Google Scholar
Breslau, N, Novak, SP, Kessler, RC (2004). Daily smoking and the subsequent onset of psychiatric disorders. Psychological Medicine 34, 323333.CrossRefGoogle ScholarPubMed
Compton, WM, Thomas, YF, Stinson, FS, Grant, BF (2007). Prevalence, correlates, disability, and comorbidity of DSM-IV drug abuse and dependence in the United States: results from the National Epidemiologic Survey on Alcohol and Related Conditions. Archives of General Psychiatry 64, 566576.CrossRefGoogle ScholarPubMed
Copeland, W, Shanahan, L, Costello, EJ, Angold, A (2011). Cumulative prevalence of psychiatric disorders by young adulthood: a prospective cohort analysis from the Great Smoky Mountains Study. Journal of the American Academy of Child and Adolescent Psychiatry 50, 252261.CrossRefGoogle ScholarPubMed
Galambos, NL, Barker, ET, Krahn, HJ (2006). Depression, self-esteem, and anger in emerging adulthood: seven-year trajectories. Developmental Psychology 42, 350365.CrossRefGoogle ScholarPubMed
Hasin, DS, Stinson, FS, Grant, BF (2007). Prevalence, correlates, disability and comorbidity of DSM-IV alcohol abuse and dependence in the United States: results from the National Epidemiologic Survey on Alcohol and Related Conditions. Archives of General Psychiatry 64, 830842.CrossRefGoogle ScholarPubMed
Holdcraft, LC, Iacono, WG (2004). Cross-generational effects on gender differences in psychoactive drug abuse and dependence. Drug and Alcohol Dependence 74, 147158.CrossRefGoogle ScholarPubMed
Iacono, WG, Carlson, SR, Taylor, J, Elkins, IJ, McGue, M (1999). Behavioral disinhibition and the development of substance-use disorders: findings from the Minnesota Twin Family Study. Development and Psychopathology 11, 869900.CrossRefGoogle ScholarPubMed
Iacono, WG, McGue, M (2002). Minnesota Twin Family Study. Twin Research 5, 482487.CrossRefGoogle ScholarPubMed
Kendler, KS, Martin, NG, Heath, AC, Eaves, LJ (1995). Self-report psychiatric symptoms in twins and their nontwin relatives: are twins different? American Journal of Medical Genetics 60, 588591.CrossRefGoogle ScholarPubMed
Kessler, RC, Berglund, P, Chiu, WT, Demler, O, Heeringa, S, Hiripi, E, Pennell, BE, Walters, EE, Zaslavsky, A, Zheng, H (2004). The US National Comorbidity Survey Replication (NCS-R): design and field procedures. International Journal of Methods in Psychiatric Research 13, 6992.CrossRefGoogle ScholarPubMed
Kessler, RC, Berglund, P, Demler, O, Jin, R, Merikangas, KR, Walters, EE (2005). Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the National Comorbidity Survey Replication. Archives of General Psychiatry 62, 593602.CrossRefGoogle ScholarPubMed
Kessler, RC, McGonagle, KA, Zhao, S, Nelson, CB, Hughes, M, Eshleman, S, Wittchen, HU, Kendler, KS (1994). Lifetime and 12-month prevalence of DSM-III-R psychiatric disorders in the United States: results from the National Comorbidity Study. Archives of General Psychiatry 51, 819.CrossRefGoogle Scholar
King-Kallimanis, B, Gum, AM, Kohn, R (2009). Comorbidity of depressive and anxiety disorders for older Americans in the National Comorbidity Survey-Replication. American Journal of Geriatric Psychiatry 17, 782792.CrossRefGoogle ScholarPubMed
Liang, K-Y, Zeger, SL (1986). Longitudinal data analysis using generalized linear models. Biometrika 73, 1322.CrossRefGoogle Scholar
Merikangas, KR (2011). What is a case? New lessons from the Great Smoky Mountains Study. Journal of the American Academy of Child and Adolescent Psychiatry 50, 213215.CrossRefGoogle ScholarPubMed
Moffitt, TE, Caspi, A, Taylor, A, Kokaua, J, Milne, BJ, Polanczyk, G, Poulton, R (2010). How common are common mental disorders? Evidence that lifetime prevalence rates are doubled by prospective versus retrospective ascertainment. Psychological Medicine 40, 899909.CrossRefGoogle ScholarPubMed
Murray, CJL, Vos, T, Lozano, R, Naghavi, M, Flaxman, AD, Michaud, C, et al. (2012). Disability-adjusted life years (DALYs) for 291 diseases and injuries in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet 380, 21972223.CrossRefGoogle ScholarPubMed
Regier, DA, Myers, JK, Kramer, M, Robins, LN, Blazer, DG, Hough, RL, Eaton, WW, Locke, BZ (1984). The NIMH Epidemiologic Catchment Area program. Historical context, major objectives, and study population characteristics. Archives of General Psychiatry 41, 934941.CrossRefGoogle ScholarPubMed
Reich, W, Welner, Z (1988). Diagnostic Interview for Children and Adolescents – Revised (DICA-R): DSM-III-R Version. Washington University: St Louis, MO.Google Scholar
Robins, LN, Cottler, LB, Babor, T (1987). WHO/ADAMHA Composite International Diagnostic Interview – Substance Abuse Module (SAM). WHO/ADAMHA: St Louis, MO.Google Scholar
Robins, LN, Cottler, L, Bucholz, KK, Compton, W (1995). Diagnostic Interview Schedule for DSM-IV. Washington University School of Medicine: St Louis, MO.Google Scholar
Robins, LN, Helzer, JE, Cottler, L, Goldring, E (1989). Diagnostic Interview Schedule, version III-R. Washington University School of Medicine: St Louis, MO.Google Scholar
Robins, LN, Wing, J, Wittchen, HU, Helzer, JE, Babor, TF, Burke, J, Farmer, A, Jablenski, A, Pickens, R, Regier, DA, Sartorius, N, Towle, LH (1988). The Composite International Diagnostic Interview: an epidemiologic instrument suitable for use in conjunction with different diagnostic systems and in different cultures. Archives of General Psychiatry 45, 10691077.CrossRefGoogle ScholarPubMed
Semple, DM, McIntosh, AM, Lawrie, SM (2005). Cannabis as a risk factor for psychosis: systematic review. Journal of Psychopharmacology 19, 187194.CrossRefGoogle ScholarPubMed
Simon, GE, VonKorff, M (1995). Recall of psychiatric history in cross-sectional surveys: implications for epidemiologic research. Epidemiologic Reviews 17, 221227.CrossRefGoogle ScholarPubMed
Spitzer, RL, Williams, JBW, Gibbon, M (1987). Structured Clinical Interview for DSM-III-R (SCID). New York State Psychiatric Institute, Biometrics Research: New York.Google Scholar
Swendsen, J, Conway, KP, Degenhardt, L, Glantz, M, Jin, R, Merikangas, KR, Sampson, N, Kessler, RC (2010). Mental disorders as risk factors for substance use, abuse and dependence: results from the 10-year follow-up of the National Comorbidity Survey. Addiction 105, 11171128.CrossRefGoogle ScholarPubMed
Tanner, JL, Reinherz, HZ, Beardslee, WR, Fitzmaurice, GM, Leis, JA, Berger, SR (2007). Change in prevalence of psychiatric disorders from ages 21 to 30 in a community sample. Journal of Nervous and Mental Disease 195, 298306.CrossRefGoogle Scholar