Hostname: page-component-5d59c44645-jqctd Total loading time: 0 Render date: 2024-03-03T19:22:56.263Z Has data issue: false hasContentIssue false

Lifetime co-morbidity of DSM-IV disorders in the US National Comorbidity Survey Replication Adolescent Supplement (NCS-A)

Published online by Cambridge University Press:  25 January 2012

R. C. Kessler*
Affiliation:
Department of Health Care Policy, Harvard Medical School, Boston, MA, USA
S. Avenevoli
Affiliation:
Division of Developmental Translational Research, National Institute of Mental Health, Bethesda, MD, USA
K. A. McLaughlin
Affiliation:
Division of General Pediatrics, Children's Hospital Boston, Harvard Medical School, Boston, MA, USA
J. Greif Green
Affiliation:
School of Education, Boston University, Boston, MA, USA
M. D. Lakoma
Affiliation:
Department of Population Medicine, Harvard Medical School, Boston, MA, USA
M. Petukhova
Affiliation:
Department of Health Care Policy, Harvard Medical School, Boston, MA, USA
D. S. Pine
Affiliation:
The Mood and Anxiety Disorders Program, National Institute of Mental Health, Bethesda, MD, USA
N. A. Sampson
Affiliation:
Department of Health Care Policy, Harvard Medical School, Boston, MA, USA
A. M. Zaslavsky
Affiliation:
Department of Health Care Policy, Harvard Medical School, Boston, MA, USA
K. Ries Merikangas
Affiliation:
Division of Intramural Research Programs, National Institute of Mental Health, Bethesda, MD, USA
*
*Address for correspondence: R. C. Kessler, Ph.D., Department of Health Care Policy, Harvard Medical School, 180 Longwood Avenue, Boston, MA 02115, USA. (Email: ncs@hcp.med.harvard.edu)

Abstract

Background

Research on the structure of co-morbidity among common mental disorders has largely focused on current prevalence rather than on the development of co-morbidity. This report presents preliminary results of the latter type of analysis based on the US National Comorbidity Survey Replication Adolescent Supplement (NCS-A).

Method

A national survey was carried out of adolescent mental disorders. DSM-IV diagnoses were based on the Composite International Diagnostic Interview (CIDI) administered to adolescents and questionnaires self-administered to parents. Factor analysis examined co-morbidity among 15 lifetime DSM-IV disorders. Discrete-time survival analysis was used to predict first onset of each disorder from information about prior history of the other 14 disorders.

Results

Factor analysis found four factors representing fear, distress, behavior and substance disorders. Associations of temporally primary disorders with the subsequent onset of other disorders, dated using retrospective age-of-onset (AOO) reports, were almost entirely positive. Within-class associations (e.g. distress disorders predicting subsequent onset of other distress disorders) were more consistently significant (63.2%) than between-class associations (33.0%). Strength of associations decreased as co-morbidity among disorders increased. The percentage of lifetime disorders explained (in a predictive rather than a causal sense) by temporally prior disorders was in the range 3.7–6.9% for earliest-onset disorders [specific phobia and attention deficit hyperactivity disorder (ADHD)] and much higher (23.1–64.3%) for later-onset disorders. Fear disorders were the strongest predictors of most other subsequent disorders.

Conclusions

Adolescent mental disorders are highly co-morbid. The strong associations of temporally primary fear disorders with many other later-onset disorders suggest that fear disorders might be promising targets for early interventions.

Type
Original Articles
Copyright
Copyright © Cambridge University Press 2012

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

Alonso, J, Vilagut, G, Chatterji, S, Heeringa, S, Schoenbaum, M, Bedirhan Üstün, T, Rojas-Farreras, S, Angermeyer, M, Bromet, E, Bruffaerts, R, de Girolamo, G, Gureje, O, Haro, JM, Karam, AN, Kovess, V, Levinson, D, Liu, Z, Medina-Mora, ME, Ormel, J, Posada-Villa, J, Uda, H, Kessler, RC (2011). Including information about co-morbidity in estimates of disease burden: results from the World Health Organization World Mental Health Surveys. Psychological Medicine 41, 873886.Google Scholar
Angold, A, Costello, EJ, Erkanli, A (1999). Comorbidity. Journal of Child Psychology and Psychiatry 40, 5787.Google Scholar
Beesdo, K, Bittner, A, Pine, DS, Stein, MB, Hofler, M, Lieb, R, Wittchen, HU (2007). Incidence of social anxiety disorder and the consistent risk for secondary depression in the first three decades of life. Archives of General Psychiatry 64, 903912.Google Scholar
Beesdo, K, Pine, DS, Lieb, R, Wittchen, HU (2010). Incidence and risk patterns of anxiety and depressive disorders and categorization of generalized anxiety disorder. Archives of General Psychiatry 67, 4757.Google Scholar
Braaten, EB, Biederman, J, DiMauro, A, Mick, E, Monuteaux, MC, Muehl, K, Faraone, SV (2001). Methodological complexities in the diagnosis of major depression in youth: an analysis of mother and youth self-reports. Journal of Child and Adolescent Psychopharmacology 11, 395407.Google Scholar
Burnham, KP, Anderson, DR (2002). Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach, 2nd edn. Springer-Verlag: New York.Google Scholar
Copeland, WE, Shanahan, L, Costello, EJ, Angold, A (2009). Childhood and adolescent psychiatric disorders as predictors of young adult disorders. Archives of General Psychiatry 66, 764772.Google Scholar
Costello, EJ, Angold, A, Burns, BJ, Stangl, DK, Tweed, DL, Erkanli, A, Worthman, CM (1996). The Great Smoky Mountains Study of Youth. Goals, design, methods, and the prevalence of DSM-III-R disorders. Archives of General Psychiatry 53, 11291136.Google Scholar
Costello, EJ, Erkanli, A, Federman, E, Angold, A (1999). Development of psychiatric comorbidity with substance abuse in adolescents: effects of timing and sex. Journal of Clinical Child Psychology 28, 298311.Google Scholar
Costello, EJ, Mustillo, S, Erkanli, A, Keeler, G, Angold, A (2003). Prevalence and development of psychiatric disorders in childhood and adolescence. Archives of General Psychiatry 60, 837844.Google Scholar
Elkins, IJ, McGue, M, Iacono, WG (2007). Prospective effects of attention-deficit/hyperactivity disorder, conduct disorder, and sex on adolescent substance use and abuse. Archives of General Psychiatry 64, 11451152.Google Scholar
Fergusson, DM, Horwood, LJ, Lynskey, MT (1993). Prevalence and comorbidity of DSM-III-R diagnoses in a birth cohort of 15 year olds. Journal of the American Academy of Child and Adolescent Psychiatry 32, 11271134.Google Scholar
Fergusson, DM, Horwood, LJ, Lynskey, MT (1994). The comorbidities of adolescent problem behaviors: a latent class model. Journal of Abnormal Child Psychology 22, 339354.Google Scholar
Fergusson, DM, Horwood, LJ, Ridder, EM (2007). Conduct and attentional problems in childhood and adolescence and later substance use, abuse and dependence: results of a 25-year longitudinal study. Drug and Alcohol Dependence 88 (Suppl. 1), S14S26.Google Scholar
Godart, N, Berthoz, S, Rein, Z, Perdereau, F, Lang, F, Venisse, JL, Halfon, O, Bizouard, P, Loas, G, Corcos, M, Jeammet, P, Flament, M, Curt, F (2006). Does the frequency of anxiety and depressive disorders differ between diagnostic subtypes of anorexia nervosa and bulimia? International Journal of Eating Disorders 39, 772778.Google Scholar
Gros, DF, Antony, MM (2006). The assessment and treatment of specific phobias: a review. Current Psychiatry Reports 8, 298303.Google Scholar
Halli, SS, Rao, KV, Halli, SS (1992). Advanced Techniques of Population Analysis. Plenum: New York.Google Scholar
Hamm, AO (2009). Specific phobias. Psychiatric Clinics of North America 32, 577591.Google Scholar
Johnston, C, Murray, C (2003). Incremental validity in the psychological assessment of children and adolescents. Psychological Assessment 15, 496507.Google Scholar
Kaufman, J, Birmaher, B, Brent, D, Rao, U, Flynn, C, Moreci, P, Williamson, D, Ryan, N (1997). Schedule for Affective Disorders and Schizophrenia for School-Age Children – Present and Lifetime Version (K-SADS-PL): initial reliability and validity data. Journal of the American Academy of Child and Adolescent Psychiatry 36, 980988.Google Scholar
Kendler, KS, Prescott, CA, Myers, J, Neale, MC (2003). The structure of genetic and environmental risk factors for common psychiatric and substance use disorders in men and women. Archives of General Psychiatry 60, 929937.Google Scholar
Kendler, KS, Schmitt, E, Aggen, SH, Prescott, CA (2008). Genetic and environmental influences on alcohol, caffeine, cannabis, and nicotine use from early adolescence to middle adulthood. Archives of General Psychiatry 65, 674682.Google Scholar
Kessler, RC, Amminger, GP, Aguilar-Gaxiola, S, Alonso, J, Lee, S, Üstün, TB (2007). Age of onset of mental disorders: a review of recent literature. Current Opinion in Psychiatry 20, 359364.Google Scholar
Kessler, RC, Avenevoli, S, Costello, EJ, Green, JG, Gruber, MJ, Heeringa, S, Merikangas, KR, Pennell, BE, Sampson, NA, Zaslavsky, AM (2009 a). Design and field procedures in the US National Comorbidity Survey Replication Adolescent Supplement (NCS-A). International Journal of Methods in Psychiatric Research 18, 6983.Google Scholar
Kessler, RC, Avenevoli, S, Costello, EJ, Green, JG, Gruber, MJ, Heeringa, S, Merikangas, KR, Pennell, BE, Sampson, NA, Zaslavsky, AM (2009 b). National Comorbidity Survey Replication Adolescent Supplement (NCS-A): II. Overview and design. Journal of the American Academy of Child and Adolescent Psychiatry 48, 380385.Google Scholar
Kessler, RC, Avenevoli, S, Green, J, Gruber, MJ, Guyer, M, He, Y, Jin, R, Kaufman, J, Sampson, NA, Zaslavsky, AM (2009 c). National Comorbidity Survey Replication Adolescent Supplement (NCS-A): III. Concordance of DSM-IV/CIDI diagnoses with clinical reassessments. Journal of the American Academy of Child and Adolescent Psychiatry 48, 386399.Google Scholar
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.Google Scholar
Kessler, RC, Little, RJ, Groves, RM (1995). Advances in strategies for minimizing and adjusting for survey nonresponse. Epidemiologic Reviews 17, 192204.Google Scholar
Kessler, RC, Merikangas, KR (2004). The National Comorbidity Survey Replication (NCS-R): background and aims. International Journal of Methods in Psychiatric Research 13, 6068.Google Scholar
Kessler, RC, Ormel, J, Petukhova, M, McLaughlin, KA, Green, JG, Russo, LJ, Stein, DJ, Zaslavsky, AM, Aguilar-Gaxiola, S, Alonso, J, Andrade, L, Benjet, C, de Girolamo, G, de Graaf, R, Demyttenaere, K, Fayyad, J, Haro, JM, Hu, C, Karam, A, Lee, S, Lepine, JP, Matchsinger, H, Mihaescu-Pintia, C, Posada-Villa, J, Sagar, R, Ustun, TB (2011). Development of lifetime comorbidity in the World Health Organization world mental health surveys. Archives of General Psychiatry 68, 90–100.Google Scholar
Kim-Cohen, J, Caspi, A, Moffitt, TE, Harrington, H, Milne, BJ, Poulton, R (2003). Prior juvenile diagnoses in adults with mental disorder: developmental follow-back of a prospective-longitudinal cohort. Archives of General Psychiatry 60, 709717.Google Scholar
Knauper, B, Cannell, CF, Schwarz, N, Bruce, ML, Kessler, RC (1999). Improving the accuracy of major depression age of onset reports in the US National Comorbidity Survey. International Journal of Methods in Psychiatric Research 8, 3948.Google Scholar
Kraemer, HC, Kazdin, AE, Offord, DR, Kessler, RC, Jensen, PS, Kupfer, DJ (1997). Coming to terms with the terms of risk. Archives of General Psychiatry 54, 337343.Google Scholar
Krueger, RF (1999). The structure of common mental disorders. Archives of General Psychiatry 56, 921926.Google Scholar
Lahey, BB, Applegate, B, Waldman, ID, Loft, JD, Hankin, BL, Rick, J (2004). The structure of child and adolescent psychopathology: generating new hypotheses. Journal of Abnormal Psychology 113, 358385.Google Scholar
Lewinsohn, PM, Gotlib, IH, Seeley, JR (1995). Adolescent psychopathology: IV. Specificity of psychosocial risk factors for depression and substance abuse in older adolescents. Journal of the American Academy of Child and Adolescent Psychiatry 34, 12211229.Google Scholar
Lieb, R, Isensee, B, von Sydow, K, Wittchen, HU (2000). The Early Developmental Stages of Psychopathology Study (EDSP): a methodological update. European Addiction Research 6, 170182.Google Scholar
Mantel, N, Haenszel, W (1988). Statistical aspects of the analysis of data from retrospective studies of disease. In The Challenge of Epidemiology: Issues and Selected Readings (ed. Buck, C., Liopis, A., Najera, E. and Terris, M.), pp. 533553. Pan American Health Organization (PAHO): Washington, DC.Google Scholar
Marmorstein, NR, von Ranson, KM, Iacono, WG, Succop, PA (2007). Longitudinal associations between externalizing behavior and dysfunctional eating attitudes and behaviors: a community-based study. Journal of Clinical Child and Adolescent Psychology 36, 8794.Google Scholar
McGee, R, Feehan, M, Williams, S, Anderson, J (1992). DSM-III disorders from age 11 to age 15 years. Journal of the American Academy of Child and Adolescent Psychiatry 31, 5059.Google Scholar
Merikangas, K, Avenevoli, S, Costello, J, Koretz, D, Kessler, RC (2009). National Comorbidity Survey Replication Adolescent Supplement (NCS-A): I. Background and measures. Journal of the American Academy of Child and Adolescent Psychiatry 48, 367369.Google Scholar
Merikangas, KR, He, J, Burstein, M, Swanson, SA, Avenevoli, S, Cui, L, Benjet, C, Georgiades, K, Swendsen, J (2010). Lifetime prevalence of mental disorders in U.S. adolescents: results from the National Comorbidity Survey – Adolescent Supplement (NCS-A). Journal of the American Academy of Child and Adolescent Psychiatry 49, 980989.Google Scholar
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.Google Scholar
Moses, EB, Barlow, DH (2006). A new unified approach for emotional disorders based on emotion science. Current Directions in Psychological Science 15, 146150.Google Scholar
Newman, DL, Moffit, TE, Caspi, A, Magdol, L, Silva, PA, Stanton, WR (1996). Psychiatric disorder in a birth cohort of young adults: prevalence, comorbidity, clinical significance and new case incidence from ages 11 to 21. Journal of Consulting and Clinical Psychology 64, 552562.Google Scholar
Olino, TM, Klein, DN, Lewinsohn, PM, Rohde, P, Seeley, JR (2010). Latent trajectory classes of depressive and anxiety disorders from adolescence to adulthood: descriptions of classes and associations with risk factors. Comprehensive Psychiatry 51, 224235.Google Scholar
Patten, SB (2009). Accumulation of major depressive episodes over time in a prospective study indicates that retrospectively assessed lifetime prevalence estimates are too low. BMC Psychiatry 9, 19.Google Scholar
Pine, DS, Cohen, P, Gurley, D, Brook, J, Ma, Y (1998). The risk for early-adulthood anxiety and depressive disorders in adolescents with anxiety and depressive disorders. Archives of General Psychiatry 55, 5664.Google Scholar
Reinke, WM, Ostrander, R (2008). Heterotyic and homotypic continuity: the moderating effects of age and gender. Journal of Abnormal Child Psychology 36, 11091121.Google Scholar
Shankman, SA, Lewinsohn, PM, Klein, DN, Small, JW, Seeley, JR, Altman, SE (2009). Subthreshold conditions as precursors for full syndrome disorders: a 15-year longitudinal study of multiple diagnostic classes. Journal of Child Psychology and Psychiatry 50, 14851494.Google Scholar
Simon, GE, von Korff, M (1995). Recall of psychiatric history in cross-sectional surveys: implications for epidemiologic research. Epidemiologic Reviews 17, 221227.Google Scholar
Stein, MB, Fuetsch, M, Muller, N, Hofler, M, Lieb, R, Wittchen, HU (2001). Social anxiety disorder and the risk of depression: a prospective community study of adolescents and young adults. Archives of General Psychiatry 58, 251256.Google Scholar
SUDAAN (2002). SUDAAN: Professional Software for Survey Data Analysis, Version 8.0.1. Research Triangle Institute: Research Triangle Park, NC.Google Scholar
Tapert, SF, Baratta, MV, Abrantes, AM, Brown, SA (2002). Attention dysfunction predicts substance involvement in community youths. Journal of the American Academy of Child and Adolescent Psychiatry 41, 680686.Google Scholar
Vollebergh, WA, Iedema, J, Bijl, RV, de Graaf, R, Smit, F, Ormel, J (2001). The structure and stability of common mental disorders: the NEMESIS study. Archives of General Psychiatry 58, 597603.Google Scholar
Watson, D (2005). Rethinking the mood and anxiety disorders: a quantitative hierarchical model for DSM-V. Journal of Abnormal Psychology 114, 522536.Google Scholar
Willett, JB, Singer, JD (1993). Investigating onset, cessation, relapse, and recovery: why you should, and how you can, use discrete-time survival analysis to examine event occurrence. Journal of Consulting and Clinical Psychology 61, 952965.Google Scholar
Wittchen, HU, Perkonigg, A, Lachner, G, Nelson, CB (1998). Early developmental stages of psychopathology study (EDSP): objectives and design. European Addiction Research 4, 1827.Google Scholar