Hostname: page-component-cd9895bd7-8ctnn Total loading time: 0 Render date: 2024-12-27T13:08:13.115Z Has data issue: false hasContentIssue false
  • English
  • Français

Age and birth cohort differences in depression in repeated cross-sectional surveys in England: the National Psychiatric Morbidity Surveys, 1993 to 2007

Published online by Cambridge University Press:  17 February 2012

N. Spiers ,
T. S. Brugha ,
P. Bebbington ,
S. McManus ,
R. Jenkins  and
H. Meltzer
N. Spiers*
Affiliation:
Department of Health Sciences, University of Leicester, UK
T. S. Brugha
Affiliation:
Department of Health Sciences, University of Leicester, UK
P. Bebbington
Affiliation:
Department of Mental Health Sciences, University College London, UK
S. McManus
Affiliation:
National Centre for Social Research, London, UK
R. Jenkins
Affiliation:
Institute of Psychiatry, King's College London, UK
H. Meltzer
Affiliation:
Department of Health Sciences, University of Leicester, UK
*
*Address for correspondence: Dr N. Spiers, Department of Health Sciences, University of Leicester, 22–28 Princess Rd West, Leicester LE1 6TP, UK. (Email: [email protected])
Get access Rights & Permissions [Opens in a new window]

Abstract

Background

The National Psychiatric Morbidity Survey (NPMS) programme was partly designed to monitor trends in mental disorders, including depression, with comparable data spanning 1993 to 2007. Findings already published from this programme suggest that concerns about increasing prevalence of common mental disorders (CMDs) may be unfounded. This article focuses on depression and tests the hypothesis that successive birth cohorts experience the same prevalence of depression as they age.

Method

We carried out a pseudo-cohort analysis of a sequence of three cross-sectional surveys of the English household population using identical diagnostic instruments. The main outcome was ICD-10 depressive episode or disorder. Secondary outcomes were the depression subscales of the Clinical Interview Schedule – Revised (CIS-R).

Results

There were 8670, 6977 and 6815 participants in 1993, 2000 and 2007 respectively. In men, the prevalence of depression increased between cohorts born in 1943–1949 and 1950–1956 [odds ratio (OR) 2.5, 95% confidence interval (CI) 1.4–4.2], then remained relatively stable across subsequent cohorts. In women, there was limited evidence of change in prevalence of depression. Women born in 1957–1963, surveyed aged 44–50 years in 2007, had exceptionally high prevalence. It is not clear whether this represents a trend or a quirk of sampling.

Conclusions

There is no evidence of an increase in the prevalence of depression in male cohorts born since 1950. In women, there is limited evidence of increased prevalence. Demand for mental health services may stabilize or even fall for men.

Keywords

Depressive episodeepidemiologyprevalencepseudo-cohort analysis
Type
Original Articles
Information
Psychological Medicine , Volume 42 , Issue 10 , October 2012 , pp. 2047 - 2055
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

Arroll, B, Elley, CR, Fishman, T, Goodyear-Smith, FA, Kenealy, T, Blashki, G, Kerse, N, Macgillivray, S (2009). Antidepressants versus placebo for depression in primary care. Cochrane Database of Systematic Reviews 3, CD007954.Google Scholar
Baker, RP, Bradburn, NM, Johnson, RA (1995). Computer-assisted personal interviewing: an experimental evaluation of data quality and cost. Journal of Official Statistics 11, 413–431.Google Scholar
Bebbington, P, Brugha, T, Meltzer, H, Farrell, M, Ceresa, C, Jenkins, R, Lewis, G (2000 a). Psychiatric disorder and dysfunction in the UK National Survey of Psychiatric Morbidity. Social Psychiatry and Psychiatric Epidemiology 35, 191–197.CrossRefGoogle ScholarPubMed
Bebbington, P, Brugha, T, Meltzer, H, Jenkins, R, Ceresa, C, Farrell, M, Lewis, G (2000 b). Neurotic disorders and the receipt of psychiatric treatment. Psychological Medicine 30, 1369–1376.CrossRefGoogle ScholarPubMed
Blazer, DG, Hybels, CF (2005). The origins of depression in later life. Psychological Medicine 35, 1241–1252.CrossRefGoogle ScholarPubMed
Brugha, TS, Bebbington, PE, Singleton, N, Melzer, D, Jenkins, R, Lewis, G, Farrell, M, Bhugra, D, Lee, A, Meltzer, H (2004). Trends in service use and treatment for mental disorders in adults throughout Great Britain. British Journal of Psychiatry 185, 378–384.CrossRefGoogle ScholarPubMed
Colman, I, Ataullahjan, A (2010). Life course perspectives on the epidemiology of depression. Candaian Journal of Psychiatry 55, 622–632.CrossRefGoogle ScholarPubMed
Compton, WM, Conway, KP, Stinson, FS, Grant, BF (2006). Changes in the prevalence of major depression and comorbid substance use disorders in the United States between 1991–1992 and 2001–2002. American Journal of Psychiatry 163, 2141–2147.CrossRefGoogle ScholarPubMed
De Winter, AF, Oldehinkel, AJ, Veenstra, R, Brunnekreef, JA, Verhulst, FC, Ormel, J (2005). Evaluation of non-response bias in mental health determinants and outcomes in a large sample of pre-adolescents. European Journal of Epidemiology 20, 173–181.CrossRefGoogle Scholar
Fichter, MM, Quadfleig, N, Fischer, UC, Kohlboeck, G (2010). Twenty-five-year course and outcome in anxiety and depression in the Upper Bavarian Longitudinal Community Study. Acta Psychiatrica Scandinavica 122, 75–85.CrossRefGoogle ScholarPubMed
Hurry, J, Sturt, E (1981). Social performance in a population sample: relation to psychiatric symptoms. In What is a Case? (ed. Wing, J. K., Bebbington, P. and Robins, L. N.), pp. 202–213. Grant McIntyre: London.Google Scholar
Jenkins, R, Meltzer, H (1995). The National Survey of Psychiatric Morbidity in Great Britain. Social Psychiatry and Psychiatric Epidemiology 30, 1–4.CrossRefGoogle ScholarPubMed
Jenkins, R, Meltzer, H, Bebbington, P, Brugha, T, Farrell, M, McManus, S, Singleton, N (2009). The British Mental Health Survey Programme: achievements and latest findings. Social Psychiatry and Psychiatric Epidemiology 44, 899–904.CrossRefGoogle ScholarPubMed
Kessler, R, Berglund, PO, Demler, O, Jin, R, Koretz, D, Merikangas, KR, Rush, J, 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 Associaton 289, 3095–3105.CrossRefGoogle ScholarPubMed
Kessler, RC, Demler, O, Frank, RG, Olfson, M, Pincus, HA, Walters, EE, Wang, P, Wells, KB, Zaslavskt, AM (2005). Prevalence and treatment of mental disorders, 1990 to 2003. New England Journal of Medicine 352, 2515–2523.CrossRefGoogle ScholarPubMed
Keyes, KM, Utz, RL, Robinson, W, Guohua, L (2010). What is a cohort effect? Comparison of three statistical methods for modelling cohort effects in obesity prevalence in the United States, 1971–2006. Social Science and Medicine 10, 1100–1108.CrossRefGoogle Scholar
Klermann, GL, Weismann, MM (1989). Increasing rates of depression. Journal of the American Medical Association 261, 2229–2235.CrossRefGoogle Scholar
Korkeila, K, Suominen, S, Ahvenainen, J, Ojanlatva, A, Rautava, P, Helenius, H, Koskenvuo, M (2001). Non-response and related factors in a nation-wide health survey. European Journal of Epidemiology 17, 983–1057.CrossRefGoogle Scholar
Lewis, G, Pelosi, AJ, Araya, A, Dunn, G (1992). Measuring psychiatric disorder in the community: a standard assessment for use by lay interviewers. Psychological Medicine 22, 465–486.CrossRefGoogle ScholarPubMed
Marcus, SC, Olfson, M (2010). National trends in the treatment for depression from 1998 to 2007. Archives of General Psychiatry 67, 1265–1273.CrossRefGoogle ScholarPubMed
McManus, S, Meltzer, H, Brugha, T, Bebbington, P, Jenkins, R (2009). Adult Psychiatric Morbidity in England, 2007: Results of a Household Survey. The NHS Information Centre for Health and Social Care: Leeds.Google Scholar
Meltzer, H, Bebbington, P, Brugha, T, Farrell, M, Jenkins, R, Lewis, G (2000). The reluctance to seek treatment for neurotic disorders. Journal of Mental Health 9, 319–327.CrossRefGoogle Scholar
Meltzer, H, Gill, B, Petticrew, M, Hinds, K (1995). OPCS Surveys of Psychiatric Morbidity in Great Britain, Report 1: The Prevalence of Psychiatric Morbidity Among Adults Living in Private Households. HMSO: London.Google Scholar
Moore, M, Yuen, H-M, Dunn, N, Mullee, MA, Maskell, J, Kendrick, T (2009). Explaining the rise in antidepressant prescribing: a descriptive study using the General Practice Research Database. British Medical Journal 339, b3999.CrossRefGoogle ScholarPubMed
Munoz-Arroyo, R, Sutton, M, Morrison, J (2006). Exploring potential explanations for the increase in antidepressant prescribing in Scotland using secondary analyses of routine data. British Journal of General Practice 56, 423–428.Google ScholarPubMed
Murphy, JM, Gilman, SE, Lesage, A, Horton, NJ, Rasic, D, Trinh, NH, Alamiri, B, Sobol, AM, Fava, M, Smoller, JW (2010). Time trends in mortality associated with depression: findings from the Stirling County Study. Canadian Journal of Psychiatry 55, 776–783.CrossRefGoogle ScholarPubMed
NICE (2010). Depression: The Treatment and Management of Depression in Adults (update). National Institute for Health and Clinical Excellence (NICE) clinical guidelines CG90 (www.nice.org.uk/CG90). Accessed 15 April 2011.Google Scholar
Patten, SB, Bilsker, D, Goldner, E (2008). The evolving understanding of major depression epidemiology: implications for practice and policy. Canadian Journal of Psychiatry 53, 689–695.CrossRefGoogle ScholarPubMed
Patten, SB, Wang, JL, Williams, JV, Lavorato, DH, Khaled, SM, Bulloch, AG (2010). Predictors of the longitudinal course of major depression in a Canadian population sample. Canadian Journal of Psychiatry 55, 669–676.CrossRefGoogle Scholar
Rait, G, Walters, K, Griffin, M, Buszewicz, M, Petersen, I, Nazareth, I (2009). Recent trends in the incidence of recorded depression in primary care. British Journal of Psychiatry 195, 520–524.CrossRefGoogle ScholarPubMed
Rice, NE, Lang, IA, Henley, W, Melzer, D (2010). Baby boomers nearing retirement: the healthiest generation? Rejuvenation Research 13, 105–114.CrossRefGoogle ScholarPubMed
Rix, S, Paykel, ES, Lelliott, P, Tylee, A, Freeling, P, Gask, L, Hart, D (1999). Impact of a national campaign on GP education: an evaluation of the Defeat Depression Campaign. British Journal of General Practice 49, 99–102.Google ScholarPubMed
Singleton, N, Bumpstead, R, O'Brien, M, Lee, A, Meltzer, H (2000). Psychiatric Morbidity Among Adults Living in Private Households. The Stationery Office: London.Google Scholar
Smith, HL (2008). Advances in age-period-cohort analysis. Sociological Methods and Research 36, 287–296.CrossRefGoogle Scholar
Sogaard, AJ, Selmer, R, Bjertness, E, Thelle, D (2004). The Oslo Health Study: the impact of self-selection in a large, population-based survey. International Journal for Equity in Health 3, 3.CrossRefGoogle Scholar
Spiers, N, Bebbington, P, McManus, S, Brugha, TS, Jenkins, R, Meltzer, H (2011). Age and birth cohort differences in the prevalence of common mental disorder in England: National Psychiatric Morbidity Surveys 1993–2007. British Journal of Psychiatry 198, 479–484.CrossRefGoogle ScholarPubMed
Vuorilehto, MS, Melartin, TK, Isometsä, ET (2009). Course and outcome of depressive disorders in primary care: a prospective 18-month study. Psychological Medicine 39, 1697–1707.CrossRefGoogle ScholarPubMed
WHO (1992). The ICD-10 Classification of Mental and Behavioural Disorders: Clinical Descriptions and Diagnostic Guidelines. World Health Organization: Geneva.Google Scholar
Young, AS, Klap, R, Shoai, R, Wells, KB (2008). Persistent depression and anxiety in the United States: prevalence and quality of care. Psychiatric Services 59, 1391–1398.CrossRefGoogle ScholarPubMed