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Depressive symptoms in the Belgian population: disentangling age and cohort effects

  • Marie-Christine BraultEmail author
  • Bart Meuleman
  • Piet Bracke
Original Paper

Abstract

Objective

Although the association between age and depression has been previously demonstrated, uncertainty remains because of the confounding relationship existing between age and cohort. A study by Yang (J Health Soc Behav 48(1):16, 2007) has evidenced important cohort effects and age-by-cohort interactions in depressive symptoms among US citizens. A crucial limitation, however, is that this study confines itself to elderly population. The objective of the present study is to bring further clarification to the association between age, cohort membership and depressive symptoms, by analyzing a sample with a wider age range.

Methods

The Panel Study of Belgian Households is a prospective longitudinal survey, following adults ages 25–74, annually from 1992 to 2002. Missing data were replaced using multiple imputation, allowing for a complete dataset (N = 7,000) at each wave. Respondents were classified into one of five birth cohorts: 1918–1927; 1928–1937; 1938–1947; 1948–1957; 1958–1967. Frequency of depressive symptoms was reported using a modified version of the Health and Daily Living form. Growth curve modeling was used to determine the effect of age and cohort on depression trajectory.

Results

All cohorts differed significantly from one another, with recent cohorts always obtaining the highest mean HDL-depression score. The intensity of depressive symptoms increases linearly with age, but significant age-by-cohorts interactions were detected, indicating that the relationship between age and depression varies across cohorts. No evidence of a WW2 effect was found.

Conclusion

The association between age and depression has to take cohort membership into account. Cohort replacement effects explain the increase in depression in Belgium.

Keywords

Depressive symptoms Age effects Cohort effects Growth curve modelling Belgium 

Notes

Acknowledgments

The first author is thankful to the Fonds québécois de la recherche sur la société et la culture (FQRSC) from which she received a doctoral funding and to the Québec inter-university center for social statistics (QICSS) which allowed her stay at Ghent University and led to the realization of this project.

References

  1. 1.
    Mathers CD, Loncar D (2006) Projections of global mortality and burden of disease from 2002 to 2030. PLoS Med 3(11):2011–2030CrossRefGoogle Scholar
  2. 2.
    Baumeister H, Harter M (2007) Prevalence of mental disorders based on general population surveys. Soc Psychiatry Psychiatr Epidemiol 42(7):537–546PubMedCrossRefGoogle Scholar
  3. 3.
    Wittchen HU, Jacobi F (2005) Size and burden of mental disorders in Europe—a critical review and appraisal of 27 studies. Eur Neuropsychopharmacol 15(4):357–376PubMedCrossRefGoogle Scholar
  4. 4.
    Kessler R, Birnbaum H, Shahly V, Bromet E, Hwang I, McLaughlin K, Sampson N, Andrade L, de Girolamo G, Demyttenaere K (2009) Age differences in the prevalence and co-morbidity of dsm-iv major depressive episodes: results from the who world mental health survey initiative. Depress Anxiety 0:1–14Google Scholar
  5. 5.
    Fombonne E (1994) Increased rates of depression: update of epidemiological findings and analytical problems. Acta Psychiatr Scand 90(3):145–156PubMedCrossRefGoogle Scholar
  6. 6.
    Twenge J, Gentile B, DeWall C, Ma D, Lacefield K, Schurtz D (2010) Birth cohort increases in psychopathology among young Americans, 1938–2007: a cross-temporal meta-analysis of the MMPI. Clin Psychol Rev 30:145–154PubMedCrossRefGoogle Scholar
  7. 7.
    Wauterickx N, Bracke P (2005) Unipolar depression in the belgian population—trends and sex differences in an eight-wave sample. Soc Psychiatry Psychiatr Epidemiol 40(9):691–699PubMedCrossRefGoogle Scholar
  8. 8.
    Riley M (1973) Aging and cohort succession: interpretations and misinterpretations. Public Opin Q 37(1):35–49CrossRefGoogle Scholar
  9. 9.
    Riley M (1987) On the significance of age in sociology. Am Sociol Rev 52(1):1–14CrossRefGoogle Scholar
  10. 10.
    Ryder NB (1965) The cohort as a concept in the study of social-change. Am Sociol Rev 30(6):843–861PubMedCrossRefGoogle Scholar
  11. 11.
    Yang Y (2007) Is old age depressing? Growth trajectories and cohort variations in late-life depression. J Health Soc Behav 48(1):16PubMedCrossRefGoogle Scholar
  12. 12.
    Mirowsky J, Ross C (1992) Age and depression. J Health Soc Behav 33(3):187–205PubMedCrossRefGoogle Scholar
  13. 13.
    Klerman G (1988) The current age of youthful melancholia. Evidence for increase in depression among adolescents and young adults. Br J Psychiatry 152(1):4PubMedCrossRefGoogle Scholar
  14. 14.
    Jorm A (2000) Does old age reduce the risk of anxiety and depression? A review of epidemiological studies across the adult life span. Psychol Med 30(01):11–22PubMedCrossRefGoogle Scholar
  15. 15.
    Jorm A, Windsor T, Dear K, Anstey K, Christensen H, Rodgers B (2005) Age group differences in psychological distress: the role of psychosocial risk factors that vary with age. Psychol Med 35(09):1253–1263PubMedCrossRefGoogle Scholar
  16. 16.
    Kessler R, Birnbaum H, Bromet E, Hwang I, Sampson N, Shahly V (2010) Age differences in major depression: results from the national comorbidity survey replication (ncs-r). Psychol Med 40(02):225–237PubMedCrossRefGoogle Scholar
  17. 17.
    Scott K, Von Korff M, Alonso J, Angermeyer M, Bromet E, Bruffaerts R, de Girolamo G, de Graaf R, Fernandez A, Gureje O (2008) Age patterns in the prevalence of dsm-iv depressive/anxiety disorders with and without physical co-morbidity. Psychol Med 38(11):1659–1669PubMedCrossRefGoogle Scholar
  18. 18.
    Stordal E, Krüger M, Dahl N, Krüger Ø, Mykletun A, Dahl A (2001) Depression in relation to age and gender in the general population: the nord-trøndelag health study (hunt). Acta Psychiatr Scand 104(3):210–216PubMedCrossRefGoogle Scholar
  19. 19.
    Stordal E, Mykletun A, Dahl A (2003) The association between age and depression in the general population: a multivariate examination. Acta Psychiatr Scand 107(2):132–141PubMedCrossRefGoogle Scholar
  20. 20.
    Yang Y, Lee L (2009) Sex and race disparities in health: cohort variations in life course patterns. Soc Forces 87(4):2093–2124CrossRefGoogle Scholar
  21. 21.
    Eckersley R (2006) Is modern western culture a health hazard? Int J Epidemiol 35(2):252PubMedCrossRefGoogle Scholar
  22. 22.
    Murphy J, Laird N, Monson R, Sobol A, Leighton A (2000) Incidence of depression in the stirling county study: historical and comparative perspectives. Psychol Med 30(03):505–514PubMedCrossRefGoogle Scholar
  23. 23.
    Roberts R, Lee E, Roberts C (1991) Changes in prevalence of depressive symptoms in alameda county: age, period, and cohort trends. J Aging Health 3(1):66–86CrossRefGoogle Scholar
  24. 24.
    Bonnewyn A, Bruffaerts R, Vilagut G, Almansa J, Demyttenaere K (2007) Lifetime risk and age-of-onset of mental disorders in the belgian general population. Soc Psychiatry Psychiatr Epidemiol 42(7):522–529PubMedCrossRefGoogle Scholar
  25. 25.
    Klerman G, Weissman MM (1989) Increasing rates of depression. JAMA 261(15):2229–2235PubMedCrossRefGoogle Scholar
  26. 26.
    Kessler R, McGonagle K, Nelson C, Hughes M, Swartz M, Blazer D (1994) Sex and depression in the national comorbidity survey II: cohort effects. J Affect Disord 30(1):15–26PubMedCrossRefGoogle Scholar
  27. 27.
    Lewinsohn PM, Rohde P, Seeley JR, Fischer SA (1993) Age-cohort changes in the lifetime occurrence of depression and other mental-disorders. J Abnorm Psychol 102(1):110–120PubMedCrossRefGoogle Scholar
  28. 28.
    Chen H, Cohen P, Kasen S (2007) Cohort differences in self-rated health: evidence from a three-decade, community-based, longitudinal study of women. Am J Epidemiol 166(4):439–446PubMedCrossRefGoogle Scholar
  29. 29.
    Kasen S, Cohen P, Chen H, Castille D (2003) Depression in adult women: age changes and cohort effects. Am J Public Health 93(12):2061–2066PubMedCrossRefGoogle Scholar
  30. 30.
    Elder GH (1998) The life course as developmental theory. Child Dev 69(1):1–12PubMedGoogle Scholar
  31. 31.
    Gallo JJ, Anthony JC, Muthen BO (1994) Age-differences in the symptoms of depression—a latent trait analysis. J Gerontol 49(6):P251–P264PubMedGoogle Scholar
  32. 32.
    Bracke P, Wauterickx N (2003) Complaints of depression in a representative sample of the belgian population. Arch Pub Health 61(5):223–247Google Scholar
  33. 33.
    Graham JW (2009) Missing data analysis: making it work in the real world. Annu Rev Psychol 60:549–576PubMedCrossRefGoogle Scholar
  34. 34.
    McKnight PE, McKnight KM, Sidani S, Figueredo AJ (2007) Missing data: a gentle introduction. The Guilford Press, New YorkGoogle Scholar
  35. 35.
    Rubin DB (1996) Multiple imputation after 18 + years. J Am Stat Assoc 91(434):473–489Google Scholar
  36. 36.
    Schafer J (1997) Analysis of incomplete multivariate data. Chapman & Hall/CRCGoogle Scholar
  37. 37.
    Graham JW, Olchowski AE, Gilreath TD (2007) How many imputations are really needed? Some practical clarifications of multiple imputation theory. Prev Sci 8(3):206–213PubMedCrossRefGoogle Scholar
  38. 38.
    Verbeke G, Molenberghs G (2000) Linear mixed models for longitudinal data. Springer, New YorkGoogle Scholar
  39. 39.
    Buhi ER, Goodson P, Neilands TB (2008) Out of sight, not out of mind: Strategies for handling missing data. Am J Health Behav 32(1):83–92PubMedCrossRefGoogle Scholar
  40. 40.
    Shrive F, Stuart H, Quan H, Ghali W (2006) Dealing with missing data in a multi-question depression scale: a comparison of imputation methods. BMC Med Res Methodol 6(1):57PubMedCrossRefGoogle Scholar
  41. 41.
    Moos RH, Cronkite RC, Billings AG, Finney JW (1985) Health and daily living form manual, revised version. Social Ecological Laboratory, Veterans Administration and Stanford University Medical Centers, StanfordGoogle Scholar
  42. 42.
    Angst J, Gamma A, Gastpar M, Lepine JP, Mendlewicz J, Tylee A (2002) Gender differences in depression—epidemiological findings from the European DEPRES I and II studies. Eur Arch Psychiatry Clin Neurosci 252(5):201–209PubMedCrossRefGoogle Scholar
  43. 43.
    Bracke P (1996) Geslachtsverschillen in depressief gedrag in een representatieve steekproef van de vlaamse bevolking: De validiteit van een zelf-rapportageschaal. Arch Pub Health 54(7-8):275–300Google Scholar
  44. 44.
    Bracke P (1998) Sex differences in the course of depression: evidence from a longitudinal study of a representative sample of the Belgian population. Soc Psychiatry Psychiatr Epidemiol 33(9):420–429PubMedCrossRefGoogle Scholar
  45. 45.
    Bracke P (2000) The three-year persistence of depressive symptoms in men and women. Soc Sci Med 51(1):51–64PubMedCrossRefGoogle Scholar
  46. 46.
    Schlomer GL, Bauman S, Card NA (2010) Best practices for missing data management in counseling psychology. J Couns Psychol 57(1):1PubMedCrossRefGoogle Scholar
  47. 47.
    Raudenbush SW, Chan WS (1992) Growth curve analysis in accelerated longitudinal designs. J Res Crime Del 29(4):387CrossRefGoogle Scholar
  48. 48.
    Van de Velde S, Bracke P, Levecque K, Meuleman B (2010) Gender differences in depression in 25 European countries after eliminating measurement bias in the CES-D 8. Soc Sci Res 39(3):396–404CrossRefGoogle Scholar
  49. 49.
    Zimmerman F, Katon W (2005) Socioeconomic status, depression disparities, and financial strain: what lies behind the income-depression relationship? Health Econ 14(12):1197–1215PubMedCrossRefGoogle Scholar
  50. 50.
    Raudenbush SW, Bryk AS (2002) Hierarchical linear models: applications and data analysis methods. Advanced quantitative techniques in the social sciences, vol 1, 2nd edn. Sage Publications, Thousand OaksGoogle Scholar
  51. 51.
    Singer J, Willett J (2003) Applied longitudinal data analysis: modeling change and event occurrence. Oxford University Press, USAGoogle Scholar
  52. 52.
    Boyle MH, Willms JD (2001) Multilevel modelling of hierarchical data in developmental studies. J Child Psychol Psychiatry 42(1):141–162PubMedCrossRefGoogle Scholar
  53. 53.
    Twenge J (2000) The age of anxiety? The birth cohort change in anxiety and neuroticism, 1952-1993. J Pers Soc Psychol 79(6):1007–1021PubMedCrossRefGoogle Scholar
  54. 54.
    Ehrenberg A (1998) La fatigue d’être soi : Dépression et société. O. Jacob, ParisGoogle Scholar
  55. 55.
    Schwartz B (2004) The tyranny of choice. Scientific American Mind, pp 71–75Google Scholar
  56. 56.
    Whitley R (2008) Postmodernity and mental health. Harv Rev Psychiatry 16(6):352–364PubMedCrossRefGoogle Scholar
  57. 57.
    Horwitz A, Wakefield J (2009) The medicalization of sadness: how psychiatry transformed a natural emotion into a mental disorder. Salute e Società 8(2):49–66Google Scholar
  58. 58.
    Rose N (2003) Neurochemical selves. Society 41(1):46–59CrossRefGoogle Scholar
  59. 59.
    Colla J, Buka S, Harrington D, Murphy JM (2006) Depression and modernization: across-cultural study of women. Soc Psychiatry Psychiatr Epidemiol 41(4):271–279PubMedCrossRefGoogle Scholar
  60. 60.
    Stevenson B, Wolfers J (2007) Marriage and divorce: changes and their driving forces. J Econ Perspect 21(2):27–52CrossRefGoogle Scholar
  61. 61.
    Mason K, Mason W, Winsborough H, Poole W (1973) Some methodological issues in cohort analysis of archival data. Am Sociol Rev 38(2):242–258CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • Marie-Christine Brault
    • 1
    Email author
  • Bart Meuleman
    • 2
  • Piet Bracke
    • 3
  1. 1.Department of SociologyUniversity of MontrealMontréalCanada
  2. 2.Centre for Sociological ResearchKatholieke Universiteit LeuvenLeuvenBelgium
  3. 3.Department of SociologyGhent UniversityGhentBelgium

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