Abstract
Childhood socioeconomic disadvantage may contribute to adult depression. Understanding pathways by which early socioeconomic adversity may shape adult depression is important for identifying areas for intervention. Studies to date have focused on one potential pathway, adult socioeconomic status (SES), and assessed depression at only one or a few time points. Our aims were to examine (a) the association between childhood SES (low vs. high) and depressive symptom burden in midlife and (b) whether adult socioeconomic, psychosocial, and physical health characteristics are important pathways. Using annual data from a cohort of 1109 black and white US women recruited in 1996–1997, we evaluated the association between childhood SES and depressive symptom burden across 15 years in midlife and whether adult characteristics—financial difficulty, lower education, stressful events, low social support, low role functioning, medical conditions, and bodily pain—mediated the association. Depressive symptom burden was estimated by calculating area under the curve of annual scores across 15 years of the Center for Epidemiological Studies Depression (CES-D). In unadjusted models, low childhood SES was associated with greater depressive burden (P = 0.0002). Each hypothesized mediator, individually, did not reduce the association. However, when five of the hypothesized mediators were included together in the same analysis, they explained more than two thirds of the association between childhood SES and depressive symptom burden reducing the P value for childhood SES to non-significance (P = 0.20). These results suggest that childhood SES influences midlife depressive symptom burden through a cluster of economic stress, limited social resources, and physical symptoms in adulthood.
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References
Bromberger JT, Matthews KA, Schott LL, Brockwell S, Avis NE, Kravitz HM, Everson-Rose SA, Gold EB, Sowers M, Randolph JF Jr (2007) Depressive symptoms during the menopausal transition: the Study of Women’s Health Across the Nation (SWAN). J Affect Disord 103(1–3):267–272
Bromberger JT, Kravitz HM, Chang YF, Cyranowski JM, Brown C, Matthews KA (2011) Major depression during and after the menopausal transition: Study of Women’s Health Across the Nation (SWAN). Psychol Med 41(9):1879–1888
Bromberger JT, Kravitz HM, Chang Y, Randolph JF Jr, Avis NE, Gold EB, Matthews KA (2013) Does risk for anxiety increase during the menopausal transition? Study of women’s health across the nation. Menopause 20(5):488–495
Bromberger JT, Schott L, Kravitz HM, Joffe H (2015) Risk factors for major depression during midlife among a community sample of women with and without prior major depression: are they the same or different? Psychol Med 45(8):1653–1664
Gibb SJ, Fergusson DM, Horwood LJ (2012) Childhood family income and life outcomes in adulthood: findings from a 30-year longitudinal study in New Zealand. Soc Sci Med 74(12):1979–1986
Gilman SE (2002) Childhood socioeconomic status, life course pathways and adult mental health. Int J Epidemiol 31(2):403–404
Glaser D (2000) Child abuse and neglect and the brain—a review. J Child Psychol Psychiatry 41(1):97–116
Guarnaccia PJ, Angel R, Worobey JL (1989) The factor structure of the CES-D in the Hispanic Health and Nutrition Examination Survey: the influences of ethnicity, gender and language. Soc Sci Med 29(1):85–94
Harper S, Lynch J, Hsu WL, Everson SA, Hillemeier MM, Raghunathan TE, Salonen JT, Kaplan GA (2002) Life course socioeconomic conditions and adult psychosocial functioning. Int J Epidemiol 31(2):395–403
Hayes AF (2013) Methodology in the social sciences: introduction to mediation moderation and conditional process analysis: a regression-based approach. Guilford Press, New York Appendix A p
Herbers PM, Elder DA, Woo JG (2011) Area under a curve: calculation and visualization. Report No.: DG12–2011
Johnson SB, Riis JL, Noble KG 2016 State of the art review: poverty and the developing brain. Pediatrics 137(4)
Jones-Webb RJ, Snowden LR (1993) Symptoms of depression among blacks and whites. Am J Public Health 83(2):240–244
Kendler KS, Gardner CO (2010) Dependent stressful life events and prior depressive episodes in the prediction of major depression: the problem of causal inference in psychiatric epidemiology. Arch Gen Psychiatry 67(11):1120–1127
Kessler RC (2003) Epidemiology of women and depression. J Affect Disord 74(1):5–13
Luo Y, Waite LJ (2005) The impact of childhood and adult SES on physical, mental, and cognitive well-being in later life. J Gerontol B Psychol Sci Soc Sci 60(2):S93–S101
Makinen T, Laaksonen M, Lahelma E, Rahkonen O (2006) Associations of childhood circumstances with physical and mental functioning in adulthood. Soc Sci Med 62(8):1831–1839
Matthews KA, Chang Y, Bromberger JT, Karvonen-Gutierrez CA, Kravitz HM, Thurston RC, Montez JK (2016) Childhood socioeconomic circumstances, inflammation, and hemostasis among midlife women: Study of Women’s Health Across the Nation. Psychosom Med 78(3):311–318
McKenzie SK, Carter KN, Blakely T, Ivory V (2011) Effects of childhood socioeconomic position on subjective health and health behaviours in adulthood: how much is mediated by adult socioeconomic position? BMC Public Health 11:269
Montez JK, Bromberger JT, Harlow SD, Kravitz HM, Matthews KA (2016) Life Course Socioeconomic Status and Metabolic Syndrome among Midlife Women. Journal of Gerontology: Psychological Sciences and Social Sciences 71(6):1097–1107
Muthén LK, Muthén BO (1998–2017). Mplus User’s Guide. Eighth Edition. Los Angeles, CA: Muthén & Muthén
Non AL, Rewak M, Kawachi I, Gilman SE, Loucks EB, Appleton AA, Roman JC, Buka SL, Kubzansky LD (2014) Childhood social disadvantage, cardiometabolic risk, and chronic disease in adulthood. Am J Epidemiol 180(3):263–271
Poulton R, Caspi A, Milne BJ, Thomson WM, Taylor A, Sears MR, Moffitt TE (2002) Association between children’s experience of socioeconomic disadvantage and adult health: a life-course study. Lancet 360(9346):1640–1645
Power C, Atherton K, Strachan DP, Shepherd P, Fuller E, Davis A, Gibb I, Kumari M, Lowe G, Macfarlane GJ et al (2007) Life-course influences on health in British adults: effects of socio-economic position in childhood and adulthood. Int J Epidemiol 36(3):532–539
Radloff L (1977) The CES-D scale in a self-report depression scale for research in the general population. Appl Psychol Meas 1(3):385–401
Raposa EB, Hammen CL, Brennan PA, O'Callaghan F, Najman JM (2014) Early adversity and health outcomes in young adulthood: the role of ongoing stress. Health Psychol 33(5):410–418
Rose MS, Koshman ML, Spreng S, Sheldon R (1999) Statistical issues encountered in the comparison of health-related quality of life in diseased patients to published general population norms: problems and solutions. J Clin Epidemiol 52(5):405–412
Schaan B (2014) The interaction of family background and personal education on depressive symptoms in later life. Soc Sci Med 102:94–102
Sheikh MA, Abelsen B, Olsen JA (2014) Role of respondents’ education as a mediator and moderator in the association between childhood socio-economic status and later health and wellbeing. BMC Public Health 14:1172
Sheikh MA, Abelsen B, Olsen JA (2016) Clarifying associations between childhood adversity, social support, behavioral factors, and mental health, health, and well-being in adulthood: a population-based study. Front Psychol 7:727
Sherbourne CD, Stewart AL (1991) The MOS social support survey. Soc Sci Med 32(6):705–714
Sobel ME (1982) Asymptotic confidence intervals for indirect effects in structural equation models. In: Leinhardt S (ed) Sociological methodology 1982. American Sociological Association, Washington, DC, pp 290–312
Sowers M, Crawford SL, Sternfeld B, Morganstein D, Gold EB, Greendale GA, Evans D, Neer R, Matthews KA, Sherman S et al (2000) SWAN: a multicenter, multiethnic, community-based cohort study of women and the menopausal transition. In: Lobo RA, Kelsey J, Marcus R (eds) Menopause: biology and pathobiology. Academic Press, San Diego, pp 175–188
Taylor SE (2010) Mechanisms linking early life stress to adult health outcomes. Proc Natl Acad Sci USA 107(19):8507–8512
Taylor SE, Way BM, Seeman TE (2011) Early adversity and adult health outcomes. Dev Psychopathol 23(3):939–954
Wang J, Wang X (2012) Structural equation modeling: applications using mplus, 1st edn. John Wiley & Sons, Inc., Hoboken
Ware JE Jr, Sherbourne CD (1992) The MOS 36-item short-form health survey (SF-36). I. Conceptual framework and item selection. Med Care 30(6):473–483
Ying YW (1988) Depressive symptomatology among Chinese-Americans as measured by the CES-D. J Clin Psychol 44(5):739–746
Acknowledgements
Clinical Centers: University of Michigan, Ann Arbor—Siobán Harlow, PI 2011–present, MaryFran Sowers, PI 1994-2011; Massachusetts General Hospital, Boston, MA—Joel Finkelstein, PI 1999–present; Robert Neer, PI 1994–1999; Rush University, Rush University Medical Center, Chicago, IL—Howard Kravitz, PI 2009–present; Lynda Powell, PI 1994–2009; University of California, Davis/Kaiser—Ellen Gold, PI; Albert Einstein College of Medicine, Bronx, NY—Carol Derby, PI 2011–present, Rachel Wildman, PI 2010–2011; Nanette Santoro, PI 2004–2010; University of Medicine and Dentistry—New Jersey Medical School, Newark—Gerson Weiss, PI 1994–2004; and the University of Pittsburgh, Pittsburgh, PA—Karen Matthews, PI.
NIH Program Office: National Institute on Aging, Bethesda, MD—Chhanda Dutta 2016–present, Winifred Rossi 2012–2016; Sherry Sherman 1994–2012; Marcia Ory 1994–2001; National Institute of Nursing Research, Bethesda, MD—Program Officers.
Central Laboratory: University of Michigan, Ann Arbor—Daniel McConnell (Central Ligand Assay Satellite Services).
Coordinating Center: University of Pittsburgh, Pittsburgh, PA—Maria Mori Brooks, PI 2012–present; Kim Sutton-Tyrrell, PI 2001–2012; New England Research Institutes, Watertown, MA—Sonja McKinlay, PI 1995–2001.
Steering Committee: Susan Johnson, Current Chair, Chris Gallagher, Former Chair
We thank the study staff at each site and all the women who participated in SWAN.
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The Study of Women’s Health Across the Nation (SWAN) has grant support from the National Institutes of Health (NIH), DHHS, through the National Institute on Aging (NIA), the National Institute of Nursing Research (NINR), and the NIH Office of Research on Women’s Health (ORWH) (Grants NR004061; AG012505, AG012535, AG012531, AG012546, AG012553, AG012554, AG012495). The content of this manuscript is solely the responsibility of the authors and does not necessarily represent the official views of the NIA, NINR, ORWH, or the NIH. The authors have no relationships with industry.
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Bromberger, J.T., Schott, L.L., Matthews, K.A. et al. Childhood socioeconomic circumstances and depressive symptom burden across 15 years of follow-up during midlife: Study of Women’s Health Across the Nation (SWAN). Arch Womens Ment Health 20, 495–504 (2017). https://doi.org/10.1007/s00737-017-0747-4
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DOI: https://doi.org/10.1007/s00737-017-0747-4