Hostname: page-component-cd9895bd7-p9bg8 Total loading time: 0 Render date: 2024-12-26T23:06:27.459Z Has data issue: false hasContentIssue false
  • English
  • Français

Decomposing the effects of childhood adversity on later-life depression among Europeans: a comparative analysis by gender

Published online by Cambridge University Press:  15 August 2019

Georgia Verropoulou Open the ORCID record for Georgia Verropoulou [Opens in a new window] ,
Eleni Serafetinidou  and
Cleon Tsimbos Open the ORCID record for Cleon Tsimbos [Opens in a new window]
Georgia Verropoulou*
Affiliation:
Department of Statistics and Insurance Science, University of Piraeus, Piraeus, Greece Centre for Longitudinal Studies, UCL Institute of Education, London, UK
Eleni Serafetinidou
Affiliation:
Department of Statistics and Insurance Science, University of Piraeus, Piraeus, Greece
Cleon Tsimbos
Affiliation:
Department of Statistics and Insurance Science, University of Piraeus, Piraeus, Greece
*
*Corresponding author. Email: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

The aims of the present study are twofold: first, to examine the importance of socio-economic disadvantage, adverse experiences and poor health in childhood on later-life depression by sex and, second, to discern the direct and indirect effects of childhood circumstances using a decomposition technique. Data are derived from Waves 2 and 3 of the Survey of Health, Ageing and Retirement in Europe (SHARE). The methods involve use of logistic regression models and a decomposition approach. The findings indicate that childhood socio-economic status (SES) for both genders and cognitive function for men have only a significant direct effect, consistent with the critical period model. Childhood health for men and poor parental mental health for women are nearly fully mediated by adulthood and later-life circumstances, a fact in line with the pathway model. Poor childhood health, parental excessive alcohol consumption and cognitive function for women and adverse experiences for men have both significant direct and indirect effects, consistent with both models. Mediating factors include poor adulthood and later-life health, socio-economic adversity and stress; adulthood and later-life SES mediate early life health and adverse experiences more strongly for men, whereas stress seems to mediate early life adverse experiences to a greater extent among women. Intervening policies should address childhood adversity while considering the differential vulnerability of men and women.

Keywords

later-life depressionchildhood adversitymediationKHB methodcritical period modelpathway modelSurvey of Health, Ageing and Retirement in Europe (SHARE)Europe
Type
Article
Information
Ageing & Society , Volume 41 , Issue 1 , January 2021 , pp. 158 - 186
Copyright
Copyright © Cambridge University Press 2019

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

Albert, PR (2015) Why is depression more prevalent in women? Journal of Psychiatry & Neuroscience 40, 219–221.CrossRefGoogle ScholarPubMed
Almuneef, M, ElChoueiry, N, Saleheen, HN and Al-Eissa, M (2017) Gender-based disparities in the impact of adverse childhood experiences on adult health: findings from a national study in the Kingdom of Saudi Arabia. International Journal for Equity in Health 16, 90.CrossRefGoogle ScholarPubMed
Amlaev, Κ (2015) Health Inequity, Treatment Compliance, and Health Literacy at the Local Level: Theoretical and Practical Aspects. Russia: Ridero.Google Scholar
Andersson, D, Magnusson, H, Carstensen, J and Borgquist, L (2011) Co-morbidity and health care utilisation five years prior to diagnosis for depression. A register-based study in a Swedish population. BMC Public Health 11, 552–560.CrossRefGoogle Scholar
Angelini, V, Howdon, DDH and Mierau, JO (2019) Childhood socioeconomic status and late-adulthood mental health: results from the Survey on Health, Ageing and Retirement in Europe. Journals of Gerontology: Psychological Sciences and Social Sciences 74B, 95–104.CrossRefGoogle Scholar
Angelini, V, Klijs, B, Smidt, N and Mierau, JO (2016) Associations between childhood parental mental health difficulties and depressive symptoms in late adulthood: the influence of life-course socioeconomic, health and lifestyle factors. PLOS ONE 11, 12.CrossRefGoogle ScholarPubMed
Arpino, B, Gumà, J and Julià, A (2018) Early-life conditions and health at older ages: the mediating role of educational attainment, family and employment trajectories. PLOS ONE 13, 4.CrossRefGoogle ScholarPubMed
Aziz, R and Steffens, DC (2013) What are the causes of late-life depression? Psychiatric Clinics of North America 36, 497–516.CrossRefGoogle ScholarPubMed
Back, JH and Lee, Y (2011) Gender differences in the association between socioeconomic status (SES) and depressive symptoms in older adults. Archives of Gerontology and Geriatrics 52, e140–e144.CrossRefGoogle ScholarPubMed
Beekman, AT, Copeland, JR and Prince, MJ (1999) Review of community prevalence of depression in later life. British Journal of Psychiatry 174, 307–311.CrossRefGoogle ScholarPubMed
Belloni, A, Morgan, D and Paris, V (2016) Pharmaceutical expenditure and policies: past trends and future challenges. Organisation for Economic Co-operation and Development, Health Working Paper 87.Google Scholar
Berg, LVD, Kalmijn, M and Leopold, T (2018) Family structure and early home leaving: a mediation analysis. European Journal of Population 34, 873–900.CrossRefGoogle ScholarPubMed
Börsch-Supan, A, Brandt, M, Hunkler, C, Kneip, T, Korbmacher, J, Malter, F, Schaan, B, Stuck, S, Zuber, S and SHARE Central Coordination Team (2013) Data resource profile: the Survey of Health, Ageing and Retirement in Europe (SHARE). International Journal of Epidemiology 42, 992–1001.CrossRefGoogle Scholar
Börsch-Supan, A and Jurges, H (2005) The Survey of Health, Aging and Retirement in Europe. Methodology. Mannheim, Germany: Mannheim Research Institute for the Economics of Ageing.Google Scholar
Breen, R, Karlson, KB and Holm, A (2013) Total, direct, and indirect effects in logit and probit models. Sociological Methods & Research 42, 164–191.CrossRefGoogle Scholar
Butterworth, P, Rodgers, B and Windsor, TD (2009) Financial hardship, socio-economic position and depression: results from the PATH Through Life Survey. Social Science & Medicine 69, 229–237.CrossRefGoogle ScholarPubMed
Case, A, Fertig, A and Paxson, C (2005) The lasting impact of childhood health and circumstance. Journal of Health Economics 24, 365–389.CrossRefGoogle ScholarPubMed
Castro-Costa, E, Dewey, M, Stewart, R, Banerjee, S, Hupper, F, Mendonca-Lima, C, Bula, C, Reisches, F, Wancata, J, Ritchie, K, Tsolaki, M, Mateos, R and Prince, M (2007) Prevalence of depressive symptoms and syndromes in later life in ten European countries: the SHARE study. British Journal of Psychiatry 191, 393–401.CrossRefGoogle ScholarPubMed
Castro-Costa, E, Dewey, M, Stewart, R, Banerjee, S, Huppert, F, Mendonca-Lima, C, Bula, C, Reisches, F, Wancata, J, Ritchie, K, Tsolaki, M, Mateos, R and Prince, M (2008) Ascertaining late-life depressive symptoms in Europe: an evaluation of the survey version of the EURO-D scale in 10 nations. The SHARE project. International Journal of Methods in Psychiatric Research 17, 12–29.CrossRefGoogle ScholarPubMed
Cavapozzi, D, Garrouste, C and Paccagnela, O (2011) Childhood, schooling and income inequality. In Börsch-Supan, A, Brandt, M, Hank, K and Schröder, M (eds), The Individual and the Welfare State. Life Histories in Europe. Berlin: Springer, pp. 31–43.CrossRefGoogle Scholar
Conklin, AI, Forouhi, NG, Suhrcke, M, Surtees, P, Wareham, NJ and Monsivais, P (2013) Socioeconomic status, financial hardship and measured obesity in older adults: a cross-sectional study of the EPIC-Norfolk cohort. BMC Public Health 13, 1039.Google ScholarPubMed
Crowe, L and Butterworth, P (2016) The role of financial hardship, mastery and social support in the association between employment status and depression: results from an Australian longitudinal cohort study. BMJ Open 6, e009834.Google ScholarPubMed
D'Alisa, S, Miscio, G, Baudo, S, Simone, A, Tesio, L and Mauro, A (2006) Depression is the main determinant of quality of life in multiple sclerosis: a classification-regression (CART) study. Disability and Rehabilitation 28, 307–314.CrossRefGoogle ScholarPubMed
Dewey, ME and Prince, MJ (2005) Mental health. In Borsch-Supan, A, Brugiavini, A, Jurges, H, Mackenbach, J, Siegrist, J and Weber, G (eds), Health, Ageing and Retirement in Europe, First Results from the Survey of Health, Ageing and Retirement in Europe. Mannheim, Germany: Mannheim Research Institute for the Economics of Ageing.Google Scholar
Doblhammer, G, Van den Berg, GJ and Fritze, T (2013) Economic conditions at the time of birth and cognitive abilities late in life: evidence from ten European countries. PLOS ONE 8, 9.Google ScholarPubMed
Dube, SR, Anda, RF, Felitti, VJ, Croft, JB, Edwards, VJ and Giles, WH (2001) Growing up with parental alcohol abuse: exposure to childhood abuse, neglect, and household dysfunction. Child Abuse & Neglect 25, 1627–1640.CrossRefGoogle ScholarPubMed
Dvir, Y, Ford, JD, Hill, M and Frazier, JA (2014) Childhood maltreatment, emotional dysregulation, and psychiatric comorbidities. Harvard Review of Psychiatry 22, 149–161.CrossRefGoogle ScholarPubMed
Farrokhi, F, Abedi, N, Beyene, J, Kurdyak, P and Jassal, SV (2014) Association between depression and mortality in patients receiving long-term dialysis: a systematic review and meta-analysis. American Journal of Kidney Diseases 63, 623–635.CrossRefGoogle ScholarPubMed
Flores, M and Kalwij, A (2014) The associations between early life circumstances and later life health and employment in Europe. Empirical Economics 47, 1251–1282.CrossRefGoogle Scholar
Gallagher, D, Sawa, GM, Kenny, R and Lawlor, BA (2013) What predicts persistent depression in older adults across Europe? Utility of clinical and neuropsychological predictors from the SHARE study. Journal of Affective Disorders 147, 192–197.CrossRefGoogle ScholarPubMed
Galobardes, B, Lynch, JW and Davey, G (2004) Childhood socioeconomic circumstances and cause-specific mortality in adulthood: systematic review and interpretation. Epidemiologic Reviews 26, 7–21.CrossRefGoogle ScholarPubMed
Haas, SA (2007) The long-term effects of poor childhood health: an assessment and application of retrospective reports. Demography 44, 113–135.CrossRefGoogle ScholarPubMed
Halmdienst, N and Winter-Ebmer, R (2014) Long-run relations between childhood shocks and health in late adulthood – evidence from the Survey of Health, Ageing, and Retirement in Europe. CESifo Economic Studies 60, 402–434.CrossRefGoogle ScholarPubMed
Hankin, BL (2002) Gender differences in depression from childhood through adulthood: a review of course, causes, and treatment. Primary Psychiatry 9, 32–38.Google Scholar
Hertzman, C and Boyce, T (2010) How experience gets under the skin to create gradients in developmental health. Annual Review of Public Health 31, 329–347.CrossRefGoogle ScholarPubMed
Imai, K, Keele, L and Tingley, D (2010 a) A general approach to causal mediation analysis. Psychological Methods 15, 309–334.CrossRefGoogle ScholarPubMed
Imai, K, Keele, L and Yamamoto, T (2010 b) Identification, inference and sensitivity analysis for causal mediation effects. Statistical Science 25, 51–71.CrossRefGoogle Scholar
Jakobsen, JC, Gluud, C, Wetterslev, J and Winkel, P (2017) When and how should multiple imputation be used for handling missing data in randomised clinical trials – a practical guide with flowcharts. BMC Medical Research Methodology 17, 162.CrossRefGoogle ScholarPubMed
Kendig, H, Gong, CH, Yiengprugsawan, V, Silverstein, M and Nazroo, J (2017) Life course influences on later life health in China: childhood health exposure and socioeconomic mediators during adulthood. SSM – Population Health 3, 795–802.CrossRefGoogle ScholarPubMed
Kohler, U, Karlson, KB and Holm, A (2011) Comparing coefficients of nested nonlinear probability models using khb. Stata Journal 11, 420–438.CrossRefGoogle Scholar
Ladin, K (2008) Risk of late-life depression across 10 European Union countries: deconstructing the education effect. Journal of Aging and Health 20, 653–670.CrossRefGoogle ScholarPubMed
Luo, Υ and Waite, LJ (2005) The impact of childhood and adult SES on physical, mental, and cognitive well-being in later life. Journals of Gerontology: Psychological Sciences and Social Sciences 60B, S93–S101.CrossRefGoogle Scholar
McLean, CP, Asnaani, A, Litz, BT and Hofmann, SG (2011) Gender differences in anxiety disorders: prevalence, course of illness, comorbidity and burden of illness. Journal of Psychiatric Research 45, 1027–1035.CrossRefGoogle ScholarPubMed
Monnat, SM and Chandler, RF (2015) Long-term physical health consequences of adverse childhood experiences. Sociological Quarterly 56, 723–752.CrossRefGoogle ScholarPubMed
Montez, JK, Bromberger, JT, Harlow, SD, Kravitz, HM and Matthews, KA (2016) Life-course socioeconomic status and metabolic syndrome among midlife women. Journals of Gerontology: Psychological Sciences and Social Sciences 71B, 1097–1107.CrossRefGoogle Scholar
Moore, T, McDonald, M and McHugh-Dillon, H (2014) Early Childhood Development and the Social Determinants of Health Inequities: A Review of the Evidence. Parkville, Australia: Centre for Community Child Health at the Murdoch Children's Research Institute and the Royal Children's Hospital.Google Scholar
Norden (2013) Focus on the Nordic Welfare Model. Available at http://www.nordicwelfare.org/PageFiles/7117/Nordic_Welfare_Model_Web.pdf.Google Scholar
Nurius, PS, Green, S, Logan-Greene, P and Borja, S (2015) Life course pathways of adverse childhood experiences toward adult psychological well-being: a stress process analysis. Child Abuse & Neglect 45, 143–153.CrossRefGoogle ScholarPubMed
Nuyen, J, Volkers, AC, Verhaak, PFM and Schellevis, FG (2005) Accuracy of diagnosing depression in primary care: the impact of chronic somatic and psychiatric co-morbidity. Psychological Medicine 35, 1185–1195.CrossRefGoogle ScholarPubMed
Padayachey, U, Ramlall, S and Chipps, J (2017) Depression in older adults: prevalence and risk factors in a primary health care sample. South African Family Practice 59, 61–66.CrossRefGoogle Scholar
Pakpahan, E, Hoffmann, R and Kröger, H (2017 a) The long arm of childhood circumstances on health in old age: evidence from SHARELIFE. Advances in Life Course Research 31, 1–10.CrossRefGoogle Scholar
Pakpahan, E, Hoffmann, R and Kröger, H (2017 b) Retrospective life course data from European countries on how early life experiences determine health in old age and possible mid-life mediators. Data in Brief 10, 277–282.CrossRefGoogle ScholarPubMed
Popova, Y and Kozhevnikova, M (2013) Interdependence of HDI and budget redistribution within the Scandinavian and Continental Social Models. Economics and Management 18, 562–575.CrossRefGoogle Scholar
Prince, MJ, Beekman, AT, Deeq, DJ, Fuhrer, R, Kivela, SL, Lawlor, BA, Lobo, A, Magnusson, H, Meller, I, van Oyen, H, Reischies, F, Roelands, M, Skoog, I, Turrina, C and Copeland, JR (1999 a) Depression symptoms in late life assessed using the EURO-D scale. Effect of age, gender and marital status in 14 European centres. British Journal of Psychiatry 174, 339–345.CrossRefGoogle ScholarPubMed
Prince, MJ, Reischies, F, Beekman, AT, Fuhrer, R, Jonker, C, Kivela, SL, Lawlor, BA, Lobo, A, Magnusson, H, Fichter, M, van Oyen, H, Roelands, M, Skoog, I, Turrina, C and Copeland, JR (1999 b) Development of the EURO-D scale – a European Union initiative to compare symptoms of depression in 14 European centres. British Journal of Psychiatry 174, 330–338.CrossRefGoogle ScholarPubMed
Pudrovska, T and Anikputa, B (2014) Early-life socioeconomic status and mortality in later life: an integration of four life-course mechanisms. Journals of Gerontology: Psychological Sciences and Social Sciences 69B, 451–460.CrossRefGoogle Scholar
Schaan, B (2014) The interaction of family background and personal education on depressive symptoms in later life. Social Science & Medicine 102, 94–102.CrossRefGoogle ScholarPubMed
Segel-Karpas, D (2015) Number of illnesses, self-perceived health, and depressive symptoms: the moderating role of employment in older adulthood and old age. Work, Aging and Retirement 1, 382–392.CrossRefGoogle Scholar
Sengoku, M (2003) Emerging Eastern European Welfare States: A Variant of the ‘European’ Welfare Model? Available at http://src-h.slav.hokudai.ac.jp/coe21/publish/no2_ses/3-2_Sengoku.pdf.Google Scholar
Small, DS (2013) Mediation analysis without sequential ignorability: using baseline covariates interacted with random assignment as instrumental variables. arXiv 1109.1070.Google Scholar
St Clair, M, Croudace, T, Dunn, V, Jones, P, Herbert, J and Goodyer, I (2015) Childhood adversity subtypes and depressive symptoms in early and late adolescence. Development and Psychopathology 27, 885–899.CrossRefGoogle ScholarPubMed
Tani, Y, Fujiwara, T, Kondo, N, Noma, H, Sasaki, Y and Kondo, K (2016) Childhood socioeconomic status and onset of depression among Japanese older adults: the JAGES prospective cohort study. American Journal of Geriatric Psychiatry 24, 717–726.CrossRefGoogle ScholarPubMed
Torres, JM and Wong, R (2013) Childhood poverty and depressive symptoms for older adults in Mexico: a life-course analysis. Journal of Cross-cultural Gerontology 28, 317–337.CrossRefGoogle ScholarPubMed
Van Bergen, E, van Zuijen, T, Bishop, D and de Jong, PF (2017) Why are home literacy environment and children's reading skills associated? What parental skills reveal. Reading Research Quarterly 52, 147–160.CrossRefGoogle Scholar
Van de Velde, S, Bracke, P and Levecque, K (2010) Gender differences in depression in 23 European countries. Cross-national variation in the gender gap in depression. Social Science & Medicine 71, 305–313.CrossRefGoogle ScholarPubMed
Verma, R, Balhara, YP and Gupta, CS (2011) Gender differences in stress response: role of developmental and biological determinants. Industrial Psychiatry Journal 20, 4–10.Google ScholarPubMed
Verropoulou, G (2014) Specific versus general self-reported health indicators predicting mortality among older adults in Europe: disparities by gender employing SHARE longitudinal data. International Journal of Public Health 59, 665–678.CrossRefGoogle ScholarPubMed
Verropoulou, G and Zakynthinou, M (2016) Contrasting concurrent and childhood socioeconomic predictors of self-rated health among older European men and women. Journal of Biosocial Science 49, 478–491.CrossRefGoogle ScholarPubMed
World Health Organization (WHO) (2014) Social Determinants of Mental Health. Geneva: WHO.Google Scholar
World Health Organization (WHO) (2017 a) Depression and Other Common Mental Disorders. Global Health Estimates. Geneva: WHO.Google Scholar
World Health Organization (WHO) (2017 b) World Population Ageing 2017 – Highlights. New York, NY: United Nations.Google Scholar
Zender, R and Olshansky, E (2009) Women's mental health: depression and anxiety. Nursing Clinics of North America 44, 355–364.CrossRefGoogle ScholarPubMed
Zimmer, Z, Hanson, HA and Smith, KR (2016) Childhood socioeconomic status, adult socioeconomic status, and old-age health trajectories: connecting early, middle, and late life. Demographic Research 34, 285–320.CrossRefGoogle Scholar