Childhood and adulthood circumstances predicting affective suffering and motivation among older adults: a comparative study of European welfare systems

Abstract

The aims of the study are, first, to examine the effect of childhood and adulthood predictors on affective suffering and motivational symptoms among older adults in Europe and, second, to assess differentials across European welfare systems. The mediating role of adulthood circumstances is also explored. Data are derived from the Survey of Health, Ageing and Retirement in Europe (SHARE) waves 2 (cross-sectional material) and 3 (retrospective information). The sample includes 23,050 respondents aged 50 +. The EUROD subscales were obtained using factor analysis; scores were transformed to binary constructs; logistic regression models were used to identify predictors; mediation was assessed employing a decomposition technique. Prevalence of both subscales is higher in Southern and Central/Eastern Europe and lower in Nordic countries, which are characterised by more equitable and generous welfare provisions. Though health, childhood socioeconomic status and childhood adversity are significant for both subscales, there are also differences; female gender, adulthood socioeconomic status and stress are associated with affective suffering, whereas age and educational attainment are of greater consequence for motivational symptoms. These findings are quite consistent across regions, indicating that the subscales represent different aspects of depression. By contrast, childhood circumstances are attenuated differentially by adulthood factors across Europe. Nevertheless, important mediating circumstances are stress for affective suffering and poor health for motivational symptoms. The importance of childhood circumstances in all aspects of later life mental health highlights the need for policy interventions across welfare systems, which should target vulnerable groups early in life.

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References

  1. Alexopoulos GS (2005) Depression in the elderly. Lancet 365(9475):1961–1970

    Google Scholar 

  2. Angelini V, Klijs B, Smidt N, Mierau JO (2016) Associations between childhood parental mental health difficulties and depressive symptoms in late adulthood: the influence of life-course socioeconomic. Health Lifestyle Factors 11(12):e0167703. https://doi.org/10.1371/journal.pone.0167703

    Article  Google Scholar 

  3. Bambra C, Eikemo TA (2009) Welfare state regimes, unemployment and health: a comparative study of the relationship between unemployment and self-reported health in 23 European countries. J Epidemiol Community Health 63(2):92–98

    Google Scholar 

  4. Banks J, Nazroo J, Steptoe A (2012) The dynamics of ageing: evidence from the English Longitudinal Study of Ageing 2002-2010. Institute for Fiscal Studies, London

    Google Scholar 

  5. Beblavy M (2008) New welfare state models based on the new member states’ experience?. Comenius University, Bratislava, Slovak Governance Institute

    Google Scholar 

  6. Bloom DE, Chatterji S, Kowal P, Lloyd-Sherlock P, McKee M, Rechel B, Rosenberg L, Smith JP (2015) Macroeconomic implications of population ageing and selected policy responses. Lancet 385(9968):649–657

    Google Scholar 

  7. Börsch-Supan A (2015) Survey of health, ageing and retirement in Europe (SHARE). In: Pachana NA (ed) Encyclopedia of geropsychology. Springer Science+Business Media, Singapore, pp 1–9

    Google Scholar 

  8. Börsch-Supan A, Brandt M, Hunkler C, Kneip T, Korbmacher J, Malter F, Schaan B, Stuck S, Zuber S (2013) Data resource profile: the survey of health, ageing and retirement in Europe (SHARE). Int J Epidemiol 42(4):992–1001

    Google Scholar 

  9. Brailean A, Guerra M, Chua K-C, Prince M, Prina MA (2015) A multiple indicators multiple causes model of late-life depression in Latin American countries. J Affect Disord 184:129–136

    Google Scholar 

  10. Breen R, Karlson KB, Holm A (2013) Total, direct, and indirect effects in logit and probit models. Sociol Methods Res 42(2):164–191

    Google Scholar 

  11. 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, Prince M (2007) Prevalence of depressive symptoms and syndromes in later life in ten European countries: the SHARE study. Br J Psychiatry 191(5):393–401

    Google Scholar 

  12. 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, 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. Int J Methods Psychiatr Res 17(1):12–29

    Google Scholar 

  13. Cheval B, Boisgontier MP, Orsholits D, Sieber S, Guessous I, Gabriel R, Stringhini S, Blane D, van der Linden BWA, Kliegel M, Burton-Jeangros C, Courvoisier DS, Cullati S (2018) Association of early- and adult-life socioeconomic circumstances with muscle strength in older age. Age Ageing 47(3):398–407

    Google Scholar 

  14. Copeland JRM, Beekman ATF, Braam AW et al (2004) Depression among older people in Europe: the EURODEP studies. World Psychiatry 3(1):45–49

    Google Scholar 

  15. Crespo L, López-Noval B, Mira P (2014) Compulsory schooling, education, depression and memory: new evidence from SHARELIFE. Econ Educ Rev 43:36–46

    Google Scholar 

  16. Crowe L, 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(5):e009834. https://doi.org/10.1136/bmjopen-2015-009834

    Article  Google Scholar 

  17. Deacon B (2000) Eastern European welfare states: the impact of the politics of globalization. J Eur Soc Policy 10(2):146–161

    Google Scholar 

  18. Djernes JK (2006) Prevalence and predictors of depression in populations of elderly: a review. Acta Psychiatr Scand 113(5):372–387

    Google Scholar 

  19. Dvir Y, Ford JD, Hill M, Frazier JA (2014) Childhood maltreatment, emotional dysregulation, and psychiatric comorbidities. Harv Rev Psychiatry 22(3):149–161

    Google Scholar 

  20. Eikemo TA, Bambra C, Judge K, Ringdal K (2008a) Welfare state regimes and differences in self-perceived health in Europe: a multilevel analysis. Soc Sci Med 66(11):2281–2295

    Google Scholar 

  21. Eikemo TA, Huisman M, Bambra C, Kunst AE (2008b) Health inequalities according to educational level in different welfare regimes: a comparison of 23 European countries. Sociol Health Illn 30(4):565–582

    Google Scholar 

  22. Esping-Andersen G (1990) Three worlds of welfare capitalism. Polity Press, Cambridge

    Google Scholar 

  23. Eurostat (2013) GDP per capita in PPS, Index (EU28 = 100). Retrieved July 8, 2014, from Eurostat: http://epp.eurostat.ec.europa.eu/tgm/graph.do?tab=graph&plugin=1 &pcode=tec00114 &language=en&toolbox=type

  24. Ferrera M (1996) The ‘southern model’ of welfare in social Europe. J Eur Soc Policy 6(1):17–37

    Google Scholar 

  25. Ferrera M, Rhodes M (2013) Recasting European welfare states. Routledge, Abingdon

    Google Scholar 

  26. Floyd FJ, Widaman KF (1995) Factor analysis in the development and refinement of clinical assessment instruments. Pyschol Assess 7(3):286–299

    Google Scholar 

  27. Gameiro GR, Minguini IP, de Alves TC (2014) The role of stress and life events in the onset of depression in the elderly. Rev Med (São Paulo) 93(1):31–40

    Google Scholar 

  28. Gelman A (2007) Struggles with survey weighting and regression modeling. Stat Sci 22(2):153–164

    Google Scholar 

  29. Halmdienst N, 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 Econ Stud 60(2):402–434

    Google Scholar 

  30. Hoffmann R, Kröger H, Pakpahan E (2018) The reciprocal relationship between material factors and health in the life course: evidence from SHARE and ELSA. Eur J Ageing 15:379–391

    Google Scholar 

  31. Hoffmann R, Kröger H, Geyer S (2019) Social causation versus health selection in the life course: does their relative importance differ by dimension of SES? Soc Indic Res 141(3):1341–1367

    Google Scholar 

  32. Hosmer DW, Lemeshow SL (2000) Applied logistic regression, 2nd edn. Wiley, New York

    Google Scholar 

  33. Imai K, Keele L, Tingley D (2010a) A general approach to causal mediation analysis. Psychol Methods 15(4):309–334

    Google Scholar 

  34. Imai K, Keele L, Yamamoto T (2010b) Identification, inference and sensitivity analysis for causal mediation effects. Stat Sci 25(1):51–71

    Google Scholar 

  35. Jakobsen JC, Gluud C, Wetterslev J, 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 Med Res Methodol 17(1):162

    Google Scholar 

  36. Jirapramukpitak T, Darawuttimaprakorn N, Punpuing S, Abas M (2009) Validation and factor structure of the Thai version of the EURO-D scale for depression among older psychiatric patients. Aging Mental Health 13(6):899–904

    Google Scholar 

  37. Kessler RC (2003) Epidemiology of women and depression. J Affect Disord 74(1):5–13

    Google Scholar 

  38. Kohler U, Karlson KB, Holm A (2011) Comparing coefficients of nested nonlinear probability models using khb. Stata J 11(3):420–438

    Google Scholar 

  39. Landös A, von Arx M, Cheval B, Sieber S, Kliegel M, Gabriel R, Orsholits D, van der Linden BWA, Blane D, Boisgontier MP, Courvoisier DS, Guessous I, Burton-Jeangros C, Cullati S (2019) Childhood socioeconomic circumstances and disability trajectories in older men and women: a European cohort study. Eur J Pub Health 29(1):50–58

    Google Scholar 

  40. Le CT (2010) Applied categorical data analysis and translational research, 2nd edn. Wiley, Minneapolis

    Google Scholar 

  41. Lunau T, Bambra C, Eikemo TA, van der Wel KA, Dragano N (2014) A balancing act? Work–life balance, health and well-being in European welfare states. Eur J Pub Health 24(3):422–427

    Google Scholar 

  42. McLean CP, Asnaani A, Litz BT, Hofmann SG (2011) Gender differences in anxiety disorders: prevalence, course of illness, comorbidity and burden of illness. J Psychiatr Res 45(8):1027–1035

    Google Scholar 

  43. Norden (2013) Focus on the Nordic welfare model. Retrieved May 14, 2014, from Norden: http://www.nordicwelfare.org/PageFiles/7117/Nordic_Welfare_Model_Web.pdf

  44. Pakpahan E, Hoffmann R, Kröger H (2017a) The long arm of childhood circumstances on health in old age: evidence from SHARELIFE. Adv Life Course Res 31:1–10

    Google Scholar 

  45. Pakpahan E, Hoffmann R, Kröger H (2017b) 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

    Google Scholar 

  46. Popova Y, Kozhevnikova M (2013) Interdependence of HDI and budget redistribution within the Scandinavian and Continental Social Models. Econ Manag 18(3):562–575

    Google Scholar 

  47. Portellano-Ortiz C, Garre-Olmo J, Calvó-Perxas L, Conde-Sala JL (2017) Factor structure of depressive symptoms using the EURO-D scale in the over-50 s in Europe. Findings from the SHARE project. Agi Mental Health 22:1477–1485. https://doi.org/10.1080/13607863.2017.1370688

    Article  Google Scholar 

  48. Pöschl J, Valkova K (2015) Welfare state regimes and social determinants of health in Europe, wiiw Working paper 118

  49. 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, Copeland JR (1999a) Development of the EURO-D scale–a European, Union initiative to compare symptoms of depression in 14 European centres. Br J Psychiatry 174(4):330–338

    Google Scholar 

  50. Prince MJ, Beekman ATF, Deeg DJH, Fuhrur R, Jonker C, Kivela SL, Lawlor BA, Lobo A, Magnusson H, Meller I, van Oyen H, Reischies F, Roelands M, Skoog I, Turrina C, Copeland JRM (1999b) Depression symptoms in late life assessed using the EURO-D scale. Effect of age, gender and marital status in 14 European centres. Br J Psychiatry 174(4):339–345

    Google Scholar 

  51. Richardson S, Carr E, Netuveli G, Sacker A (2018) Country-level welfare-state measures and change in wellbeing following work exit in early old age: evidence from 16 European countries. Int J Epidemiol 48(2):389–401. https://doi.org/10.1093/ije/dyy205

    Article  Google Scholar 

  52. Rodrigues R, Huber M, Lamura G (2012) Facts and figures on healthy ageing and long-term care. European Centre for Social Welfare Policy and Research, Vienna

    Google Scholar 

  53. Sengoku M (2003) Emerging Eastern European Welfare States: A variant of the “European” Welfare Model? Retrieved July 9, 2014, from http://src-h.slav.hokudai.ac.jp/coe21/publish/no2_ses/3-2_Sengoku.pdf

  54. Sieber S, Cheval B, Orsholits D, van der Linden R, Guessous I, Gabriel R, Kliegel M, Aartsen M, Boisgontier M, Courvoisier D, Burton-Jeangros C, Cullati S (2019) Welfare regimes modify the association of disadvantaged adult-life socioeconomic circumstances with self-rated health in old age. Int J Epidemiol 5:5. https://doi.org/10.1093/ije/dyy283

    Article  Google Scholar 

  55. Small DS (2013) Mediation analysis without sequential ignorability: using baseline covariates interacted with random assignment as instrumental variables, eprint arXiv:1109.1070

  56. Tani Y, Fujiwara T, Kondo N, Noma H, Sasaki Y, Kondo K (2016) Childhood socioeconomic status and onset of depression among Japanese older adults: the JAGES prospective cohort study. Am J Geriatr Psychiatry 24(9):717–726

    Google Scholar 

  57. Van Bergen E, van Zuijen T, Bishop D, de Jong PF (2017) Why are home literacy environment and children’s reading skills associated? What parental skills reveal. Read Res Q 52(2):147–160

    Google Scholar 

  58. Verropoulou G, Tsimbos C (2007) Socio-demographic and health-related factors affecting depression of the Greek population in later life: an analysis using SHARE data. Eur J Ageing 4(3):171–181

    Google Scholar 

  59. Wahrendorf M, Blane D (2015) Does labour market disadvantage help to explain why childhood circumstances are related to quality of life at older ages? Results from SHARE. Aging Mental Health 19(7):584–594

    Google Scholar 

  60. Yohannes AM, Doherty P, Bundy C, Yalfani A (2010) The long-term benefits of cardiac rehabilitation on depression, anxiety, physical activity and quality of life. J Clin Nurs 19:2806–2813

    Google Scholar 

  61. Zimmer Z, Hanson HA, Smith KR (2016) Childhood socioeconomic status, adult socioeconomic status, and old-age health trajectories: connecting early, middle, and late life. Demogr Res 34(10):285–320

    Google Scholar 

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Acknowledgements

This paper uses data from SHARE waves 2 and 3 (SHARELIFE) (DOIs: https://doi.org/10.6103/share.w2.600, https://doi.org/10.6103/share.w3.600), see Börsch-Supan et al. (2013) for methodological details. The SHARE data collection has been primarily funded by the European Commission through FP5 (QLK6-CT-2001-00360), FP6 (SHARE-I3: RII-CT-2006-062193, COMPARE: CIT5-CT-2005-028857, SHARELIFE: CIT4-CT-2006-028812) and FP7 (SHARE-PREP: N°211909, SHARE-LEAP: N°227822, SHARE M4: N°261982). Additional funding from the German Ministry of Education and Research, the Max Planck Society for the Advancement of Science, the U.S. National Institute on Aging (U01_AG09740-13S2, P01_AG005842, P01_AG08291, P30_AG12815, R21_AG025169, Y1-AG-4553-01, IAG_BSR06-11, OGHA_04-064, HHSN271201300071C) and various national funding sources is gratefully acknowledged (see www.share-project.org).

Funding

Regarding the second author, this research has been financially supported by General Secretariat for Research and Technology (GSRT) and the Hellenic Foundation for Research and Innovation (HFRI) (Scholarship Code:991).

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Correspondence to Georgia Verropoulou.

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Verropoulou, G., Serafetinidou, E. Childhood and adulthood circumstances predicting affective suffering and motivation among older adults: a comparative study of European welfare systems. Eur J Ageing 16, 425–438 (2019). https://doi.org/10.1007/s10433-019-00518-w

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Keywords

  • Depression
  • Affective suffering
  • Motivation
  • European welfare systems
  • Decomposition method