Literature DB >> 31798368

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

Georgia Verropoulou1,2, Eleni Serafetinidou1.   

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. © Springer Nature B.V. 2019.

Entities:  

Keywords:  Affective suffering; Decomposition method; Depression; European welfare systems; Motivation

Year:  2019        PMID: 31798368      PMCID: PMC6857123          DOI: 10.1007/s10433-019-00518-w

Source DB:  PubMed          Journal:  Eur J Ageing        ISSN: 1613-9372


  35 in total

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Journal:  Int J Epidemiol       Date:  2019-08-01       Impact factor: 7.196

3.  Socio-demographic and health-related factors affecting depression of the Greek population in later life: an analysis using SHARE data.

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Journal:  Eur J Ageing       Date:  2007-08-11

4.  Epidemiology of women and depression.

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5.  Welfare state regimes, unemployment and health: a comparative study of the relationship between unemployment and self-reported health in 23 European countries.

Authors:  C Bambra; T A Eikemo
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6.  Childhood socioeconomic circumstances and disability trajectories in older men and women: a European cohort study.

Authors:  Aljoscha Landös; Martina von Arx; Boris Cheval; Stefan Sieber; Matthias Kliegel; Rainer Gabriel; Dan Orsholits; Bernadette W A van der Linden; David Blane; Matthieu P Boisgontier; Delphine S Courvoisier; Idris Guessous; Claudine Burton-Jeangros; Stéphane Cullati
Journal:  Eur J Public Health       Date:  2019-02-01       Impact factor: 3.367

Review 7.  Macroeconomic implications of population ageing and selected policy responses.

Authors:  David E Bloom; Somnath Chatterji; Paul Kowal; Peter Lloyd-Sherlock; Martin McKee; Bernd Rechel; Larry Rosenberg; James P Smith
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8.  A multiple indicators multiple causes model of late-life depression in Latin American countries.

Authors:  Anamaria Brailean; Mariella Guerra; Kia-Chong Chua; Martin Prince; Matthew A Prina
Journal:  J Affect Disord       Date:  2015-06-10       Impact factor: 4.839

9.  Retrospective life course data from European countries on how early life experiences determine health in old age and possible mid-life mediators.

Authors:  Eduwin Pakpahan; Rasmus Hoffmann; Hannes Kröger
Journal:  Data Brief       Date:  2016-12-07

10.  When and how should multiple imputation be used for handling missing data in randomised clinical trials - a practical guide with flowcharts.

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Journal:  BMC Med Res Methodol       Date:  2017-12-06       Impact factor: 4.615

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