Article Text
Abstract
Background Recent analyses explored associations of welfare state regimes with population health, with particular interest in differences between social protection-oriented versus more liberal regimes. Little is known about such associations with work-related health. The aims of this contribution are (1) to study variations of quality of work according to type of welfare regime and (2) to analyse differences in the size of effects of quality of work on workers' health according to type of welfare regime.
Methods The authors use cross-sectional and longitudinal data from two studies (‘Survey of Health, Ageing and Retirement in Europe’ and the ‘English Longitudinal Study on Ageing’) with 9917 employed men and women (aged 50 to 64) in 12 European countries. Psychosocial quality of work is measured by low control and effort–reward imbalance at work. Depressive symptoms are introduced as a health indicator. Linear multilevel models and logistic regression analyses are performed to test the hypotheses. In addition to the welfare regime typology, the authors introduce labour policy and economy-related macro indicators.
Results Between-country variations in quality of work are largely explained by macro indicators and welfare regimes, with poorer quality of work in countries with less emphasis on older workers' protection. Moreover, in the Liberal and Southern welfare regime, effects of quality of work on depressive symptoms are relatively strongest (adjusted ORs varying from 1.45 to 2.64).
Conclusion Active labour policies and reliable social protection measures (eg, Scandinavian welfare regime) exert beneficial effects on the health and well-being of older workers. More emphasis on improving quality of work among this group is warranted.
- Occupational health
- occupational stress
- elderly
- social policy
- multilevel modelling
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Footnotes
Funding This paper uses data from SHARE waves 1 and 2, as of December 2008. SHARE data collection in 2004–2007 was primarily funded by the European Commission through its 5th and 6th framework programmes (project numbers QLK6-CT-2001- 00360; RII-CT- 2006-062193; CIT5-CT-2005-028857). Additional funding by the US National Institute on Ageing (grant numbers U01 AG09740-13S2; P01 AG005842; P01 AG08291; P30 AG12815; Y1-AG-4553-01; OGHA 04-064; R21 AG025169) as well as by various national sources is gratefully acknowledged (see http://www.share-project.org for a full list of funding institutions). Data from ELSA were made available through the UK Data Archive. ELSA has been supported by grants 2RO1AG7644-01A1 and 2RO1AG017644 from the NIA and a consortium of UK government departments coordinated by the Office for National Statistics. The authors are grateful to A Börsch-Supan and to M Marmot, the directors SHARE and ELSA respectively, for their support. Moreover, we would like to thank the Hans-Boeckler-Foundation, Duesseldorf, Germany, for continued funding of the presented comparative analyses (project no S-2007-997-4 and S-2009-311-4).
Competing interests None.
Ethics approval Ethics approval was provided by the SHARE/ELSA: respective national ethics/data safety authorities.
Provenance and peer review Not commissioned; externally peer reviewed.