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European Journal of Ageing

, Volume 9, Issue 1, pp 51–64 | Cite as

Decomposing differences in utilization of health services between depressed and non-depressed elders in Europe

  • Keren Ladin
Original Investigation

Abstract

Utilization rates of non-psychiatric health services are often higher in depressed compared to non-depressed adults. We examine whether these differences can be explained by the increased prevalence or the increased impact of demographic, socioeconomic, geographic, and health-related factors. The sample was taken from The Survey of Health, Ageing and Retirement in Europe (Wave 1 Release 2), a prospective observational study of 31,115 randomly selected people ages 50+ living in Austria, Germany, Sweden, the Netherlands, Spain, Italy, France, Denmark, Greece, Switzerland, Belgium, and Israel. Blinder–Oaxaca decomposition methods for multivariate linear regression models were used to estimate the influence of prevalence and impact of covariates on utilization among depressed and non-depressed participants. We find robust evidence that the gap in utilization between depressed and non-depressed can be accounted for by both prevalence (explained) and impact (unexplained) differences. The prevalence effect accounted for 57.7% whereas differences in the impact of covariates between depressed and non-depressed persons explained 42.3% of differences in utilization rates. Despite cross-national differences in quality and coverage of health services, in all countries, the prevalence effect was explained entirely by health measures, including: chronic diseases, functional mobility, painful symptoms, and self-reported health. The impact effect varied cross-nationally, but was largely explained by socioeconomic status and urbanicity. Hospitalization among depressed adults was twice that of non-depressed adults. Policies aimed at improving adherence and improving disease management among depressed adults should be explored.

Keywords

Depression Disparities Decomposition methods Aging 

Notes

Acknowledgments

The author gratefully acknowledges instructive comments from Tom McGuire, Ph.D., Amartya Sen, PhD, Jürgen Maurer, Ph.D., and participants of the Mannheim Research Institute for the Economics of Aging (MEA) seminar. The author gratefully acknowledges financial support from NIA-NBER Pre-Doctoral Training Grant in Aging and Health Economics.

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Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  1. 1.Interfaculty Initiative on Health PolicyHarvard UniversityCambridgeUSA

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