Abstract

BackgroundStudies state profound cross-country differences in healthy life years and its time trends, suggesting either the health scenario of expansion or compression of morbidity. A much-discussed question in public health research is whether the health scenarios are heterogeneous or homogeneous on the subnational level as well. Furthermore, the question arises whether the morbidity trends or the mortality trends are the decisive drivers of the care need-free life years (CFLY), the life years with care need (CLY), and, ultimately, the health scenarios.MethodsThis study uses administrative census data of all beneficiaries in Germany from the Statutory Long-Term Care Insurance 2001–2009. We compute the CFLY and CLY at age 65+ for 412 counties. The CFLY and CLY gains are decomposed into the effects of survival and of the prevalence of care need, and we investigate their linkages with the health scenarios by applying multinomial regression models.ResultsWe show an overall increase in CFLY, which is higher for men than for women and higher for severe than for any care need. However, spatial variation in CFLY and in CLY has increased. In terms of the health scenarios, a majority of counties show an expansion of any care need but a compression of severe care need. There is high spatial heterogeneity, with expansion-counties surrounding compression-counties and vice versa, which is mainly caused by divergent trends in the prevalence of care need. We show that mortality is responsible for the absolute changes in CFLY and CLY, while morbidity is the decisive driver that determines the health scenario of a county.ConclusionCombining regionalized administrative data and advanced statistical methods permits a deeper insight into the complex relationship between health and mortality. Our findings demonstrate a compression of life years with severe care need, which however, depends on the region of residence. To attenuate regional inequalities, more efforts are needed that improve health by medical and infrastructural interventions and by the exchange of insights in the efficiency of small- and large-area policy measures between the vanguard and the rearguard counties. In future research, the underlying latent mechanisms should be investigated in more detail.Electronic supplementary materialThe online version of this article (doi:10.1186/s12963-016-0093-1) contains supplementary material, which is available to authorized users.

Highlights

  • Introduction & BackgroundThe health scenarios Three hypothetical scenarios with contrasting assumptions about future developments of morbidity in populations with decreasing mortality were established and repeatedly examined

  • Combining regionalized administrative data and advanced statistical methods permits a deeper insight into the complex relationship between health and mortality

  • Our findings demonstrate a compression of life years with severe care need, which depends on the region of residence

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Summary

Introduction

Introduction & BackgroundThe health scenarios Three hypothetical scenarios with contrasting assumptions about future developments of morbidity in populations with decreasing mortality were established and repeatedly examined. Fries [5, 6] later developed a modified and differentiated scenario: the absolute and the relative compression of morbidity. Absolute compression describes a situation in which the total number of unhealthy life years decreases, while there is a relative compression when the proportion of unhealthy life time to total remaining life time declines. Relative compression is defined as a special case of absolute compression - differing in the development of the disabled life years. Studies state profound cross-country differences in healthy life years and its time trends, suggesting either the health scenario of expansion or compression of morbidity. The question arises whether the morbidity trends or the mortality trends are the decisive drivers of the care need-free life years (CFLY), the life years with care need (CLY), and, the health scenarios

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