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Estimating the contribution of mortality selection to the East–West German mortality convergence

Overview of attention for article published in Population Health Metrics, September 2017
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Title
Estimating the contribution of mortality selection to the East–West German mortality convergence
Published in
Population Health Metrics, September 2017
DOI 10.1186/s12963-017-0151-3
Pubmed ID
Authors

Tobias C. Vogt, Trifon I. Missov

Abstract

Before German reunification, old-age mortality was considerably higher in East Germany than West Germany but converged quickly afterward. Previous studies attributed this rapid catch-up to improved living conditions. We add to this discussion by quantifying for the first time the impact of mortality selection. We use a gamma-Gompertz mortality model to estimate the contribution of selection to the East-West German mortality convergence before and after reunification. We find that, compared to the West, frailer East Germans died earlier due to deteriorating mortality conditions leading to converging mortality rates for women and men already over age 70 before 1990. After 1990, the selection of frailer individuals played only a minor role in closing the East-west German mortality gap. However, our study suggests that, after reunification, old-age mortality improved quickly because the more robust population in the East benefitted greatly from ameliorating external factors such as health care and better living standards. Our results from a natural experiment show that selection of frail individuals plays an important role in population-level mortality dynamics. In the case of the German reunification, East German old-age mortality already converged before 1990 because of stronger selection pressure.

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The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 13 100%

Demographic breakdown

Readers by professional status Count As %
Lecturer 3 23%
Student > Ph. D. Student 2 15%
Student > Master 2 15%
Student > Bachelor 1 8%
Student > Doctoral Student 1 8%
Other 1 8%
Unknown 3 23%
Readers by discipline Count As %
Social Sciences 4 31%
Medicine and Dentistry 3 23%
Psychology 2 15%
Mathematics 1 8%
Arts and Humanities 1 8%
Other 0 0%
Unknown 2 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 October 2017.
All research outputs
#14,955,443
of 23,002,898 outputs
Outputs from Population Health Metrics
#296
of 391 outputs
Outputs of similar age
#188,422
of 318,242 outputs
Outputs of similar age from Population Health Metrics
#5
of 8 outputs
Altmetric has tracked 23,002,898 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 391 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.9. This one is in the 21st percentile – i.e., 21% of its peers scored the same or lower than it.
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We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.