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Changes in life expectancy 1950–2010: contributions from age- and disease-specific mortality in selected countries

Overview of attention for article published in Population Health Metrics, May 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (84th percentile)
  • High Attention Score compared to outputs of the same age and source (85th percentile)

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10 X users
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2 Wikipedia pages

Citations

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71 Dimensions

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108 Mendeley
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Title
Changes in life expectancy 1950–2010: contributions from age- and disease-specific mortality in selected countries
Published in
Population Health Metrics, May 2016
DOI 10.1186/s12963-016-0089-x
Pubmed ID
Authors

Jochen Klenk, Ulrich Keil, Andrea Jaensch, Marcus C. Christiansen, Gabriele Nagel

Abstract

Changes of life expectancy over time serve as an interesting public health indicator for medical, social and economic developments within populations. The aim of this study was to quantify changes of life expectancy between 1950 and 2010 and relate these to main causes of death. Pollard's actuarial method of decomposing life expectancy was applied to compare the contributions of different age- and disease-groups on life expectancy in 5-year intervals. From the 1960 to 70s on, declines in cardiovascular disease (CVD) mortality play an increasing role in improving life expectancy in many developed countries. During the past decades gains in life expectancy in these countries were mainly observed in age groups ≥65 years. A further consistent pattern was that life expectancy increases were stronger in men than in women, although life expectancy is still higher in women. In Japan, an accelerated epidemiologic transition in causes of death was found, with the highest increases between 1950 and 1955. Short-term declines and subsequent gains in life expectancy were observed in Eastern Europe and the former states of the Union of Soviet Socialist Republics (USSR), reflecting the changes of the political system. Changes of life years estimated with the decomposing method can be directly interpreted and may therefore be useful in public health communication. The development within specific countries is highly sensitive to changes in the political, social and public health environment.

X Demographics

X Demographics

The data shown below were collected from the profiles of 10 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 108 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 108 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 15 14%
Student > Master 13 12%
Student > Ph. D. Student 12 11%
Student > Doctoral Student 5 5%
Researcher 5 5%
Other 17 16%
Unknown 41 38%
Readers by discipline Count As %
Medicine and Dentistry 17 16%
Social Sciences 12 11%
Biochemistry, Genetics and Molecular Biology 7 6%
Nursing and Health Professions 6 6%
Psychology 5 5%
Other 18 17%
Unknown 43 40%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 09 May 2023.
All research outputs
#3,225,986
of 25,161,628 outputs
Outputs from Population Health Metrics
#82
of 410 outputs
Outputs of similar age
#52,960
of 341,309 outputs
Outputs of similar age from Population Health Metrics
#2
of 7 outputs
Altmetric has tracked 25,161,628 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 410 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.4. This one has done well, scoring higher than 79% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 341,309 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 84% of its contemporaries.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 5 of them.