| Title |
The impact of heterogeneity in individual frailty on the dynamics of mortality
|
|---|---|
| Published in |
Demography, August 1979
|
| DOI | 10.2307/2061224 |
| Pubmed ID | |
| Authors |
James W. Vaupel, Kenneth G. Manton, Eric Stallard |
| Abstract |
Life table methods are developed for populations whose members differ in their endowment for longevity. Unlike standard methods, which ignore such heterogeneity, these methods use different calculations to construct cohort, period, and individual life tables. The results imply that standard methods overestimate current life expectancy and potential gains in life expectancy from health and safety interventions, while underestimating rates of individual aging, past progress in reducing mortality, and mortality differentials between pairs of populations. Calculations based on Swedish mortality data suggest that these errors may be important, especially in old age. |
X Demographics
The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 38% |
| Canada | 2 | 25% |
| Italy | 1 | 13% |
| United Kingdom | 1 | 13% |
| Unknown | 1 | 13% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 7 | 88% |
| Members of the public | 1 | 13% |
Mendeley readers
The data shown below were compiled from readership statistics for 490 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | 1% |
| United Kingdom | 5 | 1% |
| France | 3 | <1% |
| Canada | 2 | <1% |
| Spain | 2 | <1% |
| Germany | 2 | <1% |
| Netherlands | 1 | <1% |
| Switzerland | 1 | <1% |
| Brazil | 1 | <1% |
| Other | 0 | 0% |
| Unknown | 467 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 121 | 25% |
| Researcher | 79 | 16% |
| Student > Master | 63 | 13% |
| Professor > Associate Professor | 33 | 7% |
| Student > Doctoral Student | 26 | 5% |
| Other | 95 | 19% |
| Unknown | 73 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 85 | 17% |
| Social Sciences | 62 | 13% |
| Mathematics | 51 | 10% |
| Medicine and Dentistry | 50 | 10% |
| Economics, Econometrics and Finance | 29 | 6% |
| Other | 113 | 23% |
| Unknown | 100 | 20% |
Attention Score in Context
This research output has an Altmetric Attention Score of 29. 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 24 April 2023.
All research outputs
#1,360,994
of 26,017,215 outputs
Outputs from Demography
#363
of 2,036 outputs
Outputs of similar age
#65
of 5,864 outputs
Outputs of similar age from Demography
#1
of 2 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,036 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.8. This one has done well, scoring higher than 82% 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 5,864 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 98% of its contemporaries.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them