Evidence map›Paper›PMID 21609727›Full record

ReviewTheoretical population biology2011

A unifying framework for assessing changes in life expectancy associated with changes in mortality: the case of violent deaths.

Hiram Beltrán-Sánchez, Samir Soneji

Abstract readReview
In one paragraph

Review in Theoretical population biology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Observational
  2. Article
  3. Article
  4. The entropy of the life table: A reappraisal.Theoretical population biology · 2015
    Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Hiram Beltrán-SánchezDavis School of Gerontology at the University of Southern California, USA. beltrans@usc.edu
Samir Soneji

Funding

GRADUATE TRAINING IN DEMOGRAPHYT32HD007242 · NICHD · UNIVERSITY OF PENNSYLVANIA · PI MICHEL GUILLOT · 1985 to 2026
$6.6M
Comparative Effectiveness of Advanced Imaging in CancerRC2CA148259 · NCI · DARTMOUTH COLLEGE · PI BLACK, WILLIAM C, HILLNER, BRUCE ELLIS · 2009 to 2009
$2.0M
Comparative Effectiveness of Advanced Imaging in CancerUC2CA148259 · NCI · DARTMOUTH COLLEGE · PI BLACK, WILLIAM C, HILLNER, BRUCE ELLIS · 2010 to 2010
$2.0M
DEMOGRAPHY OF AGINGT32AG000177 · NIA · UNIVERSITY OF PENNSYLVANIA · PI KOHLER, HANS-PETER, PRESTON, SAMUEL H · 1989 to 2012
$1.5M
NCI NIH HHS RC2 CA148259NCI NIH HHS UC2 CA148259NIA NIH HHS T32 AG000177NICHD NIH HHS T32 HD007242
6 · The paper itself

Abstract

For over forty years, demographers have worked intensely to develop methods that assess a gain in life expectancy from a reduction in mortality, either hypothetical or observed. This considerable body of research was motivated by assessing the gains in life expectancy when mortality declined in a particular manner and determining the contribution of a cause of death in observed changes in life expectancy over time. As yet, there has been no framework unifying this important demographic work. In this paper, we provide a unifying framework for assessing the change in life expectancy given a change in age- and cause-specific mortality. We consider both conceptualizations of mortality change-counterfactual assessment of a hypothetical change and a retrospective assessment of an observed change. We apply our methodology to violent deaths, the leading cause of death among young adults, and show that realistic targeted reductions could have important impacts on life expectancy.

Indexed as

Life ExpectancyMathematicsMortalityAccidents, TrafficAdolescentAdultAgedAged, 80 and overAge DistributionAlgorithmsCause of DeathChildChild, PreschoolFemaleHomicideHumans

Identifiers

PMID21609727
PMCPMC3125714

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.