Literature DB >> 9314796

Quantifying the future impact of disease on society: life table-based measures of potential life lost.

W C Lee1.   

Abstract

OBJECTIVES: Quantifying health status in human populations by means of an index such as "years of potential life lost" has recently received attention. However, such an index, being cross-sectional in nature, only measures the current burden to society resulting from a specific cause of death.
METHODS: The author proposes new indices of potential life lost to quantify future impacts on society of particular causes of death. These indices also properly reflect the effects of competing risks. The computation is simple, requiring no more than a standard life-table calculation. Real-world as well as hypothetical data are used to illustrate the method.
RESULTS: The new indices convey valuable health status information about a population that is not revealed by traditional indices.
CONCLUSIONS: The new indices are promising alternatives as measures of future potential life lost.

Entities:  

Mesh:

Year:  1997        PMID: 9314796      PMCID: PMC1380969          DOI: 10.2105/ajph.87.9.1456

Source DB:  PubMed          Journal:  Am J Public Health        ISSN: 0090-0036            Impact factor:   9.308


  9 in total

1.  Years of potential life lost (YPLL)--what does it measure?

Authors:  J W Gardner; J S Sanborn
Journal:  Epidemiology       Date:  1990-07       Impact factor: 4.822

Review 2.  Competing risks in mortality analysis.

Authors:  C L Chiang
Journal:  Annu Rev Public Health       Date:  1991       Impact factor: 21.981

3.  Estimating life expectancy using an age-cohort model in Taiwan.

Authors:  W C Lee; R L Hsieh
Journal:  J Epidemiol Community Health       Date:  1996-04       Impact factor: 3.710

4.  Potential years of life lost: what is the denominator?

Authors:  A K Marlow
Journal:  J Epidemiol Community Health       Date:  1995-06       Impact factor: 3.710

5.  Disability and the years of potential productivity lost: modifying the years of potential life lost and the investment-production-consumer model by disability level.

Authors:  S Linn; S Sheps
Journal:  Epidemiology       Date:  1993-09       Impact factor: 4.822

6.  Methods for age-adjustment of rates.

Authors:  H Inskip; V Beral; P Fraser; J Haskey
Journal:  Stat Med       Date:  1983 Oct-Dec       Impact factor: 2.373

7.  Changes in life expectancy in the United States due to declines in mortality, 1968-1975.

Authors:  S P Tsai; E S Lee; J A Kautz
Journal:  Am J Epidemiol       Date:  1982-08       Impact factor: 4.897

8.  The effect of a reduction in leading causes of death: potential gains in life expectancy.

Authors:  S P Tsai; E S Lee; R J Hardy
Journal:  Am J Public Health       Date:  1978-10       Impact factor: 9.308

9.  Cohort-specific risks of developing breast cancer to age 85 in Connecticut.

Authors:  M K Campbell; E J Feuer; L M Wun
Journal:  Epidemiology       Date:  1994-05       Impact factor: 4.822

  9 in total
  2 in total

1.  Inequalities in health. Analytic approaches based on life expectancy and suitable for small area comparisons.

Authors:  P J Veugelers; A L Kim; J R Guernsey
Journal:  J Epidemiol Community Health       Date:  2000-05       Impact factor: 3.710

2.  The contribution of specific causes of death to sex differences in mortality.

Authors:  Mitchell D Wong; Anne K Chung; W John Boscardin; Ming Li; Hsin-ju Hsieh; Susan L Ettner; Martin F Shapiro
Journal:  Public Health Rep       Date:  2006 Nov-Dec       Impact factor: 2.792

  2 in total

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