2000
DOI: 10.1093/gerona/55.8.b381
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Why Do Life Spans Differ? Partitioning Mean Longevity Differences in Terms of Age-Specific Mortality Parameters

Abstract: Populations typically differ in mean life spans because of genetic, environmental, or experimental factors. In this paper methods are presented that clarify the relationship between differences in the longevity of two populations and differences in their underlying age-specific patterns of mortality. Data are examined from rodent and fruit fly (Drosophila melanogaster) experiments that investigated the longevity effects of a variety of environmental and genetic manipulations, including temperature, dietary res… Show more

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Cited by 184 publications
(147 citation statements)
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“…For this reason, we examined the effect of diet on agespecific mortality rates and parameters. We used the freely available WinModest Demographic Analysis Tool, version 1.0.2 (Pletcher et al 2000), to fit the observed data to a class of mathematical models that assume an exponential rise in the mortality rate with increasing age, while allowing for age-independent and senescent changes in mortality rates. The program determines the model that best fits the observed data …”
Section: Food Intake Assessmentmentioning
confidence: 99%
See 1 more Smart Citation
“…For this reason, we examined the effect of diet on agespecific mortality rates and parameters. We used the freely available WinModest Demographic Analysis Tool, version 1.0.2 (Pletcher et al 2000), to fit the observed data to a class of mathematical models that assume an exponential rise in the mortality rate with increasing age, while allowing for age-independent and senescent changes in mortality rates. The program determines the model that best fits the observed data …”
Section: Food Intake Assessmentmentioning
confidence: 99%
“…Scatter plot of observed mortality rates -lnμ x (triangles) and projected mortality curves (lines) as a function of age. The projected mortality curves are fitted according to the parameters derived from the Gompertz-Makeham models given in Table 3 using a maximum likelihood procedure and facilitates hypothesis testing of whether the fitted models differ by experimental treatment (Pletcher 1999;Pletcher et al 2000). Mortality models fitted with the WinModest program established that the GompertzMakeham function provided the best fit model for all diets.…”
Section: Age (Days)mentioning
confidence: 99%
“…These methods were adapted for climbing speed from techniques developed for analysis of general demographic data (Pletcher et al 2000;Horiuchi et al 2008). In brief, the total distance climbed was decomposed into an additive function of latency and climbing speed.…”
Section: Decomposition Analysesmentioning
confidence: 99%
“…In brief, the total distance climbed was decomposed into an additive function of latency and climbing speed. If D = (4−l)s, where D is the total distance traveled in 4 seconds, l is the response latency, and s is the climbing speed, then the difference in negative geotaxis measures between two ages or genotypes can be broken down into additive contributions from l and s as In practice, the contribution from each parameter to the total difference in negative geotaxis was calculated based on the aggregate from a series of sub intervals, which allows an arbitrary degree of accuracy to be obtained (Pletcher et al 2000). Decomposition values are represented as the percentage contribution to the total difference in negative geotaxis.…”
Section: Decomposition Analysesmentioning
confidence: 99%
“…For rats, it is clear that dietary restriction (DR) decreases senescence [3] (Yen et al unpublished) but not initial mortality rate, but for mice and fruit flies, the relationship is more ambiguous. One study has shown that DR in fruit flies decreases initial mortality rate and not the agedependent acceleration of mortality rate [4], but another study in flies suggests the opposite [5].…”
Section: Introductionmentioning
confidence: 99%