ReviewAging clinical and experimental research2023
Focus on age at death in field epidemiology.
Review in Aging clinical and experimental research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Ecological Correlates of Differences in Mean Age at Death Across Nearly Extinct Cohorts: The Role of Dietary Habits.Nutrients · 2026Observational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Age at death (AD) is an old metric recently re-evaluated for the study of longevity and mainly used in demography. Developed experience using AD in field epidemiology is summarized with cohorts followed-up for variable periods of time, frequently until extinction or close to extinction, a must to correctly adopt this metric. For practical purposes, a small number of examples is reported condensing previously published results to highlight various aspects of the problem. AD became the alternative of overall death rates when comparing cohorts reaching extinction or near extinction. AD was useful to characterize different causes of death in order to describe their natural history and possible etiology. With the use of multiple linear regression, a large number of possible determinants of AD were identified and some combinations of them resulted in large estimated differences in AD of 10 years or more across individuals. AD is a powerful tool to study population samples followed-up until extinction or near extinction. It allows to compare the life-long experience of different populations, to compare the role of different causes of death and to study the determinants of AD that are conditioning longevity.
Indexed as
Identifiers
37145267What OpenQuestion holds
Registered trials
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.