ArticleDemography2018
Separating the Signal From the Noise: Evidence for Deceleration in Old-Age Death Rates.
Article in Demography, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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
9 citing papers in PubMed.
- Global evidence for bounded human lifespan growth.Biogerontology · 2026Article
- Gerontology lost in translation from demography to biology of aging and back.Biogerontology · 2026Review
- Exploring Patterns of Human Mortality and Aging: A Reliability Theory Viewpoint.Biochemistry. Biokhimiia · 2024Review
- Article
- Information measures and design issues in the study of mortality deceleration: findings for the gamma-Gompertz model.Lifetime data analysis · 2021Article
- Comparative analysis of completeness of death registration, adult mortality and life expectancy at birth in Brazil at the subnational level.Population health metrics · 2020Article
- Late-life mortality is underestimated because of data errors.PLoS biology · 2019Article
- Review
- Probabilistic forecasting of maximum human lifespan by 2100 using Bayesian population projections.Demographic researchArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
Abstract
Widespread population aging has made it critical to understand death rates at old ages. However, studying mortality at old ages is challenging because the data are sparse: numbers of survivors and deaths get smaller and smaller with age. I show how to address this challenge by using principled model selection techniques to empirically evaluate theoretical mortality models. I test nine models of old-age death rates by fitting them to 360 high-quality data sets on cohort mortality after age 80. Models that allow for the possibility of decelerating death rates tend to fit better than models that assume exponentially increasing death rates. No single model is capable of universally explaining observed old-age mortality patterns, but the log-quadratic model most consistently predicts well. Patterns of model fit differ by country and sex. I discuss possible mechanisms, including sample size, period effects, and regional or cultural factors that may be important keys to understanding patterns of old-age mortality. I introduce mortfit, a freely available R package that enables researchers to extend the analysis to other models, age ranges, and data sources.
Indexed as
Identifiers
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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.