Evidence map›Paper›PMID 41994215›Full record

ArticleDemographic research

Jointly Estimating Subnational Mortality for Multiple Populations.

Ameer Dharamshi, Monica Alexander, Celeste Winant, Magali Barbieri

Abstract read
In one paragraph

Article in Demographic research. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Observational
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

4 authors.

Ameer DharamshiDepartment of Biostatistics, University of Washington, Seattle, USA.
Monica AlexanderDepartments of Statistics and Sociology, University of Toronto, Toronto, Canada.
Celeste WinantDepartment of Demography, University of California, Berkeley, USA.
Magali BarbieriDepartment of Demography, University of California, Berkeley, USA; Institut National d'Études Démographiques, Aubervilliers, France.

Funding

Program Development (Pilot)P30AG012839 · NIA · UNIVERSITY OF CALIFORNIA BERKELEY · PI RONALD D LEE · 1999 to 2026
$18.6M
NIA NIH HHS P30 AG012839
6 · The paper itself

Abstract

backgroundUnderstanding patterns in mortality across subpopulations is essential for local health policy decision making. One of the key challenges of subnational mortality rate estimation is the presence of small populations and zero or near zero death counts. When studying differences between subpopulations, this challenge is compounded as the small populations are further divided along socioeconomic or demographic lines.

objectiveWe aim to develop a model to estimate subnational age-specific mortality rates that accounts for the dependencies in mortality experiences across subpopulations.

methodsWe develop a Bayesian hierarchical principal components based model that models correlations across subpopulations.

resultsWe test this approach in a simulation study and also use the model to estimate age- and sex-specific mortality rates for counties in the United States. The model performs well in validation exercises and the US estimates suggest substantial variation in mortality trends over time across geographic lines.

Identifiers

PMID41994215
PMCPMC13082840

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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.