Evidence map›Paper›PMID 38666633›Full record

ArticlePopulation studies2025

Method for redistributing ill-defined causes of death.

Pavel Grigoriev, Florian Bonnet, Elsa Perdrix

Abstract read
In one paragraph

Article in Population studies, 2025. 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. Article
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

3 authors.

Pavel GrigorievFederal Institute for Population Research.ORCID 0000-0003-1419-9885
Florian BonnetFrench Institute for Demographic Studies.ORCID 0000-0001-6125-3317
Elsa PerdrixUniversité Paris Dauphine.ORCID 0000-0002-9836-3269

Funding

European Research Council under the European Union’s Horizon 2020 research and innovation programme GRANT AGREEMENT NUMBER 851485
6 · The paper itself

Abstract

Analysis of causes of death is crucial for monitoring an epidemiological situation and for developing adequate policy responses. However, the comparability of cause-specific mortality data depends on the proportion of ill-defined deaths. To eliminate the bias resulting from the varying proportions of such causes over time and between populations, deaths from ill-defined causes need to be reassigned to other categories. We provide thorough documentation of and tools for the practical implementation of a regression-based method for redistributing ill-defined causes of death, as first proposed by Sully Ledermann in the 1950s. The method relies on subnational cause-specific mortality data to estimate unbiased death rates at both national and subnational levels. We refine Ledermann's method by elaborating on its mathematical properties, making additional adjustments, and evaluating the performance of the approach through simulations. To illustrate the practical application of the method, we rely on French subnational cause-of-death data and provide the R code for performing all calculations.

Indexed as

Cause of DeathFranceHumansModels, StatisticalRegression Analysisill-defined causes of deathmethod of redistributionmortality

Identifiers

PMID38666633
PMCPMC11956782

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.