Evidence map›Paper›PMID 38779973›Full record

ArticleDemography2024

Estimating 1a0 and 4a1 in a Life Table: A Model Approach Based on Newly Collected Data.

Julio Romero-Prieto, Andrea Verhulst, Michel Guillot

Abstract read
In one paragraph

Article in Demography, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Julio Romero-PrietoDepartment of Population Health, London School of Hygiene and Tropical Medicine, London, UK.ORCID 0000-0002-8131-7821
Andrea VerhulstInstitut National d'Études Démographiques, Aubervilliers, France.ORCID 0000-0003-0571-1330
Michel GuillotPopulation Studies Center, University of Pennsylvania, Philadelphia, PA, USA; Institut National d'Études Démographiques, Aubervilliers, France.ORCID 0000-0001-5142-6835

Funding

Global Age Patterns of Under-Five MortalityR01HD090082 · NICHD · UNIVERSITY OF PENNSYLVANIA · PI GUILLOT, MICHEL · 2017 to 2021
$3.6M
NICHD NIH HHS R01 HD090082
6 · The paper itself

Abstract

The average age of infant deaths, a10, and the average number of years lived-in the age interval-by those dying between ages 1 and 5, a41, are important quantities allowing the construction of any life table including these ages. In many applications, the direct calculation of these parameters is not possible, so they are estimated using the infant mortality rate-or the death rate from 0 to 1-as a predictor. Existing methods are general approximations that do not consider the full variability in the age patterns of mortality below the age of 5. However, at the same level of mortality, under-five deaths can be more or less concentrated during the first weeks and months of life, thus resulting in very different values of a10 and a41. This article proposes an indirect estimation of these parameters by using a recently developed model of under-five mortality and taking advantage of a new, comprehensive database by detailed age-which is used for validation. The model adapts to a variety of inputs (e.g., rates, probabilities, or the proportion of deaths by sex or for both sexes combined), providing more flexibility for the users and increasing the precision of the estimates. This fresh perspective consolidates a new method that outperforms all previous approaches.

Indexed as

Infant MortalityLife TablesAge FactorsChild MortalityChild, PreschoolFemaleHumansInfantInfant, NewbornLife ExpectancyMaleModels, StatisticalDemographic estimationFormal demographyInfant and child mortalityLife table construction

Identifiers

PMID38779973
PMCPMC11463669

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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.