Evidence map›Paper›PMID 37700289›Full record

ArticlePopulation health metrics2023

Flexible parametric methods for calculating life expectancy in small populations.

Freya Tyrer, Yogini V Chudasama, Paul C Lambert, Mark J Rutherford

Abstract read
In one paragraph

Article in Population health metrics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Freya TyrerBiostatistics Research Group, Department of Population Health Sciences, George Davies Centre, University of Leicester, University Road, Leicester, LE1 7RH, UK. fct2@le.ac.uk.
Yogini V ChudasamaLeicester Real World Evidence Unit, Diabetes Research Centre, University of Leicester, Leicester, UK.
Paul C LambertBiostatistics Research Group, Department of Population Health Sciences, George Davies Centre, University of Leicester, University Road, Leicester, LE1 7RH, UK.
Mark J RutherfordBiostatistics Research Group, Department of Population Health Sciences, George Davies Centre, University of Leicester, University Road, Leicester, LE1 7RH, UK.

Funding

Department of Health
6 · The paper itself

Abstract

backgroundLife expectancy is a simple measure of assessing health differences between two or more populations but current life expectancy calculations are not reliable for small populations. A potential solution to this is to borrow strength from larger populations from the same source, but this has not formally been investigated.

methodsUsing data on 451,222 individuals from the Clinical Practice Research Datalink on the presence/absence of intellectual disability and type 2 diabetes mellitus, we compared stratified and combined flexible parametric models, and Chiang's methods, for calculating life expectancy. Confidence intervals were calculated using the Delta method, Chiang's adjusted life table approach and bootstrapping.

resultsThe flexible parametric models allowed calculation of life expectancy by exact age and beyond traditional life expectancy age thresholds. The combined model that fit age interaction effects as a spline term provided less bias and greater statistical precision for small covariate subgroups by borrowing strength from the larger subgroups. However, careful consideration of the distribution of events in the smallest group was needed.

conclusionsLife expectancy is a simple measure to compare health differences between populations. The use of combined flexible parametric methods to calculate life expectancy in small samples has shown promising results by allowing life expectancy to be modelled by exact age, greater statistical precision, less bias and prediction of different covariate patterns without stratification. We recommend further investigation of their application for both policymakers and researchers.

Indexed as

Diabetes Mellitus, Type 2HumansLife ExpectancyLife TablesChiangElectronic health recordsEpidemiologyFlexible parametric methodsLife expectancyObservational studies

Identifiers

PMID37700289
PMCPMC10498577

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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.