Evidence map›Paper›PMID 34653419›Full record

ArticleThe Lancet. Public health2021

Life expectancy and risk of death in 6791 communities in England from 2002 to 2019: high-resolution spatiotemporal analysis of civil registration data.

Theo Rashid, James E Bennett, Christopher J Paciorek, Yvonne Doyle, Jonathan Pearson-Stuttard, Seth Flaxman, Daniela Fecht, Mireille B Toledano, Guangquan Li, Hima I Daby and 3 more

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In one paragraph

Article in The Lancet. Public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 2 pooled it
–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

35 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Is Austerity Responsible for the Stalled Mortality Trends Across Many High-Income Countries? A Systematic Review.International journal of social determinants of health and health services · 2024
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  20. Lifehistory Trade-Offs Influence Women's Reproductive Strategies.Adaptive human behavior and physiology · 2024
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors.

Theo RashidDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK.
James E BennettDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK.
Christopher J PaciorekDepartment of Statistics, University of California, Berkeley, CA, USA.
Yvonne DoyleLondon School of Hygiene & Tropical Medicine, London, UK.
Jonathan Pearson-StuttardDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK.
Seth FlaxmanDepartment of Computer Science, University of Oxford, Oxford, UK.
Daniela FechtDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK; UK Small Area Health Statistics Unit, Imperial College London, London, UK.
Mireille B ToledanoDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK; Mohn Centre for Children's Health and Wellbeing, School of Public Health, Imperial College London, London, UK.
Guangquan LiDepartment of Mathematics, Physics and Electrical Engineering, Northumbria University, Newcastle-upon-Tyne, UK.
Hima I DabyDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK; UK Small Area Health Statistics Unit, Imperial College London, London, UK.
Eric JohnsonDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK; UK Small Area Health Statistics Unit, Imperial College London, London, UK.
Bethan DaviesDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK; UK Small Area Health Statistics Unit, Imperial College London, London, UK.
Majid EzzatiDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK; Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK; Regional Institute for Population Studies, University of Ghana, Accra, Ghana. Electronic address: majid.ezzati@imperial.ac.uk.

Funding

Medical Research Council MR/L01341X/1Medical Research Council MR/T03226X/1
6 · The paper itself

Abstract

backgroundHigh-resolution data for how mortality and longevity have changed in England, UK are scarce. We aimed to estimate trends from 2002 to 2019 in life expectancy and probabilities of death at different ages for all 6791 middle-layer super output areas (MSOAs) in England.

methodsWe performed a high-resolution spatiotemporal analysis of civil registration data from the UK Small Area Health Statistics Unit research database using de-identified data for all deaths in England from 2002 to 2019, with information on age, sex, and MSOA of residence, and population counts by age, sex, and MSOA. We used a Bayesian hierarchical model to obtain estimates of age-specific death rates by sharing information across age groups, MSOAs, and years. We used life table methods to calculate life expectancy at birth and probabilities of death in different ages by sex and MSOA.

findingsIn 2002-06 and 2006-10, all but a few (0-1%) MSOAs had a life expectancy increase for female and male sexes. In 2010-14, female life expectancy decreased in 351 (5·2%) of 6791 MSOAs. By 2014-19, the number of MSOAs with declining life expectancy was 1270 (18·7%) for women and 784 (11·5%) for men. The life expectancy increase from 2002 to 2019 was smaller in MSOAs where life expectancy had been lower in 2002 (mostly northern urban MSOAs), and larger in MSOAs where life expectancy had been higher in 2002 (mostly MSOAs in and around London). As a result of these trends, the gap between the first and 99th percentiles of MSOA life expectancy for women increased from 10·7 years (95% credible interval 10·4-10·9) in 2002 to reach 14·2 years (13·9-14·5) in 2019, and for men increased from 11·5 years (11·3-11·7) in 2002 to 13·6 years (13·4-13·9) in 2019.

interpretationIn the decade before the COVID-19 pandemic, life expectancy declined in increasing numbers of communities in England. To ensure that this trend does not continue or worsen, there is a need for pro-equity economic and social policies, and greater investment in public health and health care throughout the entire country.

fundingWellcome Trust, Imperial College London, Medical Research Council, Health Data Research UK, and National Institutes of Health Research.

Indexed as

AdolescentAdultAgedAged, 80 and overBayes TheoremChildChild, PreschoolEnglandFemaleHumansInfantInfant, NewbornLife ExpectancyMaleMiddle AgedMortality

Identifiers

PMID34653419
PMCPMC8554392

What OpenQuestion holds

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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.