Evidence map›Paper›PMID 34479953›Full record

ArticleBMJ global health2021

Who dies where? Estimating the percentage of deaths that occur at home.

Tim Adair

Abstract read
In one paragraph

Article in BMJ global health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing 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

32 citing papers in PubMed.

  1. Article
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  3. Quality of Medical Certification of Cause of Death in a City of Assam.Indian journal of community medicine : official publication of Indian Association of Preventive & Social Medicine · 2026
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  4. Review
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  6. Trends in place of death in Peru, 2017-2024: a nationwide analysis.Archives of public health = Archives belges de sante publique · 2026
    Article
  7. Article
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  9. Turning toward mortality: yoga'sFrontiers in public health · 2026
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  12. Review
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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

1 author.

Tim AdairMelbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia timothy.adair@unimelb.edu.au.ORCID 0000-0002-1562-4452

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe majority of low-income and middle-income countries (LMICs) have incomplete death registration systems and so the proportion of deaths that occur at home (ie, home death percentage) is generally unknown. However, home death percentage is important to estimate population-level causes of death from integration of data of deaths at home (verbal autopsies) and in hospitals (medical certification), and to monitor completeness of death notification and verbal autopsy data collection systems. This study proposes a method to estimate home death percentage using data readily available at the national and subnational level.

methodsData on place of death from 152 country-years in 49 countries from 2005 to 2019, predominantly from vital registration systems, were used to model home death percentage standardised for population age and cause distribution. A national-level model was developed using Bayesian model averaging to estimate national, regional and global home death percentage. A subnational-level model was also developed and assessed in populations where alternative data on home death percentage were available.

resultsGlobally, it is estimated that 53.4% (95% uncertainty interval (UI) 50.8%-55.9%) of deaths occur at home, slightly higher (59.7%, 95% UI 56.5%-62.7%) in LMICs, substantially higher in low-income countries (79.5%, 95% UI 77.3%-81.5%) and much lower (27.3%, 95% UI 25.2%-29.6%) in high-income countries. Countries with the highest home death percentage are mostly found in South, East and Southeast Asia and sub-Saharan Africa (above 90% in Ethiopia, Chad and South Sudan). As expected, the national model has smaller error than the subnational model.

conclusionThe study demonstrates substantial diversity in the location of deaths in LMICs and fills a significant gap in knowledge about where people die, given its importance for health systems and policies. The high proportion of deaths in LMICs that occur at home reinforces the need for routine verbal autopsy to determine the causes of death.

Indexed as

Global HealthBayes TheoremEthiopiaHumanshealth systemsindices of health and disease and standardisation of ratesmedical demographypublic health

Identifiers

PMID34479953
PMCPMC8420738

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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.