Evidence map›Paper›PMID 39030059›Full record

ArticleThe Lancet. Global health2024

Temporal changes in cause of death among adolescents and adults in six countries in eastern and southern Africa in 1995-2019: a multi-country surveillance study of verbal autopsy data.

Yue Chu, Milly Marston, Albert Dube, Charles Festo, Eveline Geubbels, Simon Gregson, Kobus Herbst, Chodziwadziwa Kabudula, Kathleen Kahn, Tom Lutalo and 9 more

Erratum issuedAbstract read
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Article in The Lancet. Global health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

19 authors.

Yue ChuDepartment of Sociology, The Ohio State University, Columbus, OH, USA; Institute for Population Research, The Ohio State University, Columbus, OH, USA; Translational Data Analytics Institute, The Ohio State University, Columbus, OH, USA. Electronic address: chu.282@osu.edu.
Milly MarstonDepartment of Population Health, London School of Hygiene & Tropical Medicine, London, UK.
Albert DubeMalawi Epidemiology and Intervention Research Unit, Karonga, Malawi.
Charles FestoHealth System, Impact Evaluation and Policy Department, Ifakara Health Institute, Ifakara, Tanzania.
Eveline GeubbelsHealth System, Impact Evaluation and Policy Department, Ifakara Health Institute, Ifakara, Tanzania.
Simon GregsonMRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK; Manicaland Centre for Public Health Research, Biomedical Research and Training Institute, Harare, Zimbabwe.
Kobus HerbstAfrica Health Research Institute, KwaZulu-Natal, Durban, South Africa; Department of Science and Innovation-Medical Research Council South African Population Research Infrastructure Network, Durban, South Africa.
Chodziwadziwa KabudulaMRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of Witwatersrand, Johannesburg, South Africa.
Kathleen KahnMRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of Witwatersrand, Johannesburg, South Africa.
Tom LutaloRakai Health Sciences Program, Kalisizo, Uganda.
Louisa MoorhouseMRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK.
Robert NewtonMedical Research Council/Uganda Virus Research Institute and London School of Hygiene & Tropical Medicine Uganda Research Unit, Entebbe, Uganda; Department of Health Sciences, University of York, York, UK.
Constance NyamukapaMRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK; Manicaland Centre for Public Health Research, Biomedical Research and Training Institute, Harare, Zimbabwe.
Ronald MakangaMedical Research Council/Uganda Virus Research Institute and London School of Hygiene & Tropical Medicine Uganda Research Unit, Entebbe, Uganda.
Emma SlaymakerDepartment of Population Health, London School of Hygiene & Tropical Medicine, London, UK.
Mark UrassaNational Institute for Medical Research, Mwanza Centre, Mwanza, Tanzania.
Abdhalah ZirabaAfrican Population and Health Research Center, Nairobi, Kenya.
Clara CalvertDepartment of Population Health, London School of Hygiene & Tropical Medicine, London, UK; Usher Institute, University of Edinburgh, Edinburgh, UK.
Samuel J ClarkDepartment of Sociology, The Ohio State University, Columbus, OH, USA; Institute for Population Research, The Ohio State University, Columbus, OH, USA; Translational Data Analytics Institute, The Ohio State University, Columbus, OH, USA; MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of Witwatersrand, Johannesburg, South Africa.

Funding

Verbal Autopsy: Reimagining Data & Automated Cause Assignment (using ALPHA Network data)R01HD086227 · NICHD · OHIO STATE UNIVERSITY · PI CLARK, SAMUEL J · 2016 to 2021
$2.4M
Medical Research Council MC_UU_00033/1NICHD NIH HHS R01 HD086227Wellcome Trust
6 · The paper itself

Abstract

backgroundThe absence of high-quality comprehensive civil registration and vital statistics systems across many settings in Africa has led to little empirical data on causes of death in the region. We aimed to use verbal autopsy data to provide comparative, population-based estimates of cause-specific mortality among adolescents and adults in eastern and southern Africa.

methodsIn this surveillance study, we harmonised verbal autopsy and residency data from nine health and demographic surveillance system (HDSS) sites in Kenya, Malawi, Tanzania, South Africa, Uganda, and Zimbabwe, each with variable coverage from Jan 1, 1995, to Dec 31, 2019. We included all deaths to adolescents and adults aged 12 or over that were residents of the study sites and had a verbal autopsy conducted. InSilicoVA, a probabilistic model, was used to assign cause of death on the basis of the signs and symptoms reported in the verbal autopsy. Levels and trends in all-cause and cause-specific mortality rates and cause-specific mortality fractions were calculated, stratified by HDSS site, sex, age, and calendar periods.

findings52 484 deaths and 5 157 802 person-years were reported among 1 071 913 individuals across the nine sites during the study period. 47 961 (91·4%) deaths had a verbal autopsy, of which 46 570 (97·1%) were assigned a cause of death. All-cause mortality generally decreased across the HDSS sites during this period, particularly for adults aged 20-59 years. In many of the HDSS sites, these decreases were driven by reductions in HIV and tuberculosis-related deaths. In 2010-14, the top causes of death were: road traffic accidents, HIV or tuberculosis, and meningitis or sepsis in adolescents (12-19 years); HIV or tuberculosis in adults aged 20-59 years; and neoplasms and cardiovascular disease in adults aged 60 years and older. There was greater between-HDSS and between-sex variation in causes of death for adolescents compared with adults.

interpretationThis study shows progress in reducing mortality across eastern and southern Africa but also highlights age, sex, within-HDSS, and between-HDSS differences in causes of adolescent and adult deaths. These findings highlight the importance of detailed local data to inform health needs to ensure continued improvements in survival.

fundingNational Institute of Child Health and Human Development of the US National Institutes of Health.

Indexed as

AutopsyCause of DeathAdolescentAdultAfrica, EasternAfrica, SouthernChildFemaleHumansKenyaMalawiMaleMiddle AgedPopulation SurveillanceSouth AfricaTanzania

Identifiers

PMID39030059
PMCPMC11416856

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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.