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Who died of what in rural KwaZulu-Natal, South Africa: a cause of death analysis using InterVA-4

BACKGROUND: For public health purposes, it is important to see whether men and women in different age groups die of the same causes in South Africa. OBJECTIVE: We explored sex- and age-specific patterns of causes of deaths in a rural demographic surveillance site in northern KwaZulu-Natal in South A...

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Autores principales: Mossong, Joël, Byass, Peter, Herbst, Kobus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Co-Action Publishing 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4220127/
https://www.ncbi.nlm.nih.gov/pubmed/25377332
http://dx.doi.org/10.3402/gha.v7.25496
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author Mossong, Joël
Byass, Peter
Herbst, Kobus
author_facet Mossong, Joël
Byass, Peter
Herbst, Kobus
author_sort Mossong, Joël
collection PubMed
description BACKGROUND: For public health purposes, it is important to see whether men and women in different age groups die of the same causes in South Africa. OBJECTIVE: We explored sex- and age-specific patterns of causes of deaths in a rural demographic surveillance site in northern KwaZulu-Natal in South Africa over the period 2000–2011. DESIGN: Deaths reported through the demographic surveillance were followed up by a verbal autopsy (VA) interview using a standardised questionnaire. Causes of death were assigned likelihoods using the publicly available tool InterVA-4. Cause-specific mortality fractions were determined by age and sex. RESULTS: Over the study period, a total of 5,416 (47%) and 6,081 (53%) deaths were recorded in men and women, respectively. Major causes of death proportionally affecting more women than men were (all p<0.0001): human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS) (20.1% vs. 13.6%), other and unspecified cardiac disease (5.9% vs. 3.2%), stroke (4.5% vs. 2.7%), reproductive neoplasms (1.7% vs. 0.4%), diabetes (2.4% vs. 1.2%), and breast neoplasms (0.4% vs. 0%). Major causes of deaths proportionally affecting more men than women were (all p<0.0001) assault (6.1% vs. 1.7%), pulmonary tuberculosis (34.5% vs. 30.2%), road traffic accidents (3.0% vs. 1.0%), intentional self-harm (1.3% vs. 0.3%), and respiratory neoplasms (2.5% vs. 1.5%). Causes of death due to communicable diseases predominated in all age groups except in older persons. CONCLUSIONS: While mortality during the 2000s was dominated by tuberculosis and HIV/AIDS, we found substantial sex-specific differences both for communicable and non-communicable causes of death, some which can be explained by a differing sex-specific age structure. InterVA-4 is likely to be a valuable tool for investigating causes of death patterns in other similar Southern African settings.
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spelling pubmed-42201272014-12-02 Who died of what in rural KwaZulu-Natal, South Africa: a cause of death analysis using InterVA-4 Mossong, Joël Byass, Peter Herbst, Kobus Glob Health Action Indepth Network Cause-Specific Mortality BACKGROUND: For public health purposes, it is important to see whether men and women in different age groups die of the same causes in South Africa. OBJECTIVE: We explored sex- and age-specific patterns of causes of deaths in a rural demographic surveillance site in northern KwaZulu-Natal in South Africa over the period 2000–2011. DESIGN: Deaths reported through the demographic surveillance were followed up by a verbal autopsy (VA) interview using a standardised questionnaire. Causes of death were assigned likelihoods using the publicly available tool InterVA-4. Cause-specific mortality fractions were determined by age and sex. RESULTS: Over the study period, a total of 5,416 (47%) and 6,081 (53%) deaths were recorded in men and women, respectively. Major causes of death proportionally affecting more women than men were (all p<0.0001): human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS) (20.1% vs. 13.6%), other and unspecified cardiac disease (5.9% vs. 3.2%), stroke (4.5% vs. 2.7%), reproductive neoplasms (1.7% vs. 0.4%), diabetes (2.4% vs. 1.2%), and breast neoplasms (0.4% vs. 0%). Major causes of deaths proportionally affecting more men than women were (all p<0.0001) assault (6.1% vs. 1.7%), pulmonary tuberculosis (34.5% vs. 30.2%), road traffic accidents (3.0% vs. 1.0%), intentional self-harm (1.3% vs. 0.3%), and respiratory neoplasms (2.5% vs. 1.5%). Causes of death due to communicable diseases predominated in all age groups except in older persons. CONCLUSIONS: While mortality during the 2000s was dominated by tuberculosis and HIV/AIDS, we found substantial sex-specific differences both for communicable and non-communicable causes of death, some which can be explained by a differing sex-specific age structure. InterVA-4 is likely to be a valuable tool for investigating causes of death patterns in other similar Southern African settings. Co-Action Publishing 2014-10-29 /pmc/articles/PMC4220127/ /pubmed/25377332 http://dx.doi.org/10.3402/gha.v7.25496 Text en © 2014 Joël Mossong et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Indepth Network Cause-Specific Mortality
Mossong, Joël
Byass, Peter
Herbst, Kobus
Who died of what in rural KwaZulu-Natal, South Africa: a cause of death analysis using InterVA-4
title Who died of what in rural KwaZulu-Natal, South Africa: a cause of death analysis using InterVA-4
title_full Who died of what in rural KwaZulu-Natal, South Africa: a cause of death analysis using InterVA-4
title_fullStr Who died of what in rural KwaZulu-Natal, South Africa: a cause of death analysis using InterVA-4
title_full_unstemmed Who died of what in rural KwaZulu-Natal, South Africa: a cause of death analysis using InterVA-4
title_short Who died of what in rural KwaZulu-Natal, South Africa: a cause of death analysis using InterVA-4
title_sort who died of what in rural kwazulu-natal, south africa: a cause of death analysis using interva-4
topic Indepth Network Cause-Specific Mortality
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4220127/
https://www.ncbi.nlm.nih.gov/pubmed/25377332
http://dx.doi.org/10.3402/gha.v7.25496
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