Mortality trends and differentials in South Africa from 1997 to 2012: second National Burden of Disease Study

The poor health of South Africans is known to be associated with a quadruple disease burden. In the second National Burden of Disease (NBD) study, we aimed to analyse cause of death data for 1997–2012 and develop national, population group, and provincial estimates of the levels and causes of mortal...

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Veröffentlicht in:The Lancet global health Jg. 4; H. 9; S. e642 - e653
Hauptverfasser: Pillay-van Wyk, Victoria, Msemburi, William, Laubscher, Ria, Dorrington, Rob E, Groenewald, Pam, Glass, Tracy, Nojilana, Beatrice, Joubert, Jané D, Matzopoulos, Richard, Prinsloo, Megan, Nannan, Nadine, Gwebushe, Nomonde, Vos, Theo, Somdyala, Nontuthuzelo, Sithole, Nomfuneko, Neethling, Ian, Nicol, Edward, Rossouw, Anastasia, Bradshaw, Debbie
Format: Journal Article
Sprache:Englisch
Veröffentlicht: England Elsevier Ltd 01.09.2016
Elsevier
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ISSN:2214-109X, 2214-109X
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Abstract The poor health of South Africans is known to be associated with a quadruple disease burden. In the second National Burden of Disease (NBD) study, we aimed to analyse cause of death data for 1997–2012 and develop national, population group, and provincial estimates of the levels and causes of mortality. We used underlying cause of death data from death notifications for 1997–2012 obtained from Statistics South Africa. These data were adjusted for completeness using indirect demographic techniques for adults and comparison with survey and census estimates for child mortality. A regression approach was used to estimate misclassified HIV/AIDS deaths and so-called garbage codes were proportionally redistributed by age, sex, and population group population group (black African, Indian or Asian descent, white [European descent], and coloured [of mixed ancestry according to the preceding categories]). Injury deaths were estimated from additional data sources. Age-standardised death rates were calculated with mid-year population estimates and the WHO age standard. Institute of Health Metrics and Evaluation Global Burden of Disease (IHME GBD) estimates for South Africa were obtained from the IHME GHDx website for comparison. All-cause age-standardised death rates increased rapidly since 1997, peaked in 2006 and then declined, driven by changes in HIV/AIDS. Mortality from tuberculosis, non-communicable diseases, and injuries decreased slightly. In 2012, HIV/AIDS caused the most deaths (29·1%) followed by cerebrovascular disease (7·5%) and lower respiratory infections (4·9%). All-cause age-standardised death rates were 1·7 times higher in the province with the highest death rate compared to the province with the lowest death rate, 2·2 times higher in black Africans compared to whites, and 1·4 times higher in males compared with females. Comparison with the IHME GBD estimates for South Africa revealed substantial differences for estimated deaths from all causes, particularly HIV/AIDS and interpersonal violence. This study shows the reversal of HIV/AIDS, non-communicable disease, and injury mortality trends in South Africa during the study period. Mortality differentials show the importance of social determinants, raise concerns about the quality of health services, and provide relevant information to policy makers for addressing inequalities. Differences between GBD estimates for South Africa and this study emphasise the need for more careful calibration of global models with local data. South African Medical Research Council's Flagships Awards Project.
AbstractList The poor health of South Africans is known to be associated with a quadruple disease burden. In the second National Burden of Disease (NBD) study, we aimed to analyse cause of death data for 1997–2012 and develop national, population group, and provincial estimates of the levels and causes of mortality. We used underlying cause of death data from death notifications for 1997–2012 obtained from Statistics South Africa. These data were adjusted for completeness using indirect demographic techniques for adults and comparison with survey and census estimates for child mortality. A regression approach was used to estimate misclassified HIV/AIDS deaths and so-called garbage codes were proportionally redistributed by age, sex, and population group population group (black African, Indian or Asian descent, white [European descent], and coloured [of mixed ancestry according to the preceding categories]). Injury deaths were estimated from additional data sources. Age-standardised death rates were calculated with mid-year population estimates and the WHO age standard. Institute of Health Metrics and Evaluation Global Burden of Disease (IHME GBD) estimates for South Africa were obtained from the IHME GHDx website for comparison. All-cause age-standardised death rates increased rapidly since 1997, peaked in 2006 and then declined, driven by changes in HIV/AIDS. Mortality from tuberculosis, non-communicable diseases, and injuries decreased slightly. In 2012, HIV/AIDS caused the most deaths (29·1%) followed by cerebrovascular disease (7·5%) and lower respiratory infections (4·9%). All-cause age-standardised death rates were 1·7 times higher in the province with the highest death rate compared to the province with the lowest death rate, 2·2 times higher in black Africans compared to whites, and 1·4 times higher in males compared with females. Comparison with the IHME GBD estimates for South Africa revealed substantial differences for estimated deaths from all causes, particularly HIV/AIDS and interpersonal violence. This study shows the reversal of HIV/AIDS, non-communicable disease, and injury mortality trends in South Africa during the study period. Mortality differentials show the importance of social determinants, raise concerns about the quality of health services, and provide relevant information to policy makers for addressing inequalities. Differences between GBD estimates for South Africa and this study emphasise the need for more careful calibration of global models with local data. South African Medical Research Council's Flagships Awards Project.
The poor health of South Africans is known to be associated with a quadruple disease burden. In the second National Burden of Disease (NBD) study, we aimed to analyse cause of death data for 1997-2012 and develop national, population group, and provincial estimates of the levels and causes of mortality.BACKGROUNDThe poor health of South Africans is known to be associated with a quadruple disease burden. In the second National Burden of Disease (NBD) study, we aimed to analyse cause of death data for 1997-2012 and develop national, population group, and provincial estimates of the levels and causes of mortality.We used underlying cause of death data from death notifications for 1997-2012 obtained from Statistics South Africa. These data were adjusted for completeness using indirect demographic techniques for adults and comparison with survey and census estimates for child mortality. A regression approach was used to estimate misclassified HIV/AIDS deaths and so-called garbage codes were proportionally redistributed by age, sex, and population group population group (black African, Indian or Asian descent, white [European descent], and coloured [of mixed ancestry according to the preceding categories]). Injury deaths were estimated from additional data sources. Age-standardised death rates were calculated with mid-year population estimates and the WHO age standard. Institute of Health Metrics and Evaluation Global Burden of Disease (IHME GBD) estimates for South Africa were obtained from the IHME GHDx website for comparison.METHODWe used underlying cause of death data from death notifications for 1997-2012 obtained from Statistics South Africa. These data were adjusted for completeness using indirect demographic techniques for adults and comparison with survey and census estimates for child mortality. A regression approach was used to estimate misclassified HIV/AIDS deaths and so-called garbage codes were proportionally redistributed by age, sex, and population group population group (black African, Indian or Asian descent, white [European descent], and coloured [of mixed ancestry according to the preceding categories]). Injury deaths were estimated from additional data sources. Age-standardised death rates were calculated with mid-year population estimates and the WHO age standard. Institute of Health Metrics and Evaluation Global Burden of Disease (IHME GBD) estimates for South Africa were obtained from the IHME GHDx website for comparison.All-cause age-standardised death rates increased rapidly since 1997, peaked in 2006 and then declined, driven by changes in HIV/AIDS. Mortality from tuberculosis, non-communicable diseases, and injuries decreased slightly. In 2012, HIV/AIDS caused the most deaths (29·1%) followed by cerebrovascular disease (7·5%) and lower respiratory infections (4·9%). All-cause age-standardised death rates were 1·7 times higher in the province with the highest death rate compared to the province with the lowest death rate, 2·2 times higher in black Africans compared to whites, and 1·4 times higher in males compared with females. Comparison with the IHME GBD estimates for South Africa revealed substantial differences for estimated deaths from all causes, particularly HIV/AIDS and interpersonal violence.FINDINGSAll-cause age-standardised death rates increased rapidly since 1997, peaked in 2006 and then declined, driven by changes in HIV/AIDS. Mortality from tuberculosis, non-communicable diseases, and injuries decreased slightly. In 2012, HIV/AIDS caused the most deaths (29·1%) followed by cerebrovascular disease (7·5%) and lower respiratory infections (4·9%). All-cause age-standardised death rates were 1·7 times higher in the province with the highest death rate compared to the province with the lowest death rate, 2·2 times higher in black Africans compared to whites, and 1·4 times higher in males compared with females. Comparison with the IHME GBD estimates for South Africa revealed substantial differences for estimated deaths from all causes, particularly HIV/AIDS and interpersonal violence.This study shows the reversal of HIV/AIDS, non-communicable disease, and injury mortality trends in South Africa during the study period. Mortality differentials show the importance of social determinants, raise concerns about the quality of health services, and provide relevant information to policy makers for addressing inequalities. Differences between GBD estimates for South Africa and this study emphasise the need for more careful calibration of global models with local data.INTERPRETATIONThis study shows the reversal of HIV/AIDS, non-communicable disease, and injury mortality trends in South Africa during the study period. Mortality differentials show the importance of social determinants, raise concerns about the quality of health services, and provide relevant information to policy makers for addressing inequalities. Differences between GBD estimates for South Africa and this study emphasise the need for more careful calibration of global models with local data.South African Medical Research Council's Flagships Awards Project.FUNDINGSouth African Medical Research Council's Flagships Awards Project.
Summary Background The poor health of South Africans is known to be associated with a quadruple disease burden. In the second National Burden of Disease (NBD) study, we aimed to analyse cause of death data for 1997–2012 and develop national, population group, and provincial estimates of the levels and causes of mortality. Method We used underlying cause of death data from death notifications for 1997–2012 obtained from Statistics South Africa. These data were adjusted for completeness using indirect demographic techniques for adults and comparison with survey and census estimates for child mortality. A regression approach was used to estimate misclassified HIV/AIDS deaths and so-called garbage codes were proportionally redistributed by age, sex, and population group population group (black African, Indian or Asian descent, white [European descent], and coloured [of mixed ancestry according to the preceding categories]). Injury deaths were estimated from additional data sources. Age-standardised death rates were calculated with mid-year population estimates and the WHO age standard. Institute of Health Metrics and Evaluation Global Burden of Disease (IHME GBD) estimates for South Africa were obtained from the IHME GHDx website for comparison. Findings All-cause age-standardised death rates increased rapidly since 1997, peaked in 2006 and then declined, driven by changes in HIV/AIDS. Mortality from tuberculosis, non-communicable diseases, and injuries decreased slightly. In 2012, HIV/AIDS caused the most deaths (29·1%) followed by cerebrovascular disease (7·5%) and lower respiratory infections (4·9%). All-cause age-standardised death rates were 1·7 times higher in the province with the highest death rate compared to the province with the lowest death rate, 2·2 times higher in black Africans compared to whites, and 1·4 times higher in males compared with females. Comparison with the IHME GBD estimates for South Africa revealed substantial differences for estimated deaths from all causes, particularly HIV/AIDS and interpersonal violence. Interpretation This study shows the reversal of HIV/AIDS, non-communicable disease, and injury mortality trends in South Africa during the study period. Mortality differentials show the importance of social determinants, raise concerns about the quality of health services, and provide relevant information to policy makers for addressing inequalities. Differences between GBD estimates for South Africa and this study emphasise the need for more careful calibration of global models with local data. Funding South African Medical Research Council's Flagships Awards Project.
Background: The poor health of South Africans is known to be associated with a quadruple disease burden. In the second National Burden of Disease (NBD) study, we aimed to analyse cause of death data for 1997–2012 and develop national, population group, and provincial estimates of the levels and causes of mortality. Method: We used underlying cause of death data from death notifications for 1997–2012 obtained from Statistics South Africa. These data were adjusted for completeness using indirect demographic techniques for adults and comparison with survey and census estimates for child mortality. A regression approach was used to estimate misclassified HIV/AIDS deaths and so-called garbage codes were proportionally redistributed by age, sex, and population group population group (black African, Indian or Asian descent, white [European descent], and coloured [of mixed ancestry according to the preceding categories]). Injury deaths were estimated from additional data sources. Age-standardised death rates were calculated with mid-year population estimates and the WHO age standard. Institute of Health Metrics and Evaluation Global Burden of Disease (IHME GBD) estimates for South Africa were obtained from the IHME GHDx website for comparison. Findings: All-cause age-standardised death rates increased rapidly since 1997, peaked in 2006 and then declined, driven by changes in HIV/AIDS. Mortality from tuberculosis, non-communicable diseases, and injuries decreased slightly. In 2012, HIV/AIDS caused the most deaths (29·1%) followed by cerebrovascular disease (7·5%) and lower respiratory infections (4·9%). All-cause age-standardised death rates were 1·7 times higher in the province with the highest death rate compared to the province with the lowest death rate, 2·2 times higher in black Africans compared to whites, and 1·4 times higher in males compared with females. Comparison with the IHME GBD estimates for South Africa revealed substantial differences for estimated deaths from all causes, particularly HIV/AIDS and interpersonal violence. Interpretation: This study shows the reversal of HIV/AIDS, non-communicable disease, and injury mortality trends in South Africa during the study period. Mortality differentials show the importance of social determinants, raise concerns about the quality of health services, and provide relevant information to policy makers for addressing inequalities. Differences between GBD estimates for South Africa and this study emphasise the need for more careful calibration of global models with local data. Funding: South African Medical Research Council's Flagships Awards Project.
Author Prinsloo, Megan
Vos, Theo
Joubert, Jané D
Nannan, Nadine
Sithole, Nomfuneko
Groenewald, Pam
Nojilana, Beatrice
Bradshaw, Debbie
Msemburi, William
Laubscher, Ria
Gwebushe, Nomonde
Glass, Tracy
Matzopoulos, Richard
Neethling, Ian
Rossouw, Anastasia
Pillay-van Wyk, Victoria
Nicol, Edward
Dorrington, Rob E
Somdyala, Nontuthuzelo
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  givenname: Victoria
  surname: Pillay-van Wyk
  fullname: Pillay-van Wyk, Victoria
  email: victoria.pillayvanwyk@mrc.ac.za
  organization: Burden of Disease Research Unit, South African Medical Research Council, Cape Town, South Africa
– sequence: 2
  givenname: William
  surname: Msemburi
  fullname: Msemburi, William
  organization: Burden of Disease Research Unit, South African Medical Research Council, Cape Town, South Africa
– sequence: 3
  givenname: Ria
  surname: Laubscher
  fullname: Laubscher, Ria
  organization: Biostatistics Unit, South African Medical Research Council, Cape Town, South Africa
– sequence: 4
  givenname: Rob E
  surname: Dorrington
  fullname: Dorrington, Rob E
  organization: Centre for Actuarial Research, University of Cape Town, South Africa
– sequence: 5
  givenname: Pam
  surname: Groenewald
  fullname: Groenewald, Pam
  organization: Burden of Disease Research Unit, South African Medical Research Council, Cape Town, South Africa
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  surname: Glass
  fullname: Glass, Tracy
  organization: Burden of Disease Research Unit, South African Medical Research Council, Cape Town, South Africa
– sequence: 7
  givenname: Beatrice
  surname: Nojilana
  fullname: Nojilana, Beatrice
  organization: Burden of Disease Research Unit, South African Medical Research Council, Cape Town, South Africa
– sequence: 8
  givenname: Jané D
  surname: Joubert
  fullname: Joubert, Jané D
  organization: Burden of Disease Research Unit, South African Medical Research Council, Cape Town, South Africa
– sequence: 9
  givenname: Richard
  surname: Matzopoulos
  fullname: Matzopoulos, Richard
  organization: Burden of Disease Research Unit, South African Medical Research Council, Cape Town, South Africa
– sequence: 10
  givenname: Megan
  surname: Prinsloo
  fullname: Prinsloo, Megan
  organization: Burden of Disease Research Unit, South African Medical Research Council, Cape Town, South Africa
– sequence: 11
  givenname: Nadine
  surname: Nannan
  fullname: Nannan, Nadine
  organization: Burden of Disease Research Unit, South African Medical Research Council, Cape Town, South Africa
– sequence: 12
  givenname: Nomonde
  surname: Gwebushe
  fullname: Gwebushe, Nomonde
  organization: Biostatistics Unit, South African Medical Research Council, Cape Town, South Africa
– sequence: 13
  givenname: Theo
  surname: Vos
  fullname: Vos, Theo
  organization: Institute of Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
– sequence: 14
  givenname: Nontuthuzelo
  surname: Somdyala
  fullname: Somdyala, Nontuthuzelo
  organization: Burden of Disease Research Unit, South African Medical Research Council, Cape Town, South Africa
– sequence: 15
  givenname: Nomfuneko
  surname: Sithole
  fullname: Sithole, Nomfuneko
  organization: Burden of Disease Research Unit, South African Medical Research Council, Cape Town, South Africa
– sequence: 16
  givenname: Ian
  surname: Neethling
  fullname: Neethling, Ian
  organization: Burden of Disease Research Unit, South African Medical Research Council, Cape Town, South Africa
– sequence: 17
  givenname: Edward
  surname: Nicol
  fullname: Nicol, Edward
  organization: Burden of Disease Research Unit, South African Medical Research Council, Cape Town, South Africa
– sequence: 18
  givenname: Anastasia
  surname: Rossouw
  fullname: Rossouw, Anastasia
  organization: Burden of Disease Research Unit, South African Medical Research Council, Cape Town, South Africa
– sequence: 19
  givenname: Debbie
  surname: Bradshaw
  fullname: Bradshaw, Debbie
  organization: Burden of Disease Research Unit, South African Medical Research Council, Cape Town, South Africa
BackLink https://www.ncbi.nlm.nih.gov/pubmed/27539806$$D View this record in MEDLINE/PubMed
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Snippet The poor health of South Africans is known to be associated with a quadruple disease burden. In the second National Burden of Disease (NBD) study, we aimed to...
Summary Background The poor health of South Africans is known to be associated with a quadruple disease burden. In the second National Burden of Disease (NBD)...
Background: The poor health of South Africans is known to be associated with a quadruple disease burden. In the second National Burden of Disease (NBD) study,...
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StartPage e642
SubjectTerms Adolescent
Adult
Cause of Death - trends
Child
Communicable Diseases - epidemiology
Female
Global Health
HIV Infections
Humans
Internal Medicine
Male
Middle Aged
Mortality - ethnology
Mortality - trends
South Africa - epidemiology
Title Mortality trends and differentials in South Africa from 1997 to 2012: second National Burden of Disease Study
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https://www.clinicalkey.es/playcontent/1-s2.0-S2214109X16301139
https://dx.doi.org/10.1016/S2214-109X(16)30113-9
https://www.ncbi.nlm.nih.gov/pubmed/27539806
https://www.proquest.com/docview/1812882796
https://doaj.org/article/945fa2bbd8d649ca83c5859f9520108c
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