Lancet Glob Health. 2016 Sep;4(9):e642-53. doi: 10.1016/S2214-109X(16)30113-9.

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

Pillay-van Wyk V¹, Msemburi W², Laubscher R³, Dorrington RE⁴, Groenewald P², Glass T², Nojilana B², Joubert JD², Matzopoulos R⁵, Prinsloo M²,Nannan N², Gwebushe N³, Vos T⁶, Somdyala N², Sithole N², Neethling I², Nicol E², Rossouw A², Bradshaw D⁵.

Author information

• ¹Burden of Disease Research Unit, South African Medical Research Council, Cape Town, South Africa. Electronic address: victoria.pillayvanwyk@mrc.ac.za.
• ²Burden of Disease Research Unit, South African Medical Research Council, Cape Town, South Africa.
• ³Biostatistics Unit, South African Medical Research Council, Cape Town, South Africa.
• ⁴Centre for Actuarial Research, University of Cape Town, South Africa.
• ⁵Burden of Disease Research Unit, South African Medical Research Council, Cape Town, South Africa; School of Public Health and Family Medicine, University of Cape Town, South Africa.
• ⁶Institute of Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.

Abstract below; full text is at http://www.thelancet.com/journals/langlo/article/PIIS2214-109X(16)30113-9/abstract

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.

Copyright © 2016 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY license. Published by Elsevier Ltd.. All rights reserved.

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