OBJECTIVE: To quantify the HIV/AIDS deaths misclassified to AIDS-related conditions in South Africa. DESIGN: Retrospective analysis of vital registration data. METHODS: Cause-specific death rates for 1996 and 2000-2001 were calculated using vital registration cause-of-death profiles applied to a model (ASSA2000) estimate of total mortality rates by age and sex. The difference in the age-specific death rates for these two periods was examined to identify conditions where there was a noticeable increase in mortality following the same age pattern as the HIV deaths, thus likely to be misclassified AIDS deaths. RESULTS: The increase in the age-specific death rates for HIV-related deaths showed a distinct age pattern, which has been observed elsewhere. Out of the 22 potential causes of death investigated, there were nine that increased in the same distinct age pattern (tuberculosis, pneumonia, diarrhoea, meningitis, other respiratory disease, non-infective gastroenteritis, other infectious and parasitic diseases, deficiency anaemias and protein energy malnutrition) and could be considered AIDS-related conditions. The increase in these conditions accounted for 61% of the total deaths related to HIV/AIDS. When added to the deaths classified as HIV-related on the death certificate, the total accounts for 93% of the ASSA2000 model estimates of the number of AIDS deaths in 2000. CONCLUSION: As a large proportion of AIDS deaths appear to be classified to AIDS-related conditions, without reference to HIV, interpretation of death statistics in South Africa cannot be made on face value as a large proportion of deaths caused by HIV infection are misclassified.
OBJECTIVE: To quantify the HIV/AIDS deaths misclassified to AIDS-related conditions in South Africa. DESIGN: Retrospective analysis of vital registration data. METHODS: Cause-specific death rates for 1996 and 2000-2001 were calculated using vital registration cause-of-death profiles applied to a model (ASSA2000) estimate of total mortality rates by age and sex. The difference in the age-specific death rates for these two periods was examined to identify conditions where there was a noticeable increase in mortality following the same age pattern as the HIV deaths, thus likely to be misclassified AIDS deaths. RESULTS: The increase in the age-specific death rates for HIV-related deaths showed a distinct age pattern, which has been observed elsewhere. Out of the 22 potential causes of death investigated, there were nine that increased in the same distinct age pattern (tuberculosis, pneumonia, diarrhoea, meningitis, other respiratory disease, non-infective gastroenteritis, other infectious and parasitic diseases, deficiency anaemias and protein energy malnutrition) and could be considered AIDS-related conditions. The increase in these conditions accounted for 61% of the total deaths related to HIV/AIDS. When added to the deaths classified as HIV-related on the death certificate, the total accounts for 93% of the ASSA2000 model estimates of the number of AIDS deaths in 2000. CONCLUSION: As a large proportion of AIDS deaths appear to be classified to AIDS-related conditions, without reference to HIV, interpretation of death statistics in South Africa cannot be made on face value as a large proportion of deaths caused by HIV infection are misclassified.
Authors: Pam Groenewald; Debbie Bradshaw; Johann Daniels; Nesbert Zinyakatira; Richard Matzopoulos; David Bourne; Najma Shaikh; Tracey Naledi Journal: Bull World Health Organ Date: 2010-01-08 Impact factor: 9.408
Authors: Philippe Glaziou; Katherine Floyd; Eline L Korenromp; Charalambos Sismanidis; Ana L Bierrenbach; Brian G Williams; Rifat Atun; Mario Raviglione Journal: Bull World Health Organ Date: 2011-05-31 Impact factor: 9.408
Authors: Jané Joubert; Debbie Bradshaw; Chodziwadziwa Kabudula; Chalapati Rao; Kathleen Kahn; Paul Mee; Stephen Tollman; Alan D Lopez; Theo Vos Journal: Int J Epidemiol Date: 2014-08-21 Impact factor: 7.196
Authors: B Lopman; A Cook; J Smith; G Chawira; M Urassa; Y Kumogola; R Isingo; C Ihekweazu; J Ruwende; M Ndege; S Gregson; B Zaba; T Boerma Journal: J Epidemiol Community Health Date: 2009-10-23 Impact factor: 3.710