Pam Groenewald

Identifying deaths from AIDS in South Africa.

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.

Estimating the burden of disease attributable to smoking in South Africa in 2000

OBJECTIVES To quantify the burden of disease attributable to smoking in South Africa for 2000. DESIGN The absolute difference between observed lung cancer death rate and the level in non-smokers, adjusted for occupational and indoor exposure to lung carcinogens, was used to estimate the proportion of lung cancer deaths attributable to smoking and the smoking impact ratio (SIR). The SIR was substituted for smoking prevalence in the attributable fraction formula for chronic obstructive pulmonary disease (COPD) and cancers to allow for the long lag between exposure and outcome. Assuming a shorter lag between exposure and disease, the current prevalence of smoking was used to estimate the population-attributable fractions (PAF) for the other outcomes. Relative risks (RR) from the American Cancer Society cancer prevention study (CPS-II) were used to calculate PAF. SETTING South Africa. OUTCOME MEASURES Deaths and disability-adjusted life years (DALYs) due to lung and other cancers, COPD, cardiovascular conditions, respiratory tuberculosis, and other respiratory and medical conditions. RESULTS Smoking caused between 41,632 and 46,656 deaths in South Africa, accounting for 8.0 - 9.0% of deaths and 3.7 - 4.3% of DALYs in 2000. Smoking ranked third (after unsafe sex/ sexually transmitted disease and high blood pressure) in terms of mortality among 17 risk factors evaluated. Three times as many males as females died from smoking. Lung cancer had the largest attributable fraction due to smoking. However, cardiovascular diseases accounted for the largest proportion of deaths attributed to smoking. CONCLUSION Cigarette smoking accounts for a large burden of preventable disease in South Africa. While the government has taken bold legislative action to discourage tobacco use since 1994, it still remains a major public health priority.

Estimating the burden of disease attributable to physical inactivity in South Africa in 2000

OBJECTIVES To quantify the burden of disease attributable to physical inactivity in persons 15 years or older, by age group and sex, in South Africa for 2000. DESIGN The global comparative risk assessment (CRA) methodology of the World Health Organization was followed to estimate the disease burden attributable to physical inactivity. Levels of physical activity for South Africa were obtained from the World Health Survey 2003. A theoretical minimum risk exposure of zero, associated outcomes, relative risks, and revised burden of disease estimates were used to calculate population-attributable fractions and the burden attributed to physical inactivity. Monte Carlo simulation-modelling techniques were used for the uncertainty analysis. SETTING South Africa. SUBJECTS Adults >or= 15 years. OUTCOME MEASURES Deaths and disability-adjusted life years (DALYs) from ischaemic heart disease, ischaemic stroke, breast cancer, colon cancer, and type 2 diabetes mellitus. RESULTS Overall in adults >or= 15 years in 2000, 30% of ischaemic heart disease, 27% of colon cancer, 22% of ischaemic stroke, 20% of type 2 diabetes, and 17% of breast cancer were attributable to physical inactivity. Physical inactivity was estimated to have caused 17,037 (95% uncertainty interval 11,394 - 20,407), or 3.3% (95% uncertainty interval 2.2 - 3.9%) of all deaths in 2000, and 176,252 (95% uncertainty interval 133,733 - 203,628) DALYs, or 1.1% (95% uncertainty interval 0.8 - 1.3%) of all DALYs in 2000. CONCLUSIONS Compared with other regions and the global average, South African adults have a particularly high prevalence of physical inactivity. In terms of attributable deaths, physical inactivity ranked 9th compared with other risk factors, and 12th in terms of DALYs. There is a clear need to assess why South Africans are particularly inactive, and to ensure that physical activity/inactivity is addressed as a national health priority.

Provincial mortality in South Africa, 2000- priority-setting for now and a benchmark for the future

BACKGROUND Cause-of-death statistics are an essential component of health information. Despite improvements, underregistration and misclassification of causes make it difficult to interpret the official death statistics. OBJECTIVE To estimate consistent cause-specific death rates for the year 2000 and to identify the leading causes of death and premature mortality in the provinces. METHODS Total number of deaths and population size were estimated using the Actuarial Society of South Africa ASSA2000 AIDS and demographic model. Cause-of-death profiles based on Statistics South Africas 15% sample, adjusted for misclassification of deaths due to ill-defined causes and AIDS deaths due to indicator conditions, were applied to the total deaths by age and sex. Age-standardised rates and years of life lost were calculated using age weighting and discounting. RESULTS Life expectancy in KwaZulu-Natal and Mpumalanga is about 10 years lower than that in the Western Cape, the province with the lowest mortality rate. HIV/AIDS is the leading cause of premature mortality for all provinces. Mortality due to pre-transitional causes, such as diarrhoea, is more pronounced in the poorer and more rural provinces. In contrast, non-communicable disease mortality is similar across all provinces, although the cause profiles differ. Injury mortality rates are particularly high in provinces with large metropolitan areas and in Mpumalanga. CONCLUSION The quadruple burden experienced in all provinces requires a broad range of interventions, including improved access to health care; ensuring that basic needs such as those related to water and sanitation are met; disease and injury prevention; and promotion of a healthy lifestyle. High death rates as a result of HIV/AIDS highlight the urgent need to accelerate the implementation of the treatment and prevention plan. In addition, there is an urgent need to improve the cause-of-death data system to provide reliable cause-of-death statistics at health district level.

Quality of cause of death certification at an academic hospital in Cape Town, South Africa.

OBJECTIVES To investigate the quality of cause of death certification and assess the level of under-reporting of HIV/AIDS as a cause of death at an academic hospital. DESIGN Cross-sectional descriptive retrospective review of death notification forms (DNFs) of deaths due to natural causes in an academic hospital in Cape Town during 2004. Errors in cause of death certification and ability to code causes of death according to the 10th revision of the International Statistical Classification of Diseases and Related Health Problems (ICD-10) were assessed. The association between serious errors and age, gender, cause of death and hospital ward was analysed. A sample of DNFs (N=243) was assessed for level of under-reporting of HIV/AIDS. RESULTS A total of 983 death certificates were evaluated. Almost every DNF had a minor error; serious errors were found in 32.2% (95% confidence interval (CI) 29.3-35.1%). Errors increased with patient age, and cause of death was the most important factor associated with serious errors. Compared with neoplasms, which had the lowest error rate, the odds ratios for errors in endocrine and metabolic diseases and genito-urinary diseases were 17.2 (95% CI 8.7-34.0) and 17.3 (95% CI 7.8-38.2), respectively. Based on the sub-sample, the minimum prevalence of HIV among the deceased patients was 15.7% (95% CI 11.1-20.3%) and the under-reporting of deaths due to AIDS was 53.1% (95% CI 35.8-70.4%). CONCLUSION Errors were sufficiently serious to affect identification of underlying cause of death in almost a third of the DNFs, confirming the need to improve the quality of medical certification.

Deaths caused by HIV disease under-reported in South Africa

Modelling of trends in age-specific death rates in South Africa suggests that deaths attributable to HIV are often misclassified on death notification forms. We compared the underlying cause of death from death notification forms with that based on scrutiny of medical records for 683 deaths in Cape Town. Of 129 deaths caused by HIV according to medical records, only 35 (27.1%) were ascribed to HIV on the death notification form using strict coding and 83 (64.3%) using interpretive coding.

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

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 Councils Flagships Awards Project.

Second National Burden of Disease Study South Africa: national and subnational mortality trends, 1997–2009

Abstract Background Global Burden of Diseases, Injuries, and Risk Factors Study 2010 results show continued limitations of data quality and availability in most of the African region. Focused efforts in South Africa, however, have contributed to improved completeness and availability of mortality data, such that South Africa is currently undertaking a second National Burden of Disease Study. Mortality estimates have been developed nationally and for the nine provinces for 1997–2009. Methods Vital registration data obtained for 1997–2009 were adjusted for completeness using indirect demographic techniques. A regression approach was used to identify misclassified AIDS deaths, and garbage codes were proportionally redistributed by age, sex, and population group. Injury deaths were estimated from additional data sources. Age-standardised mortality rate (ASMR) trends for the nine provinces were calculated using ASSA 2008 population estimates and the WHO age standard. Findings All-cause mortality peaked in 2006 and thereafter started to decline. ASMRs showed a two-fold difference between the highest-affected and lowest-affected provinces for the 1997–2009 period. ASMR from HIV/AIDS increased threefold since 1997 with provincial variation, while mortality from non-HIV-related tuberculosis declined. Mortality rates from non-communicable diseases decreased over the period nationally but increased for some provinces and remained stable for others as a result of differing trends in hypertensive heart disease and respiratory diseases. Nationally, preliminary analyses for 2009 show that HIV/AIDS was responsible for the highest number of deaths (31·2%; n=194 322 of 622 300 deaths), followed by cerebrovascular disease (6·2%; n=38 666), tuberculosis (5·4%; n=33 375), lower respiratory infections (5·2%; n=32 568), and ischaemic heart disease (4·4%; n=27 688). However, tuberculosis and interpersonal violence ranked among the top five causes for males, while hypertensive heart disease and ischaemic heart disease featured for females. Interpretation The downward trend in HIV/AIDS mortality can be attributed to the extensive antiretroviral treatment rollout since 2005. Differential provincial mortality trends reflect the different stages of epidemiological transition and differential health services in the provinces, providing relevant information for policy makers to address inequalities. Funding South African Medical Research Council.

Validation study of cause of death statistics in Cape Town, South Africa, found poor agreement

OBJECTIVE The validity of the underlying cause of death on death notification forms was assessed by comparing it to the underlying cause determined independently from medical records. STUDY DESIGN AND SETTING Retrospective study of 703 deaths in two suburbs of Cape Town, South Africa. Two medical doctors completed a medical review death certificate to validate the registration death certificate for each decedent. Agreement, sensitivity, and positive predictive value were measured for underlying causes of death using the World Health Organization (WHO) mortality tabulation list 1. RESULTS Agreement was poor, with only 55.3% (95% confidence interval [CI]: 51.7, 59.0) of diagnoses matching at WHO mortality tabulation list 1 level. Validity of reported causes of death was poor for HIV, cardiovascular diseases, and diabetes. With correct reporting, the cause-specific mortality fraction for HIV increased from 11.9% to 18.3% (53.6%; 95% CI: 36.9, 77.6), for ischemic heart disease from 3.3% to 7.3% (121.7%; 95% CI: 53.5, 228.7), and for hypertensive diseases from 3.3% to 5.7% (73.9%; 95% CI: 14.4, 167.8). For diabetes, the mortality fraction decreased from 6.0% to 2.3% (-64.3%; 95% CI: -77.1, -37.8) and for ill-defined deaths from 7.4% to 2.3% (-69.2%; 95% CI: -81.0, -51.6). CONCLUSION Current cause-specific mortality levels should be cautiously interpreted. Death certification training is required to improve the validity of mortality data.

Local-level mortality surveillance in resource-limited settings: a case study of Cape Town highlights disparities in health

OBJECTIVE To identify the leading causes of mortality and premature mortality in Cape Town, South Africa, and its subdistricts, and to compare levels of mortality between subdistricts. METHODS Cape Town mortality data for the period 2001-2006 were analysed by age, cause of death and sex. Cause-of-death codes were aggregated into three main cause groups: (i) pre-transitional causes (e.g. communicable diseases, maternal causes, perinatal conditions and nutritional deficiencies), (ii) noncommunicable diseases and (iii) injuries. Premature mortality was calculated in years of life lost (YLLs). Population estimates for the Cape Town Metro district were used to calculate age-specific rates per 100,000 population, which were then age-standardized and compared across subdistricts. FINDINGS The pattern of mortality in Cape Town reflects the quadruple burden of disease observed in the national cause-of-death profile, with HIV/AIDS, other infectious diseases, injuries and noncommunicable diseases all accounting for a significant proportion of deaths. HIV/AIDS has replaced homicide as the leading cause of death. HIV/AIDS, homicide, tuberculosis and road traffic injuries accounted for 44% of all premature mortality. Khayelitsha, the poorest subdistrict, had the highest levels of mortality for all main cause groups. CONCLUSION Local mortality surveillance highlights the differential needs of the population of Cape Town and provides a wealth of data to inform planning and implementation of targeted interventions. Multisectoral interventions will be required to reduce the burden of disease.