Linking mortuary data improves vital statistics on cause of death of children under five years in the Western Cape Province of South Africa.

OBJECTIVES: Reducing child mortality requires good information on its causes. Whilst South African vital registration data have improved, the quality of cause-of-death data remains inadequate. To improve this, data from death certificates were linked with information from forensic mortuaries in Western Cape Province. METHODS: A local mortality surveillance system was established in 2007 by the Western Cape Health Department to improve data quality. Cause-of-death data were captured from copies of death notification forms collected at Department of Home Affairs Offices. Using unique identifiers, additional forensic mortuary data were linked with mortality surveillance system records. Causes of death were coded to the ICD-10 classification. Causes of death in children under five were compared with those from vital registration data for 2011. RESULTS: Cause-of-death data were markedly improved with additional data from forensic mortuaries. The proportion of ill-defined causes was halved (25-12%), and leading cause rankings changed. Lower respiratory tract infections moved above prematurity to rank first, accounting for 20.8% of deaths and peaking in infants aged 1-3 months. Only 11% of deaths from lower respiratory tract infections occurred in hospital, resulting in 86% being certified in forensic mortuaries. Road traffic deaths increased from 1.1-3.1% (27-75) and homicides from 3 to 28. CONCLUSIONS: The quality and usefulness of cause-of-death information for children in the WC was enhanced by linking mortuary and vital registration data. Given the death profile, interventions are required to prevent and manage LRTI, diarrhoea and injuries and to reduce neonatal deaths.

Differences among the coloured, white, black, and other South African populations in smoking-attributed mortality at ages 35-74 years: a case-control study of 481,640 deaths.

BACKGROUND: The full eventual effects of current smoking patterns cannot yet be seen in Africa. In South Africa, however, men and women in the coloured (mixed black and white ancestry) population have smoked for many decades. We assess mortality from smoking in the coloured, white, and black (African) population groups. METHODS: In this case-control study, 481,640 South African notifications of death at ages 35-74 years between 1999 and 2007 yielded information about age, sex, population group, education, smoking 5 years ago (yes or no), and underlying disease. Cases were deaths from diseases expected to be affected by smoking; controls were deaths from selected other diseases, excluding only HIV, cirrhosis, unknown causes, external causes, and mental disorders. Disease-specific case-control comparisons yielded smoking-associated relative risks (RRs; diluted by combining some ex-smokers with the never-smokers). These RRs, when combined with national mortality rates, yielded smoking-attributed mortality rates. Summation yielded RRs and smoking-attributed numbers for overall mortality. FINDINGS: In the coloured population, smoking prevalence was high in both sexes and smokers had about 50% higher overall mortality than did otherwise similar non-smokers or ex-smokers (men, RR 1·55, 95% CI 1·43-1·67; women, 1·49, 1·38-1·60). RRs were similar in the white population (men, 1·37, 1·29-1·46; women, 1·51, 1·40-1·62), but lower among Africans (men, 1·17, 1·15-1·19; women, 1·16, 1·13-1·20). If these associations are largely causal, smoking-attributed proportions for overall male deaths at ages 35-74 years were 27% (5608/20,767) in the coloured, 14% (3913/28,951) in the white, and 8% (20,398/264,011) in the African population. For female deaths, these proportions were 17% (2728/15,593) in the coloured, 12% (2084/17,899) in the white, and 2% (4038/205,623) in the African population. Because national mortality rates were also substantially higher in the coloured than in the white population, the hazards from smoking in the coloured population were more than double those in the white population. INTERPRETATION: The highest smoking-attributed mortality rates were in the coloured population and the lowest were in Africans. The substantial hazards already seen among coloured South Africans suggest growing hazards in all populations in Africa where young adults now smoke. FUNDING: South African Medical Research Council, UK Medical Research Council, Cancer Research UK, British Heart Foundation, New South Wales Cancer Council.

Agreement between cause of death assignment by computer-coded verbal autopsy methods and physician coding of verbal autopsy interviews in South Africa.

BACKGROUND: The South African national cause of death validation (NCODV 2017/18) project collected a national sample of verbal autopsies (VA) with cause of death (COD) assignment by physician-coded VA (PCVA) and computer-coded VA (CCVA). OBJECTIVE: The performance of three CCVA algorithms (InterVA-5, InSilicoVA and Tariff 2.0) in assigning a COD was compared with PCVA (reference standard). METHODS: Seven performance metrics assessed individual and population level agreement of COD assignment by age, sex and place of death subgroups. Positive predictive value (PPV), sensitivity, overall agreement, kappa, and chance corrected concordance (CCC) assessed individual level agreement. Cause-specific mortality fraction (CSMF) accuracy and Spearman's rank correlation assessed population level agreement. RESULTS: A total of 5386 VA records were analysed. PCVA and CCVAs all identified HIV/AIDS as the leading COD. CCVA PPV and sensitivity, based on confidence intervals, were comparable except for HIV/AIDS, TB, maternal, diabetes mellitus, other cancers, and some injuries. CCVAs performed well for identifying perinatal deaths, road traffic accidents, suicide and homicide but poorly for pneumonia, other infectious diseases and renal failure. Overall agreement between CCVAs and PCVA for the top single cause (48.2-51.6) indicated comparable weak agreement between methods. Overall agreement, for the top three causes showed moderate agreement for InterVA (70.9) and InSilicoVA (73.8). Agreement based on kappa (-0.05-0.49)and CCC (0.06-0.43) was weak to none for all algorithms and groups. CCVAs had moderate to strong agreement for CSMF accuracy, with InterVA-5 highest for neonates (0.90), Tariff 2.0 highest for adults (0.89) and males (0.84), and InSilicoVA highest for females (0.88), elders (0.83) and out-of-facility deaths (0.85). Rank correlation indicated moderate agreement for adults (0.75-0.79). CONCLUSIONS: Whilst CCVAs identified HIV/AIDS as the leading COD, consistent with PCVA, there is scope for improving the algorithms for use in South Africa.

Rapid mortality surveillance using a national population register to monitor excess deaths during SARS-CoV-2 pandemic in South Africa.

This paper describes how an up-to-date national population register recording deaths by age and sex, whether deaths were due to natural or unnatural causes, and the offices at which the deaths were recorded can be used to monitor excess death during the SARS-CoV-2 pandemic, both nationally, and sub-nationally, in a country with a vital registration system that is neither up to date nor complete. Apart from suggesting an approach for estimating completeness of reporting at a sub-national level, the application produces estimates of the number of deaths in excess of those expected in the absence of the SARS-CoV-2 epidemic that are highly correlated with the confirmed number of COVID-19 deaths over time, but at a level 2.5 to 3 times higher than the official numbers of COVID-19 deaths. Apportioning the observed excess deaths more precisely to COVID, COVID-related and collateral deaths, and non-COVID deaths averted by interventions with reduced mobility and gatherings, etc., requires access to real-time cause-of-death information. It is suggested that the transition from ICD-10 to ICD-11 should be used as an opportunity to change from a paper-based system to electronic capture of the medical cause-of-death information.

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.

Where do children die and what are the causes? Under-5 deaths in the Metro West geographical service area of the Western Cape, South Africa, 2011.

BACKGROUND: Accurate child mortality data are essential to plan health interventions to reduce child deaths. OBJECTIVES: To review the deaths of children aged <5 years during 2011 in the Metro West geographical service area (GSA) of the Western Cape Province (WC), South Africa, from routine data sources. METHODS: A retrospective study of under-5 deaths in the Metro West GSA was done using the WC Local Mortality Surveillance System (LMSS), the Child Healthcare Problem Identification Programme (Child PIP) and the Perinatal Problem Identification Programme (PPIP), and linking where possible. RESULTS: The LMSS reported 700 under-5 deaths, Child PIP 99 and PPIP 252, with an under-5 mortality rate of 18 deaths per 1 000 live births. The leading causes of death were pneumonia (25%), gastroenteritis (10%), prematurity (9%) and injuries (9%). There were 316 in-hospital deaths (45%) and 384 out-of-hospital deaths (55%). Among children aged <1 year, there were significantly more pneumonia deaths out of hospital than in hospital (144 (49%) v. 16 (6%); p<0.001). Among children aged 1 - 4 years there were significantly more injury-related deaths out of hospital than in hospital (43 (47%) v. 4 (9%); p<0.001). In 56 (15%) of the cases of out-of-hospital death the child had visited a public healthcare facility within 1 week of death. Thirty-six (64%) of these children had died of pneumonia or gastroenteritis. CONCLUSIONS: Health interventions targeted at reducing under-5 deaths from pneumonia, gastroenteritis, prematurity and injuries need to be implemented across the service delivery platform in the Metro West GSA. It is important to consider all routine data sources in the evaluation of child mortality.

HIV/AIDS in South Africa: how many people died from the disease between 1997 and 2010?

OBJECTIVES: Empirical estimates of the number of HIV/AIDS deaths are important for planning, budgeting, and calibrating models. However, there is an extensive misattribution of HIV/AIDS as an underlying cause-of-death. This study estimates the true numbers of AIDS deaths from South African vital statistics between 1997 and 2010. METHODS: Individual-level cause-of-death data were grouped according to a local burden of disease list and source causes (i.e. causes under which AIDS deaths are misclassified) that recorded a rapid increase. After adjusting for completeness of registration, the mortality rate of the source causes, by age and sex, was regressed on the lagged HIV prevalence to estimate the rate of increase correlated with HIV. Background trends in the source-cause mortality rates were estimated from the trend experienced among 75-84 year olds. RESULTS: Of 214 causes considered, 19 were identified as potential sources for cause misattribution. High proportions of deaths from tuberculosis, lower respiratory infections (mostly pneumonia), diarrhoeal diseases, and ill-defined natural causes were estimated to be HIV-related, with only 7% of the estimated AIDS deaths being recorded as HIV. Estimated HIV/AIDS deaths increased rapidly, then reversed after 2006, totalling 2.8 million deaths over the whole period. The number was lower than model estimates from Joint United Nations Programme on HIV/AIDS (UNAIDS) and the Global Burden of Disease Study. CONCLUSION: Empirically based estimates confirm the considerable loss of life from HIV/AIDS and should be used for calibrating models of the AIDS epidemic which generally appear too low for infants but too high for other ages. Doctors are urged to specify HIV on death notifications to provide reliable cause-of-death statistics.

Epidemiology of lower respiratory infection and pneumonia in South Africa (1997-2015): a systematic review protocol.

INTRODUCTION: Lower respiratory infections (LRIs) and pneumonia are among the leading causes of death worldwide, especially in children aged under 5 years, and these patterns are reflected in the South African population. Local epidemiological data for LRIs and pneumonia are required to inform the Second National Burden of Disease Study underway in South Africa. The aim of this systematic review is to identify published studies reporting the prevalence, incidence, case fatality, duration or severity of LRI and pneumonia in adults and children in South Africa. METHODS AND ANALYSIS: Electronic database searches will be conducted to obtain studies reporting on the prevalence, incidence, case fatality, duration and severity of LRI and pneumonia in South Africa between January 1997 and December 2015. Studies that are assessed to have moderate or low risk of bias will be included in a meta-analysis, if appropriate. Where meta-analysis is not possible, the articles will be described narratively. Subgroup analysis (eg, age groups) will also be conducted where enough information is available. ETHICS AND DISSEMINATION: This systematic review will only include published data with no linked patient-level information; thus, no ethics approval is required. The findings will be used to calculate the burden of disease attributed to LRI and pneumonia in South Africa and will highlight the type of epidemiological data available in the country. The article will be disseminated in a peer-reviewed publication. PROSPERO REGISTRATION NUMBER: CRD42016036520.

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 Council's Flagships Awards Project.

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.

The importance of identified cause-of-death information being available for public health surveillance, actions and research.

An amendment to the South African Births and Deaths Registration Act has compromised efforts to strengthen local mortality surveillance to provide statistics for small areas and enable data linkage to provide information for public health actions. Internationally it has been recognised that a careful balance needs to be kept between protecting individual patient confidentiality and enabling effective public health intelligence to guide patient care and service delivery and prevent harmful exposures. This article describes the public health benefits of a local mortality surveillance system in the Western Cape Province, South Africa (SA), as well as its potential for improving the quality of vital statistics data with integration into the national civil registration and vital statistics system. It also identifies other important uses for identifiable cause-of-death data in SA that have been compromised by this legislation.

Monitoring of non-communicable diseases such as hypertension in South Africa: challenges for the post-2015 global development agenda.

BACKGROUND: Examining the non-communicable disease (NCD) profile for South Africa (SA) is crucial when developing health interventions that aim to reduce the burden of NCDs. OBJECTIVE: To review NCD indicators in national data sources in order to describe the burden of NCDs in SA, using hypertension as an example. METHODS: Age, gender, district of death and underlying cause of death data were obtained for 2008 and 2009 mortality unit records from Statistics SA and adjusted using STATA 11. Data for raised blood pressure were obtained from four national household surveys: the South African Demographic and Health Survey 1998, the Study on Global Ageing and Adult Health 2007, and the National Income Dynamics Study 2008 and 2010. RESULTS: The proportion of years of life lost due to NCDs was highest in the metros and least-deprived districts, with all metros (especially Mangaung) showing high age-standardised mortality rates for ischaemic heart disease, cerebrovascular disease and hypertensive disease. The prevalence of hypertension has increased since 1998. National household surveys showed a measured hypertension prevalence of over 40% in adults aged ≥25 years in 2010. Treatment coverage was 35.7%. Only 36.4% of hypertensive cases (on treatment) were controlled. CONCLUSION: Further work is needed if NCD monitoring is to be enhanced. Priority targets for NCDs must be integrated into national health planning processes. Surveillance requires integration into national health information systems. Within primary healthcare, a larger focus on integrated chronic care is essential.

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.

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.

The high burden of injuries in South Africa.

OBJECTIVE: To estimate the magnitude and characteristics of the injury burden in South Africa within a global context. METHODS: The Actuarial Society of South Africa demographic and AIDS model (ASSA 2002) - calibrated to survey, census and adjusted vital registration data - was used to calculate the total number of deaths in 2000. Causes of death were determined from the National Injury Mortality Surveillance System profile. Injury death rates and years of life lost (YLL) were estimated using the Global Burden of Disease methodology. National years lived with disability (YLDs) were calculated by applying a ratio between YLLs and YLDs found in a local injury data source, the Cape Metropole Study. Mortality and disability-adjusted life years' (DALYs) rates were compared with African and global estimates. FINDINGS: Interpersonal violence dominated the South African injury profile with age-standardized mortality rates at seven times the global rate. Injuries were the second-leading cause of loss of healthy life, accounting for 14.3% of all DALYs in South Africa in 2000. Road traffic injuries (RTIs) are the leading cause of injury in most regions of the world but South Africa has exceedingly high numbers - double the global rate. CONCLUSION: Injuries are an important public health issue in South Africa. Social and economic determinants of violence, many a legacy of apartheid policies, must be addressed to reduce inequalities in society and build community cohesion. Multisectoral interventions to reduce traffic injuries are also needed. We highlight this heavy burden to stress the need for effective prevention programmes.

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.