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 Africa's 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.

A clarion call for action based on refined DALY estimates for South Africa

Initial estimates of the burden of disease in South Africa in 20001 have been revised on the basis of additional data to estimate the disability-adjusted life-years (DALYs) for single causes for the first time in South Africa. The findings highlight the fact that despite uncertainty in the estimates, they provide important information to guide public health responses to improve the health of the nation...

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.

Epidemiology and risk factors of oral cancer in South Africa

Head and neck cancers are some of the leading cancers in the coloured and black South African male population and the perception exists that the incidence rates are rising. Aims: To determine the standardised morbidity rates and some of the risk factors for oral cancer in South Africa. Methods: Using histologically verified data from the National Cancer Registry, the age standardised incidence rates (ASIR) and life-time risks (LR) of oral cancer in South Africa were calculated for 1988-1991.2. In an ongoing case control study (1995 +) among black patients in Johannesburg/Soweto, adjusted odds ratios for developing oral cancers in relation to tobacco and alcohol consumption were calculated. Results: Coloured males vs. females: ASIR 13.13 vs. 3.5 (/100,000/year), LR 1:65 vs. 1:244. Black males vs. females: ASIR 9.06 vs. 1.75, LR 1:86 and 1:455. White males vs. females: ASIR 8.06 vs. 3.18, LR 1:104 vs. 1:278. Asian males vs. females: ASIR 5.24 vs. 6.66, LR 1:161 vs. 1:125. The odds ratio for oral cancer in black males in relation to smoking was 7.0 (95% CI 3.0-14.6) and daily alcohol consumption 1.3 (95% CI 0.6-2.8). In black females the odds ratios in relation to smoking were 3.9 (95% CI 1.7 8.9) and daily alcohol consumption 1.7(95% CI 0.7-4.1). Conclusions: The risk factors for oral cancer in South Africa are multiple and gender discrepancies in ASIR and LR signal differences in exposure to carcinogens. It is unclear whether the incidence of oral cancers will rise in the future.

Estimating the burden of disease attributable to excess body weight in South Africa in 2000

Objective. To estimate the burden of disease attributable to excess body weight using the body mass index (BMI), by age and sex, in South Africa in 2000. Design. World Health Organization comparative risk assessment (CRA) methodology was followed. Re-analysis of the 1998 South Africa Demographic and Health Survey data provided mean BMI estimates by age and sex. Populationattributable fractions were calculated and applied to revised burden of disease estimates. Monte Carlo simulation-modelling techniques were used for the uncertainty analysis. Setting. South Africa. Subjects. Adults 30 years of age. Outcome measures. Deaths and disability-adjusted life years (DALYs) from ischaemic heart disease, ischaemic stroke, hypertensive disease, osteoarthritis, type 2 diabetes mellitus, and selected cancers. Results. Overall, 87% of type 2 diabetes, 68% of hypertensive disease, 61% of endometrial cancer, 45% of ischaemic stroke, 38% of ischaemic heart disease, 31% of kidney cancer, 24% of osteoarthritis, 17% of colon cancer, and 13% of postmenopausal breast cancer were attributable to a BMI 21 kg/m2. Excess body weight is estimated to have caused 36 504 deaths (95% uncertainty interval 31 018 - 38 637) or 7% (95% uncertainty interval 6.0 - 7.4%) of all deaths in 2000, and 462 338 DALYs (95% uncertainty interval 396 512 - 478 847) or 2.9% of all DALYs (95% uncertainty interval 2.4 - 3.0%). The burden in females was approximately double that in males. Conclusions. This study shows the importance of recognising excess body weight as a major risk to health, particularly among females, highlighting the need to develop, implement and evaluate comprehensive interventions to achieve lasting change in the determinants and impact of excess body weight.

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 ≥ 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 ≥ 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.

Estimating the burden of disease attributable to unsafe water and lack of sanitation and hygiene in South Africa in 2000

Objectives To estimate the burden of disease attributable to unsafe water, sanitation and hygiene (WSH) by age group for South Africa in 2000. Design World Health Organization comparative risk assessment methodology was used to estimate the disease burden attributable to an exposure by comparing the observed risk factor distribution with a theoretical lowest possible population distribution. A scenario-based approach was applied for estimating diarrhoeal disease burden from unsafe WSH. Six exposure scenarios were defined based on the type of water and sanitation infrastructure and environmental faecal-oral pathogen load. For ‘intestinal parasites’ and schistosomiasis, the burden was assumed to be 100% attributable to exposure to unsafe WSH. Setting South Africa. Outcome measures Disease burden from diarrhoeal diseases, intestinal parasites and schistosomiasis, measured by deaths and disability-adjusted life years (DALYs). Results 13 434 deaths were attributable to unsafe WSH accounting for 2.6% (95% uncertainty interval 2.4 - 2.7%) of all deaths in South Africa in 2000. The burden was especially high in children under 5 years, accounting for 9.3% of total deaths in this age group and 7.4% of burden of disease. Overall, the burden due to unsafe WSH was equivalent to 2.6% (95% uncertainty interval 2.5 - 2.7%) of the total disease burden for South Africa, ranking this risk factor seventh for the country. Conclusions Unsafe WSH remains an important risk factor for disease in South Africa, especially in children under 5. High priority needs to be given to the provision of safe and sustainable sanitation and water facilities and to promoting safe hygiene behaviours, particularly among children.

Estimating the burden of disease attributable to four selected environmental risk factors in South Africa

INTRODUCTION: The first South African National Burden of Disease study quantified the underlying causes of premature mortality and morbidity experienced in South Africa in the year 2000. This was followed by a Comparative Risk Assessment to estimate the contributions of 17 selected risk factors to burden of disease in South Africa. This paper describes the health impact of exposure to four selected environmental risk factors: unsafe water, sanitation and hygiene; indoor air pollution from household use of solid fuels; urban outdoor air pollution and lead exposure. METHODS: The study followed World Health Organization comparative risk assessment methodology. Population-attributable fractions were calculated and applied to revised burden of disease estimates (deaths and disability adjusted life years, [DALYs]) from the South African Burden of Disease study to obtain the attributable burden for each selected risk factor. The burden attributable to the joint effect of the four environmental risk factors was also estimated taking into account competing risks and common pathways. Monte Carlo simulation-modeling techniques were used to quantify sampling, uncertainty. RESULTS: Almost 24 000 deaths were attributable to the joint effect of these four environmental risk factors, accounting for 4.6% (95% uncertainty interval 3.8-5.3%) of all deaths in South Africa in 2000. Overall the burden due to these environmental risks was equivalent to 3.7% (95% uncertainty interval 3.4-4.0%) of the total disease burden for South Africa, with unsafe water sanitation and hygiene the main contributor to joint burden. The joint attributable burden was especially high in children under 5 years of age, accounting for 10.8% of total deaths in this age group and 9.7% of burden of disease. CONCLUSION: This study highlights the public health impact of exposure to environmental risks and the significant burden of preventable disease attributable to exposure to these four major environmental risk factors in South Africa. Evidence-based policies and programs must be developed and implemented to address these risk factors at individual, household, and community levels.

Estimating the burden of disease attributable to interpersonal violence in South Africa in 2000

Violence, previously considered a social issue, is now an acknowledged public health problem. It is defined as the intentional use of physical force or power, threatened or actual, against another person, against oneself, or against a group or community, that results in injury, death or deprivation.1 In this study we focus on exposure to the interpersonal type of violence, which includes acts of family violence and community violence. Family violence is further categorised by victim: child, intimate partner, or elder. Community violence occurs among unrelated individuals and includes sexual assault and rape by strangers as well as youth violence...

Estimating the burden of disease attributable to high cholesterol in South Africa in 2000

Objectives To estimate the burden of disease attributable to high cholesterol in adults aged 30 years and older in South Africa in 2000. Design World Health Organization comparative risk assessment (CRA) methodology was followed. Small community studies were used to derive the prevalence by population group. Population-attributable fractions were calculated and applied to revised burden of disease estimates for the relevant disease categories for each population group. The total attributable burden for South Africa in 2000 was obtained by adding the burden attributed to high cholesterol for the four population groups. Monte Carlo simulation-modelling techniques were used for uncertainty analysis. Setting South Africa. Subjects Black African, coloured, white and Indian adults aged 30 years and older. Outcome measures Mortality and disability-adjusted life years (DALYs) from ischaemic heart disease (IHD) and ischaemic stroke. Results Overall, about 59% of IHD and 29% of ischaemic stroke burden in adult males and females (30+ years) were attributable to high cholesterol (≥ 3.8 mmol/l), with marked variation by population group. High cholesterol was estimated to have caused 24 144 deaths (95% uncertainty interval 22 404 - 25 286) or 4.6% (95% uncertainty interval 4.3 - 4.9%) of all deaths in South Africa in 2000. Since most cholesterol-related cardiovascular disease events occurred in middle or old age, the loss of life years comprised a smaller proportion of the total: 222 923 DALYs (95% uncertainty interval 206 712 - 233 460) or 1.4% of all DALYs (95% uncertainty interval 1.3 - 1.4%) in South Africa in 2000. Conclusions High cholesterol is an important cardiovascular risk factor in all population groups in South Africa.

Estimating the burden of disease attributable to urban outdoor air pollution in South Africa in 2000

Objectives To quantify the mortality burden attributed to urban outdoor air pollution in South Africa in 2000. Design The study followed comparative risk assessment (CRA) methodology developed by the World Heath Organization (WHO). In most urban areas, annual mean concentrations of particulate matter (PM) with diameters less than 10 μum (PM10) from monitoring network data and PM with diameters less than 2.5 μm (PM2.5) derived using a ratio method were weighted according to population size. PM10 and PM2.5 data from air-quality assessment studies in areas not covered by the network were also included. Population-attributable fractions calculated using risk coefficients presented in the WHO study were weighted by the proportion of the total population (33%) in urban environments, and applied to revised estimates of deaths and years of life lost (YLLs) for South Africa in 2000. Setting South Africa. Subjects Children under 5 years and adults 30 years and older. Outcome measures Mortality and YLLs from lung cancer and cardiopulmonary disease in adults (30 years and older), and from acute respiratory infections (ARIs) in children aged 0 - 4 years. Results Outdoor air pollution in urban areas in South Africa was estimated to cause 3.7% of the national mortality from cardiopulmonary disease and 5.1% of mortality attributable to cancers of the trachea, bronchus and lung in adults aged 30 years and older, and 1.1% of mortality from ARIs in children under 5 years of age. This amounts to 4 637 or 0.9% (95% uncertainty interval 0.3 - 1.5%) of all deaths and about 42 000 YLLs, or 0.4% (95% uncertainty interval 0.1 - 0.7%) of all YLLs in persons in South Africa in 2000. Conclusion Urban air pollution has under-recognised public health impacts in South Africa. Fossil fuel combustion emissions and traffic-related air pollution remain key targets for public health in South Africa.