• D Bradshaw, V Pillay van-Wyk, I Neethling, R A Roomaney, A Cois, J D Joubert, N Nannan, N Abdelatief, O F Awotiwon, E B Turawa, B Nojilana, P Groenewald, R Matzopoulos, M Prinsloo, E Cairncross, C Y Wright, N Peer, R Pacella, and The Sacra Collaborative Group.
• Burden of Disease Research Unit, South African Medical Research Council, Cape Town, South Africa; School of Public Health and Family Medicine, Faculty of Health Sciences, University of Cape Town, South Africa. debbie.bradshaw@mrc.ac.za.
• S. Afr. Med. J. 2022 Sep 30; 112 (8b): 556570556-570.

BackgroundSouth Africa (SA) faces multiple health challenges. Quantifying the contribution of modifiable risk factors can be used to identify and prioritise areas of concern for population health and opportunities for health promotion and disease prevention interventions.ObjectiveTo estimate the attributable burden of 18 modifiable risk factors for 2000, 2006 and 2012.MethodsComparative risk assessment (CRA), a standardised and systematic approach, was used to estimate the attributable burden of 18 risk factors. Risk exposure estimates were sourced from local data, and meta-regressions were used to model the parameters, depending on the availability of data. Risk-outcome pairs meeting the criteria for convincing or probable evidence were assessed using relative risks against a theoretical minimum risk exposure level to calculate either a potential impact fraction or population attributable fraction (PAF). Relative risks were sourced from the Global Burden of Disease, Injuries, and Risk Factors (GBD) study as well as published cohort and intervention studies. Attributable burden was calculated for each risk factor for 2000, 2006 and 2012 by applying the PAF to estimates of deaths and years of life lost from the Second South African National Burden of Disease Study (SANBD2). Uncertainty analyses were performed using Monte Carlo simulation, and age-standardised rates were calculated using the World Health Organization standard population.ResultsUnsafe sex was the leading risk factor across all years, accounting for one in four DALYs (26.6%) of the estimated 20.6 million DALYs in 2012. The top five leading risk factors for males and females remained the same between 2000 and 2012. For males, the leading risks were (in order of descending rank): unsafe sex; alcohol consumption; interpersonal violence; tobacco smoking; and high systolic blood pressure; while for females the leading risks were unsafe sex; interpersonal violence; high systolic blood pressure; high body mass index; and high fasting plasma glucose. Since 2000, the attributable age-standardised death rates decreased for most risk factors. The largest decrease was for household air pollution (-41.8%). However, there was a notable increase in the age-standardised death rate for high fasting plasma glucose (44.1%), followed by ambient air pollution (7%).ConclusionThis study reflects the continued dominance of unsafe sex and interpersonal violence during the study period, as well as the combined effects of poverty and underdevelopment with the emergence of cardiometabolic-related risk factors and ambient air pollution as key modifiable risk factors in SA. Despite reductions in the attributable burden of many risk factors, the study reveals significant scope for health promotion and disease prevention initiatives and provides an important tool for policy makers to influence policy and programme interventions in the country.

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