Estimating the burden of disease attributable to ambient air pollution (ambient PM2.5 and ambient ozone) in South Africa for 2000, 2006 and 2012

Roomaney, R A; Cairncross, Eugene; Tesfaye, M.; Kapwata, Thandi; Abdulatif, N; Olivier, C; Mathibela, K; Cois, Annibale; Neethling, I; Botai, Joel Ongego; Turawa, E B; Awotiwon, O F; Chetty, K; Nojilana, Beatrice; Wright, Caleb; Pacella, Rosana; Bradshaw, Debbie; Wyk, Victoria Pillay-van

doi:10.7196/samj.2022.v112i8b.16483

Cited by 6 publications

(9 citation statements)

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“…[31][32][33][34][35] For the estimation of concentrations of ambient air pollution (particulate matter with an aerodynamic diameter ≤2.5 µm (PM 2.5 ) and ozone) in 2012, we employed a regionally optimised fully coupled climate-chemistry model along with locally informed model forcing datasets. [36] Fine-scale regional models allow for the generation of more realistic small-scale climate information, chemical processes and patterns compared with global coarseresolution models. [37] To further enhance the quality of modelled values and ensure their reliable applicability for regional exposure studies, bias corrections were performed using regionally obtained and quality-controlled surface observation datasets.…”

Section: Estimation Of Exposure Levelsmentioning

confidence: 99%

“…Subsequently, for exposure and population-weighted analysis, the bias-corrected gridded distribution of PM 2.5 and ozone were transferred into small area level population census polygons using a polygonal sizedependent multi-gridpoint weighted average matrix method, which has more than 99% transformation accuracy. [36] Heterogeneity in the type of measures (i.e. cases where the different sources reported on multiple related indicators for the same exposure) were addressed by converting all data to a common 'reference' format using empirically observed relationships between the reference format and the non-standard indicators.…”

Section: Estimation Of Exposure Levelsmentioning

confidence: 99%

“…The detailed evaluation of each risk factor and the quantification of the resultant attributable burden [19][20][21][22][23][24][25][26][27][31][32][33][34][35][36] revealed insights into trends. Key observations for each risk factor are summarised in Table 3.…”

Section: Researchmentioning

confidence: 99%

“…and ozone [36] • In 2012, approximately 97.6% of people in South Africa were exposed to PM 2.5 at levels above the 2005 WHO guideline: 10 μg/m 3 annual mean.…”

Section: Researchmentioning

confidence: 99%

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Overview

Bradshaw

van-Wyk²,

Neethling³

et al. 2022

S Afr Med J

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Background. South 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. Objective. To estimate the attributable burden of 18 modifiable risk factors for 2000, 2006 and 2012. Methods. Comparative 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. Results. Unsafe 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%). Conclusion. This 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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Section: Estimation Of Exposure Levelsmentioning

confidence: 99%

Section: Estimation Of Exposure Levelsmentioning

confidence: 99%

Section: Researchmentioning

confidence: 99%

“…and ozone [36] • In 2012, approximately 97.6% of people in South Africa were exposed to PM 2.5 at levels above the 2005 WHO guideline: 10 μg/m 3 annual mean.…”

Section: Researchmentioning

confidence: 99%

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Overview

Bradshaw

van-Wyk²,

Neethling³

et al. 2022

S Afr Med J

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“…PM 2.5 was reported to be responsible for an estimated 5 million premature deaths and 147 million disability-adjusted life years in 2017 9 – 11 . It is well established that PM 2.5 exposure has both acute and chronic health consequences 12 – 15 . Exposure to PM 2.5 can trigger and/or aggravate a wide range of respiratory system-related disorders, including asthma, lung cancer, silicosis, irritating mucous membrane of the respiratory track, inflammation of the mucous membrane, bronchitis, pulmonary emphysema, lung inflammatory reactions, chronic obstructive pulmonary disease (COPD), and pneumonia 4 , 16 .…”

Section: Introductionmentioning

confidence: 99%

Quantification of ambient PM2.5 concentrations adjacent to informal brick kilns in the Vhembe District using low-cost sensors

Aniyikaiye,

Piketh,

Edokpayi

2023

Sci Rep

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The widespread exposure to ambient PM2.5 poses a substantial health risk globally, with a more pronounced impact on low- to medium-income nations. This study investigates the spatiotemporal distribution of PM2.5 in the communities hosting informal brickmaking industries in Vhembe District. Utilizing Dylos DC1700, continuous monitoring of PM2.5 was conducted at nine stations adjacent to informal brick kilns from March 2021 to February 2022. The study determined the correction factor for PM2.5 measurements obtained from the Dylos DC1700 when it was collocated with the GRIMM Environmental Dust Monitor 180. Additionally, the diurnal and seasonal variations across monitoring stations were assessed, and potential PM2.5 sources were identified. The study also evaluated the compliance of ambient PM2.5 concentrations across the stations with the South African National Ambient Air Quality Standard (NAAQS) limits. Annual PM2.5 concentrations for the stations ranged from 22.6 to 36.2 μgm−3. Diurnal patterns exhibited peak concentrations in the morning and evening, while seasonal variations showed higher concentrations in winter and lower concentrations in summer and spring. All monitoring stations reported the highest daily exceedance with respect to the daily NAAQS limit in the winter. Major PM2.5 sources included domestic biomass combustion, vehicular emissions, industrial emissions, and construction sites. Well-calibrated low-cost sensors could be employed in suburb regions with scarce air quality data. Findings from the study could be used for developing mitigation strategies to reduce health risks associated with PM2.5 exposure in the area.

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