No abstract

No abstract

Multiple land use regression models (LUR) were developed for different air pollutants to characterize exposure, in the Durban metropolitan area, South Africa. Based on the European Study of Cohorts for Air Pollution Effects (ESCAPE) methodology, concentrations of particulate matter (PM10 and PM2.5), sulphur dioxide (SO2), and nitrogen dioxide (NO2) were measured over a 1-year period, at 41 sites, with Ogawa Badges and 21 sites with PM Monitors. Sampling was undertaken in two regions of the city of Durban, South Africa, one with high levels of heavy industry as well as a harbor, and the other small-scale business activity. Air pollution concentrations showed a clear seasonal trend with higher concentrations being measured during winter (25.8, 4.2, 50.4, and 20.9 µg/m3 for NO2, SO2, PM10, and PM2.5, respectively) as compared to summer (10.5, 2.8, 20.5, and 8.5 µg/m3 for NO2, SO2, PM10, and PM2.5, respectively). Furthermore, higher levels of NO2 and SO2 were measured in south Durban as compared to north Durban as these are industrial related pollutants, while higher levels of PM were measured in north Durban as compared to south Durban and can be attributed to either traffic or domestic fuel burning. The LUR NO2 models for annual, summer, and winter explained 56%, 41%, and 63% of the variance with elevation, traffic, population, and Harbor being identified as important predictors. The SO2 models were less robust with lower R2 annual (37%), summer (46%), and winter (46%) with industrial and traffic variables being important predictors. The R2 for PM10 models ranged from 52% to 80% while for PM2.5 models this range was 61–76% with traffic, elevation, population, and urban land use type emerging as predictor variables. While these results demonstrate the influence of industrial and traffic emissions on air pollution concentrations, our study highlighted the importance of a Harbor variable, which may serve as a proxy for NO2 concentrations suggesting the presence of not only ship emissions, but also other sources such as heavy duty motor vehicles associated with the port activities.

HIV has been implicated in adverse birth outcomes, due to increased oxidative stress and inflammation. In addition, HIV has been reported to increase nitric oxide levels. Therefore the combined exposures to HIV and traffic-related air pollution, within South Durban, South Africa (SA), may lead to adverse birth outcomes. However, the exact mechanism is still unknown; this study aimed to identify a potential mechanism. First, the influence of HIV on oxidative and nitrosative stress markers in pregnant women was assessed. Secondly, the effect of these stress makers and exposure to oxides of nitrogen (NOx) on neonatal birthweight (BW) was evaluated. Finally, the effect HIV and traffic-related pollution exposure has on the oxidative and endoplasmic profile and epigenetic regulation of Nrf2-Keap1 pathway by miR-144 and miR-28 in pregnant women was determined. Women, in their third trimester with singleton pregnancies, who were HIV+ and HIV-, were recruited from Durban, SA. Biomarker levels of serum nitrites/nitrates (NO) and malondialdehyde (MDA) were analysed and mRNA expression levels of oxidative and endoplasmic stress response genes were assessed. Land regression modelling was performed to determine NOx exposure levels. HIV exposure during pregnancy was associated with increased NO levels. NO was shown to reduce neonatal BW. NO and MDA was found to reciprocally increase each other, with HIV differentially influencing MDA's effect on BW. HIV down-regulated miR-144 which was negatively associated with Nrf2, suggesting a potential mechanism for HIV associated chronic oxidative stress. This study proposes that NO plays a key role in neonatal BW reduction in response to HIV and traffic-related air pollution.

No abstract