Impact of ambient air pollution exposure during pregnancy on adverse birth outcomes: generalized structural equation modeling approach.

BACKGROUND: Air pollution and several prenatal factors, such as socio-demographic, behavioural, physical activity and clinical factors influence adverse birth outcomes. The study aimed to investigate the impact of ambient air pollution exposure during pregnancy adjusting prenatal risk factors on adverse birth outcomes among pregnant women in MACE birth cohort. METHODS: Data for the study was obtained from the Mother and Child in the Environment (MACE) birth cohort study in Durban, South Africa from 2013 to 2017. Land use regression models were used to determine household level prenatal exposure to PM2.5, SO2 and NOx. Six hundred and fifty-six births of pregnant females were selected from public sector antenatal clinics in low socio-economic neighbourhoods. We employed a Generalised Structural Equation Model with a complementary log-log-link specification. RESULTS: After adjustment for potential prenatal factors, the results indicated that exposure to PM2.5 was found to have both significant direct and indirect effects on the risk of all adverse birth outcomes. Similarly, an increased level of maternal exposure to SO2 during pregnancy was associated with an increased probability of being small for gestational age. Moreover, preterm birth act a mediating role in the relationship of exposure to PM2.5, and SO2 with low birthweight and SGA. CONCLUSIONS: Prenatal exposure to PM2.5 and SO2 pollution adversely affected birth outcomes after controlling for other prenatal risk factors. This suggests that local government officials have a responsibility for better control of air pollution and health care providers need to advise pregnant females about the risks of air pollution during pregnancy.

A hybrid air pollution / land use regression model for predicting air pollution concentrations in Durban, South Africa.

The objective of this paper was to incorporate source-meteorological interaction information from two commonly employed atmospheric dispersion models into the land use regression technique for predicting ambient nitrogen dioxide (NO2), sulphur dioxide (SO2), and particulate matter (PM10). The study was undertaken across two regions in Durban, South Africa, one with a high industrial profile and a nearby harbour, and the other with a primarily commercial and residential profile. Multiple hybrid models were developed by integrating air pollution dispersion modelling predictions for source specific NO2, SO2, and PM10 concentrations into LUR models following the European Study of Cohorts for Air Pollution Effects (ESCAPE) methodology to characterise exposure, in Durban. Industrial point sources, ship emissions, domestic fuel burning, and vehicle emissions were key emission sources. Standard linear regression was used to develop annual, summer and winter hybrid models to predict air pollutant concentrations. Higher levels of NO2 and SO2 were predicted in south Durban as compared to north Durban as these are industrial related pollutants. Slightly higher levels of PM10 were predicted in north Durban as compared to south Durban and can be attributed to either traffic, bush burning or domestic fuel burning. The hybrid NO2 models for annual, summer and winter explained 60%, 58% and 63%, respectively, of the variance with traffic, population and harbour being identified as important predictors. The SO2 models were less robust with lower R2 annual (44%), summer (53%) and winter (46%), in which industrial and traffic variables emerged as important predictors. The R2 for PM10 models ranged from 80% to 85% with population and urban land use type emerging as predictor variables.

Informal-sector occupational hazards: an observational workplace assessment of the traditional medicine trade in South Africa.

Informal traditional medicine markets are trading and processing hubs for a range of plant, animal and mineral materials; however, little is known regarding the occupational risks associated with the processing and handling of these products. The aim of this study was to identify the workplace hazards of the traditional medicine trade. A walk-through observation of the workplace was conducted by two independent observers with formal training in workplace risk evaluation. Ergonomic, physical, chemical, biological and environmental hazards were identified from the handling of plant, animal and/or mineral products. The study gives an insight into a unique and diverse sector.

Harbor and Intra-City Drivers of Air Pollution: Findings from a Land Use Regression Model, Durban, South Africa.

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.

The spatial modification of the non-linear effects of ambient oxides of nitrogen during pregnancy on birthweight in a South African birth cohort.

Birthweight is strongly associated with infant mortality and is a major determinant of infant survival. Several factors such as maternal, environmental, clinical, and social factors influence birthweight, and these vary geographically, including across low, middle, and economically advanced countries. The aim of the study was to investigate the geographical modification of the effect of oxides of nitrogen exposure on birthweight adjusted for clinical and socio-demographic factors. Data for the study was obtained from the Mother and Child in the Environment birth cohort study in Durban, South Africa. Pregnant females were selected from public sector antenatal clinics in low socioeconomic neighborhoods. Land use regression models were used to determine household level antenatal exposure to oxides of nitrogen (NOx). Six hundred and seventy-seven births were analysed, using the geoadditive model with Gaussian distribution and identity link function. The newborns in the cohort had a mean birthweight of 3106.5 g (standard deviation (SD): 538.2 g and the maternal mean age was 26.1 years (SD: 5.7). A spatially modified NOx exposure-related effect on birthweight was found across two geographic regions in Durban. Prenatal exposure to NOx was also found to have a non-linear effect on the birthweight of infants. The study suggested that incorporating spatial variability is important to understand and design appropriate policies to reduce air pollution in order to prevent risks associated with birthweight.

HIV induced nitric oxide and lipid peroxidation, influences neonatal birthweight in a South African population.

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.

OGG1 Ser326Cys polymorphism, HIV, obesity and air pollution exposure influences adverse birth outcome susceptibility, within South African Women.

The global HIV and obesity epidemics are major public health concerns; particularly as both are associated with increased risk of adverse birth outcomes. Despite extensive research, their combined effect, in terms of birth outcomes, has not been investigated. A single-nucleotide polymorphism (SNP) within 8-oxoguanine glycosylase 1 (OGG1) (Ser326Cys) has been suggested to affect body mass indices and therefore could predispose South African (SA) women to adverse effects of obesity. This study investigated the associations of OGG1 Ser326Cys SNP in relation to HIV and obesity on the susceptibility of low-birthweight (LBW) and pre-term birth (PTB) in SA women exposed to ambient air-pollution living in Durban. In our study population, the OGG1 SNP was associated with HIV and obesity. Wild-type (CC)-carrying patients had increased susceptibility for HIV-associated LBW and PTB. Co-morbid HIV and obese patients delivered neonates with decreased birthweights. Living within the heavily-polluted south-Durban and carrying the CC-genotype increased the risk for PTB within our study population.

The Effect of Nitric Oxide Pollution on Oxidative Stress in Pregnant Women Living in Durban, South Africa.

The purpose of the study was to evaluate the effect nitric oxide (NO x ) pollution had on maternal serum 8-oxo-7,8-dihydro-2'-deoxyguanosine (8-OHdG) levels and neonatal outcomes in pregnant women living in Durban, South Africa (SA). Women, in their third trimester with singleton pregnancies, were recruited from the heavily industrialised south (n = 225) and less industrialised north (n = 152). Biomarker levels of serum 8-OHdG concentrations were analysed, and the women were genotyped for glutathione-S-transferases pi 1 (GSTP1) and glutathione-S-transferases mu 1 (GSTM1) polymorphisms. The level of NO x pollution in the two regions was determined by using land use regression modelling. The serum 8-OHdG was shown to correlate significantly with NO x levels; this relationship was strengthened in the south (p < 0.05). This relationship was still observed after adjusting for maternal characteristics. GSTP1 was significantly associated with the south region, where the variant (AG+GG) genotype was associated with increased 8-OHdG levels as a result of NO x exposure (p < 0.05). GSTM1 null genotype was associated with a positive correlation between NO x and 8-OHdG levels (p < 0.05). NO x levels were found marginally to reduce gestational age (p < 0.05) with mothers carrying male neonates. Variant GSTP1 and living in the north were factors that contributed to gestational age reduction (p < 0.05). Our study demonstrated that NO x exposure resulted in increased 8-OHdG levels in pregnant women living in Durban, SA, which led to gestational age reduction. The GSTP1 variant increased susceptibility of individuals to harmful effects of NO x .

Land use regression modelling estimating nitrogen oxides exposure in industrial south Durban, South Africa.

BACKGROUND: The South Durban (SD) area of Durban, South Africa, has a history of air pollution issues due to the juxtaposition of low-income communities with industrial areas. This study used measurements of oxides of nitrogen (NOx) to develop a land use regression (LUR) model to explain the spatial variation of air pollution concentrations in this area. METHODS: Ambient NOx was measured over two two-week sampling periods at 32 sites using Ogawa badges. Following the ESCAPE approach, an annual adjusted average was calculated for these results and regressed against pre-selected geographic predictor variables in a multivariate regression model. The LUR model was then applied to predict the NOx exposure of a sample of pregnant women living in South Durban. RESULTS: Measured NOx levels ranged from 22.3-50.9µg/m3 with a median of 36µg/m3. The model developed accounts for 73% of the variance in ambient NOx measurements using three input variables (length of minor roads within a 1000m radius, length of major roads within a 300m radius, and area of open space within a 1000m radius). Model cross validation yielded a R2 of 0.59. Subsequent participant exposure estimates indicated exposure to ambient NOx ranged from 19.9-53.2µg/m3, with a mean of 39µg/m3. DISCUSSION AND CONCLUSION: This is the first study to develop a land use regression model that predicts ambient concentrations of NOx in a South African context. The findings of this study indicate that the participants in the South Durban are exposed to high levels of NOx that can be attributed mainly to traffic.