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.

Maternal exposure to indoor PM and associated adverse birth outcomes in low socio-economic households, Durban, South Africa.

The association between in utero exposure to indoor PM and birth outcomes is not conclusive. We assessed the association between in utero exposure to indoor PM , birth weight, gestational age, low birth weight, and/or preterm delivery. Homes of 800 pregnant women were assessed using a structured walkthrough questionnaire.

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 (NO), sulphur dioxide (SO), and particulate matter (PM). 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 NO, SO, and PM concentrations into LUR models following the European Study of Cohorts for Air Pollution Effects (ESCAPE) methodology to characterise exposure, in Durban.

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 (PM and PM), sulphur dioxide (SO), and nitrogen dioxide (NO) 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.

Predictors of urban household variability of indoor PM in low socio-economic communities.

In epidemiological studies, levels of PM2.5 need to be estimated over time and space. Because of logistical constraints, very few studies have been conducted to assess the variability within and across homes and the predictors of this variability.