Land use regression (LUR) modelling is a common approach used in European and Northern American epidemiological studies to assess urban and traffic related air pollution exposures. Studies applying LUR in Africa are lacking. A need exists to understand if this approach holds for an African setting, where urban features, pollutant exposures and data availability differ considerably from other co...

Ambient air pollution and its exposure has been a worldwide issue can increase the possibility of health risks especially in urban areas developing countries having mixture different sources. With population, industrial development economic prosperity, is one biggest concerns Pakistan after occurrence recent smog episodes. The purpose this study was to develop land use regression (LUR) model pr...

Epidemiologic studies have consistently reported associations between outdoor fine particulate matter (PM2.5) air pollution and adverse health effects. Although Asia bears the majority of the public health burden from air pollution, few epidemiologic studies have been conducted outside of North America and Europe due in part to challenges in population exposure assessment. We assessed the feasi...

BACKGROUND The long-term health effects of coarse particular matter (PM10-2.5) are challenging to assess because of a limited understanding of the spatial variation in PM10-2.5 mass and its chemical components. OBJECTIVES We conducted a spatially intensive field study and developed spatial prediction models for PM10-2.5 mass and four selected species (copper, zinc, phosphorus, and silicon) in...

Microbial pollution in rivers poses known ecological and health risks, yet causal mechanistic linkages to sources remain difficult establish. Host-associated microbial source tracking (MST) markers help assess the risks by linking hosts contamination but do not identify locations. Land-use regression (LUR) models have been used screen locations using spatial predictors could be improved charact...