Imperial College London
Portrait Picture

ProfessorMajidEzzati

Faculty of Medicine, School of Public Health

Chair in Global Environmental Health
 
 
 
//

Contact

 

majid.ezzati Website

 
 
//

Location

 

Sir Michael Uren HubWhite City Campus

//

Summary

 

Publications

Citation

BibTex format

@article{Clark:2022:10.1016/j.envres.2022.113932,
author = {Clark, S and Alli, AS and Ezzati, M and Brauer, M and Toledano, M and Nimo, J and Bedford, Moses J and Baah, S and Hughes, A and Cavanaugh, A and Agyei-Mensah, S and Owusu, G and Robinson, B and Baumgartner, J and Bennett, J and Arku, R},
doi = {10.1016/j.envres.2022.113932},
journal = {Environmental Research},
title = {Spatial modelling and inequalities of environmental noise in Accra, Ghana},
url = {http://dx.doi.org/10.1016/j.envres.2022.113932},
volume = {214},
year = {2022}
}
Download

RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Noise pollution is a growing environmental health concern in rapidly urbanizing sub-Saharan African (SSA) cities. However, limited city-wide data constitutes a major barrier to investigating health impacts as well as implementing environmental policy in this growing population. As such, in this first of its kind study in West Africa, we measured, modelled and predicted environmental noise across the Greater Accra Metropolitan Area (GAMA) in Ghana, and evaluated inequalities in exposures by socioeconomic factors. Specifically, we measured environmental noise at 146 locations with weekly (n=136 locations) and yearlong monitoring (n=10 locations). We combined these data with geospatial and meteorological predictor variables to develop high-resolution land use regression (LUR) models to predict annual average noise levels (LAeq24hr, Lden, Lday, Lnight). The final LUR models were selected with a forward stepwise procedure and performance was evaluated with cross-validation. We spatially joined model predictions with national census data to estimate population levels of, and potential socioeconomic inequalities in, noise levels at the census enumeration-area level. Variables representing road-traffic and vegetation explained the most variation in noise levels at each site. Predicted day-evening-night (Lden) noise levels were highest in the city-center (Accra Metropolis) (median: 64.0 dBA) and near major roads (median: 68.5 dBA). In the Accra Metropolis, almost the entire population lived in areas where predicted Lden and night-time noise (Lnight) surpassed World Health Organization guidelines for road-traffic noise (Lden <53; and Lnight <45). The poorest areas in Accra also had significantly higher median Lden and Lnight compared with the wealthiest ones, with a difference of ∼5 dBA. The models can support environmental epidemiological studies, burden of disease assessments, and policies and interventions that address underlying causes of noise exposure ineq
AU  - Clark,S
AU  - Alli,AS
AU  - Ezzati,M
AU  - Brauer,M
AU  - Toledano,M
AU  - Nimo,J
AU  - Bedford,Moses J
AU  - Baah,S
AU  - Hughes,A
AU  - Cavanaugh,A
AU  - Agyei-Mensah,S
AU  - Owusu,G
AU  - Robinson,B
AU  - Baumgartner,J
AU  - Bennett,J
AU  - Arku,R
DO  - 10.1016/j.envres.2022.113932
PY  - 2022///
SN  - 0013-9351
TI  - Spatial modelling and inequalities of environmental noise in Accra, Ghana
T2  - Environmental Research
UR  - http://dx.doi.org/10.1016/j.envres.2022.113932
UR  - http://hdl.handle.net/10044/1/98470
VL  - 214
ER  -
Download