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Spatial modelling and inequalities of environmental noise in Accra, Ghana

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 firs...

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Autores principales: Clark, Sierra N., Alli, Abosede S., Ezzati, Majid, Brauer, Michael, Toledano, Mireille B., Nimo, James, Moses, Josephine Bedford, Baah, Solomon, Hughes, Allison, Cavanaugh, Alicia, Agyei-Mensah, Samuel, Owusu, George, Robinson, Brian, Baumgartner, Jill, Bennett, James E., Arku, Raphael E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9441709/
https://www.ncbi.nlm.nih.gov/pubmed/35868576
http://dx.doi.org/10.1016/j.envres.2022.113932
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author Clark, Sierra N.
Alli, Abosede S.
Ezzati, Majid
Brauer, Michael
Toledano, Mireille B.
Nimo, James
Moses, Josephine Bedford
Baah, Solomon
Hughes, Allison
Cavanaugh, Alicia
Agyei-Mensah, Samuel
Owusu, George
Robinson, Brian
Baumgartner, Jill
Bennett, James E.
Arku, Raphael E.
author_facet Clark, Sierra N.
Alli, Abosede S.
Ezzati, Majid
Brauer, Michael
Toledano, Mireille B.
Nimo, James
Moses, Josephine Bedford
Baah, Solomon
Hughes, Allison
Cavanaugh, Alicia
Agyei-Mensah, Samuel
Owusu, George
Robinson, Brian
Baumgartner, Jill
Bennett, James E.
Arku, Raphael E.
author_sort Clark, Sierra N.
collection PubMed
description 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 (LAeq(24hr), L(den), L(day), L(night)). 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 (L(den)) 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 L(den) and night-time noise (L(night)) surpassed World Health Organization guidelines for road-traffic noise (L(den) <53; and L(night) <45). The poorest areas in Accra also had significantly higher median L(den) and L(night) 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 inequalities within Accra.
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spelling pubmed-94417092022-11-01 Spatial modelling and inequalities of environmental noise in Accra, Ghana Clark, Sierra N. Alli, Abosede S. Ezzati, Majid Brauer, Michael Toledano, Mireille B. Nimo, James Moses, Josephine Bedford Baah, Solomon Hughes, Allison Cavanaugh, Alicia Agyei-Mensah, Samuel Owusu, George Robinson, Brian Baumgartner, Jill Bennett, James E. Arku, Raphael E. Environ Res Article 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 (LAeq(24hr), L(den), L(day), L(night)). 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 (L(den)) 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 L(den) and night-time noise (L(night)) surpassed World Health Organization guidelines for road-traffic noise (L(den) <53; and L(night) <45). The poorest areas in Accra also had significantly higher median L(den) and L(night) 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 inequalities within Accra. Elsevier 2022-11 /pmc/articles/PMC9441709/ /pubmed/35868576 http://dx.doi.org/10.1016/j.envres.2022.113932 Text en © 2022 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Clark, Sierra N.
Alli, Abosede S.
Ezzati, Majid
Brauer, Michael
Toledano, Mireille B.
Nimo, James
Moses, Josephine Bedford
Baah, Solomon
Hughes, Allison
Cavanaugh, Alicia
Agyei-Mensah, Samuel
Owusu, George
Robinson, Brian
Baumgartner, Jill
Bennett, James E.
Arku, Raphael E.
Spatial modelling and inequalities of environmental noise in Accra, Ghana
title Spatial modelling and inequalities of environmental noise in Accra, Ghana
title_full Spatial modelling and inequalities of environmental noise in Accra, Ghana
title_fullStr Spatial modelling and inequalities of environmental noise in Accra, Ghana
title_full_unstemmed Spatial modelling and inequalities of environmental noise in Accra, Ghana
title_short Spatial modelling and inequalities of environmental noise in Accra, Ghana
title_sort spatial modelling and inequalities of environmental noise in accra, ghana
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9441709/
https://www.ncbi.nlm.nih.gov/pubmed/35868576
http://dx.doi.org/10.1016/j.envres.2022.113932
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