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Estimating deaths attributable to airborne particles: sensitivity of the results to different exposure assessment approaches

Overview of attention for article published in Environmental Health, February 2017
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Title
Estimating deaths attributable to airborne particles: sensitivity of the results to different exposure assessment approaches
Published in
Environmental Health, February 2017
DOI 10.1186/s12940-017-0213-9
Pubmed ID
Authors

Simone Giannini, Michela Baccini, Giorgia Randi, Giovanni Bonafè, Paolo Lauriola, Andrea Ranzi

Abstract

Epidemiological evidences support the existence of an effect of airborne particulate on population health. However, few studies evaluated the robustness of the results to different exposure assessment approaches. In this paper, we estimated short term effects and impacts of high levels of particulate matter with aerodynamic diameter ≤10 μm (PM10) and ≤2.5 μm (PM2.5) in the Emilia-Romagna region (Northern Italy), one of the most polluted areas in Europe, in the period 2006-2010, and checked if the results changed when different exposure definitions were used. Short-term impact of particles on population mortality was assessed, both considering the 9 provincial capitals of the Emilia-Romagna and the region as a whole. We estimated the effects of PM10 and PM2.5 on natural mortality by combining city-specific results in a Bayesian random-effects meta-analysis, and we used these estimates to calculate impacts in terms of attributable deaths. For PM10, we considered different definitions of exposure, based on the use of the air pollutant levels measured by different monitoring stations (background or traffic monitors) or predicted by a dispersion model. Annual average concentrations of PM10 and PM2.5 exceeding the WHO limits of 20 and 10 μg/m(3) were respectively responsible for 5.9 and 3.0 deaths per 100 000 inhabitants per year in the provincial capitals, during the period 2006-2010. The total impact in the region in 2010 amounted to 4.4 and 2.8 deaths per 100 000 for PM10 and PM2.5, respectively. The impact estimates for PM10 did not substantially change when the exposure levels were derived from background or traffic monitoring stations, or arose from the dispersion model, in particular when the counterfactual value of 20 μg/m(3) was considered. The effect estimates appeared more sensitive to the exposure definition. A reduction in particle concentrations could have produced significant health benefits in the region. This general conclusion did not change when different exposure definitions were used, provided that the same exposure assessment approach was used for both effect and impact estimations. Caution is therefore recommended when using effect estimates from the literature to assess health impacts of air pollution in actual contexts.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Australia 1 3%
Unknown 37 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 29%
Student > Ph. D. Student 4 11%
Other 3 8%
Student > Postgraduate 3 8%
Lecturer 2 5%
Other 8 21%
Unknown 7 18%
Readers by discipline Count As %
Environmental Science 10 26%
Medicine and Dentistry 7 18%
Nursing and Health Professions 3 8%
Mathematics 2 5%
Agricultural and Biological Sciences 2 5%
Other 5 13%
Unknown 9 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 February 2017.
All research outputs
#20,406,219
of 22,955,959 outputs
Outputs from Environmental Health
#1,348
of 1,498 outputs
Outputs of similar age
#271,129
of 311,194 outputs
Outputs of similar age from Environmental Health
#32
of 36 outputs
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