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Quantitative Characterization of Uncertainty in the Concentration-Response Relationship between Long-Term PM_2.5 Exposure and Mortality at Low Concentrations.

ABSTRACT: Extensive epidemiologic evidence supports a linear, no-threshold concentration-response (C-R) relationship between long-term exposure to fine particles (PM_2.5) and mortality in the United States. While examinations of the C-R relationship are designed to assess the shape of the C-R curve, they do not provide the information needed to quantitatively characterize uncertainty at specific PM_2.5 concentrations, which is often needed in the context of risk assessments and benefits analyses. We developed a novel approach, using information that is typically available in published epidemiologic studies, to quantitatively characterize uncertainty at different concentrations along the PM_2.5 concentration distribution. Our approach utilizes the annual mean PM_2.5 concentration and corresponding standard deviation from a published epidemiologic study to estimate the standard deviation of hypothetical PM_2.5 concentration distributions defined at 0.1 μg/m³ increments. The hypothetical distributions are then used to derive adjusted uncertainty estimates in the reported effect estimate at low concentrations (i.e., concentrations lower than the annual mean observed in the study). We demonstrate the application of this method in six individual epidemiologic studies that examined the relationship between long-term PM_2.5 exposure and mortality and were conducted in different geographic locations worldwide and at different PM_2.5 concentrations. This new method allows for a more comprehensive quantitative evaluation of uncertainty in the shape of the C-R relationship between long-term PM_2.5 exposure and mortality at concentrations below the mean annual concentrations observed in current studies.

SUBMITTER: Coffman E

PROVIDER: S-EPMC8167809 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:ObjectiveTo compare estimates of spatiotemporal variations of surface PM2.5 concentrations in Colombia from 2014 to 2019 derived from two global air quality models, as well as to quantify the avoidable deaths attributable to the long-term exposure to concentrations above the current and projected Colombian standard for PM2.5 annual mean at municipality level.MethodsWe retrieved PM2.5 concentrations at the surface level from the ACAG and CAMSRA global air quality models for all 1,122 municipalities, and compare 28 of them with available concentrations from monitor stations. Annual mortality data 2014-2019 by municipality of residence and pooled effect measures for total, natural and specific causes of mortality were used to calculate the number of annual avoidable deaths and years of potential life lost (YPLL) related to the excess of PM2.5 concentration over the current mean annual national standard of 25 µg/m3 and projected standard of 15 µg/m3.ResultsCompared to surface data from 28 municipalities with monitoring stations in 2019, ACAG and CAMSRA models under or overestimated annual mean PM2.5 concentrations. Estimations from ACAG model had a mean bias 1,7 µg/m3 compared to a mean bias of 4,7 µg/m3 from CAMSRA model. Using ACAG model, estimations of total nationally attributable deaths to PM2.5 exposure over 25 and 15 µg/m3 were 142 and 34,341, respectively. Cardiopulmonary diseases accounted for most of the attributable deaths due to PM2.5 excess of exposure (38%). Estimates of YPLL due to all-cause mortality for exceeding the national standard of 25 µg/m3 were 2,381 years.ConclusionComparison of two global air quality models for estimating surface PM2.5 concentrations during 2014-2019 at municipality scale in Colombia showed important differences. Avoidable deaths estimations represent the total number of deaths that could be avoided if the current and projected national standard for PM2.5 annual mean have been met, and show the health-benefit of the implementation of more restrictive air quality standards.

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Quantitative Characterization of Uncertainty in the Concentration-Response Relationship between Long-Term PM_2.5 Exposure and Mortality at Low Concentrations.

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OmicsDI is part of the ELIXIR infrastructure

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Dataset Information

Quantitative Characterization of Uncertainty in the Concentration-Response Relationship between Long-Term PM2.5 Exposure and Mortality at Low Concentrations.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Quantitative Characterization of Uncertainty in the Concentration-Response Relationship between Long-Term PM_2.5 Exposure and Mortality at Low Concentrations.