Dataset Information

The estimated change in the level and distribution of PM2.5-attributable health impacts in the United States: 2005-2014.

ABSTRACT: BACKGROUND:Photochemical modeling can predict the level and distribution of pollutant concentrations over time, but is resource-intensive. Partly for this reason, there are few studies exploring the multi-year trajectory of the historical change in fine particle (PM2.5) levels and associated health impacts in the U.S. OBJECTIVES:We used a unique dataset of Community Multi-Scale Air Quality (CMAQ) model simulations performed for a subset of years over a decade-long period fused with observations to estimate the change in ambient levels of PM2.5 across the contiguous U.S. We also quantified the change in PM2.5-attributable health risks and characterized the level of risk inequality over this period. METHODS:We estimated annual mean PM2.5 concentrations in 2005, 2011 and 2014. Using log-linear and logistic concentration-response coefficients we estimated changes in the numbers of deaths, hospital admissions and other morbidity outcomes. Calculating the Gini coefficient and Atkinson Index, we characterized the extent to which PM2.5 attributable risks were shared equally across the population or instead concentrated among certain subgroups. RESULTS:In 2005 the estimated fraction of deaths due to PM2.5 was 6.1%. This estimated value falls to 4.6% by 2014. Every portion of the contiguous U.S. experiences a decline in the risk of PM-related premature death over the 10-year period. As measured by the Gini coefficient and Atkinson index, the level of PM mortality risk is shared more equally in 2014 than in 2005 among all subgroups. CONCLUSIONS:Between 2005 and 2014, the level of PM2.5 concentrations fall, and the risk of premature death, declined and became more equitably distributed across the U.S. POPULATION:

SUBMITTER: Fann N

PROVIDER: S-EPMC6716061 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

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The estimated change in the level and distribution of PM<sub>2.5</sub>-attributable health impacts in the United States: 2005-2014.

Fann Neal N Coffman Evan E Timin Brian B Kelly James T JT

Environmental research 20180813

<h4>Background</h4>Photochemical modeling can predict the level and distribution of pollutant concentrations over time, but is resource-intensive. Partly for this reason, there are few studies exploring the multi-year trajectory of the historical change in fine particle (PM<sub>2.5</sub>) levels and associated health impacts in the U.S.<h4>Objectives</h4>We used a unique dataset of Community Multi-Scale Air Quality (CMAQ) model simulations performed for a subset of years over a decade-long perio ...[more]

PMID: 30142626

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Project description:BackgroundThe respiratory system of children is vulnerable to exposure to particulate matter (PM) with a diameter of less than 2.5 and 10 μm (PM2.5 and PM10) or even lower.ObjectiveThis study assessed PM10 and PM2.5 levels and respiratory health impacts on children in schools located in an industrialized suburb in Kenya.MethodThe PM10 and PM2.5 levels were sampled from five public primary schools in Athi River Township and a control school during the wet and dry seasons. Outdoor and classroom samples were collected concurrently on an 8-hour mean during school hours on two consecutive days in each school and analyzed using gravimetric techniques. Five hundred and seventy-eight (n = 578) pupils aged 9-14 years from these schools were also evaluated for symptoms of respiratory illnesses and lung function using a questionnaire and spirometric method, respectively, during the same periods.ResultsIndoor median PM10 levels (μg/m3) ranged from 60.8-269.1 and 52.8-232.3 and PM2.5 values (μg/m3) of 17.7-52.4 and 28.5-75.5 during the dry and wet seasons, respectively. The control classrooms had significantly (p <0.05) lower median PM10 levels (μg/m3) of 5.2 and 4.2, and PM2.5 levels (μg/m3) of 3.5 and 3.0 during the respective seasons. Nearly all the classrooms in Athi River schools had PM2.5 and PM10 median levels that exceeded the World Health Organization (WHO) recommended levels. The indoor-to-outdoor ratios varied from 0.35-1.40 and 0.80-2.40 for PM10 and 0.30-0.80 and 0.80-1.40 for PM2.5 during the dry and wet seasons, respectively, suggesting higher levels in the classrooms during the wet season. The relative risk (RR) and odds ratio (OR) presented higher prevalence of respiratory diseases following PM exposure in all the Athi River schools than the control during the dry and wet seasons. At 95% CI, the RR and OR showed strong associations between high PM10 and PM2.5 levels and lung function deficits and vice versa. The association was more prevalent during the wet season.ConclusionsThe study calls for effective indoor air management programs in school environments to reduce PM exposure and respiratory health impacts.Participant consentObtained.Ethics approvalThe research permit and approvals were obtained from the University of Nairobi/Kenyatta National Hospital Ethics and Research Committee (KNH-UoN ERC Reference: P599/08/2016) and the National Commission for Science, Technology and Innovation (Reference: NACOSTI/P/18/4268/25724).Competing interestsThe authors declare no competing financial interests.

Project description:BackgroundSubstantial increases in wildfire activity have been recorded in recent decades. Wildfires influence the chemical composition and concentration of particulate matter ≤2.5 μm in aerodynamic diameter (PM2.5). However, relatively few epidemiologic studies focus on the health impacts of wildfire smoke PM2.5 compared with the number of studies focusing on total PM2.5 exposure.ObjectivesWe estimated the associations between cardiorespiratory acute events and exposure to smoke PM2.5 in Colorado using a novel exposure model to separate smoke PM2.5 from background ambient PM2.5 levels.MethodsWe obtained emergency department visits and hospitalizations for acute cardiorespiratory outcomes from Colorado for May-August 2011-2014, geocoded to a 4 km geographic grid. Combining ground measurements, chemical transport models, and remote sensing data, we estimated smoke PM2.5 and non-smoke PM2.5 on a 1 km spatial grid and aggregated to match the resolution of the health data. Time-stratified, case-crossover models were fit using conditional logistic regression to estimate associations between fire smoke PM2.5 and non-smoke PM2.5 for overall and age-stratified outcomes using 2-day averaging windows for cardiovascular disease and 3-day windows for respiratory disease.ResultsPer 1 μg/m3 increase in fire smoke PM2.5, statistically significant associations were observed for asthma (OR = 1.081 (1.058, 1.105)) and combined respiratory disease (OR = 1.021 (1.012, 1.031)). No significant relationships were evident for cardiovascular diseases and smoke PM2.5. Associations with non-smoke PM2.5 were null for all outcomes. Positive age-specific associations related to smoke PM2.5 were observed for asthma and combined respiratory disease in children, and for asthma, bronchitis, COPD, and combined respiratory disease in adults. No significant associations were found in older adults.DiscussionThis is the first multi-year, high-resolution epidemiologic study to incorporate statistical and chemical transport modeling methods to estimate PM2.5 exposure due to wildfires. Our results allow for a more precise assessment of the population health impact of wildfire-related PM2.5 exposure in a changing climate.

Dataset Information

The estimated change in the level and distribution of PM2.5-attributable health impacts in the United States: 2005-2014.

Publications

The estimated change in the level and distribution of PM<sub>2.5</sub>-attributable health impacts in the United States: 2005-2014.

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