Associations of wildfire smoke PM 2.5 exposure with cardiorespiratory events in Colorado 2011-2014.

Background: Substantial 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 (PM _2.5 ). However, relatively few epidemiologic studies focus on the health impacts of wildfire smoke PM _2.5 compared with the number of studies focusing on total PM _2.5 exposure.
Objectives: We estimated the associations between cardiorespiratory acute events and exposure to smoke PM _2.5 in Colorado using a novel exposure model to separate smoke PM _2.5 from background ambient PM _2.5 levels.
Methods: We 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 PM _2.5 and non-smoke PM _2.5 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 PM _2.5 and non-smoke PM _2.5 for overall and age-stratified outcomes using 2-day averaging windows for cardiovascular disease and 3-day windows for respiratory disease.
Results: Per 1 μg/m ³ increase in fire smoke PM _2.5 , 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 PM _2.5 . Associations with non-smoke PM _2.5 were null for all outcomes. Positive age-specific associations related to smoke PM _2.5 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.
Discussion: This is the first multi-year, high-resolution epidemiologic study to incorporate statistical and chemical transport modeling methods to estimate PM _2.5 exposure due to wildfires. Our results allow for a more precise assessment of the population health impact of wildfire-related PM _2.5 exposure in a changing climate.
(Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.)