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Comparison of wildfire smoke estimation methods and associations with cardiopulmonary-related hospital admissions

Filetype[PDF-1.12 MB]


  • English
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    Details:

    • Alternative Title:
      Geohealth
    • Personal Author:
    • Description:
      Climate forecasts predict an increase in frequency and intensity of wildfires. Associations between health outcomes and population exposure to smoke from Washington 2012 wildfires were compared using surface monitors, chemical-weather models, and a novel method blending three exposure information sources. The association between smoke particulate matter ≤2.5 μm in diameter (PM|) and cardiopulmonary hospital admissions occurring in Washington from 1 July to 31 October 2012 was evaluated using a time-stratified case-crossover design. Hospital admissions aggregated by ZIP code were linked with population-weighted daily average concentrations of smoke PM| estimated using three distinct methods: a simulation with the Weather Research and Forecasting with Chemistry (WRF-Chem) model, a kriged interpolation of PM| measurements from surface monitors, and a geographically weighted ridge regression (GWR) that blended inputs from WRF-Chem, satellite observations of aerosol optical depth, and kriged PM|. A 10 μg/m| increase in GWR smoke PM| was associated with an 8% increased risk in asthma-related hospital admissions (odds ratio (OR): 1.076, 95% confidence interval (CI): 1.019-1.136); other smoke estimation methods yielded similar results. However, point estimates for chronic obstructive pulmonary disease (COPD) differed by smoke PM| exposure method: a 10 μg/m| increase using GWR was significantly associated with increased risk of COPD (OR: 1.084, 95%CI: 1.026-1.145) and not significant using WRF-Chem (OR: 0.986, 95%CI: 0.931-1.045). The magnitude (OR) and uncertainty (95%CI) of associations between smoke PM| and hospital admissions were dependent on estimation method used and outcome evaluated. Choice of smoke exposure estimation method used can impact the overall conclusion of the study.
    • Source:
      Geohealth. 1(3):122-136
    • Pubmed ID:
      28868515
    • Pubmed Central ID:
      PMC5580836
    • Document Type:
      Journal Article
    • Funding:
      CC999999/Intramural CDC HHSUnited States/
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