An Integrated Risk Function for Estimating the Global Burden of Disease Attributable to Ambient Fine Particulate Matter Exposure

April 2, 2014 · 0 comments

An Integrated Risk Function for Estimating the Global Burden of Disease Attributable to Ambient Fine Particulate Matter Exposure. Environmental Health Perspectives, Feb 2014.

Authors: Richard T. Burnett, et al.

Background: Estimating the burden of disease attributable to long-term exposure to fine particulate matter (PM2.5) in ambient air requires knowledge of both the shape and magnitude of the relative risk function (RR). However, there is inadequate direct evidence to identify the shape of the mortality RR functions at high ambient concentrations observed in many places in the world.

Objective: Develop relative risk (RR) functions over entire global exposure range for causes of mortality in adults: ischemic heart disease (IHD), cerebrovascular disease (stroke), chronic obstructive pulmonary disease (COPD), and lung cancer (LC). In addition, develop RR functions for the incidence of acute lower respiratory infection (ALRI) that can be used to estimate mortality and lost-years of healthy life in children less than 5 years old.

Methods: An Integrated Exposure-Response (IER) model was fit by integrating available RR information from studies of ambient air pollution (AAP), second hand tobacco smoke (SHS), household solid cooking fuel (HAP) and active smoking (AS). AS exposures were converted to estimated annual PM2.5 exposure equivalents using inhaled doses of particle mass. Population attributable fractions (PAF) were derived for every country based on estimated world-wide ambient PM2.5 concentrations.

Results: The IER model was a superior predictor of RR compared to seven other forms previously used in burden assessments. The PAF (%) attributable to AAP exposure varied among countries from: 2-41 for IHD, 1-43 for stroke, < 1-21 for COPD, < 1-25 for LC, and < 1-38 for ALRI.

Conclusions: We developed a fine particulate mass-based RR model that covered the global range of exposure by integrating RR information from different combustion types that generate emissions of particulate matter. The model can be updated as new RR information becomes available.

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