A hierarchical modeling approach to estimate regional acute health
effects of particulate matter sources.
Krall JR, Hackstadt AJ, Peng RD. A hierarchical modeling approach to
estimate regional acute health effects of particulate matter sources.
Statistics in Medicine
Exposure to particulate matter (PM) air pollution has been associated
with a range of adverse health outcomes, including cardiovascular
disease hospitalizations and other clinical parameters. Determining
which sources of PM, such as traffic or industry, are most associated
with adverse health outcomes could help guide future recommendations
aimed at reducing harmful pollution exposure for susceptible
individuals. Information obtained from multisite studies, which is
generally more precise than information from a single location, is
critical to understanding how PM impacts health and to informing local
strategies for reducing individual-level PM exposure. However, few
methods exist to perform multisite studies of PM sources, which are not
generally directly observed, and adverse health outcomes. We developed
SHared Across a REgion (SHARE), a hierarchical modeling approach that
facilitates reproducible, multisite epidemiologic studies of PM sources.
SHARE is a two-stage approach that first summarizes information about PM
sources across multiple sites. Then, this information is used to
determine how community-level (i.e., county-level or city-level) health
effects of PM sources should be pooled to estimate regional-level health
effects. SHARE is a type of population value decomposition that aims to
separate out regional-level features from site-level data. Unlike
previous approaches for multisite epidemiologic studies of PM sources,
the SHARE approach allows the specific PM sources identified to vary by
site. Using data from 2000 to 2010 for 63 northeastern US counties, we
estimated regional-level health effects associated with short-term
exposure to major types of PM sources. We found that PM from secondary
sulfate, traffic, and metals sources was most associated with
cardiovascular disease hospitalizations.