Abstract for the 2017 HEI Annual Conference
Susceptibility to Multiple Air Pollutants in Cardiovascular Disease
Jane E. Clougherty1, Laura D. Kubzansky2, Colleen Reid3, Leslie McClure1
1Drexel University Dornsife School of Public Health, Philadelphia PA, USA; 2Harvard T.H. Chan School of Public Health, Boston MA, USA; 3University of Colorado at Boulder, Boulder CO, USA
Cardiovascular disease (CVD) is the leading cause of death in the U.S., and substantial research links chronic and acute ambient air pollution exposures to CVD. Much of this research identifies stronger effects of air pollution in lower socioeconomic position (SEP) communities, where pollution exposures are often higher. The specific factors underlying this susceptibility, however, remain unknown. The interplay between social and environmental exposures is particularly relevant for CVD, as pollution and chronic stress each impact inflammation, metabolic function, oxidative stress, hypertension, atherosclerosis, and other processes in CVD etiology. More clearly elucidating pollution susceptibility will improve our ability to identify and characterize at-risk populations, to offer new methods for investigating multiple exposures, and, ultimately, to develop more cost-effective interventions to reduce the disproportionate CVD burdens and health disparities.
We aim to quantify combined effects of multiple pollutants and stressor exposures on CVD events, using four unique datasets that we have compiled and validated, including:
(1) Spatial data on community SEP and chronic social stressors across NYC: We have aggregated, re-formulated, and examined 27 indicators of community susceptibility factors from US and NYC administrative data, capturing 6 key domains (i.e., SEP, violence/ crime, healthcare access, physical disorder, noise/ pollution, school quality). All indicators have citywide coverage and were ‘validated’ against citywide focus groups and survey data on perceived stress and stressor exposures.
(2) Multi-pollutant spatial surfaces from the NYC Community Air Survey (NYCCAS), which monitored multiple pollutants year-round at 150 sites, and used Land Use Regression (LUR) to estimate intra-urban spatial variance in fine particles (PM2.5), nitrogen dioxide (NO2), and summertime ozone (O3).
(3) Daily data and time-trends derived from EPA Air Quality System (AQS) monitors in NYC for 2005-11, which we combine with NYCCAS surfaces to create spatio-temporal exposure estimates.
(4) Complete data on in- and outpatient unscheduled cardiovascular events presented in emergency departments of NYC hospitals 2005-2011 (n = 843,958), from NYS Department of Health Statewide Planning and Research Cooperative System (SPARCS).
We will quantify relationships between chronic and acute exposures to multiple pollutant exposures in NYC, and test whether associations vary by community SEP/ stressor exposures. We will use ecologic cross-sectional models to examine spatial relationships between multiple “chronic” pollutant and stressor exposures and age-adjusted community CVD rates. We will then examine combined effects of multiple pollutant exposures, using spatio-temporal exposure estimates and case-level hospital data in case-crossover models, which inherently adjust for individual confounders and co-morbidities. Finally, we will test whether relationships between spatio-temporal pollutant exposures and CVD events differ by community SEP and/ or chronic stressor exposures.
Poster by Clougherty et al, 2017 HEI Annual Conference