Online Program

333681
Geospatial Analysis and Modeling of the Associations between Climate Change, Air Pollution and Cardiovascular Risk in the United States


Tuesday, November 3, 2015

Longjian Liu, MD, PhD, MSc (LSHTM), FAHA, Dornsife School of Public Health, Department of Epidemiology and Biostatistics, Drexel University, Philadelphia, PA
Hui Liu, MSc, Epidemiology and Biostatistics, Drexel University School of Public Health, Philadelphia, PA
Xuan Yang, MPH, Epidemiology and Biostatistics, Drexel University School of Public Health, Philadephia, PA
Shannon Marquez, PhD, MEng, School of Public Health, Drexel University, Philadelphia, PA
Seth Welles, ScD, PhD, Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Philadelphia, PA
Arthur Frank, MD, Enviromental and Occupational Health, Drexel University School of Public Health, Philadephia, PA
Charles N. Haas, PhD, F. AEESP, BCEEM, F ASCE, F AAAS, F AAM, F IWA, F SRA, Civil, Architectural, and Environmental Engineering, Drexel University College of Engineering, Philadephia, PA
No study was conducted to test the complex geospatial associations of climate change, air pollution with health outcomes using data from nationally representative sample. The present study, as part of the Drexel-SARI Low-Carbon and Urban Health Study, aimed to fill in this gap. We used 2010-2013 EPA daily surveillance air pollution data among 170 to 825 cities and counties of 50 U.S. states, and annual average health outcomes data of the prevalence of coronary heart disease (CHD), stroke, diabetes mellitus (DM), hypertension and all-cause mortality from U.S. census and CDC between 2010 and 2013. Six standard air pollution indicators [particulate matter (PM2.5 and PM10), carbon monoxide (CO), nitrogen dioxide (NO), Ozone (O3), sulfur dioxide (SO2), and lead] were included in the analysis. Average annual pollution values were estimated at city and county levels. Partial correlation and multilevel regression analysis were conducted using an ecological study design. The results show that cities and counties with higher levels of air pollutant indexes in the southeast and northeast had significantly higher prevalence of CHD, stroke, DM, hypertension and all-cause mortality. After adjustment for average annual temperature and percentage of rural population, PM2.5 and SO2 remained significantly correlated with the study outcomes of the interest. These corresponding correlation coefficients of PM2.5 were 0.59 (p<.001) with CHD, 0.47 (p=0.002) with stroke, 0.52 (p=0.001) with DM, 0.43 (p=0.01) with hypertension, and 0.35 (p=0.026) with all-cause mortality, respectively; and of SO2 were 0.49 (p=0.001), 0.62 (p<.001), 0.22 (p=0.18), 0.47 (p=0.002), and 0.55 (p=0.002) with CHD, stroke, DM, hypertension, and all-cause mortality, respectively.  In conclusion, using nationally representative data the present study provides new evidence of a positive and significant association of air pollution with several major noncommunicable diseases, and this air quality – disease association is partly modified by climate changes.        

Learning Areas:

Chronic disease management and prevention
Environmental health sciences
Epidemiology

Learning Objectives:
Analyze the association between climate change, air pollution and non-communicable disease

Keyword(s): Climate and Health, Air Pollution & Respiratory Health

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I am qualified to be an abstract on the content I am responsible for because I have worked in publication health for years.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.