2012 Progress Report: Intra-Urban Variation of Air Pollution and Cardiovascular Health Effects

EPA Grant Number: R834898
Title: Intra-Urban Variation of Air Pollution and Cardiovascular Health Effects
Investigators: Ito, Kazuhiko , Matte, Thomas , Ross, Zev
Current Investigators: Ito, Kazuhiko , Clougherty, Jane E. , Matte, Thomas , Ross, Zev
Institution: New York University School of Medicine , Hunter College , New York University
Current Institution: New York University School of Medicine , Hunter College , New York University , University of Pittsburgh
EPA Project Officer: Ilacqua, Vito
Project Period: April 1, 2011 through March 31, 2013 (Extended to December 31, 2015)
Project Period Covered by this Report: April 1, 2012 through March 31,2013
Project Amount: $299,998
RFA: Exploring New Air Pollution Health Effects Links in Existing Datasets (2010) RFA Text |  Recipients Lists
Research Category: Air Quality and Air Toxics , Health Effects , Air


The objectives of this project are to: (1) determine the impacts of air pollution and weather effects on the cardiovascular health outcomes available at New York City Department of Hygiene and Mental Health (NYCDOHMH) including cardiovascular emergency department syndrome data, hospitalizations, and mortality; (2) determine the effect modification of the cardiovascular effects by intra-urban variation of combustion sources as measured by the NYC Community Air Survey (NYCCAS); and (3) determine the effect modification of the cardiovascular effects of air pollution by socio-economic status. We recently have developed a cardiovascular ED syndrome indicator that is useful in determining near-real time impacts of weather and air pollution. NYC residents are exposed to multiple air pollutants coming from a variety of combustion sources including transported secondary aerosols, local sources including traffic, building space-heating, and oil burning from ships in nearby ports. NYC residents also reflect a wide range of health and socio-economic status, and therefore likely present a range of susceptibility indicators associated with neighborhood characteristics. Thus, this study takes advantage of the unique databases that have been developed recently to determine the cardiovascular effects of air pollution in unique environmental and population settings of NYC to answer the relevant research questions.

Progress Summary:

Analysis of PM2.5 chemical constituents collected in NYCCAS: We have been analyzing the PM2.5 chemical constituents data collected during the first year of NYCCAS measurements. PM2.5 filters from 150 NYCCAS sites (each site sampled for 2 weeks in each season) in the first year, December 2008 – November 2009, were analyzed by X-ray fluorescence method. Of 51 elements measured, we retained 15 elements with sufficient signals (i.e., 70% of measurements above uncertainty) for data analysis (in elemental symbol): Na, Al, Si, S, K, Ca, Ti, V, Mn, Fe, Ni, Cu, Zn, Br, Pb. The 2-week measurements were temporally adjusted using PM2.5 mass concentrations from separate reference sites before computing annual average at each site. We conducted a hybrid factor analysis in which emission/land-use indicators for traffic, residual oil burning, tree/grass cover, marine vessels, and industrial emissions were included along with the 15 elements, black carbon (BC), nitrogen dioxide (NO2), and sulfur dioxide. Factor analysis identified factors associated with residual oil burning (Ni, Zn, SO2), traffic (BC, NO2, Cu, Ti, Fe), and soil (Al, Si). The most unambiguous factor was the one associated with the indicator for marine vessels (inverse distance to navigation paths weighted by associated berth volumes) and vanadium (V), with only minor correlation with S and black carbon but not with Ni. The estimated impact of emissions from marine vessel activity explains the spatial variation of vanadium in New York City. The indicator’s lack of correlation with Ni suggests that V is, at least spatially, a good indicator of ship-related emissions in New York City. The results are being presented at the annual conference of the International Society of Environmental Epidemiology. We also conducted land-use regressions for these chemical components and currently are a reparing a manuscript for publication.

Cardiovascular health outcome, weather, and air pollution data processing: Since the EPA IRB’s approval in last December, we have procured three types of cardiovascular disease (CVD) health outcomes to be analyzed for this project: (1) CVD emergency department (ED) visits syndrome data (2002-2011); (2) CVD hospitalizations data (2000-2010); and (3) CVD mortality (1967-2011). The ED visits syndrome and hospitalizations data are available at zip code level; mortality data are available at census-tract level from 1985. The cardiovascular ED visits syndrome data were prepared by the Bureau of Communicable Disease using the CVD syndrome definition we developed in our previous EPA project (Mathes, Ito, and Matte, 2011, doi: 10.1371/journal.pone.0014677). For CVD hospitalizations and mortality, we additionally prepared CVD sub-categories: hypertension, myocardial infarction, ischemic heart disease, dysrhythmia, heart failure, and stroke, as we did in the 2011 Ito, et al., analysis (doi:10.1289/ehp.1002667).

Analysis of citywide PM2.5 and cardiovascular health outcome data: The final goal of this project is to examine, using the NYCCAS data, the role of intra-urban variations of air pollutants in the observed associations between PM2.5 (and gaseous pollutants) and CVD health outcomes. However, we first determined if the relationships between the citywide average PM2.5 levels and CVD outcomes that we observed in our past studies (Ito, et al., 2011; Mathes, et al., 2011) remained using the database that incorporated more recent years when PM2.5 levels are lower compared to the study periods analyzed in our previous studies (years 2000-2006 in Ito, et al., 2011; 2004-2006 in Mathes, et al., 2011). We analyzed the relationship between the citywide daily average PM2.5 and CVD ED syndrome, hospitalizations, and mortality during the years 2002-2010 when all of the CVD outcomes were available. We used a Poisson time-series regression model to estimate PM2.5 risk estimates for these outcomes at lag 0 through 3 days adjusting for seasonal/temporal trends, day-of-week, and immediate and delayed temperature effects using the same model described in our studies mentioned above. We found statistically significant positive associations between PM2.5 and all the CVD outcomes in the updated database with similar patterns of associations both in terms of season and lag structure as those in the published studies mentioned above: for CVD mortality, the strongest associations were in the warm season at lag 0 and 1 days (1.5~2% per 10 mg/m3 increase); for CVD ED visits syndrome and hospitalizations, the strongest association was in the cold season at lag 0 day (~1% per 10 mg/m3 increase). Thus, the positive associations found in our past studies are still seen in the updated database that contain more recent years of data. We now are organizing the data to conduct spatially stratified analyses.

Future Activities:

Based on the land-use regression and factor analysis results we mentioned above, we will construct exposure categories to stratify the geographic units (zip codes) and conduct spatially stratified analyses (time-series and case-crossover) of CVD ED visits syndrome, hospitalizations, and mortality. In addition, we will analyze the chemical constituent data in the winters and summers of the second through fourth years of NYCCAS as they recently became available. Using this information, we will modify the spatially stratified health effects analyses taking into consideration the trend in air pollution levels and the change in spatial pattern, if any.

Journal Articles:

No journal articles submitted with this report: View all 10 publications for this project

Supplemental Keywords:

weather, mortality, hospitalizations, emergency department visits, CVD, cardiovascular disease, air pollution

Progress and Final Reports:

Original Abstract
  • 2011 Progress Report
  • 2013 Progress Report
  • 2014 Progress Report
  • Final Report