2014 Progress Report: A Multi-City Time-Series Study of Pollutant Mixtures and Acute Morbidity

EPA Grant Number: R834799C004
Subproject: this is subproject number 004 , established and managed by the Center Director under grant R834799
(EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).

Center: The Southeastern Center for Air Pollution and Epidemiology: Multiscale Measurements and Modeling of Mixtures
Center Director: Tolbert, Paige
Title: A Multi-City Time-Series Study of Pollutant Mixtures and Acute Morbidity
Investigators: Sarnat, Stefanie Ebelt , Bilonick, Richard , Darrow, Lyndsey , Klein, Mitchel , Mulholland, James , Russell, Armistead G. , Talbott, Evelynn , Tolbert, Paige , Winquist, Andrea
Institution: Emory University , Georgia Institute of Technology
EPA Project Officer: Chung, Serena
Project Period: January 1, 2011 through December 31, 2016
Project Period Covered by this Report: October 1, 2013 through September 30,2014
RFA: Clean Air Research Centers (2009) RFA Text |  Recipients Lists
Research Category: Health Effects , Air

Objective:

Although associations between ambient air pollution and acute cardiorespiratory outcomes have been observed in numerous studies, questions remain about the degree to which these findings are generalizable between locations and whether the observed health effects are due to the individual pollutants measured or to pollutants acting in combination with other pollutants. In Project 4, we are conducting a multi-city time-series study to clarify the impacts of air quality on acute cardiorespiratory morbidity in five US cities (Atlanta, GA; Birmingham, AL; Dallas, TX; Pittsburgh, PA; St. Louis, IL-MO) using novel mixture characterization metrics. Our overarching hypothesis is that factors related to air pollution mixtures, seasonality and climate, concentration-response functions, exposure measurement error, and population susceptibility and vulnerability can help explain apparent between-city heterogeneity in short-term associations between air quality measures and cardiorespiratory emergency department (ED) visits.

Progress Summary:

During the current reporting period, work on Project 4 has focused on remaining data acquisition and management activities as well as furthering work on single- and multi-city epidemiologic analyses. 

Database development.  Database activities included air quality, health outcome, and Census data focuses:

  1. From the Air Quality Core, we received and processed CMAQ-fused estimates for 12 pollutants (criteria pollutants and major PM2.5 species) for each of the five cities; this approach involves fusion of monitoring and CMAQ modeled data to enable comparison of pollutant concentrations across the five cities.  These estimates are available as daily population weighted averages (i.e., 1 value per day per study area) calculated for different study area sizes in each city (e.g., 20-county, 5-county, and 2-county Atlanta) for overarching epidemiologic analyses as well as daily ZIP code level averages for use in spatially-stratified epidemiologic analyses. 
  2. Health outcome data for Atlanta, Dallas, and St. Louis are complete.  In the past year, processing of Birmingham data was completed and a subcontract with University of Pittsburgh collaborators was initiated as planned.  University of Pittsburgh collaborators have acquired and processed ED visit data from Pittsburgh-area hospitals; for sharing these data with Emory, data use agreements between Emory and relevant Pittsburgh-area hospitals are currently being negotiated.
  3. For assessment of neighborhood-level socioeconomic conditions among the five cities, ZIP code tabulation area (ZCTA)-level data from the 5-yr average (2007-2011) American Community Survey were acquired and processed in addition to those previously acquired for Census 2000.  With the Biostatistics core, we have made plans for appropriate merging of these data with spatially-resolved AQ and ED data, accounting for changes in ZIP code boundaries over time.

Data analyses. A number of activities were conducted over the project period:

  1. Conducted single- and multi-city epidemiologic analyses of asthma/wheeze and selected cardiovascular ED visits, with a focus on model development, comparison of modeling approaches, assessment of model misspecification, and assessment of pollutant lag effects.
  2. Continued efforts on application of spatially-refined modeled estimates of ambient concentrations and population exposures in Atlanta epidemiologic analyses: a) we completed work comparing exposure estimates from different exposure tiers in collaboration with EPA scientists (Baxter et al., 2013; Dionisio et al., 2013, 2014); b) we conducted preliminary analyses comparing the use of central monitor site, monitoring-based population weighted averages, and CMAQ-fused population weighted averages in epidemiologic models.  In this comparison, health effect estimates among spatiotemporally homogeneous pollutants (e.g., ozone, PM2.5) appear similar regardless of exposure assignment approach, while estimates of effect for NO2 and CO are stronger in some cities with use of CMAQ-fused data.
  3. With the Air Quality and Biostatistics Cores, continued work on methods for detecting and analyzing air pollution mixtures using multi-pollutant monitoring data: a) an approach for using classification and regression trees (C&RT) in air pollution epidemiologic research was published (Gass et al., 2014) and an extension of this approach to the multi-city context has been submitted for publication (Gass et al., submitted) and is being presented at both SER and ISEE 2014 meetings; b) our self-organizing maps approach to characterizing air pollution mixtures has been accepted for publication (Pearce et al., accepted) and an extension of this approach for use in epidemiologic analyses is in progress and will be presented at ISEE in 2014; c) an approach to estimate the joint effects of multiple pollutants was published (Winquist et al., 2014) and is being incorporated in several additional analyses throughout the project; and d) working with Project 1, we have conducted a preliminary examination of the effect of reactive oxygen species (ROS) on asthma/wheeze ED visits by retrospectively predicting DTT activity using a prediction model developed based on Project 1 data; preliminary results suggest a strong association between DTT and asthma/wheeze ED visits that is independent of the effect of PM2.5.
  4. Continued work on examining detailed PM2.5 components data in epidemiologic analyses: a) analyses examining the impact of carbon measurement methods on epidemiologic results in St. Louis was published (Winquist et al., accepted) and a manuscript examining the health effects of a range of PM components from the St. Louis Supersite is submitted (Sarnat et al., submitted); b) we compiled a dataset of speciated gaseous and particle-phase organic components available at the Jefferson St. monitoring station in Atlanta and have applied several approaches to examining the impact of organic chemical groupings on cardiorespiratory ED visits.
  5. Continued work on developing a statistical modeling approach to quantify projection uncertainties in future ambient ozone levels and their health impact due to climate change, which we have published (Chang et al., 2014) and will present at ISEE 2014.
  6. Assessed potential modifiers of the effects of ambient air pollution on health: a) multi-city analyses examining modification of air pollution-health associations by age were conducted for asthma/wheeze (see Brooke et al. ISEE 2014 abstract) and congestive heart failure outcomes; b) analyses examining modification of air pollution-health associations by neighborhood socioeconomic factors were conducted for pediatric asthma/wheeze (see O’Lenick ISEE 2014 abstract) as well as for congestive heart failure outcomes; c) we extended our approach to estimate air exchange rates (previously conducted for a 4-yr period in Atlanta; see Sarnat J et al., 2013) to the full time periods in each of the five cities; application of these data in epidemiologic models is being implemented; d) finally, preliminary analyses examining modification of effects by season have been conducted.

Future Activities:

Over the coming year, we anticipate completing our ED visit database by incorporating data from University of Pittsburgh collaborators as well as conducting further work on merging of ZIP code level air quality, ED visit, and Census/ACS data that accounts for changing ZIP code boundaries over time.  Manuscript preparation will begin and/or continue for analyses conducted over the past year.  Current manuscripts in preparation include: 1) A framework for exploring the temporal associations between air quality day types and pediatric asthma using self-organizing maps; 2) An evaluation of neighborhood-level socioeconomic influences on air pollution-asthma associations in Atlanta; and 3) Ambient air pollution and emergency department visits for asthma: a multi-city assessment of effect modification by age.  Additional planned manuscripts will focus on our multi-city assessment of air pollution and congestive heart failure ED visits, and an examination of retrospectively-predicted ROS on health.  We will also continue our work on other analyses, including assessment of air exchange rates as a modifier of ambient air pollution health effects.


Journal Articles on this Report : 25 Displayed | Download in RIS Format

Other subproject views: All 101 publications 43 publications in selected types All 42 journal articles
Other center views: All 334 publications 136 publications in selected types All 132 journal articles
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Journal Article Balachandran S, Pachon JE, Hu Y, Lee D, Mulholland JA, Russell AG. Ensemble-trained source apportionment of fine particulate matter and method uncertainty analysis. Atmospheric Environment 2012;61:387-394. R834799 (2012)
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  • Journal Article Baxter LK, Dionisio KL, Burke J, Sarnat SE, Sarnat JA, Hodas N, Rich DQ, Turpin BJ, Jones RR, Mannshardt E, Kumar N, Beevers SD, Ozkaynak H. Exposure prediction approaches used in air pollution epidemiology studies: key findings and future recommendations. Journal of Exposure Science & Environmental Epidemiology 2013;23(6):654-659. R834799 (2014)
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  • Journal Article Brown MS, Sarnat SE, DeMuth KA, Brown LAS, Whitlock DR, Brown SW, Tolbert PE, Fitzpatrick AM. Residential proximity to a major roadway is associated with features of asthma control in children. PLoS ONE 2012;7(5):e37044 ( pp.). R834799 (2012)
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  • Journal Article Chang HH, Hao H, Sarnat SE. A statistical modeling framework for projecting future ambient ozone and its health impact due to climate change. Atmospheric Environment 2014;89:290-297. R834799 (2014)
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  • Journal Article Darrow LA, Hess J, Rogers CA, Tolbert PE, Klein M, Sarnat SE. Ambient pollen concentrations and emergency department visits for asthma and wheeze. Journal of Allergy and Clinical Immunology 2012;130(3):630-638. R834799 (2012)
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  • Journal Article Dionisio KL, Isakov V, Baxter LK, Sarnat JA, Sarnat SE, Burke J, Rosenbaum A, Graham SE, Cook R, Mulholland J, Ozkaynak H. Development and evaluation of alternative approaches for exposure assessment of multiple air pollutants in Atlanta, Georgia. Journal of Exposure Science & Environmental Epidemiology 2013;23(6):581-592. R834799 (2014)
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  • Journal Article Dionisio KL, Baxter LK, Chang HH. An empirical assessment of exposure measurement error and effect attenuation in bipollutant epidemiologic models. Environmental Health Perspectives 2014;122(11):1216-1224. R834799 (2014)
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  • Journal Article Flanders WD, Klein M, Darrow LA, Strickland MJ, Sarnat SE, Sarnat JA, Waller LA, Winquist A, Tolbert PE. A method for detection of residual confounding in time-series and other observational studies. Epidemiology 2011;22(1):59-67. R834799 (2013)
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  • Journal Article Flanders WD, Klein M, Darrow LA, Strickland MJ, Sarnat SE, Sarnat JA, Waller LA, Winquist A, Tolbert PE. A method to detect residual confounding in spatial and other observational studies. Epidemiology 2011;22(6):823-826. R834799 (2012)
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  • Journal Article Gass K, Klein M, Chang HH, Flanders WD, Strickland MJ. Classification and regression trees for epidemiologic research: an air pollution example. Environmental Health 2014;13(1):17 (10 pp.). R834799 (2014)
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  • Journal Article Gass K, Klein M, Sarnat SE, Winquist A, Darrow LA, Flanders WD, Chang HH, Mulholland JA, Tolbert PE, Strickland MJ. Associations between ambient air pollutant mixtures and pediatric asthma emergency department visits in three cities: a classification and regression tree approach. Environmental Health 2015;14:58 (14 pp.). R834799 (2015)
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  • Journal Article Goldman GT, Mulholland JA, Russell AG, Strickland MJ, Klein M, Waller LA, Tolbert PE. Impact of exposure measurement error in air pollution epidemiology: effect of error type in time-series studies. Environmental Health 2011;10:61 (11 pp.). R834799 (2011)
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  • Journal Article Goldman GT, Mulholland JA, Russell AG, Gass K, Strickland MJ, Tolbert PE. Characterization of ambient air pollution measurement error in a time-series health study using a geostatistical simulation approach. Atmospheric Environment 2012;57:101-108. R834799 (2012)
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  • Journal Article Maier ML, Balachandran S, Sarnat SE, Turner JR, Mulholland JA, Russell AG. Application of an ensemble-trained source apportionment approach at a site impacted by multiple point sources. Environmental Science & Technology 2013;47(8):3743-3751. R834799 (2013)
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  • Journal Article Pachon JE, Balachandran S, Hu Y, Mulholland JA, Darrow LA, Sarnat JA, Tolbert PE, Russell AG. Development of outcome-based, multipollutant mobile source indicators. Journal of the Air & Waste Management Association 2012;62(4):431-442. R834799 (2012)
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  • Journal Article Pachon JE, Weber RJ, Zhang X, Mulholland JA, Russell AG. Revising the use of potassium (K) in the source apportionment of PM2.5. Atmospheric Pollution Research 2013;4(1):14-21. R834799 (2014)
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  • Journal Article Pearce JL, Waller LA, Chang HH, Klein M, Mulholland JA, Sarnat JA, Sarnat SE, Strickland MJ, Tolbert PE. Using self-organizing maps to develop ambient air quality classifications: a time series example. Environmental Health 2014;13:56. R834799 (2014)
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  • Journal Article Sarnat JA, Sarnat SE, Flanders WD, Chang HH, Mulholland J, Baxter L, Isakov V, Ozkaynak H. Spatiotemporally resolved air exchange rate as a modifier of acute air pollution-related morbidity in Atlanta. Journal of Exposure Science & Environmental Epidemiology 2013;23(6):606-615. R834799 (2013)
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  • Journal Article Sarnat SE, Sarnat JA, Mulholland J, Isakov V, Ozkaynak H, Chang HH, Klein M, Tolbert PE. Application of alternative spatiotemporal metrics of ambient air pollution exposure in a time-series epidemiological study in Atlanta. Journal of Exposure Science & Environmental Epidemiology 2013;23(6):593-605. R834799 (2014)
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  • Journal Article Sarnat SE, Winquist A, Schauer JJ, Turner JR, Sarnat JA. Fine particulate matter components and emergency department visits for cardiovascular and respiratory diseases in the St. Louis, Missouri-Illinois, metropolitan area. Environmental Health Perspectives 2015;123(5):437-444. R834799 (2015)
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  • Journal Article Strickland MJ, Darrow LA, Mulholland JA, Klein M, Flanders WD, Winquist A, Tolbert PE. Implications of different approaches for characterizing ambient air pollutant concentrations within the urban airshed for time-series studies and health benefits analyses. Environmental Health 2011;10:36 (9 pp.). R834799 (2011)
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  • Journal Article Winquist A, Klein M, Tolbert P, Sarnat SE. Power estimation using simulations for air pollution time-series studies. Environmental Health 2012;11:68 (12 pp.). R834799 (2012)
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  • Journal Article Winquist A, Klein M, Tolbert P, Flanders WD, Hess J, Sarnat SE. Comparison of emergency department and hospital admissions data for air pollution time-series studies. Environmental Health 2012;11:70 (14 pp.). R834799 (2012)
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  • Journal Article Winquist A, Kirrane E, Klein M, Strickland M, Darrow LA, Sarnat SE, Gass K, Mulholland J, Russell A, Tolbert P. Joint effects of ambient air pollutants on pediatric asthma emergency department visits in Atlanta, 1998-2004. Epidemiology 2014;25(5):666-673. R834799 (2014)
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  • Journal Article Winquist A, Schauer JJ, Turner JR, Klein M, Sarnat SE. Impact of ambient fine particulate matter carbon measurement methods on observed associations with acute cardiorespiratory morbidity. Journal of Exposure Science & Environmental Epidemiology 2015;25(2):215-221. R834799 (2014)
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  • Supplemental Keywords:

    ambient air, health effects, sensitive populations, dose-response, cumulative effects, epidemiology, exposure, air quality modeling, PM2.5, organics, elemental carbon, metals, oxidants, sulfates, source characterization, Health, Scientific Discipline, Health Risk Assessment, Risk Assessments, Biochemistry, Environmental Monitoring, particulate matter, children's health, morbidity, ambient air monitoring, climate change, air pollution, susceptibility, ambient particle health effects, airshed modeling, human health risk

    Relevant Websites:

    www.scape.gatech.edu Exit

    Progress and Final Reports:

    Original Abstract
  • 2011 Progress Report
  • 2012 Progress Report
  • 2013 Progress Report
  • 2015 Progress Report
  • Final Report

  • Main Center Abstract and Reports:

    R834799    The Southeastern Center for Air Pollution and Epidemiology: Multiscale Measurements and Modeling of Mixtures

    Subprojects under this Center: (EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).
    R834799C001 Development and Deployment of an Instrumentation Suite for Comprehensive Air Quality Characterization Including Aerosol ROS
    R834799C002 Examining In-Vehicle Pollution and Oxidative Stress in a Cohort of Daily Commuters
    R834799C003 Novel Estimates of Pollutant Mixtures and Pediatric Health in Two Birth Cohorts
    R834799C004 A Multi-City Time-Series Study of Pollutant Mixtures and Acute Morbidity