Final Report: Novel Estimates of Pollutant Mixtures and Pediatric Health in Two Birth Cohorts

EPA Grant Number: R834799C003
Subproject: this is subproject number 003 , 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: Novel Estimates of Pollutant Mixtures and Pediatric Health in Two Birth Cohorts
Investigators: Strickland, Matthew J , Chang, Howard , Darrow, Lyndsey , Guensler, Randy , Klein, Mitchel , Liu, Yang , Mulholland, James , Russell, Armistead G. , Waller, Lance
Institution: Emory University , Georgia Institute of Technology , University of Nevada - Reno
EPA Project Officer: Chung, Serena
Project Period: January 1, 2011 through December 31, 2016
RFA: Clean Air Research Centers (2009) RFA Text |  Recipients Lists
Research Category: Health Effects , Air

Objective:

In utero and early life experiences affect physiological development and can influence sensitivity to environmental factors throughout life. In this project, we explored the interplay between certain early life events, characterizations of air pollutant mixtures developed as part of the Center’s Mixtures Characterization Toolkit, and a range of pediatric health outcomes using two large, population-based birth cohorts. One cohort consisted of roughly 1.7 million Georgia birth records that had been geocoded to the Census block level and linked with pediatric emergency department visits by staff at the Georgia Department of Human Resources. Using this statewide birth cohort, we investigated acute effects of air pollution mixtures on respiratory health outcomes and ear infections in children, and we assessed whether children who were born premature or low birth weight were more sensitive to ambient air pollutant concentrations than their counterparts. Further, we used the statewide birth cohort to investigate whether ambient air pollutant mixtures during pregnancy were associated with the risk of preterm delivery or reduced birth weight. The second birth cohort was comprised of children who were members of the Kaiser Permanente Georgia Health Maintenance Organization in metropolitan Atlanta. In this birth cohort, where comprehensive medical and residential histories were available for each study subject, we examined whether air pollutant mixtures during the first year of life were associated with the incidence of childhood asthma. We used these two birth cohorts to address the Project 3 specific objectives:

Specific Objective 1. Characterize the multipollutant atmosphere using five complementary approaches from the Mixtures Characterization Toolkit:

  • Model 1 – Community Multiscale Air Quality (CMAQ)–receptor data assimilation model for spatial interpolation of ambient monitoring data
  • Model 2 – PM2.5 source apportionment that incorporates a chemical mass balance approach to provide refined source profiles and contributions
  • Model 3 – CMAQ-MOVES-RLINE (CALINE and MOBILE were proposed, but were updated in the project) grid integration for fine-scale modeling of near-roadway gradients
  • Model 4 – Satellite remote sensing data providing regional air quality information and more detailed characterization of biomass burn events
  • Model 5 – Measurements and modeling of Reactive Oxygen Species (Project 1)

Specific Objective 2. Use the statewide birth cohort to investigate short-term relationships between ambient air pollutant mixtures and pediatric emergency department visits for:

  • Bronchiolitis and wheeze in infants and toddlers
  • Otitis media (ear infections) in infants and toddlers
  • Asthma in children age 5 years and older and investigate whether these relationships are modified by gestational age or birth weight.

Specific Objective 3. Use the statewide birth cohort to investigate relationships between ambient air pollutant mixtures during pregnancy and risk of preterm delivery and reduced birth weight.

Specific Objective 4. Use the Kaiser Permanente birth cohort to investigate longer-term relationships between ambient air pollutant mixtures during pregnancy and the first year of life and incident asthma in childhood.

Specific Objective 5. Use the Kaiser Permanente birth cohort to describe residential mobility during pregnancy and implications for exposure estimation.

Summary/Accomplishments (Outputs/Outcomes):

In Project 3, we used a variety of complementary air quality characterizations and statistical approaches to estimate associations of ambient air pollutant mixtures on child health. Together, these findings highlight the important role of ambient air pollutants in the exacerbation of several common pediatric diseases. Most prominently, our epidemiologic analyses show associations for both ozone and PM2.5 on pediatric asthma exacerbations. These conclusions are strengthened by the consistency of findings across a variety of air quality models and statistical analyses. For example, we observed associations with ozone and PM2.5 in time series models using measured concentrations in Atlanta (Strickland et al., 2014; Darrow et al., 2014); similar findings were obtained when we used joint effects models (Winquist et al., 2014), classification and regression trees (Gass et al., 2014) and self-organizing maps (Pearce et al., 2015) to better characterize air quality mixtures. Through this work, we reported that associations between short-term changes in several pollutant concentrations (including both ozone and PM2.5) and pediatric asthma emergency visits tended to be of greater magnitude for children born premature and for children born to African American mothers (Strickland et al., 2014).

Expanding beyond Atlanta to the state of Georgia, we observed associations of pediatric asthma with short-term changes in both ozone and PM2.5 concentrations (Xiao et al., 2016) using observation-fused CMAQ models (Friberg et al., 2016), and we observed associations of pediatric asthma with PM2.5 concentration estimates obtained from a geographically weighted regression model that included satellite aerosol optical depth measurements (Hu et al., 2013; Chang et al., 2014; Strickland et al., 2016). Looking more closely at the PM2.5 associations, our epidemiologic analyses that utilized Bayesian ensemble source apportionment results (Balachandran et al., 2013) found positive associations of PM2.5 from biomass burning, diesel-fueled vehicles, and gasoline-fueled vehicles with pediatric asthma exacerbations (Gass et al., 2015). Through the Center’s work on measuring the oxidative potential of PM2.5 using the dithiothreitol (DTT) assay, we also found associations between all ages asthma emergency visits and the oxidative potential of PM2.5 (Bates et al., 2015; Fang et al., 2016; Abrams et al., submitted).

Pediatric outcomes other than asthma were also investigated. For example, in Xiao et al. (2016) bronchiolitis, pneumonia, bronchitis, otitis media, and upper respiratory infection were associated with short-term changes in several ambient air pollutant concentrations estimated using the observation-fused CMAQ models, including PM2.5 components such as elemental carbon and organic carbon. The satellite-based models of PM2.5, however, only showed associations for asthma and upper respiratory infection; the associations for the other outcome groups in this study were null (Strickland et al., 2016).

Statewide analyses of air pollution concentrations and pregnancy outcomes were investigated in Hao et al. (2016) and Keller et al. (2017). Hao et al. (2016) estimated associations of preterm birth with trimester-long and total pregnancy average concentrations of 11 pollutants estimated using the observation-fused CMAQ models. Associations were observed for several gaseous pollutants and for PM2.5, although the ozone associations were null. Stratification by potentially susceptible subgroups showed associations tended to be of stronger magnitude for births to African American mothers, mothers in large metropolitan counties, and mothers with less than high school education. In Keller et al. (2017), we observed associations between third-trimester PM2.5 concentrations and birth weight after performing measurement error correction for the spatial incompatibility between the locations of the air quality monitors and the birth locations. This project was part of a collaborative study between Emory University and University of Washington. As work in progress, we are finalizing a quantile regression analysis of the association between air pollutant concentrations and birth weight to investigate whether the magnitude of the association differs for various quantiles of the birth weight distribution.

Using Kaiser Permanente data, we investigated associations of early life exposure to PM2.5 from traffic and development of asthma. An RLINE dispersion model at 250 meter resolution (Zhai et al., 2016) and an RLine + CMAQ fusion model at 250 meter resolution (Bates et al., in progress) were created to estimate near-roadway pollutant impacts at fine spatial scale. Epidemiologic analysis using the RLine dispersion model showed increases in cumulative incidence of asthma among children over several age intervals (Pennington et al., work in progress). In this study, we also estimated the potential impact of exposure misclassification due to maternal mobility during pregnancy on association estimates and found biases of between -2% and -10% (Pennington et al., 2016a). We also examined the predictive ability of various early life definitions of asthma as markers of subsequent asthma (Pennington et al., 2016b).

Conclusions:

Our analyses of short-term changes in pollutant concentrations in relation to pediatric respiratory events support the conclusion that several different pollutants are associated with these diseases. Various approaches to characterize pollutant mixtures, including joint effects modeling, classification and regression trees, source apportionment, and self-organizing maps, were implemented to investigate the health effects of pollutant mixtures. Broadly, we did not observe consistent evidence for positive synergism among pollutants across our studies. More evidence was found to support effect modification of pollutant associations by susceptibility factors such as preterm birth, maternal race, and maternal education (Strickland et al., 2014; Hao et al., 2016). Future work will help to inform the validity of these potentially important susceptibility factors. Our analyses of early life traffic exposures and incident asthma in a racially diverse population provide evidence to further support previous literature on this association. Through this work, we have developed an innovative modeling approach to fuse chemical transport model results with dispersion model estimates to better estimate near-roadway impacts, and we found that exposure misclassification due to maternal mobility during pregnancy is not likely to cause a large bias in the effect estimates.


Journal Articles on this Report : 35 Displayed | Download in RIS Format

Other subproject views: All 91 publications 39 publications in selected types All 37 journal articles
Other center views: All 334 publications 136 publications in selected types All 132 journal articles
Type Citation Sub Project Document Sources
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 Bates JT, Weber RJ, Abrams J, Verma V, Fang T, Klein M, Strickland MJ, Sarnat SE, Chang HH, Mulholland JA, Tolbert PE, Russell AG. Reactive oxygen species generation linked to sources of atmospheric particulate matter and cardiorespiratory effects. Environmental Science & Technology 2015;49(22):13605-13612. R834799 (2015)
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  • Journal Article Chang HH, Hu X, Liu Y. Calibrating MODIS aerosol optical depth for predicting daily PM2.5 concentrations via statistical downscaling. Journal of Exposure Science & Environmental Epidemiology 2014;24(4):398-404. R834799 (2014)
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  • Journal Article Chang HH, Warren JL, Darrow LA, Reich BJ, Waller LA. Assessment of critical exposure and outcome windows in time-to-event analysis with application to air pollution and preterm birth study. Biostatistics 2015;16(3):509-521. R834799 (2015)
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  • Journal Article Darrow LA, Klein M, Flanders WD, Mulholland JA, Tolbert PE, Strickland MJ. Air pollution and acute respiratory infections among children 0-4 years: an 18-year time-series study. American Journal of Epidemiology 2014;180(10):968-977. R834799 (2015)
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  • Journal Article Fang T, Verma V, Bates JT, Abrams J, Klein M, Strickland MJ, Sarnat SE, Chang HH, Mulholland JA, Tolbert PE, Russell AG, Weber RJ. Oxidative potential of ambient water-soluble PM2.5 in the southeastern United States: contrasts in sources and health associations between ascorbic acid (AA) and dithiothreitol (DTT) assays. Atmospheric Chemistry and Physics 2016;16(6):3865-3879. R834799 (2015)
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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 Flanders WD, Strickland MJ, Klein M. A new method for partial correction of residual confounding in time-series and other observational studies. American Journal of Epidemiology 2017;185(10):941-949. R834799 (2016)
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  • Journal Article Friberg MD, Zhai X, Holmes HA, Chang HH, Strickland MJ, Sarnat SE, Tolbert PE, Russell AG, Mulholland JA. Method for fusing observational data and chemical transport model simulations to estimate spatiotemporally resolved ambient air pollution. Environmental Science & Technology 2016;50(7):3695-3705. R834799 (2016)
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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, Balachandran S, Chang HH, Russell AG, Strickland MJ. Ensemble-based source apportionment of fine particulate matter and emergency department visits for pediatric asthma. American Journal of Epidemiology 2015;181(7):504-512. R834799 (2015)
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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 Hao H, Chang HH, Holmes HA, Mulholland JA, Klein M, Darrow LA, Strickland MJ. Air pollution and preterm birth in the U.S. state of Georgia (2002-2006): associations with concentrations of 11 ambient air pollutants estimated by combining Community Multiscale Air Quality Model (CMAQ) simulations with stationary monitor measurements. Environmental Health Perspectives 2016;124(6):875-880. R834799 (2015)
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  • Journal Article Hu X, Waller LA, Al-Hamdan MZ, Crosson WL, Estes Jr. MG, Estes SM, Quattrochi DA, Sarnat JA, Liu Y. Estimating ground-level PM2.5 concentrations in the southeastern U.S. using geographically weighted regression. Environmental Research 2013;121:1-10. R834799 (2013)
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  • Journal Article Hu X, Waller LA, Lyapustin A, Wang Y, Al-Hamdan MZ, Crosson WL, Estes Jr. MG, Estes SM, Quattrochi DA, Puttaswamy SJ, Liu Y. Estimating ground-level PM2.5 concentrations in the Southeastern United States using MAIAC AOD retrievals and a two-stage model. Remote Sensing of Environment 2014;140:220-232. R834799 (2014)
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  • Journal Article Hu X, Waller LA, Lyapustin A, Wang Y, Liu Y. 10-year spatial and temporal trends of PM2.5 concentrations in the southeastern US estimated using high-resolution satellite data. Atmospheric Chemistry and Physics 2014;14(12):6301-6314. R834799 (2014)
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  • Journal Article Keller JP, Chang HH, Strickland MJ, Szpiro AA. Measurement error correction for predicted spatiotemporal air pollution exposures. Epidemiology 2017;28(3):338-345. R834799 (2016)
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  • Journal Article Ma Z, Hu X, Huang L, Bi J, Liu Y. Estimating ground-level PM2.5 in China using satellite remote sensing. Environmental Science & Technology 2014;48(13):7436-7444. R834799 (2014)
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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 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 Pearce JL, Waller LA, Mulholland JA, Sarnat SE, Strickland MJ, Chang HH, Tolbert PE. Exploring associations between multipollutant day types and asthma morbidity: epidemiologic applications of self-organizing map ambient air quality classifications. Environmental Health 2015;14:55 (12 pp.). R834799 (2015)
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  • Journal Article Pennington AF, Strickland MJ, Klein M, Zhai X, Russell AG, Hansen C, Darrow LA. Measurement error in mobile source air pollution exposure estimates due to residential mobility during pregnancy. Journal of Exposure Science and Environmental Epidemiology 2017;27(5):513-520. R834799 (2016)
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  • Journal Article Reich BJ, Chang HH, Strickland MJ. Spatial health effects analysis with uncertain residential locations. Statistical Methods in Medical Research 2014;23(2):156-168. R834799 (2012)
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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 Strickland MJ, Marsh CA, Darrow LA. Gestational age-specific associations between infantile acute bronchiolitis and asthma after age five. Pediatric and Perinatal Epidemiology 2014;28(6):521-526. R834799 (2015)
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  • Journal Article Strickland MJ, Klein M, Flanders WD, Chang HH, Mulholland JA, Tolbert PE, Darrow LA. Modification of the effect of ambient air pollution on pediatric asthma emergency visits: susceptible subpopulations. Epidemiology 2014;25(6):843-850. R834799 (2014)
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  • Journal Article Strickland MJ, Gass KM, Goldman GT, Mulholland JA. Effects of ambient air pollution measurement error on health effect estimates in time-series studies: a simulation-based analysis. Journal of Exposure Science & Environmental Epidemiology 2015;25(2):160-166. R834799 (2013)
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  • Journal Article Strickland MJ, Hao H, Hu X, Chang HH, Darrow LA, Liu Y. Pediatric emergency visits and short-term changes in PM2.5 concentrations in the U.S. state of Georgia. Environmental Health Perspectives 2016;124(5):690-696. R834799 (2015)
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  • Journal Article Waller LA. Commentary: regarding assessments of chance in investigations of ‘cluster series.’ International Journal of Epidemiology 2013;42(2):449-452. R834799 (2013)
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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 Xiao Q, Liu Y, Mulholland JA, Russell AG, Darrow LA, Tolbert PE, Strickland MJ. Pediatric emergency department visits and ambient air pollution in the U.S. state of Georgia: a case-crossover study. Environmental Health 2016;15(1):115. R834799 (2016)
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  • Journal Article Yu C, Di Girolamo L, Chen L, Zhang X, Liu Y. Statistical evaluation of the feasibility of satellite-retrieved cloud parameters as indicators of PM2.5 levels. Journal of Exposure Science & Environmental Epidemiology 2015;25(5):457-466. R834799 (2014)
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  • Supplemental Keywords:

    Ambient air, atmosphere, health effects, human health, susceptibility, vulnerability, sensitive populations, infants, children, risk, dose-response, cumulative effects, epidemiology, exposure, public policy, air quality modeling, monitoring, measurement methods, aerosol, particulates, PM2.5, organics, elemental carbon, metals, ozone, oxidants, PAH, sulfates, source characterization, mobile sources, Georgia, GA, Southeast, Health, Scientific Discipline, Health Risk Assessment, Risk Assessments, Biochemistry, Environmental Monitoring, Atmospheric Sciences, children's health, particulate matter, ambient air monitoring, climate change, air pollution, airshed modeling, ambient particle health effects, susceptibility, human health risk

    Relevant Websites:

    Southeastern Center for Air Pollution & Epidemiology (SCAPE) Exit

    Progress and Final Reports:

    Original Abstract
  • 2011 Progress Report
  • 2012 Progress Report
  • 2013 Progress Report
  • 2014 Progress Report
  • 2015 Progress 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