Ambient Air Pollution and Respiratory Emergency Department Visits

Peel, Jennifer L.; Tolbert, Paige E.; Klein, Mitchel; Metzger, Kristi; Flanders, W. Dana; Todd, Knox H.; Mulholland, James A.; Ryan, P. Barry; Frumkin, Howard

doi:10.1097/01.ede.0000152905.42113.db

Cited by 439 publications

(357 citation statements)

References 26 publications

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“…Generally, the extension of the time series for an additional 4 years led to more stable risk estimates, and the observed associations are consistent with those observed in the earlier analysis (Metzger et al, 2004;Peel et al, 2005). For the two case groups examined here, we found no additional pollutant associations compared to our previous analyses.…”

Section: Discussionsupporting

confidence: 90%

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Multipollutant modeling issues in a study of ambient air quality and emergency department visits in Atlanta

Tolbert

Klein

Peel

et al. 2007

J Expo Sci Environ Epidemiol

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136

102

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Multipollutant models are frequently used to differentiate roles of multiple pollutants in epidemiologic studies of ambient air pollution. In the presence of differing levels of measurement error across pollutants under consideration, however, they can be biased and as misleading as single-pollutant models. Their appropriate interpretation depends on the relationships among the pollutant measurements and the outcomes in question. In situations where two or more pollutant variables may be acting as surrogates for the etiologic agent(s), multipollutant models can help identify the best surrogate, but the risk estimates may be influenced by inclusion of a second variable that is not itself an independent risk factor for the outcome in question. In this paper, these issues will be illustrated in the context of an ongoing study of emergency visits in Atlanta. Emergency department visits from 41 of 42 hospitals serving the 20-county Atlanta metropolitan area for the period 1993-2004 (n ¼ 10,206,389 visits) were studied in relation to ambient pollutant levels, including speciated particle measurements from an intensive monitoring campaign at a downtown station starting in 1998. Relative to our earlier publications, reporting results through 2000, the period for which the speciated data are available is now tripled (6 years in length). Poisson generalized linear models were used to examine outcome counts in relation to 3-day moving average concentrations of pollutants of a priori interest (ozone, nitrogen dioxide, carbon monoxide, sulfur dioxide, oxygenated hydrocarbons, PM 10 , coarse PM, PM 2.5 , and the following components of PM 2.5 : elemental carbon, organic carbon, sulfate, and water-soluble transition metals). In the present analysis, we report results for two outcome groups: a respiratory outcomes group and a cardiovascular outcomes group. For cardiovascular visits, associations were observed with CO, NO 2 , and PM 2.5 elemental carbon and organic carbon. In multipollutant models, CO was the strongest predictor. For respiratory visits, associations were observed with ozone, PM 10 , CO, and NO 2 in single-pollutant models. In multipollutant models, PM 10 and ozone persisted as predictors, with ozone the stronger predictor. Caveats and considerations in interpreting the multipollutant model results are discussed.

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Section: Discussionsupporting

confidence: 90%

“…We previously published results for the time period 1993-2000, 2 years of which included speciated PM 2.5 data (Metzger et al, 2004;Peel et al, 2005). We now have data through 2004, tripling the period for which the speciated PM 2.5 data are available.…”

Section: Introductionmentioning

confidence: 99%

Multipollutant modeling issues in a study of ambient air quality and emergency department visits in Atlanta

Tolbert

Klein

Peel

et al. 2007

J Expo Sci Environ Epidemiol

Self Cite

136

102

View full text Add to dashboard Cite

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“…14 conditions. They have shown that the risk ratios for asthma visits were generally positive and strongest with a lag of 5 to 8 days (see Figure 1 in Peel et al 14 ).…”

Section: Discussionmentioning

confidence: 98%

Emergency department visits for asthma in relation to the Air Quality Health Index: A case-crossover study in Windsor, Canada

Szyszkowicz

Kousha

2014

Can J Public Health

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“…Consider CO, for example. Studies have shown CO to be associated with emergency department visits and hospital admissions for asthma (Peel et al, 2005). However, ambient levels of CO are not known to have any direct effects on lung tissue (US EPA, 2000).…”

Section: Surrogate Measures Of Pollutant Mixturesmentioning

confidence: 99%

“…The concern is that if this is true for asthma, could it not also be the case for heart disease, where an association is biologically plausible. The database used in Peel et al (2005) has since been extended and expanded, and Paige Tolbert of Emory University presented analyses of these data at the workshop. The investigators have been conducting an intensive spatiotemporal assessment of the roles of multiple pollutants in cardiorespiratory health outcomes, taking advantage of comprehensive air quality measurements and data on over 10 million emergency department visits for the time period 1993-2004 in Atlanta, GA.…”

Section: Surrogate Measures Of Pollutant Mixturesmentioning

confidence: 99%

Panel discussion review: session two — interpretation of observed associations between multiple ambient air pollutants and health effects in epidemiologic analyses

Kim

Burnett

Neas

et al. 2007

J Expo Sci Environ Epidemiol

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Air pollution epidemiologic research has often utilized ambient air concentrations measured from centrally located monitors as a surrogate measure of exposure to these pollutants. Associations between these ambient concentrations and health outcomes such as lung function, hospital admissions, and mortality have been examined in short-and long-term cohort studies as well as in time-series and case-crossover studies. The issues related to interpreting the observed associations of ambient air pollutants with health outcomes were discussed at the US EPA sponsored workshop on December 13 and 14, 2006 in Chapel Hill, North Carolina, USA. The second session of this workshop focused on the following topics: (1) statistical methodology and study designs that may improve understanding of multipollutant health effects; (2) ambient concentrations as surrogate measures of pollutant mixtures; and (3) source-focused epidemiologic research. New methodology and approaches to better distinguish the effects of individual pollutants include multicity hierarchical modeling and the use of case-crossover analysis to control for copollutants. An alternative approach is to examine the mixture as a whole using principal component analysis. Another important consideration is to what extent the observed health associations are attributable to individual pollutants, which are often from common sources and are correlated, versus the pollutant mixtures that the pollutants are representing. For example, several ambient air concentrations, such as particulate matter mass, nitrogen dioxide, and carbon monoxide, may be serving as surrogate measures of motor vehicle exhaust. Source apportionment analysis is one method that may allow further advancement in understanding the source components that contribute to multipollutant health effects.

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Ambient Air Pollution and Respiratory Emergency Department Visits

Abstract: The results of this study contribute to the evidence of an association of several correlated gaseous and particulate pollutants, including ozone, NO2, CO, PM, and organic carbon, with specific respiratory conditions.

Cited by 439 publications

References 26 publications

Multipollutant modeling issues in a study of ambient air quality and emergency department visits in Atlanta

Multipollutant modeling issues in a study of ambient air quality and emergency department visits in Atlanta

Emergency department visits for asthma in relation to the Air Quality Health Index: A case-crossover study in Windsor, Canada

Panel discussion review: session two — interpretation of observed associations between multiple ambient air pollutants and health effects in epidemiologic analyses

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