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      Electrocardiographic ST-Segment Depression and Exposure to Traffic‐Related Aerosols in Elderly Subjects with Coronary Artery Disease

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          Abstract

          Background

          Air pollutants have not been associated with ambulatory electrocardiographic evidence of ST-segment depression ≥ 1 mm (probable cardiac ischemia). We previously found that markers of primary (combustion-related) organic aerosols and gases were positively associated with circulating biomarkers of inflammation and ambulatory blood pressure in the present cohort panel study of elderly subjects with coronary artery disease.

          Objectives

          We specifically aimed to evaluate whether exposure markers of primary organic aerosols and ultrafine particles were more strongly associated with ST-segment depression of ≥ 1 mm than were secondary organic aerosols or PM 2.5 (particulate matter with aerodynamic diameter ≤ 2.5 μm) mass.

          Methods

          We evaluated relations of air pollutants to ambulatory electrocardiographic evidence of cardiac ischemia over 10 days in 38 subjects without ST depression on baseline electrocardiographs. Exposures were measured outdoors in retirement communities in the Los Angeles basin, including daily size-fractionated particle mass and hourly markers of primary and secondary organic aerosols and gases. Generalized estimating equations were used to estimate odds of hourly ST-segment depression (≥ 1 mm) from hourly air pollution exposures and to estimate relative rates of daily counts of ST-segment depression from daily average exposures, controlling for potential confounders.

          Results

          We found significant positive associations of hourly ST-segment depression with markers of combustion-related aerosols and gases averaged 1-hr through 3–4 days, but not secondary (photochemically aged) organic aerosols or ozone. The odds ratio per interquartile increase in 2-day average primary organic carbon (5.2 μg/m 3) was 15.4 (95% confidence interval, 3.5–68.2). Daily counts of ST-segment depression were consistently associated with primary combustion markers and 2-day average quasi-ultrafine particles < 0.25 μm.

          Conclusions

          Results suggest that exposure to quasi-ultrafine particles and combustion-related pollutants (predominantly from traffic) increase the risk of myocardial ischemia, coherent with our previous findings for systemic inflammation and blood pressure.

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          Most cited references38

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          Longitudinal data analysis for discrete and continuous outcomes.

          Longitudinal data sets are comprised of repeated observations of an outcome and a set of covariates for each of many subjects. One objective of statistical analysis is to describe the marginal expectation of the outcome variable as a function of the covariates while accounting for the correlation among the repeated observations for a given subject. This paper proposes a unifying approach to such analysis for a variety of discrete and continuous outcomes. A class of generalized estimating equations (GEEs) for the regression parameters is proposed. The equations are extensions of those used in quasi-likelihood (Wedderburn, 1974, Biometrika 61, 439-447) methods. The GEEs have solutions which are consistent and asymptotically Gaussian even when the time dependence is misspecified as we often expect. A consistent variance estimate is presented. We illustrate the use of the GEE approach with longitudinal data from a study of the effect of mothers' stress on children's morbidity.
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            Akaike's information criterion in generalized estimating equations.

            W. Pan (2001)
            Correlated response data are common in biomedical studies. Regression analysis based on the generalized estimating equations (GEE) is an increasingly important method for such data. However, there seem to be few model-selection criteria available in GEE. The well-known Akaike Information Criterion (AIC) cannot be directly applied since AIC is based on maximum likelihood estimation while GEE is nonlikelihood based. We propose a modification to AIC, where the likelihood is replaced by the quasi-likelihood and a proper adjustment is made for the penalty term. Its performance is investigated through simulation studies. For illustration, the method is applied to a real data set.
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              Increased particulate air pollution and the triggering of myocardial infarction.

              Elevated concentrations of ambient particulate air pollution have been associated with increased hospital admissions for cardiovascular disease. Whether high concentrations of ambient particles can trigger the onset of acute myocardial infarction (MI), however, remains unknown. We interviewed 772 patients with MI in the greater Boston area between January 1995 and May 1996 as part of the Determinants of Myocardial Infarction Onset Study. Hourly concentrations of particle mass <2.5 microm (PM(2.5)), carbon black, and gaseous air pollutants were measured. A case-crossover approach was used to analyze the data for evidence of triggering. The risk of MI onset increased in association with elevated concentrations of fine particles in the previous 2-hour period. In addition, a delayed response associated with 24-hour average exposure 1 day before the onset of symptoms was observed. Multivariate analyses considering both time windows jointly revealed an estimated odds ratio of 1.48 associated with an increase of 25 microg/m(3) PM(2.5) during a 2-hour period before the onset and an odds ratio of 1.69 for an increase of 20 microg/m(3) PM(2.5) in the 24-hour period 1 day before the onset (95% CIs 1.09, 2.02 and 1.13, 2.34, respectively). The present study suggests that elevated concentrations of fine particles in the air may transiently elevate the risk of MIs within a few hours and 1 day after exposure. Further studies in other locations are needed to clarify the importance of this potentially preventable trigger of MI.
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                Author and article information

                Journal
                Environ Health Perspect
                Environmental Health Perspectives
                National Institute of Environmental Health Sciences
                0091-6765
                1552-9924
                February 2011
                21 October 2010
                : 119
                : 2
                : 196-202
                Affiliations
                [1 ] Department of Epidemiology, School of Medicine and
                [2 ] Department of Statistics, School of Information and Computer Sciences, University of California–Irvine, Irvine, California, USA
                [3 ] Department of Civil and Environmental Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, California, USA
                [4 ] Department of Civil Engineering, Sharif University of Technology, Tehran, Iran
                [5 ] Susan Samueli Center for Integrative Medicine, and Cardiology Division, Department of Medicine, School of Medicine, University of California–Irvine, Irvine, California, USA
                Author notes
                Address correspondence to R.J. Delfino, Department of Epidemiology, School of Medicine, University of California-Irvine, 100 Theory, Suite 100, Irvine, CA 92617-7555 USA. Telephone: (949) 824-1767. Fax: (949) 824-1343. E-mail: rdelfino@ 123456uci.edu

                C.S. receives royalties from SKC Inc. for the air sampling device (Sioutas Personal Cascade Impactor Sampler) used in this research. The remaining authors declare they have no actual or potential competing financial interests.

                Article
                ehp-119-196
                10.1289/ehp.1002372
                3040606
                20965803
                ba5f5af0-33fc-4604-a0a4-4925b50a000f
                This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose, provided this notice is preserved along with the article's original DOI.
                History
                : 30 April 2010
                : 21 October 2010
                Categories
                Research

                Public health
                epidemiology,aerosols,longitudinal data analysis,size distribution,outdoor air,air,myocardial ischemia,coronary artery disease

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