Faculty Bibliography

Numerous time series studies have reported associations between daily ambient concentrations of air pollution and morbidity or mortality. Recent personal exposure studies have also reported relatively high longitudinal correlation between personal exposures to particulate matter (PM) and home outdoor PM concentrations, lending support to the health effects reported in time series studies. However, the question remains as to how well the temporal fluctuations in the air pollution levels observed at an outdoor monitor represent the temporal fluctuations in the population exposures to pollution of outdoor origins in a city, and how such representativeness affects the size and significance of risk estimates. Also, such spatio-temporal correlations would vary from pollutant to pollutant, likely influencing their relative significance of statistical associations with health outcomes. In this study, we characterized the extent of monitor-to-monitor correlation over time among multiple monitoring sites for PM less than 10 microm (PM10), gaseous criteria pollutants, and several weather variables in seven central and eastern contiguous states (IL, IN, MI, OH, PA, WI, and WV) during the study period of 1988-1990. After removing seasonal trends, the monitor-to-monitor temporal correlation among the air pollution/weather variables within 100-mile separation distance in these areas could be generally ranked into three groups: (1 ) temperature, dew point, relative humidity (r>0.9); (2) O3, PM10, NO2 (r: 0.8-0.6); and (3) CO, SO2 (r<0.5). Using the subsets for separation distance less than 100 miles, regression analyses of these monitor-to-monitor correlation coefficients were also conducted with explanatory variables including separation distance, qualitative (land use, location setting, and monitoring objectives) and quantitative (large and small variance) site characteristics, and region indicators for Air Quality Control Region (AQCR). The separation distance was a significant predictor of monitorto-monitor correlation decline especially for PM10 and NO2 (approximately 0.2 drop over 30 miles). Site characteristic variables were, in some cases, significant predictors of monitor-to-monitor correlation, but the magnitude of their impacts was not substantial. Regional differences, as examined by AQCR, were in some cases (e.g., in Metropolitan Philadelphia) substantial. In these areas, the pollutants that had generally poor monitor-to-monitor correlation in the overall seven states data (i.e., for SO2 and CO) showed higher monitor-to-monitor correlations, comparable with PM10 and O3, within the AQCR. These results are useful in interpreting some of the past time series epidemiological results. The differences in monitor-to-monitor correlations found across pollutants in this work (i.e., r approximately 0.8 vs. r approximately 0.4) are sufficiently large that they could be a factor in the different pollutant significance levels reported in the epidemiologic literature. It is recommended that future epidemiological studies collect and incorporate information on spatial variability among air pollutants in the analysis and interpretation of their results

Inflammatory stimuli cause plasma leakage and leukocyte adhesion in venules but not in capillaries or arterioles. The specific response of venules is governed by phenotypic specialization of the venular endothelial cells. What regulates this specialized phenotype? Several recent developments have shed new light on this question and may challenge our thinking about regulation of the venular endothelial cell phenotype. In this review, we consider some of the molecular markers of venular endothelial cells, the hemodynamic and molecular factors that may regulate the phenotype of venular endothelial cells, and abnormalities in endothelial cell phenotype in disease-related angiogenesis and microvascular remodeling. The expanding list of molecular markers may help clarify the physiologic and molecular factors that regulate the phenotype of venular endothelial cells in normal development and disease

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency. The information contained in this record was developed via an EPA Grant or Fellowship.

The association between ambient ozone (O3) and hospital use for asthma in children and adults is well documented. The question remains of whether there are susceptible subpopulations of asthmatic individuals who are particularly vulnerable to high O3 levels. Because tobacco use was prevalent in our cohort of inner-city adult asthmatic individuals (n = 1,216) in New York City (NYC), we investigated whether cigarette smoking was an effect modifier for asthma morbidity. We examined the relationship between personal tobacco use and O3-associated emergency department (ED) use for asthma in public hospitals in NYC. Three subpopulations were defined: never smokers (0 pack-yr), heavy smokers (>/= 13 pack-yr) and light smokers (< 13 pack-yr). Time-series regression analysis of ED use for asthma and daily O3 levels was done while controlling for temperature, seasonal/long-term trends, and day-of-week effects. Heavy smokers displayed an increased relative risk (RR) of ED visits for asthma in response to increases in 2-d lagged O3 levels (RR per 50 ppb O3 = 1.72; 95% confidence interval: 1.13 to 2.62). Logistic regression analysis confirmed that heavy cigarette use was a predictor of ED use for asthma following days with high O3 levels. Although adverse health effects of ambient O3 have also been documented in asthma populations not using cigarettes (e.g., children), our results suggest that in adult asthmatic individuals, heavy personal tobacco use may be an effect modifier for O3-associated morbidity

1. This study sought to determine whether neurogenic inflammation occurs in the airways by examining the effects of capsaicin or substance P on microvascular plasma leakage in the trachea and lungs of male pathogen-free C57BL/6 mice. 2. Single bolus intravenous injections of capsaicin (0.5 and 1 micromol kg(-1), i.v.) or substance P (1, 10 and 37 nmol kg(-10, i.v.) failed to induce significant leakage in the trachea, assessed as extravasation of Evans blue dye, but did induce leakage in the urinary bladder and skin. 3. Pretreatment with captopril (2.5 mg kg(-1), i.v.), a selective inhibitor of angiotensin converting enzyme (ACE), either alone or in combination with phosphoramidon (2.5 mg kg(-1), i.v.), a selective inhibitor of neutral endopeptidase (NEP), increased baseline leakage of Evans blue in the absence of any exogenous inflammatory mediator. The increase was reversed by the bradykinin B2 receptor antagonist Hoe 140 (0.1 mg kg(-1), i.v.). 4. After pretreatment with phosphoramidon and captopril, capsaicin increased the Evans blue leakage above the baseline in the trachea, but not in the lung. This increase was reversed by the tachykinin (NK1) receptor antagonist SR 140333 (0.7 mg kg(-1), i.v.), but not by the NK2 receptor antagonist SR 48968 (1 mg kg(-1), i.v.). 5. Experiments using Monastral blue pigment as a tracer localized the leakage to postcapillary venules in the trachea and intrapulmonary bronchi, although the labelled vessels were less numerous in mice than in comparably treated rats. Blood vessels of the pulmonary circulation were not labelled. 6. We conclude that neurogenic inflammation can occur in airways of pathogen-free mice, but only after the inhibition of enzymes that normally degrade inflammatory peptides. Neurogenic inflammation does not involve the pulmonary microvasculature.

While the mortality effects of particulate matter (PM) have been obvious during extreme historical pollution episodes (e.g., the London Fog of 1952), evaluating effects at more routine pollution levels has required the use of complex statistical modeling approaches. This paper critically reviews available time-series studies on PM10 mortality to provide a common basis for an evaluation of the PM10-mortality association. These PM10 studies confirm that an acute pollution-mortality association can occur at routine ambient levels, and suggest that such effects extend below the present United States air quality standards, especially for susceptible subpopulations. Furthermore, these new PM10 studies are consistent with the hypothesis noted in past studies that PM is a causal agent in the mortality impacts of air pollution. The relative risks (RRs) for PM10 mortality, however, were found to vary across studies. Variation probably was caused by differences in PM10 composition and in the PM10 averaging period employed in the analysis, as well as differences in whether other pollutants were considered simultaneously in the mortality-PM10 model. Overall, the RR estimates derived from available PM10-total mortality studies suggest a 24-h average, 100 micrograms/m3 PM10 acute exposure effect on the order of RR approximately 1.05-1.10 in the general population. Higher PM10 RRs were indicated for the elderly and for those with preexisting respiratory conditions, both of which represent subpopulations who appear to be especially at risk for the mortality implications of acute exposures to air pollution. A key research question remaining involves a determination of the component or components of PM10 (e.g., fine particles, sulfates, acid aerosols, or ultrafine particles) that are most important to the noted acute PM-mortality associations

Recent epidemiological studies have indicated that ambient air pollution, including PM-10, is associated with excess mortality and morbidity. These studies have included both cross-sectional comparisons across communities and rime-series analyses over time in single communities. Time-series analysis offers certain advantages, primarily in that the study population is the same over time, so that it acts as its own ''control.'' However, modeling such data is complicated by the fact that other environmental factors and other causes of illness can confound the results unless they are adequately addressed. For example, wintertime influenza epidemics cause long-wave peaks in respiratory mortality, and variations in emissions, dispersion, and atmospheric chemistry can cause seasonal cycles in pollution. Such superimposed long-wave variations in both health outcomes and pollutant concentrations can undermine the statistical validity of time-series models by inducing autocorrelation, and can create long-wave ''noise'' signals that can overwhelm a short-term ''signal'' of interest. Also, model specification can strongly affect the results of a time-series model. For example, analyses focusing on only one routinely collected pollution metric, to the exclusion of other possibly more influential pollution components, can cause the effects of the overlooked pollutants to be ascribed to the studied pollutant. In addition, the potential effects of nonnormal (e.g., Poisson) data distributions on time-series results need to be considered. It is concluded that how these various time-series modeling factors are, or are not, addressed can have a large influence on the study conclusions, or the ''message'' resulting from such analyses. Sensitivity analyses incorporating multiple modeling methods and model specifications are therefore recommended as part of such an analysis. Moreover, in this article exploratory and diagnostic procedures are recommended that may aid the modeler in assessing and avoiding the noted problems and that will allow the validity of such studies to be more easily documented and intercompared