Faculty Bibliography

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.

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

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