Faculty Bibliography

BACKGROUND: Although many studies have linked elevations in tropospheric ozone to adverse health outcomes, the effect of long-term exposure to ozone on air pollution-related mortality remains uncertain. We examined the potential contribution of exposure to ozone to the risk of death from cardiopulmonary causes and specifically to death from respiratory causes. METHODS: Data from the study cohort of the American Cancer Society Cancer Prevention Study II were correlated with air-pollution data from 96 metropolitan statistical areas in the United States. Data were analyzed from 448,850 subjects, with 118,777 deaths in an 18-year follow-up period. Data on daily maximum ozone concentrations were obtained from April 1 to September 30 for the years 1977 through 2000. Data on concentrations of fine particulate matter (particles that are < or = 2.5 microm in aerodynamic diameter [PM(2.5)]) were obtained for the years 1999 and 2000. Associations between ozone concentrations and the risk of death were evaluated with the use of standard and multilevel Cox regression models. RESULTS: In single-pollutant models, increased concentrations of either PM(2.5) or ozone were significantly associated with an increased risk of death from cardiopulmonary causes. In two-pollutant models, PM(2.5) was associated with the risk of death from cardiovascular causes, whereas ozone was associated with the risk of death from respiratory causes. The estimated relative risk of death from respiratory causes that was associated with an increment in ozone concentration of 10 ppb was 1.040 (95% confidence interval, 1.010 to 1.067). The association of ozone with the risk of death from respiratory causes was insensitive to adjustment for confounders and to the type of statistical model used. CONCLUSIONS: In this large study, we were not able to detect an effect of ozone on the risk of death from cardiovascular causes when the concentration of PM(2.5) was taken into account. We did, however, demonstrate a significant increase in the risk of death from respiratory causes in association with an increase in ozone concentration

Associations of particulate matter (PM) and ozone with morbidity and mortality have been reported in many recent observational epidemiology studies. These studies often considered other gaseous co-pollutants also as potential confounders, including nitrogen dioxide (NO2), sulfur dioxide (SO2), and carbon monoxide (CO). However, because each of these air pollutants can have different seasonal patterns and chemical interactions, the estimation and interpretation of each pollutant's individual risk estimates may not be straightforward. Multi-collinearity among the air pollution and weather variables also leaves the possibility of confounding and over- or under-fitting of meteorological variables, thereby potentially influencing the health effect estimates for the various pollutants in differing ways. To investigate these issues, we examined the temporal relationships among air pollution and weather variables in the context of air pollution health effects models. We compiled daily data for PM less than 2.5 mum (PM2.5), ozone, NO2, SO2, CO, temperature, dew point, relative humidity, wind speed, and barometric pressure for New York City for the years 1999-2002. We conducted several sets of analyses to characterize air pollution and weather data interactions, to assess different aspects of these data issues: (1) spatial/temporal variation of PM2.5 and gaseous pollutants measured at multiple monitors; (2) temporal relationships among air pollution and weather variables; and (3) extent and nature of multi-collinearity of air pollution and weather variables in the context of health effects models. The air pollution variables showed a varying extent of intercorrelations with each other and with weather variables, and these correlations also varied across seasons. For example, NO2 exhibited the strongest negative correlation with wind speed among the pollutants considered, while ozone's correlation with PM2.5 changed signs across the seasons (positive in summer and negative in winter). The extent of multi-collinearity problems also varied across pollutants and choice of health effects models commonly used in the literature. These results indicate that the health effects regression need to be run by season for some pollutants to provide the most meaningful results. We also find that model choice and interpretation needs to take into consideration the varying pollutant concurvities with the model co-variables in each pollutant's health effects model specification. Finally, we provide an example for analysis of associations between these air pollutants and asthma emergency department visits in New York City, which evaluate the relationship between the various pollutants' risk estimates and their respective concurvities, and discuss the limitations that these results imply about the interpretability of multi-pollutant health effects models

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