Jeremy A. Sarnat

Diabetes Enhances Vulnerability to Particulate Air Pollution–Associated Impairment in Vascular Reactivity and Endothelial Function

Background—Epidemiological studies suggest that people with diabetes are vulnerable to cardiovascular health effects associated with exposure to particle air pollution. Endothelial and vascular function is impaired in diabetes and may be related to increased cardiovascular risk. We examined whether endothelium-dependent and -independent vascular reactivity was associated with particle exposure in individuals with and without diabetes. Methods and Results—Study subjects were 270 greater-Boston residents. We measured 24-hour average ambient levels of air pollution (fine particles [PM2.5], particle number, black carbon, and sulfates [SO42−]) ≈500 m from the patient examination site. Pollutant concentrations were evaluated for associations with vascular reactivity. Linear regressions were fit to the percent change in brachial artery diameter (flow mediated and nitroglycerin mediated), with the particulate pollutant index, apparent temperature, season, age, race, sex, smoking history, and body mass index as predictors. Models were fit to all subjects and then stratified by diagnosed diabetes versus at risk for diabetes. Six-day moving averages of all 4 particle metrics were associated with decreased vascular reactivity among patients with diabetes but not those at risk. Interquartile range increases in SO42− were associated with decreased flow-mediated (−10.7%; 95% CI, −17.3 to −3.5) and nitroglycerin-mediated (−5.4%; 95% CI, −10.5 to −0.1) vascular reactivity among those with diabetes. Black carbon increases were associated with decreased flow-mediated vascular reactivity (−12.6%; 95% CI, −21.7 to −2.4), and PM2.5 was associated with nitroglycerin-mediated reactivity (−7.6%; 95% CI, −12.8 to −2.1). Effects were stronger in type II than type I diabetes. Conclusions—Diabetes confers vulnerability to particles associated with coal-burning power plants and traffic.

Ozone Exposure and Mortality: An Empiric Bayes Metaregression Analysis

Background: Results from time-series epidemiologic studies evaluating the relationship between ambient ozone concentrations and premature mortality vary in their conclusions about the magnitude of this relationship, if any, making it difficult to estimate public health benefits of air pollution control measures. We conducted an empiric Bayes metaregression to estimate the ozone effect on mortality, and to assess whether this effect varies as a function of hypothesized confounders or effect modifiers. Methods: We gathered 71 time-series studies relating ozone to all-cause mortality, and we selected 48 estimates from 28 studies for the metaregression. Metaregression covariates included the relationship between ozone concentrations and concentrations of other air pollutants, proxies for personal exposure–ambient concentration relationships, and the statistical methods used in the studies. For our metaregression, we applied a hierarchical linear model with known level-1 variances. Results: We estimated a grand mean of a 0.21% increase (95% confidence interval = 0.16–0.26%) in mortality per 10-μg/m3 increase of 1-hour maximum ozone (0.41% increase per 10 ppb) without controlling for other air pollutants. In the metaregression, air-conditioning prevalence and lag time were the strongest predictors of between-study variability. Air pollution covariates yielded inconsistent findings in regression models, although correlation analyses indicated a potential influence of summertime PM2.5. Conclusions: These findings, coupled with a greater relative risk of ozone in the summer versus the winter, demonstrate that geographic and seasonal heterogeneity in ozone relative risk should be anticipated, but that the observed relationship between ozone and mortality should be considered for future regulatory impact analyses.

Short-term associations between ambient air pollutants and pediatric asthma emergency department visits.

RATIONALE Certain outdoor air pollutants cause asthma exacerbations in children. To advance understanding of these relationships, further characterization of the dose-response and pollutant lag effects are needed, as are investigations of pollutant species beyond the commonly measured criteria pollutants. OBJECTIVES Investigate short-term associations between ambient air pollutant concentrations and emergency department visits for pediatric asthma. METHODS Daily counts of emergency department visits for asthma or wheeze among children aged 5 to 17 years were collected from 41 Metropolitan Atlanta hospitals during 1993-2004 (n = 91,386 visits). Ambient concentrations of gaseous pollutants and speciated particulate matter were available from stationary monitors during this time period. Rate ratios for the warm season (May to October) and cold season (November to April) were estimated using Poisson generalized linear models in the framework of a case-crossover analysis. MEASUREMENTS AND MAIN RESULTS Both ozone and primary pollutants from traffic sources were associated with emergency department visits for asthma or wheeze; evidence for independent effects of ozone and primary pollutants from traffic sources were observed in multipollutant models. These associations tended to be of the highest magnitude for concentrations on the day of the emergency department visit and were present at relatively low ambient concentrations. CONCLUSIONS Even at relatively low ambient concentrations, ozone and primary pollutants from traffic sources independently contributed to the burden of emergency department visits for pediatric asthma.

Ambient gas concentrations and personal particulate matter exposures: implications for studying the health effects of particles.

Background: Data from a previous study conducted in Baltimore, MD, showed that ambient fine particulate matter less than 2.5 &mgr;m in diameter (PM2.5) concentrations were strongly correlated with corresponding personal PM2.5 exposures, whereas ambient O3, NO2, and SO2 concentrations were weakly correlated with their personal exposures to these gases. In contrast, many of the ambient gas concentrations were reasonable surrogates of personal PM2.5 exposures. Methods: Personal multipollutant exposures and corresponding ambient air pollution concentrations were measured for 43 subjects living in Boston, MA. The cohort consisted of 20 healthy senior citizens and 23 schoolchildren. Simultaneous 24-hour integrated PM2.5, O3, NO2, and SO2 personal exposures and ambient concentrations were measured. All PM2.5 samples were also analyzed for SO42− (sulfate). We analyzed personal exposure and ambient concentration data using correlation and mixed model regression analyses to examine relationships among (1) ambient PM2.5 concentrations and corresponding ambient gas concentrations; (2) ambient PM2.5 and gas concentrations and their respective personal exposures; (3) ambient gas concentrations and corresponding personal PM2.5 exposures; and (4) personal PM2.5 exposures and corresponding personal gas exposures. Results: We found substantial correlations between ambient PM2.5 concentrations and corresponding personal exposures over the course of time. Additionally, our results support the earlier finding that summertime gaseous pollutant concentrations may be better surrogates of personal PM2.5 exposures (especially personal exposures to PM2.5 of ambient origin) than they are surrogates of personal exposures to the gases themselves. Conclusions: Particle health effects studies that include both ambient PM2.5 and gaseous concentrations as independent variables must be analyzed carefully and interpreted cautiously, since both parameters may be serving as surrogates for PM2.5 exposures.

Air pollution and inflammation in type 2 diabetes: A mechanism for susceptibility

Background: Particulate air pollution has been associated with several adverse cardiovascular health outcomes, and people with diabetes may be especially vulnerable. One potential pathway is inflammation and endothelial dysfunction—processes in which cell adhesion molecules and inflammatory markers play important roles. Aim: To examine whether plasma levels of soluble intercellular adhesion molecule 1 (ICAM-1), vascular cell adhesion molecule 1 (VCAM-1) and von Willebrand factor (vWF) were associated with particle exposure in 92 Boston area residents with type 2 diabetes. Methods: Daily average ambient levels of air pollution (fine particles (PM2.5), black carbon (BC) and sulphates) were measured approximately 500 m from the patient examination site and evaluated for associations with ICAM-1, VCAM-1 and vWF. Linear regressions were fit to plasma levels of ICAM-1, VCAM-1 and vWF, with the particulate pollutant index, apparent temperature, season, age, race, sex, glycosylated haemoglobin, cholesterol, smoking history and body mass index as predictors. Results: Air pollutant exposure measures showed consistently positive point estimates of association with the inflammatory markers. Among participants not taking statins and those with a history of smoking, associations between PM2.5, BC and VCAM-1 were particularly strong. Conclusions: These results corroborate evidence suggesting that inflammatory mechanisms may explain the increased risk of air pollution-associated cardiovascular events among those with diabetes.

Fine Particle Sources and Cardiorespiratory Morbidity: An Application of Chemical Mass Balance and Factor Analytical Source-Apportionment Methods

Background Interest in the health effects of particulate matter (PM) has focused on identifying sources of PM, including biomass burning, power plants, and gasoline and diesel emissions that may be associated with adverse health risks. Few epidemiologic studies, however, have included source-apportionment estimates in their examinations of PM health effects. We analyzed a time-series of chemically speciated PM measurements in Atlanta, Georgia, and conducted an epidemiologic analysis using data from three distinct source-apportionment methods. Objective The key objective of this analysis was to compare epidemiologic findings generated using both factor analysis and mass balance source-apportionment methods. Methods We analyzed data collected between November 1998 and December 2002 using positive-matrix factorization (PMF), modified chemical mass balance (CMB-LGO), and a tracer approach. Emergency department (ED) visits for a combined cardiovascular (CVD) and respiratory disease (RD) group were assessed as end points. We estimated the risk ratio (RR) associated with same day PM concentrations using Poisson generalized linear models. Results There were significant, positive associations between same-day PM2.5 (PM with aero-dynamic diameter ≤ 2.5 μm) concentrations attributed to mobile sources (RR range, 1.018–1.025) and biomass combustion, primarily prescribed forest burning and residential wood combustion, (RR range, 1.024–1.033) source categories and CVD-related ED visits. Associations between the source categories and RD visits were not significant for all models except sulfate-rich secondary PM2.5 (RR range, 1.012–1.020). Generally, the epidemiologic results were robust to the selection of source-apportionment method, with strong agreement between the RR estimates from the PMF and CMB-LGO models, as well as with results from models using single-species tracers as surrogates of the source-apportioned PM2.5 values. Conclusions Despite differences among the source-apportionment methods, these findings suggest that modeled source-apportioned data can produce robust estimates of acute health risk. In Atlanta, there were consistent associations across methods between PM2.5 from mobile sources and biomass burning with both cardiovascular and respiratory ED visits, and between sulfate-rich secondary PM2.5 with respiratory visits.

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

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=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, PM10, coarse PM, PM2.5, and the following components of PM2.5: 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, NO2, and PM2.5 elemental carbon and organic carbon. In multipollutant models, CO was the strongest predictor. For respiratory visits, associations were observed with ozone, PM10, CO, and NO2 in single-pollutant models. In multipollutant models, PM10 and ozone persisted as predictors, with ozone the stronger predictor. Caveats and considerations in interpreting the multipollutant model results are discussed.

An examination of exposure measurement error from air pollutant spatial variability in time-series studies.

Relatively few studies have evaluated the effects of heterogeneous spatiotemporal pollutant distributions on health risk estimates in time-series analyses that use data from a central monitor to assign exposures. We present a method for examining the effects of exposure measurement error relating to spatiotemporal variability in ambient air pollutant concentrations on air pollution health risk estimates in a daily time-series analysis of emergency department visits in Atlanta, Georgia. We used Poisson generalized linear models to estimate associations between current-day pollutant concentrations and circulatory emergency department visits for the 1998–2004 time period. Data from monitoring sites located in different geographical regions of the study area and at different distances from several urban geographical subpopulations served as alternative measures of exposure. We observed associations for spatially heterogeneous pollutants (CO and NO2) using data from several different urban monitoring sites. These associations were not observed when using data from the most rural site, located 38 miles from the city center. In contrast, associations for spatially homogeneous pollutants (O3 and PM2.5) were similar, regardless of the monitoring site location. We found that monitoring site location and the distance of a monitoring site to a population of interest did not meaningfully affect estimated associations for any pollutant when using data from urban sites located within 20 miles from the population center under study. However, for CO and NO2, these factors were important when using data from rural sites located ≥30 miles from the population center, most likely owing to exposure measurement error. Overall, our findings lend support to the use of pollutant data from urban central sites to assess population exposures within geographically dispersed study populations in Atlanta and similar cities.

Asthma and air quality.

Purpose of review There is evidence for an association between asthma and air pollutants, including ozone, NO2 and particulate matter. Since these pollutants are ubiquitous in the urban atmosphere and typically correlated with each other it has been difficult to ascertain the specific sources of air pollution responsible for the observed effects. Similarly, uncertainty in determining a causal agent, or multiple agents, has complicated efforts to identify the mechanisms involved in pollution-mediated asthma events and whether air pollution may cause asthma as well as exacerbate preexisting cases. Recent findings Numerous studies have examined specific sources of air pollution and their relationship to asthma. This review summarizes recent work conducted, specifically, on traffic pollution and presents results that elucidate several plausible biological mechanisms for the observed effects. Of note are studies linking susceptibility to several genetic polymorphisms. Together, these studies suggest that remaining uncertainties in the asthma–air pollution association may be addressed through enhanced assessment of both exposures and outcomes. Summary Air-pollution research is evolving rapidly; in the near future, clinicians and public health agencies may be able to use this new information to provide recommendations for asthmatics that go beyond only paying attention to the air-pollution forecast.

Factors influencing relationships between personal and ambient concentrations of gaseous and particulate pollutants

Previous exposure studies have shown considerable inter-subject variability in personal-ambient associations. This paper investigates exposure factors that may be responsible for inter-subject variability in these personal-ambient associations. The personal and ambient data used in this paper were collected as part of a personal exposure study conducted in Boston, MA, during 1999-2000. This study was one of a group of personal exposure panel studies funded by the U.S. Environmental Protection Agencys National Exposure Research Laboratory to address areas of exposure assessment warranting further study, particularly associations between personal exposures and ambient concentrations of particulate matter and gaseous co-pollutants. Twenty-four-hour integrated personal, home indoor, home outdoor and ambient sulfate, elemental carbon (EC), PM(2.5), ozone (O(3)), nitrogen dioxide (NO(2)) and sulfur dioxide were measured simultaneously each day. Fifteen homes in the Boston area were measured for 7 days during winter and summer. A previous paper explored the associations between personal-indoor, personal-outdoor, personal-ambient, indoor-outdoor, indoor-ambient and outdoor-ambient PM(2.5), sulfate and EC concentrations. For the current paper, factors that may affect personal exposures were investigated, while controlling for ambient concentrations. The data were analyzed using mixed effects regression models. Overall personal-ambient associations were strong for sulfate during winter (p<0.0001) and summer (p<0.0001) and PM(2.5) during summer (p<0.0001). The personal-ambient mixed model slope for PM(2.5) during winter but was not significant at p=0.10. Personal exposures to most pollutants, with the exception of NO(2), increased with ventilation and time spent outdoors. An opposite pattern was found for NO(2) likely due to gas stoves. Personal exposures to PM(2.5) and to traffic-related pollutants, EC and NO(2), were higher for those individuals living close to a major road. Both personal and indoor sulfate and PM(2.5) concentrations were higher for homes using humidifiers. The impact of outdoor sources on personal and indoor concentrations increased with ventilation, whereas an opposite effect was observed for the impact of indoor sources.