Air conditioning and source-specific particles as modifiers of the effect of PM(10) on hospital admissions for heart and lung disease

Ischaemic heart disease mortality and years of work in trucking industry workers

OBJECTIVES

Evidence from general population-based studies and occupational cohorts has identified air pollution from mobile sources as a risk factor for cardiovascular disease. In a cohort of US trucking industry workers, with regular exposure to vehicle exhaust, the authors previously observed elevated standardised mortality ratios for ischaemic heart disease (IHD) compared with members of the general US population. Therefore, the authors examined the association of increasing years of work in jobs with vehicle exhaust exposure and IHD mortality within the cohort.

METHODS

The authors calculated years of work in eight job groups for 30,758 workers using work records from four nationwide companies. Proportional hazard regression was used to examine relationships between IHD mortality, 1985-2000, and employment duration in each job group.

RESULTS

HRs for at least 1 year of work in each job were elevated for dockworkers, long haul drivers, pick-up and delivery drivers, combination workers, hostlers, and shop workers. There was a suggestion of an increased risk of IHD mortality with increasing years of work as a long haul driver, pick-up and delivery driver, combination worker, and dockworker.

CONCLUSION

These results suggest an elevated risk of IHD mortality in workers with a previous history of regular exposure to vehicle exhaust.

A framework for identifying distinct multipollutant profiles in air pollution data

BACKGROUND

The importance of describing, understanding and regulating multi-pollutant mixtures has been highlighted by the US National Academy of Science and the Environmental Protection Agency. Furthering our understanding of the health effects associated with exposure to mixtures of pollutants will lead to the development of new multi-pollutant National Air Quality Standards.

OBJECTIVES

Introduce a framework within which diagnostic methods that are based on our understanding of air pollution mixtures are used to validate the distinct air pollutant mixtures identified using cluster analysis.

METHODS

Six years of daily gaseous and particulate air pollution data collected in Boston, MA were classified solely on their concentration profiles. Classification was performed using k-means partitioning and hierarchical clustering. Diagnostic strategies were developed to identify the most optimal clustering.

RESULTS

The optimal solution used k-means analysis and contained five distinct groups of days. Pollutant concentrations and elemental ratios were computed in order to characterize the differences between clusters. Time-series regression confirmed that the groups differed in their chemical compositions. The mean values of meteorological parameters were estimated for each group and air mass origin between clusters was examined using back-trajectory analysis. This allowed us to link the distinct physico-chemical characteristics of each cluster to characteristic weather patterns and show that different clusters were associated with distinct air mass origins.

CONCLUSIONS

This analysis yielded a solution that was robust to outlier points and interpretable based on chemical, physical and meteorological characteristics. This novel method provides an exciting tool with which to identify and further investigate multi-pollutant mixtures and link them directly to health effects studies.

Time series analysis of personal exposure to ambient air pollution and mortality using an exposure simulator

This paper describes a modeling framework for estimating the acute effects of personal exposure to ambient air pollution in a time series design. First, a spatial hierarchical model is used to relate Census tract-level daily ambient concentrations and simulated exposures for a subset of the study period. The complete exposure time series is then imputed for risk estimation. Modeling exposure via a statistical model reduces the computational burden associated with simulating personal exposures considerably. This allows us to consider personal exposures at a finer spatial resolution to improve exposure assessment and for a longer study period. The proposed approach is applied to an analysis of fine particulate matter of <2.5 μm in aerodynamic diameter (PM(2.5)) and daily mortality in the New York City metropolitan area during the period 2001-2005. Personal PM(2.5) exposures were simulated from the Stochastic Human Exposure and Dose Simulation. Accounting for exposure uncertainty, the authors estimated a 2.32% (95% posterior interval: 0.68, 3.94) increase in mortality per a 10 μg/m(3) increase in personal exposure to PM(2.5) from outdoor sources on the previous day. The corresponding estimates per a 10 μg/m(3) increase in PM(2.5) ambient concentration was 1.13% (95% confidence interval: 0.27, 2.00). The risks of mortality associated with PM(2.5) were also higher during the summer months.

Variability in the fraction of ambient fine particulate matter found indoors and observed heterogeneity in health effect estimates

Exposure to ambient (outdoor-generated) fine particulate matter (PM(2.5)) occurs predominantly indoors. The variable efficiency with which ambient PM(2.5) penetrates and persists indoors is a source of exposure error in air pollution epidemiology and could contribute to observed temporal and spatial heterogeneity in health effect estimates. We used a mass balance approach to model F for several scenarios across which heterogeneity in effect estimates has been observed: with geographic location of residence, residential roadway proximity, socioeconomic status, and central air-conditioning use. We found F is higher in close proximity to primary combustion sources (e.g. proximity to traffic) and for lower income homes. F is lower when PM(2.5) is enriched in nitrate and with central air-conditioning use. As a result, exposure error resulting from variability in F will be greatest when these factors have high temporal and/or spatial variability. The circumstances for which F is lower in our calculations correspond to circumstances for which lower effect estimates have been observed in epidemiological studies and higher F values correspond to higher effect estimates. Our results suggest that variability in exposure misclassification resulting from variability in F is a possible contributor to heterogeneity in PM-mediated health effect estimates.

Air pollution and DNA methylation: interaction by psychological factors in the VA Normative Aging Study

DNA methylation is a potential pathway linking air pollution to disease. Studies indicate that psychological functioning modifies the association between pollution and morbidity. The authors estimated the association of DNA methylation with ambient particulate matter less than 2.5 µm in diameter (PM(2.5)) and black carbon, using mixed models. DNA methylation of the inducible nitric oxide synthase gene, iNOS, and the glucocorticoid receptor gene, GCR, was measured by quantitative polymerase chain reaction pyrosequencing of 1,377 blood samples from 699 elderly male participants in the VA Normative Aging Study (1999-2009). The authors also investigated whether this association was modified by psychological factors including optimism or pessimism, anxiety, and depression. iNOS methylation was decreased after acute exposure to both black carbon and PM(2.5). A 1-μg/m(3) increase in exposure to black carbon in the 4 hours preceding the clinical examination was associated with a 0.9% decrease in 5-methylcytosine (95% CI: 0.4, 1.4) in iNOS, and a 10-μg/m(3) increase in exposure to PM(2.5) was associated with a 0.6% decrease in 5-methylcytosine (95% CI: 0.03, 1.1) in iNOS. Participants with low optimism and high anxiety had associations that were 3-4 times larger than those with high optimism or low anxiety. GCR methylation was not associated with particulate air pollution exposure.

Association of particulate air pollution with daily mortality: the China Air Pollution and Health Effects Study

China is one of the few countries with some of the highest particulate matter levels in the world. However, only a small number of particulate matter health studies have been conducted in China. The study objective was to examine the association of particulate matter with an aerodynamic diameter of less than 10 μm (PM(10)) with daily mortality in 16 Chinese cities between 1996 and 2008. Two-stage Bayesian hierarchical models were applied to obtain city-specific and national average estimates. Poisson regression models incorporating natural spline smoothing functions were used to adjust for long-term and seasonal trends of mortality, as well as other time-varying covariates. The averaged daily concentrations of PM(10) in the 16 Chinese cities ranged from 52 μg/m(3) to 156 μg/m(3). The 16-city combined analysis showed significant associations of PM(10) with mortality: A 10-μg/m(3) increase in 2-day moving-average PM(10) was associated with a 0.35% (95% posterior interval (PI): 0.18, 0.52) increase of total mortality, 0.44% (95% PI: 0.23, 0.64) increase of cardiovascular mortality, and 0.56% (95% PI: 0.31, 0.81) increase of respiratory mortality. Females, older people, and residents with low educational attainment appeared to be more vulnerable to PM(10) exposure. Conclusively, this largest epidemiologic study of particulate air pollution in China suggests that short-term exposure to PM(10) is associated with increased mortality risk.

Confounding and exposure measurement error in air pollution epidemiology

Studies in air pollution epidemiology may suffer from some specific forms of confounding and exposure measurement error. This contribution discusses these, mostly in the framework of cohort studies. Evaluation of potential confounding is critical in studies of the health effects of air pollution. The association between long-term exposure to ambient air pollution and mortality has been investigated using cohort studies in which subjects are followed over time with respect to their vital status. In such studies, control for individual-level confounders such as smoking is important, as is control for area-level confounders such as neighborhood socio-economic status. In addition, there may be spatial dependencies in the survival data that need to be addressed. These issues are illustrated using the American Cancer Society Cancer Prevention II cohort. Exposure measurement error is a challenge in epidemiology because inference about health effects can be incorrect when the measured or predicted exposure used in the analysis is different from the underlying true exposure. Air pollution epidemiology rarely if ever uses personal measurements of exposure for reasons of cost and feasibility. Exposure measurement error in air pollution epidemiology comes in various dominant forms, which are different for time-series and cohort studies. The challenges are reviewed and a number of suggested solutions are discussed for both study domains.

Emergency visits and hospital admissions in aged people living close to a gas-fired power plant

BACKGROUND

Combustion of natural gas for energy generation produces less pollutants than coke/oil. However, little is known about the short-term effect of pollution generated by gas-fired power plants on the health of elderly people.

METHODS

During three months, daily emergency visits/hospital admissions of subjects living within 3 km from a gas-fueled power plant were counted and related to ambient concentrations of nitrogen dioxide (NO(2)) and particulate matter of median aerometric diameter <10 μm (PM10). A generalized additive model served to correlate visits/hospital admissions to pollutants, controlling for meteorological confounders.

RESULTS

Mean air concentrations of PM10 and NO(2) were higher after-than before the start of operation of the plant, with the highest concentrations recorded within 1 km. Although pollutants were below the limits set by the European legislation, in elderly people there was a positive correlation between the number of emergency visits and daily air concentrations of PM10 and NO(2), as measured at 1 and 3 km from the plant. In subjects aged 70 years or more, the number of hospital admissions was positively correlated with PM10 levels measured within 3 km from the power plant, whereas in older subjects (≥80 year) it was also significantly linked with the lowest air concentration of PM10 (measured at 6 km from the plant).

DISCUSSION

Combustion of natural gas for energy generation produces a rise in air concentration of PM10 and NO(2) close to the plant, with a concentration-dependent increment of daily emergency visits and hospital admissions in elderly people, and with an age-dependent susceptibility.

Measurement error in environmental epidemiology and the shape of exposure-response curves

Both classical and Berkson exposure measurement errors as encountered in environmental epidemiology data can result in biases in fitted exposure-response relationships that are large enough to affect the interpretation and use of the apparent exposure-response shapes in risk assessment applications. A variety of sources of potential measurement error exist in the process of estimating individual exposures to environmental contaminants, and the authors review the evaluation in the literature of the magnitudes and patterns of exposure measurement errors that prevail in actual practice. It is well known among statisticians that random errors in the values of independent variables (such as exposure in exposure-response curves) may tend to bias regression results. For increasing curves, this effect tends to flatten and apparently linearize what is in truth a steeper and perhaps more curvilinear or even threshold-bearing relationship. The degree of bias is tied to the magnitude of the measurement error in the independent variables. It has been shown that the degree of bias known to apply to actual studies is sufficient to produce a false linear result, and that although nonparametric smoothing and other error-mitigating techniques may assist in identifying a threshold, they do not guarantee detection of a threshold. The consequences of this could be great, as it could lead to a misallocation of resources towards regulations that do not offer any benefit to public health.

Ambient carbon monoxide and daily mortality in three Chinese cities: the China Air Pollution and Health Effects Study (CAPES)

Ambient carbon monoxide (CO) is an air pollutant primarily generated by traffic. CO has been associated with increased mortality and morbidity in developed countries, but few studies have been conducted in Asian developing countries. In the China Air Pollution and Health Effects Study (CAPES), the short-term associations between ambient CO and daily mortality were examined in three Chinese cities: Shanghai, Anshan and Taiyuan. Poisson regression models incorporating natural spline smoothing functions were used to adjust for long-term and seasonal trend of mortality, as well as other time-varying covariates. Effect estimates were obtained for each city and then for the cities combined. In both individual-city and combined analysis, significant associations of CO with both total non-accidental and cardiovascular mortality were observed. In the combined analysis, a 1 mg/m(3) increase of 2-day moving average concentrations of CO corresponded to 2.89% (95%CI: 1.68, 4.11) and 4.17% (95%CI: 2.66, 5.68) increase of total and cardiovascular mortality, respectively. CO was not significantly associated with respiratory mortality. Sensitivity analyses showed that our findings were generally insensitive to alternative model specifications. In conclusion, ambient CO was associated with increased risk of daily mortality in these three cities. Our findings suggest that the role of exposure to CO and other traffic-related air pollutants should be further investigated in China.

Chemical properties of air pollutants and cause-specific hospital admissions among the elderly in Atlanta, Georgia

BACKGROUND

Health risks differ by fine particle (aerodynamic diameter ≤ 2.5 μm) component, although with substantial variability. Traditional methods to assess component-specific risks are limited, suggesting the need for alternative methods.

OBJECTIVES

We examined whether the odds of daily hospital admissions differ by pollutant chemical properties.

METHODS

We categorized pollutants by chemical properties and examined their impacts on the odds of daily hospital admissions among Medicare recipients > 64 years of age in counties in Atlanta, Georgia, for 1998-2006. We analyzed data in two stages. In the first stage we applied a case-crossover analysis to simultaneously estimate effects of 65 pollutants measured in the Aerosol Research and Inhalation Epidemiology Study on cause-specific hospital admissions, controlling for temperature and ozone. In the second stage, we regressed pollutant-specific slopes from the first stage on pollutant properties. We calculated uncertainty estimates using a bootstrap procedure. We repeated the two-stage analyses using coefficients from first-stage models that included single pollutants plus ozone and meteorological variables only. We based our primary analyses on exposures on day of admission.

RESULTS

We found that 24-hr transition metals and alkanes were associated with increased odds [0.26%; 95% confidence interval (CI), 0.02-0.48; and 0.37%; 95% CI, 0.04-0.72, respectively] of hospital admissions for cardiovascular disease (CVD). Transition metals were significantly associated with increased hospital admissions for ischemic heart disease, congestive heart failure, and atrial fibrillation. Increased respiratory-related hospital admissions were significantly associated with alkanes. Aromatics and microcrystalline oxides were significantly associated with decreased CVD- and respiratory-related hospital admissions.

CONCLUSIONS

The two-stage approach showed transition metals to be consistently associated with increased odds of CVD-related hospital admissions.

Prolonged exposure to particulate pollution, genes associated with glutathione pathways, and DNA methylation in a cohort of older men

BACKGROUND

DNA methylation is a potential pathway linking environmental exposures to disease. Exposure to particulate air pollution has been associated with increased cardiovascular morbidity and mortality, and lower blood DNA methylation has been found in processes related to cardiovascular morbidity.

OBJECTIVE

We hypothesized that prolonged exposure to particulate pollution would be associated with hypomethylation of repetitive DNA elements and that this association would be modified by genes involved in glutathione metabolism and other host characteristics.

METHODS

DNA methylation of the long interspersed nucleotide element-1 (LINE-1) and the short interspersed nucleotide element Alu were measured by quantitative polymerase chain reaction pyrosequencing in 1,406 blood samples from 706 elderly participants in the Normative Aging Study. We estimated changes in repetitive element DNA methylation associated with ambient particles (particulate matter ≤ 2.5 µm in aerodynamic diameter), black carbon (BC), and sulfates (SO₄), with mixed models. We examined multiple exposure windows (1-6 months) before DNA methylation measurement. We investigated whether this association was modified by genotype and phenotype.

RESULTS

An interquartile range (IQR) increase in BC over a 90-day period was associated with a decrease of 0.31% 5-methylcytosine (5mC) (95% confidence interval, 0.12-0.50%) in Alu. An IQR increase in SO₄ over a 90-day period was associated with a decrease of 0.27% 5mC (0.02-0.52%) in LINE-1. The glutathione S-transferase mu-1-null genotype strengthened the association between BC and Alu hypomethylation.

CONCLUSION

Prolonged exposure to BC and SO₄ particles was associated with hypomethylation of two types of repetitive elements.

Home air-conditioning, traffic exposure, and asthma and allergic symptoms among preschool children

Epidemiological data suggest that traffic exposures can influence asthma and allergic symptoms among preschool children; however, there is no information on risk reduction via home air-conditioning (AC). The aim of this study is to evaluate the associations of self-reported traffic densities with asthma and allergic symptoms among preschool children and determine whether AC is an effect modifier. A cross-sectional study adopting an expanded and modified ISAAC--International Study of Asthma and Allergies in Childhood conducted on randomly selected 2994 children living in homes without any indoor risk factors. Specific information on demographics, indoor home risk factors, and traffic variables were obtained. Adjusted prevalence ratios (PR) and 95% confidence interval (CI) were determined by Cox proportional hazard regression model with assumption of a constant risk period controlled for covariates. We found dose-response significant relationships between validated self-reported traffic densities and asthma and rhinitis symptoms. Among children sleeping in non-air-conditioned homes, there were stronger associations between asthma and rhinitis symptoms studied. PRs for heavy traffic density were 2.06 for wheeze (95% CI 0.97-4.38), 2.89 for asthma (1.14-7.32), 1.73 for rhinitis (1.00-2.99), and 3.39 for rhinoconjunctivitis (1.24-9.27). There were no associations found for children sleeping in air-conditioned homes. Our results suggest that AC in the bedroom modifies the health effects of traffic among preschool children. This finding suggests that attention should also be paid to ventilation characteristics of the homes to remediate health-related traffic pollution problems.

Factors affecting exhaled carbon monoxide levels in coffeehouses in the Western Black Sea region of Turkey

The aim of this study was to evaluate indoor air quality and factors affecting expired carbon monoxide (CO) levels in a coffeehouse environment. This cross-sectional study was conducted at 16 randomly selected coffeehouses in Duzce, Turkey, during November 2007 to March 2008. A total of 547 people, average age 46.72 ± 17.03 (19—82) years, participated. The selected coffeehouses were divided into four groups: (1) smoking, (2) nonsmoking, (3) old-style and (iv) new-style coffeehouses. Prior to entering the coffeehouse, exhaled CO levels in smokers (mean 21.17 ± 6.73 parts per million [ppm]) were significantly higher than those for nonsmokers (6.51 ± 4.56 ppm; p < 0.001). Measurements taken after 2 hours in the coffeehouse also showed significantly higher CO concentrations for smokers (22.72 ± 5.31 ppm), compared to nonsmokers (6.51 ± 4.56 ppm; p < 0.001). It was determined that CO levels inside coffee shops were above the WHO guidelines. Exhaled CO levels in nonsmokers are influenced by the ambient CO levels as a result of the use of cigarettes in coffeehouses in addition to the structure of coffeehouses.

Ambient air pollution and hospital admission in Shanghai, China

No prior studies exist in Mainland China examining the association of outdoor air pollution with hospital admissions. In this study, we conducted a time-series analysis to examine the association of outdoor air pollutants (PM(10), SO(2), and NO(2)) with both total and cause-specific hospital admission in Shanghai, using three years of daily data (2005-2007). Hospital admission and air pollution data were collected from the Shanghai Health Insurance Bureau and Shanghai Environmental Monitoring Center. Natural spline model was used to analyze the data. We found outdoor air pollution was associated with increased risk of total and cardiovascular hospital admission in Shanghai. The effect estimates of air pollutants varied by lag (L) structures of pollutants' concentrations. For lag 5, a 10 microg/m(3) increase in concentration of PM(10), SO(2) and NO(2) corresponded to 0.18% (95% CI: -0.15%, 0.52%), 0.63% (95% CI: 0.03%, 1.23%), and 0.99% (95% CI: 0.10%, 1.88%) increase of total hospital admission; and 0.23% (95% CI: -0.03%, 0.48%), 0.65% (95% CI: 0.19%, 1.12%), and 0.80% (95% CI: 0.10%, 1.49%) increase of cardiovascular hospital admission. The associations appeared to be more evident in the cool season (from November to April) than in the warm season (from May to October). We found significant effects of gaseous pollutants (SO(2) and NO(2)) after adjustment for PM(10). Our analyses provide the first evidence in China that the current air pollution level has an effect on hospital admission and strengthen the rationale for further limiting air pollution levels in Shanghai.

Exploring variation and predictors of residential fine particulate matter infiltration

Although individuals spend the majority of their time indoors, most epidemiological studies estimate personal air pollution exposures based on outdoor levels. This almost certainly results in exposure misclassification as pollutant infiltration varies between homes. However, it is often not possible to collect detailed measures of infiltration for individual homes in large-scale epidemiological studies and thus there is currently a need to develop models that can be used to predict these values. To address this need, we examined infiltration of fine particulate matter (PM(2.5)) and identified determinants of infiltration for 46 residential homes in Toronto, Canada. Infiltration was estimated using the indoor/outdoor sulphur ratio and information on hypothesized predictors of infiltration were collected using questionnaires and publicly available databases. Multiple linear regression was used to develop the models. Mean infiltration was 0.52 ± 0.21 with no significant difference across heating and non-heating seasons. Predictors of infiltration were air exchange, presence of central air conditioning, and forced air heating. These variables accounted for 38% of the variability in infiltration. Without air exchange, the model accounted for 26% of the variability. Effective modelling of infiltration in individual homes remains difficult, although key variables such as use of central air conditioning show potential as an easily attainable indicator of infiltration.

Short-term association between sulfur dioxide and daily mortality: the Public Health and Air Pollution in Asia (PAPA) study

Sulfur dioxide (SO(2)) has been associated with increased mortality and morbidity, but only few studies were conducted in Asian countries. Previous studies suggest that SO(2) may have adverse health effects independent of other pollutants. In the Public Health and Air Pollution in Asia (PAPA) project, the short-term associations between ambient sulfur dioxide (SO(2)) and daily mortality were examined in Bangkok, Thailand, and three Chinese cities: Hong Kong, Shanghai, and Wuhan. Poisson regression models incorporating natural spline smoothing functions were used to adjust for seasonality and other time-varying covariates. Effect estimates were obtained for each city and then for the cities combined. The impact of alternative model specifications, such as lag structure of pollutants and degree of freedom (df) for time trend, on the estimated effects of SO(2) were also examined. In both individual-city and combined analysis, significant effects of SO(2) on total non-accidental and cardiopulmonary mortality were observed. An increase of 10 microg/m(3) of 2-day moving average concentrations of SO(2) corresponded to 1.00% [95% confidence interval (CI), 0.75-1.24], 1.09% (95% CI, 0.71-1.47), and 1.47% (95% CI, 0.85-2.08) increase of total, cardiovascular and respiratory mortality, respectively, in the combined analysis. Sensitivity analyzes suggested that these findings were generally insensitive to alternative model specifications. After adjustment for PM(10) or O(3), the effect of SO(2) remained significant in three Chinese cities. However, adjustment for NO(2) diminished the associations and rendered them statistically insignificant in all four cities. In conclusion, ambient SO(2) concentration was associated with daily mortality in these four Asian cities. These associations may be attributable to SO(2) serving as a surrogate of other substances. Our findings suggest that the role of outdoor exposure to SO(2) should be investigated further in this region.

Cardiovascular health and particulate vehicular emissions: a critical evaluation of the evidence

A major public health goal is to determine linkages between specific pollution sources and adverse health outcomes. This paper provides an integrative evaluation of the database examining effects of vehicular emissions, such as black carbon (BC), carbonaceous gasses, and ultrafine PM, on cardiovascular (CV) morbidity and mortality. Less than a decade ago, few epidemiological studies had examined effects of traffic emissions specifically on these health endpoints. In 2002, the first of many studies emerged finding significantly higher risks of CV morbidity and mortality for people living in close proximity to major roadways, vs. those living further away. Abundant epidemiological studies now link exposure to vehicular emissions, characterized in many different ways, with CV health endpoints such as cardiopulmonary and ischemic heart disease and circulatory-disease-associated mortality; incidence of coronary artery disease; acute myocardial infarction; survival after heart failure; emergency CV hospital admissions; and markers of atherosclerosis. We identify numerous in vitro, in vivo, and human panel studies elucidating mechanisms which could explain many of these cardiovascular morbidity and mortality associations. These include: oxidative stress, inflammation, lipoperoxidation and atherosclerosis, change in heart rate variability (HRV), arrhythmias, ST-segment depression, and changes in vascular function (such as brachial arterial caliber and blood pressure). Panel studies with accurate exposure information, examining effects of ambient components of vehicular emissions on susceptible human subjects, appear to confirm these mechanisms. Together, this body of evidence supports biological mechanisms which can explain the various CV epidemiological findings. Based upon these studies, the research base suggests that vehicular emissions are a major environmental cause of cardiovascular mortality and morbidity in the United States. As a means to reduce the public health consequences of such emissions, it may be desirable to promulgate a black carbon (BC) PM(2.5) standard under the National Ambient Air Quality Standards, which would apply to both on and off-road diesels. Two specific critical research needs are identified. One is to continue research on health effects of vehicular emissions, gaseous as well as particulate. The second is to utilize identical or nearly identical research designs in studies using accurate exposure metrics to determine whether other major PM pollutant sources and types may also underlie the specific health effects found in this evaluation for vehicular emissions.

The benefits of whole-house in-duct air cleaning in reducing exposures to fine particulate matter of outdoor origin: a modeling analysis

Health risks of fine particle air pollution (PM(2.5)) are an important public health concern that has the potential to be mitigated in part by interventions such as air cleaning devices that reduce personal exposure to ambient PM(2.5). To characterize exposure to ambient PM(2.5) indoors as a function of residential air cleaners, a multi-zone indoor air quality model was used to integrate spatially resolved data on housing, meteorology, and ambient PM(2.5), with performance testing of residential air cleaners to estimate short-term and annual average PM(2.5) of outdoor origin inside residences of three metropolitan areas. The associated public health impacts of reduced ambient PM(2.5) exposure were estimated using a standard health impact assessment methodology. Estimated indoor levels of ambient PM(2.5) varied substantially among ventilation and air cleaning configurations. The median 24-h average indoor-outdoor ratio of ambient PM(2.5) was 0.57 for homes with natural ventilation, 0.35 for homes with central air conditioning (AC) with conventional filtration, and 0.1 for homes with central AC with high efficiency in-duct air cleaner. Median modeled 24-h average indoor concentrations of PM(2.5) of outdoor origin for those three configurations were 8.4, 5.3, and 1.5 microg/m(3), respectively. The potential public health benefits of reduced exposure to ambient PM(2.5) afforded by air cleaning systems were substantial. If the entire population of single-family homes with central AC in the modeling domain converted from conventional filtration to high-efficiency in-duct air cleaning, the change in ambient PM(2.5) exposure is estimated to result in an annual reduction of 700 premature deaths, 940 hospital and emergency room visits, and 130,000 asthma attacks in these metropolitan areas. In addition to controlling emissions from sources, high-efficiency whole-house air cleaner are expected to reduce exposure to particles of outdoor origin and are projected to be an effective means of managing public health impacts of ambient particle pollution.

Seasonal effect of PM(10) concentrations on mortality and morbidity in Seoul, Korea: a temperature-matched case-crossover analysis

BACKGROUND

Explorations of interactions between air pollution and seasonal changes have represented one approach in examining the consequences of global warming. However, only a few studies have focused on evaluating the effects of seasonal air pollution using data on both morbidity and mortality in Asia.

METHOD

We examined the associations between PM(10) concentrations and mortality and hospital admissions in Seoul, Korea for the periods 2000-2006 and 2001-2006. We employed a temperature-matched case-crossover design, where reference periods matched case days in regard to temperature (same rounded to degrees celsius ( degrees C)), month, and year.

RESULTS

A total of 238,826 deaths were identified, along with 98,570 and 93,553 inpatient admissions for cardiovascular and respiratory diseases, respectively. We found that the association with PM(10) and mortality/morbidity increased during the summer. During the study period, 10microg/m(3) increase in PM(10) was associated with the increase in mortality by 0.28% (95% confidence interval: 0.12, 0.44), 0.51% (0.19, 0.83), and 0.59% (-0.08, 1.26) for non-accidental, cardiovascular, and respiratory causes. 10microg/m(3) increase in PM(10) was also associated with increase in hospitalization from cardiovascular and respiratory causes by 0.77% (0.53, 1.01) and 1.19% (0.94, 1.44). In the summer, the increase in mortality and hospitalization was 0.57% (0.20, 0.93), 0.64% (-0.10, 1.38), 0.50% (-1.02, 2.05), 1.52% (0.89, 2.16), and 1.55% (0.87, 2.22).

CONCLUSIONS

This study provides evidence that the effect of PM(10) on mortality and morbidity varies with season and increases during the summer season.

Adverse health effects of particulate air pollution: modification by air conditioning

BACKGROUND

The short-term effects of particulate matter (PM) on mortality and morbidity differ by geographic location and season. Several hypotheses have been proposed for this variation, including different exposures with air conditioning (AC) versus open windows.

METHODS

Bayesian hierarchical modeling was used to explore whether AC prevalence modified day-to-day associations between PM10 and mortality, and between PM2.5 and cardiovascular or respiratory hospitalizations, for those 65 years and older. We considered yearly, summer-only, and winter-only effect estimates and 2 types of AC (central and window units).

RESULTS

Communities with higher AC prevalence had lower PM effects. Associations were observed for cardiovascular hospitalizations and central AC. Each additional 20% of households with central AC was associated with a 43% decrease in PM2.5 effects on cardiovascular hospitalization. Central AC prevalence explained 17% of between-community variability in PM2.5 effect estimates for cardiovascular hospitalizations.

CONCLUSIONS

Higher AC prevalence was associated with lower health effect estimates for PM.

Association of ambient air pollution with hospital outpatient and emergency room visits in Shanghai, China

Few studies exist in China examining the association of ambient air pollution with morbidity outcomes. We conducted a time-series analysis to examine the association of outdoor air pollutants (PM(10), SO(2), and NO(2)) with hospital outpatient and emergency room visits in Shanghai, China, using 3 years of daily data (2005-2007). Hospital and air pollution data were collected from the Shanghai Health Insurance Bureau and Shanghai Environmental Monitoring Center. Using a natural spline model, we examined effect of air pollutants with different lag structures including both single-day lag and multi-day lag. We examined effects of air pollution for the warm season (from April to September) and cool season (from October to March) separately. We found outdoor air pollution (SO(2) and NO(2)) was associated with increased risk of hospital outpatient and emergency room visits in Shanghai. The effect estimates varied for different lag structures of pollutants' concentrations. For lag 3, a 10 microg/m(3) increase in concentration of PM(10), SO(2) and NO(2) corresponded to 0.11% (95%CI: -0.03%, 0.26%), 0.34% (95%CI: 0.06%, 0.61%) and 0.55% (95%CI: 0.14%, 0.97%) increase of outpatient visit; and 0.01% (95%CI: -0.09%, 0.10%), 0.17% (95%CI: 0.00%, 0.35%) and 0.08% (95%CI: -0.18%, 0.33%) increase of emergency room visit. The associations appeared to be more evident in the cool season than in the warm season. In conclusion, short-term exposure to outdoor air pollution was associated with increased risk of hospital outpatient and emergency room visits in Shanghai. Our analyses provide evidence that the current air pollution level has an adverse health effect and strengthen the rationale for further limiting air pollution levels in the city.

Preventing heat-related morbidity and mortality: new approaches in a changing climate

Due to global climate change, the world will, on average, experience a higher number of heat waves, and the intensity and length of these heat waves is projected to increase. Knowledge about the implications of heat exposure to human health is growing, with excess mortality and illness occurring during hot weather in diverse regions. Certain groups, including the elderly, the urban poor, and those with chronic health conditions, are at higher risk. Preventive actions include: establishing heat wave warning systems; making cool environments available (through air conditioning or other means); public education; planting trees and other vegetation; and modifying the built environment to provide proper ventilation and use materials and colors that reduce heat build-up and optimize thermal comfort. However, to inspire local prevention activities, easily understood information about the strategies' benefits needs to be incorporated into decision tools. Integrating heat health information into a comprehensive adaptation planning process can alert local decision-makers to extreme heat risks and provide information necessary to choose strategies that yield the largest health improvements and cost savings. Tools to enable this include web-based programs that illustrate effective methods for including heat health in comprehensive local-level adaptation planning; calculate costs and benefits of several activities; maps showing zones of high potential heat exposure and vulnerable populations in a local area; and public awareness materials and training for implementing preventive activities. A new computer-based decision tool will enable local estimates of heat-related health effects and potential savings from implementing a range of prevention strategies.

Modeling residential fine particulate matter infiltration for exposure assessment

Individuals spend the majority of their time indoors; therefore, estimating infiltration of outdoor-generated fine particulate matter (PM(2.5)) can help reduce exposure misclassification in epidemiological studies. As indoor measurements in individual homes are not feasible in large epidemiological studies, we evaluated the potential of using readily available data to predict infiltration of ambient PM(2.5) into residences. Indoor and outdoor light scattering measurements were collected for 84 homes in Seattle, Washington, USA, and Victoria, British Columbia, Canada, to estimate residential infiltration efficiencies. Meteorological variables and spatial property assessment data (SPAD), containing detailed housing characteristics for individual residences, were compiled for both study areas using a geographic information system. Multiple linear regression was used to construct models of infiltration based on these data. Heating (October to February) and non-heating (March to September) season accounted for 36% of the yearly variation in detached residential infiltration. Two SPAD housing characteristic variables, low building value, and heating with forced air, predicted 37% of the variation found between detached residential infiltration during the heating season. The final model, incorporating temperature and the two SPAD housing characteristic variables, with a seasonal interaction term, explained 54% of detached residential infiltration. Residences with low building values had higher infiltration efficiencies than other residences, which could lead to greater exposure gradients between low and high socioeconomic status individuals than previously identified using only ambient PM(2.5) concentrations. This modeling approach holds promise for incorporating infiltration efficiencies into large epidemiology studies, thereby reducing exposure misclassification.

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 Agency's 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.

Traffic-related air pollution and socioeconomic status: a spatial autocorrelation study to assess environmental equity on a small-area scale

BACKGROUND

: Most ecologic studies of environmental equity show that groups with lower socioeconomic status (SES) are more likely to be exposed to higher air pollution levels than groups of higher SES. However, these studies rarely consider spatial autocorrelation in the data. We investigated the associations between traffic-related air pollution and SES on a small-area level in Strasbourg (France) and assessed the impact of spatial autocorrelation on the results.

METHODS

: We used a deprivation index, constructed from census data, to estimate SES at the block level. Average ambient nitrogen dioxide (NO2) levels during year 2000, modeled at the block level by a dispersion model, served as a marker of traffic exhaust. We estimated the association between exposure to NO2 and the deprivation index by using an ordinary least squares model and a simultaneous autoregressive model that controls for the spatial autocorrelation of data.

RESULTS

: The association between the deprivation index and NO2 levels was positive and nonlinear with both regression models; the midlevel deprivation areas were the most exposed. Control of spatial autocorrelation strongly reduced the strength of the association but clearly improved the model's goodness-of-fit; the most pronounced reduction was observed for the midlevel deprivation areas (regression coefficients decreased by 67%).

CONCLUSIONS

: This study confirms the need to take spatial autocorrelation into account in ecologic studies and shows that failure to do so may lead to biased and unreliable estimates and thus to erroneous conclusions. This may be especially important in studying the role of air pollution on social inequalities in health.

Rapid DNA methylation changes after exposure to traffic particles

RATIONALE

Exposure to particulate air pollution has been related to increased hospitalization and death, particularly from cardiovascular disease. Lower blood DNA methylation content is found in processes related to cardiovascular outcomes, such as oxidative stress, aging, and atherosclerosis.

OBJECTIVES

We evaluated whether particulate pollution modifies DNA methylation in heavily methylated sequences with high representation throughout the human genome.

METHODS

We measured DNA methylation of long interspersed nucleotide element (LINE)-1 and Alu repetitive elements by quantitative polymerase chain reaction-pyrosequencing of 1,097 blood samples from 718 elderly participants in the Boston area Normative Aging Study. We used covariate-adjusted mixed models to account for within-subject correlation in repeated measures. We estimated the effects on DNA methylation of ambient particulate pollutants (black carbon, particulate matter with aerodynamic diameter < or = 2.5 microm [PM2.5], or sulfate) in multiple time windows (4 h to 7 d) before the examination. We estimated standardized regression coefficients (beta) expressing the fraction of a standard deviation change in DNA methylation associated with a standard deviation increase in exposure.

MEASUREMENTS AND MAIN RESULTS

Repetitive element DNA methylation varied in association with time-related variables, such as day of the week and season. LINE-1 methylation decreased after recent exposure to higher black carbon (beta = -0.11; 95% confidence interval [CI], -0.18 to -0.04; P = 0.002) and PM2.5 (beta = -0.13; 95% CI, -0.19 to -0.06; P < 0.001 for the 7-d moving average). In two-pollutant models, only black carbon, a tracer of traffic particles, was significantly associated with LINE-1 methylation (beta = -0.09; 95% CI, -0.17 to -0.01; P = 0.03). No association was found with Alu methylation (P > 0.12).

CONCLUSIONS

We found decreased repeated-element methylation after exposure to traffic particles. Whether decreased methylation mediates exposure-related health effects remains to be determined.

Rapid DNA methylation changes after exposure to traffic particles

RATIONALE

Exposure to particulate air pollution has been related to increased hospitalization and death, particularly from cardiovascular disease. Lower blood DNA methylation content is found in processes related to cardiovascular outcomes, such as oxidative stress, aging, and atherosclerosis.

OBJECTIVES

We evaluated whether particulate pollution modifies DNA methylation in heavily methylated sequences with high representation throughout the human genome.

METHODS

We measured DNA methylation of long interspersed nucleotide element (LINE)-1 and Alu repetitive elements by quantitative polymerase chain reaction-pyrosequencing of 1,097 blood samples from 718 elderly participants in the Boston area Normative Aging Study. We used covariate-adjusted mixed models to account for within-subject correlation in repeated measures. We estimated the effects on DNA methylation of ambient particulate pollutants (black carbon, particulate matter with aerodynamic diameter < or = 2.5 microm [PM2.5], or sulfate) in multiple time windows (4 h to 7 d) before the examination. We estimated standardized regression coefficients (beta) expressing the fraction of a standard deviation change in DNA methylation associated with a standard deviation increase in exposure.

MEASUREMENTS AND MAIN RESULTS

Repetitive element DNA methylation varied in association with time-related variables, such as day of the week and season. LINE-1 methylation decreased after recent exposure to higher black carbon (beta = -0.11; 95% confidence interval [CI], -0.18 to -0.04; P = 0.002) and PM2.5 (beta = -0.13; 95% CI, -0.19 to -0.06; P < 0.001 for the 7-d moving average). In two-pollutant models, only black carbon, a tracer of traffic particles, was significantly associated with LINE-1 methylation (beta = -0.09; 95% CI, -0.17 to -0.01; P = 0.03). No association was found with Alu methylation (P > 0.12).

CONCLUSIONS

We found decreased repeated-element methylation after exposure to traffic particles. Whether decreased methylation mediates exposure-related health effects remains to be determined.

Seasonal and regional short-term effects of fine particles on hospital admissions in 202 US counties, 1999-2005

The authors investigated whether short-term effects of fine particulate matter with an aerodynamic diameter < or =2.5 microm (PM(2.5)) on risk of cardiovascular and respiratory hospitalizations among the elderly varied by region and season in 202 US counties for 1999-2005. They fit 3 types of time-series models to provide evidence for 1) consistent particulate matter effects across the year, 2) different particulate matter effects by season, and 3) smoothly varying particulate matter effects throughout the year. The authors found statistically significant evidence of seasonal and regional variation in estimates of particulate matter effect. Respiratory disease effect estimates were highest in winter, with a 1.05% (95% posterior interval: 0.29, 1.82) increase in hospitalizations per 10-microg/m(3) increase in same-day PM(2.5). Cardiovascular diseases estimates were also highest in winter, with a 1.49% (95% confidence interval: 1.09, 1.89) increase in hospitalizations per 10-microg/m(3) increase in same-day PM(2.5), with associations also observed in other seasons. The strongest evidence of a relation between PM(2.5) and hospitalizations was in the Northeast for both respiratory and cardiovascular diseases. Heterogeneity of PM(2.5) effects on hospitalizations may reflect seasonal and regional differences in emissions and in particles' chemical constituents. Results can help guide development of hypotheses and further epidemiologic studies on potential heterogeneity in the toxicity of constituents of the particulate matter mixture.

Is epidemiology the key to cumulative risk assessment?

Although cumulative risk assessment by definition evaluates the joint effects of chemical and nonchemical stressors, studies to date have not considered both dimensions, in part because toxicological studies cannot capture many stressors of interest. Epidemiology can potentially include all relevant stressors, but developing and extracting the necessary information is challenging given some of the inherent limitations of epidemiology. In this article, I propose a conceptual framework within which epidemiological studies could be evaluated for their inclusion into cumulative risk assessment, including a problem formulation/planning and scoping step that focuses on stressors meaningful for risk management decisions, extension of the chemical mixtures framework to include nonchemical stressors, and formal consideration of vulnerability characteristics of the population. In the long term, broadening the applicability and informativeness of cumulative risk assessment will require enhanced communication and collaboration between epidemiologists and risk assessors, in which the structure of social and environmental epidemiological analyses may be informed in part by the needs of cumulative risk assessment.

On exposure and response relationships for health effects associated with exposure to vehicular traffic

This work examines various metrics and models that have been used to estimate long-term health effects of exposure to vehicular traffic. Such health impacts may include effects of air pollution due to emissions of combustion products and from vehicle or roadway wear, of noise, stress, or from socioeconomic effects associated with preferred residential locations. Both categorical and continuous exposure metrics are considered, typically for distances between residences and roadways, or for traffic density or intensity. It appears that continuous measures of exposure tend to yield lower risk estimates that are also more precise than categorical measures based on arbitrary criteria. The selection of appropriate exposure increments to characterize relative risks is also important in comparing pollutants and other agents. Confounding and surrogate variables are also important issues, since studies of traffic proximity or density cannot identify the specific agents related to traffic exposures that might be responsible for the various health endpoints that have been implicated. Studies based on ambient air quality measurements are necessarily restricted to species for which data are available, some of which may be serving as markers for the actual agents of harm. Studies based on modeled air quality are limited by the accuracy of mobile source emission inventories, which may not include poorly maintained (high emitting) vehicles. Additional exposure modeling errors may result from precision limitations of geocoding methods. Studies of the health effects of traffic are progressing from establishing the existence of relationships to describing them in more detail, but effective remedies or control strategies have generally not yet been proposed in the context of these epidemiological studies. Resolution of these dose-response uncertainties is important for the development of effective public health strategies for the future.

Cardiovascular Effects of Fine Particulate Matter Components in Highway Patrol Officers

Exposure to fine particulate matter (PM2.5) from traffic affects heart-rate variability, thrombosis, and inflammation. This reanalysis investigated components potentially contributing to such effects in nonsmoking healthy male North Carolina highway patrol troopers. Nine officers were studied four times during their late shift. PM2.5, its elemental composition, and gaseous copollutants were measured inside patrol cars. Components correlated to PM2.5 were compared to cardiac and blood parameters measured 10 and 15 h, respectively, after each shift. Mixed effects models with control for PM2.5 were used. Components that were associated with health endpoints independently from PM2.5 were calcium (increased uric acid and von Willebrand Factor [vWF], decreased protein C), chromium (increased white blood cell count and interleukin 6), aldehydes (increased vWF, mean cycle length of normal R-R intervals [MCL], and heart-rate variability parameter pNN50), copper (increased blood urea nitrogen and MCL; decreased plasminogen activator inhibitor 1), and sulfur (increased ventricular ectopic beats). Control for gaseous copollutants had little effect on the effect estimates. The changes observed are consistent with effects reported earlier for PM2.5 from speed-change traffic (characterized by copper, sulfur, and aldehydes) and from soil (with calcium). The associations of chromium with inflammation markers were not seen before for traffic particles, but they are consistent with the toxicological literature although at low concentrations. Copper, sulfur, aldehydes, calcium, and chromium or compounds containing these elements seem to directly contribute to the inflammatory, coagulatory, and cardiac response to PM2.5 from traffic in the investigated patrol troopers.

Evaluating the Health Risk from Secondary Sulfates in Eastern North American Regional Ambient Air Particulate Matter

Epidemiological studies of particulate matter (PM) using central area monitors have associated total PM mass, as well as certain individual components of PM, including sulfate, with adverse human health effects. However, some recent studies that used concentrated ambient particles (CAPs) or analyzed the effects of air pollution from different sources or geographic areas suggest that while some particles may be harmful, other particulate species including secondary sulfates may have negligible health effects. Toxicology studies to date also suggest that secondary sulfates pose little health risk. While studies using central-area monitors implicitly assume that all residents of the area are exposed to the same levels of pollution, newer studies find substantial health effects for those in close proximity to major roads. These latter studies recognize that although population exposure to widespread pollutants, such as total PM mass and sulfates, may be relatively uniform over a wide area, exposure to pollutants from local sources is not. While there is an emerging literature associating several adverse health effects with proximity to local pollution sources, the current database provides limited information that allows identification of specific particulate species that may cause little to no harm. In this article, we suggest that ambient secondary sulfates, and eastern North American regional air masses generally, appear to have little adverse impact on public health. This suggestion is based on evidence gleaned from eight avenues of investigation: (1) recent non-central-area monitor studies, including exposure gradient or proximity studies; (2) CAPs studies; (3) studies that examine effects related to different geographic areas or sources; (4) toxicology studies; (5) the limited number of studies that analyze existing central-area monitor data to explicitly examine the health impacts of sulfate and acidity versus PM mass; (6) "modern" area monitor studies with additional capabilities to distinguish among sources of pollution; (7) partial reinterpretation of two pivotal cohort studies; and (8) studies separating effects of secondary sulfates from those of primary metal sulfates. However, uncertainties remain regarding the role that secondary sulfates may play in ambient PM chemistry pathways leading to potentially harmful products, such as the possible effects of secondary organic aerosols that may be the product of acid catalysis of sulfur dioxide. Thus, more targeted study is needed, and some research suggestions are made in this regard.

A scripted activity study of the impact of protective advice on personal exposure to ultra-fine and fine particulate matter and volatile organic compounds

We evaluated the impact on personal exposure to air pollutants of following advice which typically accompanies air quality advisories and indices. Scripts prescribed the time, location, duration and nature of activities intended to simulate daily activity patterns for adults and children. Scripts were paired such that one individual would proceed with usual activities (base scenario), whereas the other (intervention scenario) would alter activities as if following advice. Other than commuting, where the intervention group walked or used public transportation rather than riding in personal vehicles, this group generally spent less time outdoors. Ultra-fine particles (UFPs), particulate matter of median aerodynamic diameter less than 2.5 mum (PM(2.5)) and total volatile organic compounds (VOCs) were measured using samplers carried by individuals during the course of daily activities. During daytime activities (e.g., work, daycare) constituting the largest share of sampling time (approximately 6 h per day), the intervention group experienced a 14% reduction in exposure to UFPs (P=0.01), a 21% reduction in exposure to PM(2.5) (P=0.08), and an 86% increase in exposure to VOCs (P=0.02). Other findings included an 89% increase in exposure to UFPs (P=0.02) and a threefold increase in exposure to VOCs (P=0.08) in the intervention group during evening cooking. Following smog advisory advice results in reduced exposures to some pollutants, while at the same time increasing exposure to others. Advice needs to be refined giving consideration to overall personal exposure.

Mechanisms and implications of air pollution particle associations with chemokines

Inflammation induced by inhalation of air pollutant particles has been implicated as a mechanism for the adverse health effects associated with exposure to air pollution. The inflammatory response is associated with upregulation of various pro-inflammatory cytokines and chemokines. We have previously shown that diesel exhaust particles (DEP), a significant constituent of air pollution particulate matter in many urban areas, bind and concentrate IL-8, an important human neutrophil-attracting chemokine, and that the chemokine remains biologically active. In this report, we examine possible mechanisms of this association and the effects on clearance of the chemokine. The binding appears to be the result of ionic interactions between negatively charged particles and positively charged chemokine molecules, possibly combined with intercalation into small pores in the particles. The association is not limited to diesel exhaust particles and IL-8: several other particle types also adsorb the chemokine and several other cytokines are adsorbed onto the diesel particles. However, there are wide ranges in the effectiveness of various particle types and various cytokines. Finally, male Fisher 344 rats were intratracheally instilled with chemokine alone or combined with diesel exhaust or silica particles under isofluorane anesthesia. In contrast to silica particles, which do not bind the chemokine, the presence of diesel exhaust particles, which bind the chemokine, prolonged the retention of the chemokine.

Quality of indoor residential air and health

About 90% of our time is spent indoors where we are exposed to chemical and biological contaminants and possibly to carcinogens. These agents may influence the risk of developing nonspecific respiratory and neurologic symptoms, allergies, asthma and lung cancer. We review the sources, health effects and control strategies for several of these agents. There are conflicting data about indoor allergens. Early exposure may increase or may decrease the risk of future sensitization. Reports of indoor moulds or dampness or both are consistently associated with increased respiratory symptoms but causality has not been established. After cigarette smoking, exposure to environmental tobacco smoke and radon are the most common causes of lung cancer. Homeowners can improve the air quality in their homes, often with relatively simple measures, which should provide health benefits.

Effect modification by community characteristics on the short-term effects of ozone exposure and mortality in 98 US communities

Previous research provided evidence of an association between short-term exposure to ozone and mortality risk and of heterogeneity in the risk across communities. The authors investigated whether this heterogeneity can be explained by community-specific characteristics: race, income, education, urbanization, transportation use, particulate matter and ozone levels, number of ozone monitors, weather, and use of air conditioning. Their study included data on 98 US urban communities for 1987 to 2000 from the National Morbidity, Mortality, and Air Pollution Study; US Census; and American Housing Survey. On average across the communities, a 10-ppb increase in the previous week's ozone level was associated with a 0.52% (95% posterior interval: 0.28, 0.77) increase in mortality. The authors found that community-level characteristics modify the relation between ozone and mortality. Higher effect estimates were associated with higher unemployment, fraction of the Black/African-American population, and public transportation use and with lower temperatures or prevalence of central air conditioning. These differences may relate to underlying health status, differences in exposure, or other factors. Results show that some segments of the population may face higher health burdens of ozone pollution.

Assessing the role of particulate matter size and composition on gene expression in pulmonary cells

Identifying the mechanisms by which air pollution causes human health effects is a daunting task. Airsheds around the world are composed of pollution mixtures made up of hundreds of chemical and biological components with an extensive array of physicochemical properties. Current in vivo approaches are limited to the identification of associations between pollutants and health but do not allow for the identification of precise biological mechanisms of effect or the component(s) responsible for the effect. High-throughput in vitro methods using relevant cell culture systems and microarray technology allow researchers to evaluate the mechanisms by which air pollutants affect human health. Our studies have used human airway epithelial cells primarily to test the toxicological effects of particles of different sizes and of various particle components from several cities across the United States. Chemical mass balance analysis is also being used to analyze these samples to establish links between physicochemical properties of particulate matter (PM) and potential sources. The ultimate goal of this line of research is to link the mechanistic data to the PM source data in order to gain an understanding about how the components and sources of PM affect human health.

Cardiovascular disease and air pollutants: evaluating and improving epidemiological data implicating traffic exposure

Evidence suggests that traffic-related pollutants play a role in the observed associations between air pollution and adverse cardiovascular health effects. The contribution of traffic to individual exposures is difficult to quantify in traditional epidemiological studies, however, and researchers have employed various approaches in attempt to isolate its effects. Many investigators have employed ambient measurements such as nitrogen oxides, carbon monoxide, or black carbon as surrogates for traffic in studying associations with health outcomes. Source-apportionment techniques also have been used in a few studies to identify associations with the mixture of pollutants from specific origins, including traffic. In other studies, estimates of traffic near a person's home have predicted cardiovascular endpoints, and local traffic levels have modified the effect of regional air pollution. More recently, studies have linked changes in cardiovascular health to time spent in traffic. In this article, we review the epidemiological evidence regarding the impact of traffic-related pollution on cardiovascular diseases and examine the different techniques used to examine this important research question. We conclude with a discussion of the future directions being used in ongoing epidemiological studies to identify the cardiovascular health impacts of traffic.

Ambient particle source apportionment and daily hospital admissions among children and elderly in Copenhagen

An association between particulate air pollution and morbidity and mortality is well established. However, little is known about which sources of particulate matter contribute most to the adverse health effects. Identification of responsible sources would merit more efficient control. For a 6-year period (01 January 1999 to 31 December 2004), we examined associations between urban background PM(10) in the presence of gaseous pollutants (CO, NO(2)) and hospital admissions due to cardiovascular and respiratory disease in the elderly (age>/=65), and asthma in children (age 5-18) in Copenhagen, Denmark. We further studied associations between fractions of PM(10) assigned to six sources (biomass, secondary, oil, crustal, sea salt, and vehicle) and admissions during a 1(1/2) -year campaign. We used Poisson generalized additive time-series model adjusted for season, day of the week, public holidays, influenza epidemics, grass pollen, school holidays, and meteorology, with up to 5 days lagged air pollution exposure. We found positive associations between PM(10) and the three health outcomes, with strongest associations for asthma. The PM(10) effect remained robust in the presence of CO and NO(2). We found different PM(10) sources to be variably associated with different outcomes: crustal and secondary sources showed strongest associations with cardiovascular, biomass with respiratory, and vehicle with asthma admissions. These novel results may merit future research of potential mechanism, whereas at present, no single PM(10) source can be attributed to all morbidity.