Estimating long-term average particulate air pollution concentrations: application of traffic indicators and geographic information systems

Mapping of background air pollution at a fine spatial scale across the European Union

BACKGROUND

There is a need to understand much more about the geographic variation of air pollutants. This requires the ability to extrapolate from monitoring stations to unsampled locations. The aim was to assess methods to develop accurate and high resolution maps of background air pollution across the EU.

METHODS

We compared the validity of ordinary kriging, universal kriging and regression mapping in developing EU-wide maps of air pollution on a 1x1 km resolution. Predictions were made for the year 2001 for nitrogen dioxide (NO(2)), fine particles <10 microm (PM(10)), ozone (O(3)), sulphur dioxide (SO(2)) and carbon monoxide (CO) using routine monitoring data in Airbase. Predictor variables from EU-wide databases were land use, road traffic, population density, meteorology, altitude, topography and distance to sea. Models were developed for the global, rural and urban scale separately. The best method to model concentrations was selected on the basis of predefined performance measures (R(2), Root Mean Square Error (RMSE)).

RESULTS

For NO(2), PM(10) and O(3) universal kriging performed better than regression mapping and ordinary kriging. Validation of the final universal kriging estimates with results from all validation sites gave R(2)-values and RMSE-values of 0.61 and 6.73 microg/m(3) for NO(2); 0.45 and 5.19 microg/m(3) for PM(10); and 0.70 and 7.69 microg/m(3) for O(3). For SO(2) and CO none of the three methods was able to provide a satisfactory prediction.

CONCLUSION

Reasonable prediction models were developed for NO(2), PM(10) and O(3) on an EU-wide scale. Our study illustrates that it is possible to develop detailed maps of background air pollution using EU-wide databases.

[Allergic respiratory diseases and outdoor air pollution]

INTRODUCTION

After having increased for some time, the prevalence of allergic diseases may have reached a plateau. During this increase, considerable concomitant changes in air pollution have occurred. Photo-oxidant air pollution, related to traffic, has become preponderant. The implication of air pollution in the epidemic of allergies is still debated.

BACKGROUND

Experimental studies have suggested that the effect of air pollutants, including particulates and ozone, on the worsening and even the induction of allergies is biologically plausible. In addition, epidemiological studies have shown a short term impact of the peaks of air pollution on exacerbations of asthma. On the other hand, the results of epidemiological studies dealing with the long-term effects of chronic exposure to air pollution on the prevalence of allergies are less consistent.

VIEWPOINTS

The implementation of new-born cohorts, the use of dispersion models to improve exposure assessment and the study of gene-environment correlations, should increase our knowledge of the role of traffic-related air pollutants in the development of allergies and identify subjects more sensitive to their effects.

CONCLUSIONS

Some traffic-related air pollutants may have played a more important role in the increase in the prevalence of allergies than was assumed from the first epidemiological studies.

A land-use regression model for estimating microenvironmental diesel exposure given multiple addresses from birth through childhood

The Cincinnati Childhood Allergy and Air Pollution Study (CCAAPS) is a prospective birth cohort whose purpose is to determine if exposure to high levels of diesel exhaust particles (DEP) during early childhood increases the risk for developing allergic diseases. In order to estimate exposure to DEP, a land-use regression (LUR) model was developed using geographic data as independent variables and sampled levels of a marker of DEP as the dependent variable. A continuous wind direction variable was also created. The LUR model predicted 74% of the variability in sampled values with four variables: wind direction, length of bus routes within 300 m of the sample site, a measure of truck intensity within 300 m of the sampling site, and elevation. The LUR model was subsequently applied to all locations where the child had spent more than eight hours per week from through age three. A time-weighted average (TWA) microenvironmental exposure estimate was derived for four time periods: 0-6 months, 7-12 months, 13-24 months, 25-36 months. By age two, one third of the children were spending significant time at locations other than home and by 36 months, 39% of the children had changed their residential addresses. The mean cumulative DEP exposure estimate increased from age 6 to 36 months from 70 to 414 microg/m3-days. Findings indicate that using birth addresses to estimate a child's exposure may result in exposure misclassification for some children who spend a significant amount of time at a location with high exposure to DEP.

Spatio-temporal modeling of chronic PM10 exposure for the Nurses' Health Study

Chronic epidemiological studies of airborne particulate matter (PM) have typically characterized the chronic PM exposures of their study populations using city- or countywide ambient concentrations, which limit the studies to areas where nearby monitoring data are available and which ignore within-city spatial gradients in ambient PM concentrations. To provide more spatially refined and precise chronic exposure measures, we used a Geographic Information System (GIS)-based spatial smoothing model to predict monthly outdoor PM(10) concentrations in the northeastern and midwestern United States. This model included monthly smooth spatial terms and smooth regression terms of GIS-derived and meteorological predictors. Using cross-validation and other pre-specified selection criteria, terms for distance to road by road class, urban land use, block group and county population density, point- and area-source PM(10) emissions, elevation, wind speed, and precipitation were found to be important determinants of PM(10) concentrations and were included in the final model. Final model performance was strong (cross-validation R(2)=0.62), with little bias (-0.4 mug m(-3)) and high precision (6.4 mug m(-3)). The final model (with monthly spatial terms) performed better than a model with seasonal spatial terms (cross-validation R(2)=0.54). The addition of GIS-derived and meteorological predictors improved predictive performance over spatial smoothing (cross-validation R(2)=0.51) or inverse distance weighted interpolation (cross-validation R(2)=0.29) methods alone and increased the spatial resolution of predictions. The model performed well in both rural and urban areas, across seasons, and across the entire time period. The strong model performance demonstrates its suitability as a means to estimate individual-specific chronic PM(10) exposures for large populations.

Meeting report: atmospheric pollution and human reproduction

BACKGROUND

There is a growing body of epidemiologic literature reporting associations between atmospheric pollutants and reproductive outcomes, particularly birth weight and gestational duration.

OBJECTIVES

The objectives of our international workshop were to discuss the current evidence, to identify the strengths and weaknesses of published epidemiologic studies, and to suggest future directions for research.

DISCUSSION

Participants identified promising exposure assessment tools, including exposure models with fine spatial and temporal resolution that take into account time-activity patterns. More knowledge on factors correlated with exposure to air pollution, such as other environmental pollutants with similar temporal variations, and assessment of nutritional factors possibly influencing birth outcomes would help evaluate importance of residual confounding. Participants proposed a list of points to report in future publications on this topic to facilitate research syntheses. Nested case-control studies analyzed using two-phase statistical techniques and development of cohorts with extensive information on pregnancy behaviors and biological samples are promising study designs. Issues related to the identification of critical exposure windows and potential biological mechanisms through which air pollutants may lead to intrauterine growth restriction and premature birth were reviewed.

CONCLUSIONS

To make progress, this research field needs input from toxicology, exposure assessment, and clinical research, especially to aid in the identification and exposure assessment of feto-toxic agents in ambient air, in the development of early markers of adverse reproductive outcomes, and of relevant biological pathways. In particular, additional research using animal models would help better delineate the biological mechanisms underpinning the associations reported in human studies.

A cohort study of traffic-related air pollution impacts on birth outcomes

BACKGROUND

Evidence suggests that air pollution exposure adversely affects pregnancy outcomes. Few studies have examined individual-level intraurban exposure contrasts.

OBJECTIVES

We evaluated the impacts of air pollution on small for gestational age (SGA) birth weight, low full-term birth weight (LBW), and preterm birth using spatiotemporal exposure metrics.

METHODS

With linked administrative data, we identified 70,249 singleton births (1999-2002) with complete covariate data (sex, ethnicity, parity, birth month and year, income, education) and maternal residential history in Vancouver, British Columbia, Canada. We estimated residential exposures by month of pregnancy using nearest and inverse-distance weighting (IDW) of study area monitors [carbon monoxide, nitrogen dioxide, nitric oxide, ozone, sulfur dioxide, and particulate matter < 2.5 (PM2.5) or < 10 (PM10) microm in aerodynamic diameter], temporally adjusted land use regression (LUR) models (NO, NO2, PM2.5, black carbon), and proximity to major roads. Using logistic regression, we estimated the risk of mean (entire pregnancy, first and last month of pregnancy, first and last 3 months) air pollution concentrations on SGA (< 10th percentile), term LBW (< 2,500 g), and preterm birth.

RESULTS

Residence within 50 m of highways was associated with a 22% (95% CI, 0.81-1.87) [corrected] increase in LBW. Exposure to all air pollutants except O3 was associated with SGA, with similar odds ratios (ORs) for LUR and monitoring estimates (e.g., LUR: OR = 1.02; 95% CI, 1.00-1.04; IDW: OR = 1.05; 95% CI, 1.03-1.08 per 10-microg/m3 increase in NO). For preterm births, associations were observed with PM2.5 for births < 37 weeks gestation (and for other pollutants at < 30 weeks). No consistent patterns suggested exposure windows of greater relevance.

CONCLUSION

Associations between traffic-related air pollution and birth outcomes were observed in a population-based cohort with relatively low ambient air pollution exposure.

Residential exposure to traffic-related air pollution and survival after heart failure

BACKGROUND

Although patients with heart failure (HF) have been identified as particularly susceptible to the acute effects of air pollution, the effects of long-term exposure to air pollution on patients with this increasingly prevalent disease are largely unknown.

OBJECTIVE

This study was designed to examine the mortality risk associated with residential exposure to traffic-related air pollution among HF patients.

METHODS

A total of 1,389 patients hospitalized with acute HF in greater Worcester, Massachusetts, during 2000 were followed for survival through December 2005. We used daily traffic within 100 and 300 m of residence as well as the distance from residence to major roadways and to bus routes as proxies for residential exposure to traffic-related air pollution. We assessed mortality risks for each exposure variable using Cox proportional hazards models adjusted for prognostic factors.

RESULTS

After the 5-year follow-up, only 334 (24%) subjects were still alive. An interquartile range increase in daily traffic within 100 m of home was associated with a mortality hazard ratio (HR) of 1.15 [95% confidence interval (CI), 1.05-1.25], whereas for traffic within 300 m this association was 1.09 (95% CI, 1.01-1.19). The mortality risk decreased with increasing distance to bus routes (HR = 0.88; 95% CI, 0.81-0.96) and was larger for those living within 100 m of a major roadway or 50 m of a bus route (HR = 1.30; 95% CI, 1.13-1.49). Adjustment for area-based income and educational level slightly attenuated these associations.

CONCLUSIONS

Residential exposure to traffic-related air pollution increases the mortality risk after hospitalization with acute HF. Reducing exposure to traffic-related emissions may improve the long-term prognosis of HF patients.

Stress and childhood asthma risk: overlapping evidence from animal studies and epidemiologic research

Rapidly expanding evidence increasingly strengthens the evidence linking psychological factors to asthma and allergy expression. Parallel studies in animals and humans demonstrating the influence of prenatal maternal stress and early caregiving experiences on the disrupted regulation of defensive biological systems [eg, sympathetic and adrenomedullary (SAM) system and the hypothalamicpituitary-adrenocortical (HPA) axis] provide strong proof of concept for this line of research. The consequent altered neuroimmune responses may influence the expression of immune-mediated disorders such as asthma as well as enhance an individual's susceptibility to other environmental factors that may also contribute to asthma risk.

Residential outdoor air pollution and lung function in schoolchildren

BACKGROUND

Long-term exposure to outdoor air pollution has typically been estimated on the aggregate level, and more individual measures of exposure are needed. We investigated the associations with lung function of residential outdoor air pollution in early life, total lifetime, and days before lung function test.

METHODS

In 2001-2002, spirometry was performed in 2307 9- and 10-year-old children who had lived in Oslo, Norway, since birth. Outdoor air pollution exposure for each child was assessed by the EPISODE dispersion model, calculating hourly concentrations of nitrogen dioxide (NO2), particulate matter (PM) with aerodynamic diameter less than 10 microm (PM10) and 2.5 microm (PM2.5). We applied linear regression analysis stratified by sex.

RESULTS

Early and lifetime exposures to outdoor air pollution were associated with reduced peak expiratory flow and reduced forced expiratory flow at 25% and 50% of forced vital capacity, especially in girls. One interquartile increase of lifetime exposure to NO2, PM10, and PM2.5 was associated with change in adjusted peak respiratory flow of, respectively, -79 mL/s (95% confidence interval = -128 to -31), -66 mL/s (-110 to -23), and -58 mL/s (-94 to -21). We also found short-term effects of NO2 that became stronger with increasing time lags, but no short-term effects of PM. When we included short- and long-term NO2 exposures simultaneously, only the long-term effect remained. We found no effect on forced volumes. Adjusting for a contextual socioeconomic factor diminished the associations.

CONCLUSIONS

Short- and long-term residential exposures to traffic-related pollutants in Oslo were associated with reduced peak expiratory flow and forced expiratory flow at 25% and 50% in 9- to 10-year-old children, especially in girls, with weaker associations after adjusting for a contextual socioeconomic factor.

In vitro toxicity evaluation of diesel exhaust particles on human eosinophilic cell

Diesel exhaust particles (DEPs), comprised mainly of particles less than 2.5 microm (PM 2.5) in aerodynamic diameter, have been assumed to enhance the response of asthma to allergen inhalation. Although eosinophilic infiltration is remarkable in the event of bronchial asthma induced by DEPs, the precise mechanisms leading to eosinophilia are unknown. To examine the effect of DEPs on eosinophils, we measured the cytokine products and activity of nuclear factor-kappa B (NF-kappa B) after addition of the proteasomal inhibitor MG132 in HL-60 clone 15 cells differentiated into eosinophils. We measured eotaxin-induced chemotaxis of cells and their activity of p38 mitogen-activated protein (MAP) kinase was analysed. Interleukin (IL)-8 and monocyte chemoattractant protein-1 (MCP-1) were increased markedly in DEPs-treated cells. The active form of NF-kappaB in cells treated with DEPs was increased, and this effect was significantly decreased by the administration of MG132. Cell migration in the presence of DEPs was significantly greater, and inhibited by adding N-acetyl l-cysteine. P38 MAP kinase activity was highly influenced by DEPs-treatment. DEPs induce MCP-1 and IL-8 production by up-regulating NF-kappa B activity, which is inhibited in the presence of an inhibitor of proteasomal degradation. DEP also promotes eotaxin-induced chemotaxis in a p38-dependent manner.

Comparison between various indices of exposure to traffic-related air pollution and their impact on respiratory health in adults

Objective:

To evaluate the association of different indices of traffic-related air pollution (self-report of traffic intensity, distance from busy roads from geographical information system (GIS), area-based emissions of particulate matter (PM), and estimated concentrations of nitrogen dioxide (NO₂) from a land-use regression model) with respiratory health in adults.

Methods:

A sample of 9488 25–59-year-old Rome residents completed a self-administered questionnaire on respiratory health and various risk factors, including education, occupation, housing conditions, smoking, and traffic intensity in their area of residence. The study used GIS to calculate the distance between their home address and the closest high-traffic road. For each subject, PM emissions in the area of residence as well as estimated NO₂ concentrations as assessed by a land-use regression model (R² value = 0.69), were available. Generalised estimating equations (GEE) were used to analyse the association between air pollution measures and prevalence of “ever” chronic bronchitis, asthma, and rhinitis taking into account the effects of age, gender, education, smoking habits, socioeconomic position, and the correlation of variables for members of the same family.

Results:

Three hundred and ninety seven subjects (4% of the study population) reported chronic bronchitis, 472 (5%) asthma, and 1227 (13%) rhinitis. Fifteen per cent of subjects reported living in high traffic areas, 11% lived within 50 m of a high traffic road, and 28% in areas with estimated NO₂ greater than 50 μg/m³. Prevalence of asthma was associated only with self-reported traffic intensity whereas no association was found for the other more objective indices. Rhinitis, on the other hand, was strongly associated with all traffic-related indicators (eg, OR = 1.13, 95% CI: 1.04 to 1.22 for 10 μg/m³ NO₂), especially among non-smokers.

Conclusions:

Indices of exposure to traffic-related air pollution are consistently associated with an increased risk of rhinitis in adults, especially among non-smokers. The results for asthma are weak, possibly due to ascertainment problems.

Increased transcription of immune and metabolic pathways in naive and allergic mice exposed to diesel exhaust

Diesel exhaust (DE) has been shown to enhance allergic sensitization in animals following high-dose instillation or chronic inhalation exposure scenarios. The purpose of this study was to determine if short-term exposures to diluted DE enhance allergic immune responses to antigen, and identify possible mechanisms using microarray technology. BALB/c mice were exposed to filtered air or diluted DE to yield particle concentrations of 500 or 2000 mug/m(3) 4 h/day on days 0-4. Mice were immunized intranasally with ovalbumin (OVA) antigen or saline on days 0-2, challenged on day 18 with OVA or saline, and all mice were challenged with OVA on day 28. Mice were necropsied either 4 h after the last DE exposure on day 4, or 18, 48, and 96 h after the last challenge. Immunological endpoints included OVA-specific serum IgE, biochemical and cellular profiles of bronchoalveolar lavage (BAL), and cytokine production in the BAL. OVA-immunized mice exposed to both concentrations of DE had increased eosinophils, neutrophils, lymphocytes, and interleukin-6 (high dose only) post-challenge compared with OVA control, whereas DE/saline exposure yielded increases in neutrophils at the high dose only. Transcriptional microarray analysis 4 h after the last DE exposure demonstrated distinct gene expression profiles for the high-dose DE/OVA and DE/saline groups. DE/OVA induced oxidative stress and metabolism pathways, whereas DE in the absence of immunization modulated cell cycle control, growth and differentiation, G-proteins, and cell adhesion pathways. This study shows for the first time early changes in gene expression induced by the combination of DE inhalation and mucosal immunization, which resulted in stronger development of allergic eosinophilia.

Intra-urban variability of air pollution in Windsor, Ontario--measurement and modeling for human exposure assessment

There are acknowledged difficulties in epidemiological studies to accurately assign exposure to air pollution for large populations, and large, long-term cohort studies have typically relied upon data from central monitoring stations. This approach has generally been adequate when populations span large areas or diverse cities. However, when the effects of intra-urban differences in exposure are being studied, the use of these existing central sites are likely to be inadequate for representing spatial variability that exists within an urban area. As part of the Border Air Quality Strategy (BAQS), an international agreement between the governments of Canada and the United States, a number of air health effects studies are being undertaken by Health Canada and the US EPA. Health Canada's research largely focuses on the chronic exposure of elementary school children to air pollution. The exposure characterization for this population to a variety of air pollutants has been assessed using land-use regression (LUR) models. This approach has been applied in several cities to nitrogen dioxide (NO2), as an assumed traffic exposure marker. However, the models have largely been developed from limited periods of saturation monitoring data and often only represent one or two seasons. Two key questions from these previous efforts, which are examined in this paper, are: If NO2 is a traffic marker, what other pollutants, potentially traffic related, might it actually represent? How well is the within city spatial variability of NO2, and other traffic-related pollutants, characterized by a single saturation monitoring campaign. Input data for the models developed in this paper were obtained across a network of 54 monitoring sites situated across Windsor, Ontario. The pollutants studied were NO2, sulfur dioxide (SO2) and volatile organic compounds, which were measured in all four seasons by deploying passive samplers for 2-week periods. Correlations among these pollutants were calculated to assess what other pollutants NO2 might represent, and correlations across seasons for a given pollutant were determined to assess how much the within-city spatial pattern varies with time. LUR models were then developed for NO2, SO2, benzene, and toluene. A multiple regression model including proximity to the Ambassador Bridge (the main Canada-US border crossing point), and proximity to highways and major roads, predicted NO2 concentrations with an R2=0.77. The SO2 model predictors included distance to the Ambassador Bridge, dwelling density within 1500m, and Detroit-based SO2 emitters within 3000m resulting in a model with an R2=0.69. Benzene and toluene LUR models included traffic predictors as well as point source emitters resulting in R2=0.73 and 0.46, respectively. Between season pollutant correlations were all significant although actual concentrations for each site varied by season. This suggests that if one season were to be selected to represent the annual concentrations for a specific site this may lead to a potential under or overestimation in exposure, which could be significant for health research. All pollutants had strong inter-pollutant correlations suggesting that NO2 could represent SO2, benzene, and toluene.

A review of land-use regression models for characterizing intraurban air pollution exposure

Epidemiologic studies of air pollution require accurate exposure assessments at unmonitored locations in order to minimize exposure misclassification. One approach gaining considerable interest is the land-use regression (LUR) model. Generally, the LUR model has been utilized to characterize air pollution exposure and health effects for individuals residing within urban areas. The objective of this article is to briefly summarize the history and application of LUR models to date outlining similarities and differences of the variables included in the model, model development, and model validation. There were 6 studies available for a total of 12 LUR models. Our findings indicated that among these studies, the four primary classes of variables used were road type, traffic count, elevation, and land cover. Of these four, traffic count was generally the most important. The model R2 explaining the variability in the exposure estimates for these LUR models ranged from .54 to .81. The number of air sampling sites generating the exposure estimates, however, was not correlated with the model R2 suggesting that the locations of the sampling sites may be of greater importance than the total number of sites. The primary conclusion of this study is that LUR models are an important tool for integrating traffic and geographic information to characterize variability in exposures.

Predicting residential indoor concentrations of nitrogen dioxide, fine particulate matter, and elemental carbon using questionnaire and geographic information system based data

Previous studies have identified associations between traffic-related air pollution and adverse health effects. Most have used measurements from a few central ambient monitors and/or some measure of traffic as indicators of exposure, disregarding spatial variability and/or factors influencing personal exposure-ambient concentration relationships. This study seeks to utilize publicly available data (i.e., central site monitors, geographic information system (GIS), and property assessment data) and questionnaire responses to predict residential indoor concentrations of traffic-related air pollutants for lower socioeconomic status (SES) urban households.As part of a prospective birth cohort study in urban Boston, we collected indoor and outdoor 3-4 day samples of nitrogen dioxide (NO(2)) and fine particulate matter (PM(2.5)) in 43 low SES residences across multiple seasons from 2003 - 2005. Elemental carbon concentrations were determined via reflectance analysis. Multiple traffic indicators were derived using Massachusetts Highway Department data and traffic counts collected outside sampling homes. Home characteristics and occupant behaviors were collected via a standardized questionnaire. Additional housing information was collected through property tax records, and ambient concentrations were collected from a centrally-located ambient monitor.The contributions of ambient concentrations, local traffic and indoor sources to indoor concentrations were quantified with regression analyses. PM(2.5) was influenced less by local traffic but had significant indoor sources, while EC was associated with traffic and NO(2) with both traffic and indoor sources. Comparing models based on covariate selection using p-values or a Bayesian approach yielded similar results, with traffic density within a 50m buffer of a home and distance from a truck route as important contributors to indoor levels of NO(2) and EC, respectively. The Bayesian approach also highlighted the uncertanity in the models. We conclude that by utilizing public databases and focused questionnaire data we can identify important predictors of indoor concentrations for multiple air pollutants in a high-risk population.

A predictive model for the home outdoor exposure to nitrogen dioxide

The aim of this study is to find and test a predictive model that could be suitable to estimate the outdoor NO(2) concentrations at individual level, by integrating ecological measurements recorded by local monitoring stations with individual information collected by a questionnaire. For this purpose, the data from the Italian centres of the European Community Respiratory Health Survey II (ECRHS II) has been used. Outdoor NO(2) concentrations were measured using NO(2) passive sampling tubes (PS-NO(2)), exposed outdoor for 14 days, between January 2001 and January 2003. Simultaneously, average NO(2) concentrations were collected from all the monitoring stations of the three centres (MS-NO(2)). Individual measurements carried out with passive samplers were compared with the corresponding NO(2) 2-week concentrations obtained as the average of all local (background and traffic) monitoring stations (MS-NO(2)). A multiple linear regression model was fitted to the data using the 2-week PS-NO(2) concentrations as the response variable and questionnaire information and MS-NO(2) concentrations as predictors. The model minimizing the root mean square error (RMSE), obtained from a ten-fold cross validation, was selected. The model with the best predictive ability included centre, season of the survey, MS-NO(2) concentrations, type and age of building, residential area and reported intensity of heavy-duty traffic and explained the 68.9% of the variance. The non-parametric correlation between PS-NO(2) and the concentrations estimated by the model is 0.81 (95% CI: 0.77-0.85). This study shows that over short periods (2 weeks) a good prediction of home outdoor exposure to NO(2) can be achieved by simply combining routinely collected ecological data with dwelling characteristics and self-reported intensity of heavy traffic. Further studies are needed to extend this prediction to long-term exposure.

Assessing uncertainty in spatial exposure models for air pollution health effects assessment

BACKGROUND

Although numerous epidemiologic studies now use models of intraurban exposure, there has been little systematic evaluation of the performance of different models.

OBJECTIVES

In this present article we proposed a modeling framework for assessing exposure model performance and the role of spatial autocorrelation in the estimation of health effects.

METHODS

We obtained data from an exposure measurement substudy of subjects from the Southern California Children's Health Study. We examined how the addition of spatial correlations to a previously described unified exposure and health outcome modeling framework affects estimates of exposure-response relationships using the substudy data. The methods proposed build upon the previous work, which developed measurement-error techniques to estimate long-term nitrogen dioxide exposure and its effect on lung function in children. In this present article, we further develop these methods by introducing between- and within-community spatial autocorrelation error terms to evaluate effects of air pollution on forced vital capacity. The analytical methods developed are set in a Bayesian framework where multistage models are fitted jointly, properly incorporating parameter estimation uncertainty at all levels of the modeling process.

RESULTS

Results suggest that the inclusion of residual spatial error terms improves the prediction of adverse health effects. These findings also demonstrate how residual spatial error may be used as a diagnostic for comparing exposure model performance.

Factors influencing the spatial extent of mobile source air pollution impacts: a meta-analysis

Background

There has been growing interest among exposure assessors, epidemiologists, and policymakers in the concept of "hot spots", or more broadly, the "spatial extent" of impacts from traffic-related air pollutants. This review attempts to quantitatively synthesize findings about the spatial extent under various circumstances.

Methods

We include both the peer-reviewed literature and government reports, and focus on four significant air pollutants: carbon monoxide, benzene, nitrogen oxides, and particulate matter (including both ultrafine particle counts and fine particle mass). From the identified studies, we extracted information about significant factors that would be hypothesized to influence the spatial extent within the study, such as the study type (e.g., monitoring, air dispersion modeling, GIS-based epidemiological studies), focus on concentrations or health risks, pollutant under study, background concentration, emission rate, and meteorological factors, as well as the study's implicit or explicit definition of spatial extent. We supplement this meta-analysis with results from some illustrative atmospheric dispersion modeling.

Results

We found that pollutant characteristics and background concentrations best explained variability in previously published spatial extent estimates, with a modifying influence of local meteorology, once some extreme values based on health risk estimates were removed from the analysis. As hypothesized, inert pollutants with high background concentrations had the largest spatial extent (often demonstrating no significant gradient), and pollutants formed in near-source chemical reactions (e.g., nitrogen dioxide) had a larger spatial extent than pollutants depleted in near-source chemical reactions or removed through coagulation processes (e.g., nitrogen oxide and ultrafine particles). Our illustrative dispersion model illustrated the complex interplay of spatial extent definitions, emission rates, background concentrations, and meteorological conditions on spatial extent estimates even for non-reactive pollutants. Our findings indicate that, provided that a health risk threshold is not imposed, the spatial extent of impact for mobile sources reviewed in this study is on the order of 100–400 m for elemental carbon or particulate matter mass concentration (excluding background concentration), 200–500 m for nitrogen dioxide and 100–300 m for ultrafine particle counts.

Conclusion

First, to allow for meaningful comparisons across studies, it is important to state the definition of spatial extent explicitly, including the comparison method, threshold values, and whether background concentration is included. Second, the observation that the spatial extent is generally within a few hundred meters for highway or city roads demonstrates the need for high resolution modeling near the source. Finally, our findings emphasize that policymakers should be able to develop reasonable estimates of the "zone of influence" of mobile sources, provided that they can clarify the pollutant of concern, the general site characteristics, and the underlying definition of spatial extent that they wish to utilize.

Mortality risk associated with short-term exposure to traffic particles and sulfates

BACKGROUND

Many studies have shown that airborne particles are associated with increased risk of death, but attention has more recently focused on the differential toxicity of particles from different sources. Geographic information system (GIS) approaches have recently been used to improve exposure assessment, particularly for traffic particles, but only for long-term exposure.

OBJECTIVES

We analyzed approximately 100,000 deaths from all, cardiovascular, and respiratory causes for the years 1995-2002 using a case-crossover analysis.

METHODS

Estimates of exposure to traffic particles were geocoded to the address of each decedent on the day before death and control days, with these estimates derived from a GIS-based exposure model incorporating deterministic covariates, such as traffic density and meteorologic factors, and a smooth function of latitude and longitude.

RESULTS

We estimate that an IQR increase in traffic particle exposure on the day before death is associated with a 2.3% increase [95% confidence interval (CI), 1.2 to 3.4%] in all-cause mortality risk. Stroke deaths were particularly elevated (4.4%; 95% CI, -0.2 to 9.3%), as were diabetes deaths (5.7%; 95% CI, -1.7 to 13.7%). Sulfate particles are spatially homogeneous, and using a central monitor, we found that an IQR increase in sulfate levels on the day before death is associated with a 1.1% (95% CI, 0.1 to 2.0%) increase in all-cause mortality risk.

CONCLUSIONS

Both traffic and powerplant particles are associated with increased deaths in Boston, with larger effects for traffic particles.

Traffic exposure and lung function in adults: the Atherosclerosis Risk in Communities study

BACKGROUND

Traffic exposure is a major contributor to ambient air pollution for people living close to busy roads. The relationship between traffic exposure and lung function remains inconclusive in adults.

METHODS

A cross-sectional study was conducted to investigate the association between traffic exposure and lung function in the Atherosclerosis Risk in Communities (ARIC) study, a community based cohort of 15 792 middle aged men and women. Traffic density and distance to major roads were used as measures of traffic exposure.

RESULTS

After controlling for potential confounders including demographic factors, personal and neighbourhood level socioeconomic characteristics, cigarette smoking and background air pollution, higher traffic density was significantly associated with lower forced expiratory volume in 1 s (FEV1) and forced vital capacity (FVC) in women. Relative to the lowest quartile of traffic density, the adjusted differences across increasing quartiles were 5.1, -15.4 and -21.5 ml for FEV1 (p value of linear trend across the quartiles = 0.041) and 1.2, -23.4 and -34.8 ml for FVC (p trend = 0.010). Using distance from major roads as a simpler index of traffic related air pollution exposure, the FEV1 was -15.7 ml (95% CI -34.4 to 2.9) lower and the FVC was -24.2 ml (95% CI -46.2 to -2.3) lower for women living within 150 m compared with subjects living further away. There was no significant effect of traffic density or distance to major roads on lung function in men. The FEV1/FVC ratio was not significantly associated with traffic exposure in either men or women.

CONCLUSIONS

This is the largest published study of traffic exposure and pulmonary function in adults to date. These results add to growing evidence that chronic exposure to traffic related air pollution may adversely affect respiratory health.

Bourdieu does environmental justice? Probing the linkages between population health and air pollution epidemiology

The environmental justice literature faces a number of conceptual and methodological shortcomings. The purpose of this paper is to probe ways in which these shortcomings can be remedied via recent developments in related literatures: population health and air pollution epidemiology. More sophisticated treatment of social structure, particularly if based on Pierre Bourdieu's relational approach to forms of capital, can be combined with the methodological rigour and established biological pathways of air pollution epidemiology. The aim is to reformulate environmental justice research in order to make further meaningful contributions to the wider movement concerned with issues of social justice and equity in health research.

Effect of exposure to traffic on lung development from 10 to 18 years of age: a cohort study

BACKGROUND

Whether local exposure to major roadways adversely affects lung-function growth during the period of rapid lung development that takes place between 10 and 18 years of age is unknown. This study investigated the association between residential exposure to traffic and 8-year lung-function growth.

METHODS

In this prospective study, 3677 children (mean age 10 years [SD 0.44]) participated from 12 southern California communities that represent a wide range in regional air quality. Children were followed up for 8 years, with yearly lung-function measurements recorded. For each child, we identified several indicators of residential exposure to traffic from large roads. Regression analysis was used to establish whether 8-year growth in lung function was associated with local traffic exposure, and whether local traffic effects were independent of regional air quality.

FINDINGS

Children who lived within 500 m of a freeway (motorway) had substantial deficits in 8-year growth of forced expiratory volume in 1 s (FEV(1), -81 mL, p=0.01 [95% CI -143 to -18]) and maximum midexpiratory flow rate (MMEF, -127 mL/s, p=0.03 [-243 to -11), compared with children who lived at least 1500 m from a freeway. Joint models showed that both local exposure to freeways and regional air pollution had detrimental, and independent, effects on lung-function growth. Pronounced deficits in attained lung function at age 18 years were recorded for those living within 500 m of a freeway, with mean percent-predicted 97.0% for FEV1 (p=0.013, relative to >1500 m [95% CI 94.6-99.4]) and 93.4% for MMEF (p=0.006 [95% CI 89.1-97.7]).

INTERPRETATION

Local exposure to traffic on a freeway has adverse effects on children's lung development, which are independent of regional air quality, and which could result in important deficits in attained lung function in later life.

A comparison of proximity and land use regression traffic exposure models and wheezing in infants

BACKGROUND

We previously reported an association between infant wheezing and residence < 100 m from stop-and-go bus and truck traffic. The use of a proximity model, however, may lead to exposure misclassification.

OBJECTIVE

Results obtained from a land use regression (LUR) model of exposure to truck and bus traffic are compared with those obtained with a proximity model. The estimates derived from the LUR model were then related to infant wheezing.

METHODS

We derived a marker of diesel combustion--elemental carbon attributable to traffic sources (ECAT)--from ambient monitoring results of particulate matter with aerodynamic diameter < 2.5 microm. We developed a multiple regression model with ECAT as the outcome variable. Variables included in the model were locations of major roads, bus routes, truck traffic count, and elevation. Model parameter estimates were applied to estimate individual ECAT levels at infants' homes.

RESULTS

The levels of estimated ECAT at the monitoring stations ranged from 0.20 to 1.02 microg/m(3). A LUR model of exposure with a coefficient of determination (R(2)) of 0.75 was applied to infants' homes. The mean (+/- SD) ambient exposure of ECAT for infants previously categorized as unexposed, exposed to stop-and-go traffic, or exposed to moving traffic was 0.32 +/- 0.06, 0.42 +/- 0.14, and 0.49 +/- 0.14 microg/m(3), respectively. Levels of ECAT from 0.30 to 0.90 mug/m(3) were significantly associated with infant wheezing.

CONCLUSIONS

The LUR model resulted in a range of ECAT individually derived for all infants' homes that may reduce the exposure misclassification that can arise from a proximity model.

Traffic intensity, dwelling value, and hospital admissions for respiratory disease among the elderly in Montreal (Canada): a case-control analysis

BACKGROUND

Persons exposed to residential traffic have increased rates of respiratory morbidity and mortality. As poverty is an important determinant of ill health, some have argued that these associations may relate to the lower socioeconomic status of those living along major roads.

AIMS

The objective was to evaluate the association between traffic intensity at home and hospital admissions for respiratory disease among Montreal residents of 60 years and older.

METHODS

Case hospitalisations were those with respiratory diagnoses and control hospitalisations were those where the primary discharge diagnosis was non-respiratory. Morning peak traffic estimates from the EMME/2 Montreal traffic model (MOTREM98) were used as an indicator of exposure to road traffic outside the homes of those hospitalised. The crude association between traffic intensity and hospitalisation for respiratory disease was adjusted by an area based estimate of the appraised value of patients' residences, expressed as a dollar average over a small segment of road (lodging value). This indicator of socioeconomic status, as calculated from the Montreal property assessment database, is available at a finer geographical scale than the neighbourhood socioeconomic indicators accessible from the Canadian census.

RESULTS

Increased odds of being hospitalised for a respiratory compared with a control diagnosis were associated with higher levels of estimated road traffic nearby patients' homes, even after adjustment for lodging value (crude OR 1.35, CI95% 1.22 to 1.49; adjusted OR 1.18, CI95% 1.06 to 1.31 for >3160 vehicles passing during the three hour morning traffic peak compared with secondary roads off network).

CONCLUSION

The results suggest that road traffic intensity itself, may affect the respiratory health of elderly residents of a large Canadian city, an association that is not solely a reflection of socioeconomic status.

Estimating the effect of air pollution from a coal-fired power station on the development of children's pulmonary function

Using geographical information systems (GIS) tools, the present study analyzed the association between children's lung function development and their long-term exposure to air pollution. The study covered the cohort of 1492 schoolchildren living in the vicinity of a major coal-fired power station in the Hadera sub-district of Israel. In 1996 and 1999, the children underwent subsequent pulmonary function tests (PFT) (forced vital capacity (FVC) and forced expiratory volume during the first second (FEV(1))), and the children's parents completed a detailed questionnaire on their health status and household characteristics. A negative association was found between changes in the results of PFT and the estimated individual levels of air pollution. A sensitivity test revealed a FEV(1) decline from -4.3% for the average pollution level to -10.2% for the high air pollution level. The results of a sensitivity test for FVC were found to be similar. Association with the reported health status was found to be insignificant. As we conclude, air pollution from a coal-fired power station, although not exceeding local pollution standards, had a negative effect on children's lung function development. As argued, previous studies carried out in the region failed to show the above association because they were based on zone approaches that assign average concentration levels of air pollutants to all individuals in each zone, leading to a misclassification bias of individual exposure.

A case-control analysis of exposure to traffic and acute myocardial infarction

BACKGROUND

Long-term exposure to particulate air pollution has been associated with an increased risk of dying from cardiopulmonary and ischemic heart disease, yet few studies have evaluated cardiovascular end points other than mortality. We investigated the relationship between long-term exposure to traffic and occurrence of acute myocardial infarction (AMI) in a case-control study.

METHODS

A total of 5,049 confirmed cases of AMI were identified between 1995 and 2003 as part of the Worcester Heart Attack Study, a community-wide study examining changes over time in the incidence of AMI among greater Worcester, Massachusetts, residents. Population controls were selected from Massachusetts resident lists. We used cumulative traffic within 100 m of subjects' residence and distance from major roadway as proxies for exposure to traffic-related air pollution. We estimated the relationship between exposure to traffic and occurrence of AMI using logistic regression, and we adjusted for the following potential confounders: age, sex, section of the study area, point sources emissions of particulate matter with aerodynamic diameter < 2.5 microm, area socioeconomic characteristics, and percentage of open space.

RESULTS

An increase in cumulative traffic near the home was associated with a 4% increase in the odds of AMI per interquartile range [95% confidence interval (CI), 2-7%], whereas living near a major roadway was associated with a 5% increase in the odds of AMI per kilometer (95% CI, 3-6%).

CONCLUSIONS

These results provide support for an association between long-term exposure to traffic and the risk of AMI.

Living near main streets and respiratory symptoms in adults: the Swiss Cohort Study on Air Pollution and Lung Diseases in Adults

The Swiss Cohort Study on Air Pollution and Lung Diseases in Adults (SAPALDIA), conducted in 1991 (SAPALDIA 1) in eight areas among 9,651 randomly selected adults aged 18-60 years, reported associations among the prevalence of respiratory symptoms, nitrogen dioxide, and particles with an aerodynamic diameter of less than 10 microg/m3. Later, 8,047 subjects reenrolled in 2002 (SAPALDIA 2). The effects of individually assigned traffic exposures on reported respiratory symptoms were estimated, while controlling for socioeconomic and exposure- and health-related factors. The risk of attacks of breathlessness increased for all subjects by 13% (95% confidence interval: 3, 24) per 500-m increment in the length of main street segments within 200 m of the home and decreased in never smokers by 12% (95% confidence interval: 0, 22) per 100-m increment in distance from home to a main street. Living within 20 m of a main street increased the risks of regular phlegm by 15% (95% confidence interval: 0, 31) and wheezing with breathing problems by 34% (95% confidence interval: 0, 79) in never smokers. In 2002, the effects related to road distance were different from those in 1991, which could be due to changes in the traffic pollution mixture. These findings among a general population provide strong confirmation that living near busy streets leads to adverse respiratory health effects.

New developments in exposure assessment: the impact on the practice of health risk assessment and epidemiological studies

The field of exposure assessment has matured significantly over the past 10-15 years. Dozens of studies have measured the concentrations of numerous chemicals in many media to which humans are exposed. Others have catalogued the various exposure pathways and identified typical values which can be used in the exposure calculations for the general population such as amount of water or soil ingested per day or the percent of a chemical than can pass through the skin. In addition, studies of the duration of exposure for many tasks (e.g. showering, jogging, working in the office) have been conducted which allow for more general descriptions of the likely range of exposures. All of this information, as well as the development of new and better models (e.g. air dispersion or groundwater models), allow for better estimates of exposure. In addition to identifying better exposure factors, and better mathematical models for predicting the aerial distribution of chemicals, the conduct of simulation studies and dose-reconstruction studies can offer extraordinary opportunities for filling in data gaps regarding historical exposures which are critical to improving the power of epidemiology studies. The use of probabilistic techniques such as Monte Carlo analysis and Bayesian statistics have revolutionized the practice of exposure assessment and has greatly enhanced the quality of the risk characterization. Lastly, the field of epidemiology is about to undergo a sea change with respect to the exposure component because each year better environmental and exposure models, statistical techniques and new biological monitoring techniques are being introduced. This paper reviews these techniques and discusses where additional research is likely to pay a significant dividend. Exposure assessment techniques are now available which can significantly improve the quality of epidemiology and health risk assessment studies and vastly improve their usefulness. As more quantitative exposure components can now be incorporated into these studies, they can be better used to identify safe levels of exposure using customary risk assessment methodologies. Examples are drawn from both environmental and occupational studies illustrating how these techniques have been used to better understand exposure to specific chemicals. Some thoughts are also presented on what lessons have been learned about conducting exposure assessment for health risk assessments and epidemiological studies.

Occupational exposure to diesel exhausts and risk for lung cancer in a population-based case–control study in Italy

BACKGROUND

We studied the effect of exposure to diesel exhausts on lung cancer risk in a population-based case-control study in the city of Turin, Italy.

PATIENTS AND METHODS

Information on occupational histories of 595 incident lung cancer cases diagnosed in 1991-1992 and 845 population controls was obtained. During the interviews, diesel job-specific modules (D-JSMs) were administered whenever subjects had worked in occupations included in the following nine categories: railroad workers, miners, professional drivers and transport conductors, heavy-machine operators, mechanics and testers, filling station attendants, motor-vehicle park attendants, transport equipment operators, and occupations carried out in/near urban roads. All D-JSMs were evaluated for probability, intensity and frequency of exposure.

RESULTS

The odds ratio for ever exposure to diesel exhausts was 1.04 (95% confidence interval 0.79-1.37), after adjusting for age, sex, smoking and having worked in occupations entailing exposure to known lung carcinogens. No association was found with intensity, probability and duration of exposure.

CONCLUSIONS

Although misclassification of the exposure may have contributed to the negative results, we did not find an association between occupational exposure to diesel exhausts and lung cancer risk.

Measurements of endotoxin on ambient loaded PM filters after long-term storage

At present there exist unsolved questions, whether endotoxin measurements on PM filters show valid measurements after long-term storage of loaded PM filters. As part of the TRAPCA study we collected particles with a 50% aerodynamic cut-off diameter of 2.5 microm (PM(2.5)) at 40 outdoor sites and particles less than 10 microm in size (PM(10)) at a subset of these sites (N=12) in Munich. The PM filters were cut in halves and endotoxin was measured in the extract of one filter half 2-3 years after PM collection. Here we present the results of repeated endotoxin measurements, where the association between previously measured endotoxin concentrations, measurements from stored eluates, and measurements in extracts of the second filter halves were determined. No statistically significant changes were seen between our old measurements and those from the stored eluates. Additionally, no change was observed between previously measured endotoxin concentrations and those from the stored set of filter halves. We found an average increase of 5% between our old measurements and those from the stored eluates and of 19% between the old measurements and those from the stored set of filter halves. The correlations between the previously measured endotoxin concentrations and the repeated measurements from the stored eluates were high (r=0.789) for EU/m(3) PM(2.5). Since endotoxin was evaluated from the same set of filter halves, it is obvious that storage over three years did not substantially effect the correlation of the endotoxin content. Regarding the outliers from previous measurements unsymmetric endotoxin spots on one out of 48 filter halves could be determined. Apart from this we conclude that the endotoxin is homogenously distributed on the filter halves and that endotoxin levels, which were repeatedly measured from filters stored over three years, could be determined validly.

Traffic-related air pollution and otitis media

BACKGROUND

Otitis media is one of the most common infections in young children. Although exposure to environmental tobacco smoke is a known risk factor associated with otitis media, little information is available regarding the potential association with air pollution.

OBJECTIVE

We set out to study the relationship between exposure to traffic-related air pollution and otitis media in two birth cohorts.

METHODS

Individual estimates of outdoor concentrations of traffic-related air pollutants-nitrogen dioxide, fine particles [particulate matter with aerodynamic diameters </= 2.5 microm (PM2.5)], and elemental carbon-were calculated for home addresses of approximately 3,700 and 650 infants from birth cohort studies in the Netherlands and Germany, respectively. Air pollution exposure was analyzed in relation to physician diagnosis of otitis media in the first 2 years of life.

RESULTS

Odds ratios (adjusted for known major risk factors) for otitis media indicated positive associations with traffic-related air pollutants. An increase in 3 microg/m3 PM2.5, 0.5 microg/m3 elemental carbon, and 10 microg/m3 NO2 was associated with odds ratios of 1.13 (95% confidence interval, 1.00-1.27) , 1.10 (1.00-1.22) , and 1.14 (1.03-1.27) in the Netherlands and 1.24 (0.84-1.83) , 1.10 (0.86-1.41) , and 1.14 (0.87-1.49) in Germany, respectively.

CONCLUSIONS

These findings indicate an association between exposure to traffic-related air pollutants and the incidence of otitis media. Given the ubiquitous nature of air pollution exposure and the importance of otitis media to children's health, these findings have significant public health implications.

Respiratory health and individual estimated exposure to traffic-related air pollutants in a cohort of young children

OBJECTIVES

To estimate long-term exposure to traffic-related air pollutants on an individual basis and to assess adverse health effects using a combination of air pollution measurement data, data from geographical information systems (GIS) and questionnaire data.

METHODS

40 measurement sites in the city of Munich, Germany were selected at which to collect particulate matter with a 50% cut-off aerodynamic diameter of 2.5 microm (PM2.5) and to measure PM2.5 absorbance and nitrogen dioxide (NO2). A pool of GIS variables (information about street length, household and population density and land use) was collected for the Munich metropolitan area and was used in multiple linear regression models to predict traffic-related air pollutants. These models were also applied to the birth addresses of two birth cohorts (German Infant Nutritional Intervention Study (GINI) and Influence of Life-style factors on the development of the Immune System and Allergies in East and West Germany (LISA)) in the Munich metropolitan area. Associations between air pollution concentrations at birth address and 1-year and 2-year incidences of respiratory symptoms were analysed.

RESULTS

The following means for the estimated exposures to PM2.5, PM2.5 absorbance and NO2 were obtained: 12.8 microg/m3, 1.7x10(-5) m(-1) and 35.3 mug/m3, respectively. Adjusted odds ratios (ORs) for wheezing, cough without infection, dry cough at night, bronchial asthma, bronchitis and respiratory infections indicated positive associations with traffic-related air pollutants. After controlling for individual confounders, significant associations were found between the pollutant PM2.5 and sneezing, runny/stuffed nose during the first year of life (OR 1.16, 95% confidence interval 1.01 to 1.34) Similar effects were observed for the second year of life. These findings are similar to those from our previous analysis that were restricted to a subcohort in Munich city. The extended study also showed significant effects for sneezing, running/stuffed nose. Additionally, significant associations were found between NO2 and dry cough at night (or bronchitis) during the first year of life. The variable "living close to major roads" (<50 m), which was not analysed for the previous inner city cohort with birth addresses in the city of Munich, turned out to increase the risk of wheezing and asthmatic/spastic/obstructive bronchitis.

CONCLUSIONS

Effects on asthma and hay fever are subject to confirmation at older ages, when these outcomes can be more validly assessed.

Chronic bronchitis and urban air pollution in an international study

OBJECTIVES

The chronic effects of urban air pollution are not well known. The authors' aim was to investigate the association between the prevalence and new onset of chronic bronchitis and urban air pollution.

METHODS

Subjects from the general population randomly selected for the European Community Respiratory Health Survey (ECRHS I) during 1991-93 in 21 centres in 10 countries were followed up from the years 2000 to 2002 (n = 3232 males and 3592 females; average response rate = 65.3%). PM2.5 and elements, with the same equipment at centre level, and home outdoor NO2 in 1634 individuals were measured. Hierarchical models were used.

RESULTS

The prevalence and new onset of chronic phlegm during follow up were 6.9% and 4.5%, respectively, 5.3% in males and 3.5% in females. Smoking, rhinitis, poor education, and low social class were associated with (prevalence and new onset of) chronic phlegm in both genders, and occupational exposures in males and traffic intensity (adjusted odds ratio for constant traffic, OR = 1.86; 95% CI 1.24 to 2.77) as well as home outdoor NO2 (OR > 50 microg/m3v < 20 microg3 = 2.71; 95% CI 1.03 to 7.16) among females. PM2.5 and S content at centre level did not show any association with prevalence or new onset of chronic phlegm. Similar results were obtained with chronic productive cough.

CONCLUSION

Individual markers of traffic at household level such as reported intensity and outdoor NO2 were risk factors for chronic bronchitis among females.

Bayesian modeling of air pollution health effects with missing exposure data

The authors propose a new statistical procedure that utilizes measurement error models to estimate missing exposure data in health effects assessment. The method detailed in this paper follows a Bayesian framework that allows estimation of various parameters of the model in the presence of missing covariates in an informative way. The authors apply this methodology to study the effect of household-level long-term air pollution exposures on lung function for subjects from the Southern California Children's Health Study pilot project, conducted in the year 2000. Specifically, they propose techniques to examine the long-term effects of nitrogen dioxide (NO2) exposure on children's lung function for persons living in 11 southern California communities. The effect of nitrogen dioxide exposure on various measures of lung function was examined, but, similar to many air pollution studies, no completely accurate measure of household-level long-term nitrogen dioxide exposure was available. Rather, community-level nitrogen dioxide was measured continuously over many years, but household-level nitrogen dioxide exposure was measured only during two 2-week periods, one period in the summer and one period in the winter. From these incomplete measures, long-term nitrogen dioxide exposure and its effect on health must be inferred. Results show that the method improves estimates when compared with standard frequentist approaches.

Think globally, breathe locally

Why the worldwide health impact of air pollution on young children begins in our neighbourhoods

Locally generated particulate pollution and respiratory symptoms in young children

BACKGROUND

Particulate matter <10 mum (PM(10)) from fossil fuel combustion is associated with an increased prevalence of respiratory symptoms in children and adolescents. However, the effect of PM(10) on respiratory symptoms in young children is unclear.

METHODS

The association between primary PM(10) (particles directly emitted from local sources) and the prevalence and incidence of respiratory symptoms was studied in a random sample cohort of 4400 Leicestershire children aged 1-5 years surveyed in 1998 and again in 2001. Annual exposure to primary PM(10) was calculated for the home address using the Airviro dispersion model and adjusted odds ratios (ORS) and 95% confidence intervals were calculated for each microg/m(3) increase.

RESULTS

Exposure to primary PM(10) was associated with the prevalence of cough without a cold in both 1998 and 2001, with adjusted ORs of 1.21 (1.07 to 1.38) and 1.56 (1.32 to 1.84) respectively. For night time cough the ORs were 1.06 (0.94 to 1.19) and 1.25 (1.06 to 1.47), and for current wheeze 0.99 (0.88 to 1.12) and 1.28 (1.04 to 1.58), respectively. There was also an association between primary PM(10) and new onset symptoms. The ORs for incident symptoms were 1.62 (1.31 to 2.00) for cough without a cold and 1.42 (1.02 to 1.97) for wheeze.

CONCLUSION

In young children there was a consistent association between locally generated primary PM(10) and the prevalence and incidence of cough without a cold and the incidence of wheeze which was independent of potential confounders.

A review of traffic-related air pollution exposure assessment studies in the developing world

Exposure assessment studies in the developing world are important. Although recent years have seen an increasing number of traffic-related pollution exposure studies, exposure assessment data on this topic are still limited. Differences among measuring methods and a lack of strict quality control in carrying out exposure assessment make it difficult to generalize and compare findings between studies. In this article, exposure assessment studies carried out in the developing world on several traffic-related air pollutants are reviewed. These pollutants include particulate matter (PM), carbon monoxide (CO), nitrogen dioxide (NO(2)), volatile organic compounds (VOCs), and polycyclic aromatic hydrocarbons (PAHs). In addition, it discusses advantages and disadvantages of various monitoring methods (ambient fixed-site monitoring, microenvironment monitoring, and personal exposure assessment using portable samplers) for these pollutants in exposure assessment studies. Also included in this paper is a brief introduction of standards for these pollutants in ambient air or in occupational settings established by the United States Environmental Protection Agency (USEPA), the United States Occupational Safety and Health Administration (OSHA) and the World Health Organization (WHO). The review ends with a summary of the limitations and gaps in recent studies and suggestions for future research in the developing world.

Opportunities for using spatial property assessment data in air pollution exposure assessments

BACKGROUND

Many epidemiological studies examining the relationships between adverse health outcomes and exposure to air pollutants use ambient air pollution measurements as a proxy for personal exposure levels. When pollution levels vary at neighbourhood levels, using ambient pollution data from sparsely located fixed monitors may inadequately capture the spatial variation in ambient pollution. A major constraint to moving toward exposure assessments and epidemiological studies of air pollution at a neighbourhood level is the lack of readily available data at appropriate spatial resolutions. Spatial property assessment data are widely available in North America and may provide an opportunity for developing neighbourhood level air pollution exposure assessments.

RESULTS

This paper provides a detailed description of spatial property assessment data available in the Pacific Northwest of Canada and the United States, and provides examples of potential applications of spatial property assessment data for improving air pollution exposure assessment at the neighbourhood scale, including: (1) creating variables for use in land use regression modelling of neighbourhood levels of ambient air pollution; (2) enhancing wood smoke exposure estimates by mapping fireplace locations; and (3) using data available on individual building characteristics to produce a regional air pollution infiltration model.

CONCLUSION

Spatial property assessment data are an extremely detailed data source at a fine spatial resolution, and therefore a source of information that could improve the quality and spatial resolution of current air pollution exposure assessments.

Exposure to traffic related air pollutants: self reported traffic intensity versus GIS modelled exposure

BACKGROUND

In epidemiological studies of the potential health effects of traffic related air pollution, self reported traffic intensity is a commonly used, but rarely validated, exposure variable.

METHODS

As part of a study on the impact of Traffic Related Air Pollution on Childhood Asthma (TRAPCA), data from 2633 and 673 infants from the Dutch and the German-Munich cohorts, respectively, were available. Parents subjectively assessed traffic intensity at the home address. Objective exposures were estimated by a combination of spatial air pollution measurements and geographic information system (GIS) based modelling using an identical method for both cohorts.

RESULTS

The agreement rates between self reported and GIS modelled exposure--accumulated over the three strata of self assessed traffic intensity--were 55-58% for PM(2.5), filter absorbance (PM(2.5) abs), and nitrogen dioxide in Munich and 39-40% in the Netherlands. Of the self reported low traffic exposed group, 71-73% in Munich and 45-47% in the Netherlands had low modelled exposure to these three air pollutants. Of the self assessed high exposed subgroups in Munich (15% of the total population) and the Netherlands (22% of the total population), only 22-33% and 30-32% respectively had high modelled exposure to the three air pollutants. The subjective assessments tend to overestimate the modelled estimates for PM(2.5) and NO2 in both study areas. When analysis was restricted to the portion of the Dutch cohort living in non-urban areas, the agreement rates were even lower.

CONCLUSIONS

Self reported and modelled assessment of exposure to air pollutants are only weakly associated.

GIS-based estimation of exposure to particulate matter and NO2 in an urban area: stochastic versus dispersion modeling

Stochastic modeling was used to predict nitrogen dioxide and fine particles [particles collected with an upper 50% cut point of 2.5 microm aerodynamic diameter (PM2.5)] levels at 1,669 addresses of the participants of two ongoing birth cohort studies conducted in Munich, Germany. Alternatively, the Gaussian multisource dispersion model IMMIS(net/em) was used to estimate the annual mean values for NO2 and total suspended particles (TSP) for the 40 measurement sites and for all study subjects. The aim of this study was to compare the measured NO2 and PM2.5 levels with the levels predicted by the two modeling approaches (for the 40 measurement sites) and to compare the results of the stochastic and dispersion modeling for all study infants (1,669 sites). NO2 and PM2.5 concentrations obtained by the stochastic models were in the same range as the measured concentrations, whereas the NO2 and TSP levels estimated by dispersion modeling were higher than the measured values. However, the correlation between stochastic- and dispersion-modeled concentrations was strong for both pollutants: At the 40 measurement sites, for NO2, r = 0.83, and for PM, r = 0.79; at the 1,669 cohort sites, for NO2, r = 0.83 and for PM, r = 0.79. Both models yield similar results regarding exposure estimate of the study cohort to traffic-related air pollution, when classified into tertiles; that is, 70% of the study subjects were classified into the same category. In conclusion, despite different assumptions and procedures used for the stochastic and dispersion modeling, both models yield similar results regarding exposure estimation of the study cohort to traffic-related air pollutants.

Characterization of a spatial gradient of nitrogen dioxide across a United States-Mexico border city during winter

A gradient of ambient nitrogen dioxide (NO(2)) concentration is demonstrated across metropolitan El Paso, Texas (USA), a city located on the international border between the United States and Mexico. Integrated measurements of NO(2) were collected over 7 days at 20 elementary schools and 4 air quality monitoring stations located throughout the city during typical winter atmospheric conditions. Replicate passive monitors were co-located with chemiluminescence analyzers at the monitoring stations for two consecutive 7-day periods. The passive measurements correlated with the analyzer measurements (R(2)=0.74) with precision of 2.5+/-2.2 ppb. Nitrogen dioxide concentrations ranged from 11.0 to 37.5 ppb (mean 20.6+/-7.1 ppb). In a multivariate regression model, the site elevation and distances to a main highway and to an international port of entry from Mexico explained 81% of the variance in the passive measurements. The results of this pilot study indicate that proximity to vehicle-related sources of NO(2) and site elevation are key predictors for future, more detailed assessments of vehicle-related air pollution exposure in the El Paso region.

Spatial variation in nitrogen dioxide in three European areas

In order to estimate the spatial variation within well-defined study areas, nitrogen dioxide was measured with diffusion samplers (Palmes tube) in 40-42 sites each in Germany (Munich), the Netherlands and Sweden (Stockholm County). Each site was measured over four 2-week periods during 1 year (spring 1999 to summer 2000). In each country, one reference site was measured during all periods and the results were used to adjust for seasonal variability, to improve the estimates of the annual average. Comparisons between the chemiluminescence method (European reference method) and Palmes tube measurement indicated a good agreement in Germany (with a ratio of 1.0 for Palmes tube/chemiluminescence) but underestimation for Palmes tube measurement in the Netherlands and Sweden (0.8 for both countries). The r2 values were between 0.86 and 0.90 for all three countries. The annual average values for NO2 for different sampling sites were between 15.9 and 50.6 (mean 28.8 microg/m3) in Germany, between 12.1 and 50.8 (mean 28.9 microg/m3) in the Netherlands and between 6.1 and 44.7 (mean 18.5 microg/m3) in Sweden. Comparing spatial variation between similar sites in the three countries, we did not find any significant differences between annual average levels for urban traffic sites. In Sweden, annual average levels in urban background and suburban backgrounds sites were about 8 microg/m3 lower than comparable sites in Germany and the Netherlands. Comparing site types within each country only urban traffic sites and suburban background sites differed in Germany. In the Netherlands and Sweden, the urban traffic sites differed from all other sites and in Sweden also the urban background sites differed from the other background sites. The observed contribution from local traffic was similar in the Netherlands and Sweden (10 and 8 microg/m3, corresponding to 26-27% of the NO2 concentration found in the urban traffic sites). In Germany, the contribution from local traffic was only 3 microg/m3, corresponding to 9% of the NO2 concentration found in the urban traffic sites. The spatial variation was substantially larger for NO2 than the variation for PM2.5 and similar to PM2.5 absorbance, measured in the same locations.

Traffic-related air pollution near busy roads: the East Bay Children's Respiratory Health Study

Recent studies, primarily in Europe, have reported associations between respiratory symptoms and residential proximity to traffic; however, few have measured traffic pollutants or provided information about local air quality. We conducted a school-based, cross-sectional study in the San Francisco Bay Area in 2001. Information on current bronchitis symptoms and asthma, home environment, and demographics was obtained by parental questionnaire (n = 1,109). Concentrations of traffic pollutants (particulate matter, black carbon, total nitrogen oxides [NO(X)], and nitrogen dioxide [NO(2)]) were measured at 10 school sites during several seasons. Although pollutant concentrations were relatively low, we observed differences in concentrations between schools nearby versus those more distant (or upwind) from major roads. Using a two-stage multiple-logistic regression model, we found associations between respiratory symptoms and traffic-related pollutants. Among those living at their current residence for at least 1 year, the adjusted odds ratio for asthma in relationship to an interquartile difference in NO(X) was 1.07 (95% confidence interval, 1.00-1.14). Thus, we found spatial variability in traffic pollutants and associated differences in respiratory symptoms in a region with good air quality. Our findings support the hypothesis that traffic-related pollution is associated with respiratory symptoms in children.

Évaluation de l’exposition à la pollution atmosphérique liée au trafic routier dans les études épidémiologiques : une revue de littérature

BACKGROUND

Automobile exhaust is a major source of air pollution in urban areas. To study health effects of traffic exhaust fumes epidemiologists need specific tools in order to achieve a precise assessment of human exposure to traffic air pollution (TAP) and avoid misclassification. The aim of this review is to study the different ways of assessing human exposure to TAP in epidemiological studies dealing with short-term or long-term health effects of TAP.

METHODS

After presenting the different designs and goals of the studies mentioned above, this review focuses on methods of assessing exposure to TAP and their different associated health endpoints.

RESULTS

To assess exposure to TAP, most published studies have used more or less complex exposure indices. Several teams have used residence location and its proximity to traffic, traffic counts, or a combination of both. More recently, some authors have developed mathematical dispersion models and statistical regression models.

DISCUSSION

Our analysis shows that reliable and validated tools would be needed to assess accurately human exposure to TAP. This can only be achieved with statistical regression models and mathematical dispersion models. Although such methods may be difficult to implement, their use can be facilitated by adding a geographic information system.

Health and environment information systems for exposure and disease mapping, and risk assessment

A large number of chemicals are used on a regular basis in modern society. Thousands of new chemicals are added each year, many of which may have toxic properties constituting potential health hazards. Rapid assessment of the risk associated with the use of these chemicals is therefore essential to protect people from exposure to potentially harmful substances. Exposures to chemicals (and physical agents) are typically unevenly distributed geographically as well as temporally. Disease occurrence also shows geographically varying patterns. Geographic information systems (GIS) may be used to produce maps of exposure and/or disease to reveal spatial patterns. Exposure mapping using advanced GIS modeling may enhance exposure assessment in environmental epidemiology studies. Disease maps can be valuable tools in risk assessment to explore changes in disease patterns potentially associated with changes in environmental exposures. Spatial variations in risk and trends related to distance from pollution sources may be studied using software tools such as the Rapid Inquiry Facility, developed by the U.K. Small Area Health Statistics Unit and enhanced in the European Health and Environment Information System project, for an initial quick evaluation of any potential health hazards associated with an environmental pollutant.