Case-control study of hospital admission with asthma in children aged 5-14 years: relation with road traffic in north west London

The Use of Geographic Data to Improve Asthma Care Delivery and Population Health

The authors examine uses of geographic data to improve asthma care delivery and population health and describe potential practice changes and areas for future research.

Spatial variation in nitrogen dioxide concentrations and cardiopulmonary hospital admissions

BACKGROUND

Air pollution episodes are associated with increased cardiopulmonary hospital admissions. Cohort studies showed associations of spatial variation in traffic-related air pollution with respiratory and cardiovascular mortality. Much less is known in particular about associations with cardiovascular morbidity. We explored the relation between spatial variation in nitrogen dioxide (NO₂) concentrations and cardiopulmonary hospital admissions.

METHODS

This ecological study was based on hospital admissions data (2001-2004) from the National Medical Registration and general population data for the West of the Netherlands (population 4.04 million). At the 4-digit postcode area level (n=683) associations between modeled annual average outdoor NO₂ concentrations and hospital admissions for respiratory and cardiovascular causes were evaluated by linear regression with the log of the postcode-specific percentage of subjects that have been admitted at least once during the study period as the dependent variable. All analyses were adjusted for differences in composition of the population of the postcode areas (age, sex, income).

RESULTS

At the postcode level, positive associations were found between outdoor NO₂ concentrations and hospital admission rates for asthma, chronic obstructive pulmonary disease (COPD), all cardiovascular causes, ischemic heart disease and stroke (e.g. adjusted relative risk (95% confidence interval) for the second to fourth quartile relative to the first quartile of exposure were 1.87 (1.46-2.40), 2.34 (1.83-3.01) and 2.81 (2.16-3.65) for asthma; 1.44 (1.19-1.74), 1.50 (1.24-1.82) and 1.60 (1.31-1.96) for COPD). Associations remained after additional (indirect) adjustment for smoking (COPD admission rate) and degree of urbanization.

CONCLUSIONS

Our study suggests an increased risk of hospitalization for respiratory and cardiovascular causes in areas with higher levels of NO₂. Our findings add to the currently limited evidence of a long-term effect of air pollution on hospitalization. The ecological design of our study is a limitation and more studies with individual data are needed to confirm our findings.

Mapping air pollution by biological monitoring in the metropolitan Tel Aviv area

Conventional environmental monitoring is not surrogate of personal exposure. In contrast, biomonitoring provides information on the presence of substances in the human body, making it highly relevant to the assessment of exposure to toxic substances. Induced sputum (IS) is a noninvasive technique for detecting inflammation and reflecting particulate matter content in the airways. In this study, we mapped particulate matter dispersion in metropolitan Tel Aviv by both biomonitoring techniques employing IS samples and by environmental monitoring. All adults referred to the Pulmonary Lab for respiratory symptom evaluation in 2007 and in 2009 were enrolled. Pulmonary function tests were performed by conventional methods. Particulate size distribution in IS was analyzed, and maps of air pollution were created. Biomonitoring was more informative and enabled mapping of wider areas. Integration of biomonitoring and environmental monitoring should be considered in forming public health policy on containment of airborne particles of toxic substances.

Environment and Health in Children Day Care Centres (ENVIRH) - Study rationale and protocol

BACKGROUND

Indoor air quality (IAQ) is considered an important determinant of human health. The association between exposure to volatile organic compounds, particulate matter, house dust mite, molds and bacteria in day care centers (DCC) is not completely clear. The aim of this project was to study these effects.

METHODS – STUDY DESIGN

This study comprised two phases. Phase I included an evaluation of 45 DCCs (25 from Lisbon and 20 from Oporto, targeting 5161 children). In this phase, building characteristics, indoor CO2 and air temperature/relative humidity, were assessed. A children's respiratory health questionnaire derived from the ISAAC (International Study on Asthma and Allergies in Children) was also distributed. Phase II encompassed two evaluations and included 20 DCCs selected from phase I after a cluster analysis (11 from Lisbon and 9 from Oporto, targeting 2287 children). In this phase, data on ventilation, IAQ, thermal comfort parameters, respiratory and allergic health, airway inflammation biomarkers, respiratory virus infection patterns and parental and child stress were collected.

RESULTS

In Phase I, building characteristics, occupant behavior and ventilation surrogates were collected from all DCCs. The response rate of the questionnaire was 61.7% (3186 children).Phase II included 1221 children. Association results between DCC characteristics, IAQ and health outcomes will be provided in order to support recommendations on IAQ and children's health. A building ventilation model will also be developed.

DISCUSSION

This paper outlines methods that might be implemented by other investigators conducting studies on the association between respiratory health and indoor air quality at DCC.

Environment and Health in Children Day Care Centres (ENVIRH) - Study rationale and protocol

BACKGROUND

Indoor air quality (IAQ) is considered an important determinant of human health. The association between exposure to volatile organic compounds, particulate matter, house dust mite, molds and bacteria in day care centers (DCC) is not completely clear. The aim of this project was to study these effects.

METHODS - STUDY DESIGN

This study comprised two phases. Phase I included an evaluation of 45 DCCs (25 from Lisbon and 20 from Oporto, targeting 5161 children). In this phase, building characteristics, indoor CO2 and air temperature/relative humidity, were assessed. A children's respiratory health questionnaire derived from the ISAAC (International Study on Asthma and Allergies in Children) was also distributed. Phase II encompassed two evaluations and included 20 DCCs selected from phase I after a cluster analysis (11 from Lisbon and 9 from Oporto, targeting 2287 children). In this phase, data on ventilation, IAQ, thermal comfort parameters, respiratory and allergic health, airway inflammation biomarkers, respiratory virus infection patterns and parental and child stress were collected.

RESULTS

In Phase I, building characteristics, occupant behavior and ventilation surrogates were collected from all DCCs. The response rate of the questionnaire was 61.7% (3186 children). Phase II included 1221 children. Association results between DCC characteristics, IAQ and health outcomes will be provided in order to support recommendations on IAQ and children's health. A building ventilation model will also be developed.

DISCUSSION

This paper outlines methods that might be implemented by other investigators conducting studies on the association between respiratory health and indoor air quality at DCC.

Truck traffic related air pollution associated with asthma symptoms in young boys: a cross-sectional study

OBJECTIVES

The aim of this study was to evaluate the influence of intensity of truck traffic on asthma symptomatology, and its relationship with age and gender.

STUDY DESIGN

A cross-sectional study was conducted on children and adolescents from Galicia (North-West Spain).

METHODS

Following the methodology of the International Study of Asthma and Allergies in Childhood (ISAAC): children from schools randomly selected, answered a self-administered questionnaire included questions on asthma symptoms and some risk factors. The association between self-reported truck traffic on the street of residence and symptoms of asthma were investigated by logistic regression adjusted for body mass index, maternal education and parental smoking.

RESULTS

Almost 40% of children in Galicia are exposed to the frequent and constant passing of heavy goods vehicles. The odds of 6-7 year-old boys having severe or exercise induced asthma is tripled when they live in streets with the constant passing of heavy goods vehicles, compared with those living in streets where these vehicles never pass. In adolescents and 6-7 year-old girls, no relationship was observed between truck traffic and asthma symptoms.

CONCLUSIONS

The results of this study appear to support a distinct effect of truck traffic on asthma symptoms depending on the age and sex of the exposed population, being more harmful for young males.

Influence of outdoor NO2 exposure on asthma in childhood: meta-analysis

BACKGROUND

It has long been assumed that the development of childhood asthma is related to exposure to environmental chemicals, but it has thus far not been possible to unequivocally establish this suspected relationship using individual studies. Moreover, studies of children have been scanty and unreliable due to the large diversity of research environments and subject cohorts. The aim of the current study was to clarify this relationship for one factor by means of a meta-analysis of studies investigating the influence of NO(2) exposure on symptomatology of childhood asthma.

METHODS

Two electronic databases (MEDLINE and EMBASE) were searched for literature on relationships between environmental chemical exposure and development of childhood asthma using the MeSH terms 'nitrogen dioxide' and 'asthma'. This was done according to the MOOSE guidelines for meta-analyses of observational studies.

RESULTS

A total of 130 papers were retrieved, of which 12 met the selection criteria. These papers described observational studies from seven countries. Study subjects were 97,932 ordinary children aged 0-18 years. Using random model analysis, the odds ratio (OR) for asthma development due to an increment of 10 p.p.b. NO(2) was 1.135 with a 95% confidence interval [CI] of 1.031-1.251 (P= 0.01), while the OR for wheezing symptoms was 1.052 with a 95%CI of 1.020-1.085 (P= 0.001). It is therefore evident that NO(2) exposure does influence the development of asthma in ordinary children.

CONCLUSIONS

Exposure to NO(2) in the air significantly influences the development of childhood asthma and symptoms of wheezing.

Residential proximity to environmental hazards and adverse health outcomes

How living near environmental hazards contributes to poorer health and disproportionate health outcomes is an ongoing concern. We conducted a substantive review and critique of the literature regarding residential proximity to environmental hazards and adverse pregnancy outcomes, childhood cancer, cardiovascular and respiratory illnesses, end-stage renal disease, and diabetes. Several studies have found that living near hazardous wastes sites, industrial sites, cropland with pesticide applications, highly trafficked roads, nuclear power plants, and gas stations or repair shops is related to an increased risk of adverse health outcomes. Government agencies should consider these findings in establishing rules and permitting and enforcement procedures to reduce pollution from environmentally burdensome facilities and land uses.

Air toxics exposure from vehicle emissions at a U.S. border crossing: Buffalo Peace Bridge Study

The Peace Bridge in Buffalo, New York, which spans the Niagara River at the east end of Lake Erie, is one of the busiest U.S. border crossings. The Peace Bridge plaza on the U.S. side is a complex of roads, customs inspection areas, passport control areas, and duty-free shops. On average 5000 heavy-duty diesel trucks and 20,000 passenger cars traverse the border daily, making the plaza area a potential "hot spot" for emissions from mobile sources. In a series of winter and summer field campaigns, we measured air pollutants, including many compounds considered by the U.S. Environmental Protection Agency (EPA*) as mobile-source air toxics (MSATs), at three fixed sampling sites: on the shore of Lake Erie, approximately 500 m upwind (under predominant wind conditions) of the Peace Bridge plaza; immediately downwind of (adjacent to) the plaza; and 500 m farther downwind, into the community of west Buffalo. Pollutants sampled were particulate matter (PM) < or = 10 microm (PM10) and < or = 2.5 microm (PM2.5) in aerodynamic diameter, elemental carbon (EC), 28 elements, 25 volatile organic compounds (VOCs) including 3 carbonyls, 52 polycyclic aromatic hydrocarbons (PAHs), and 29 nitrogenated polycyclic aromatic hydrocarbons (NPAHs). Spatial patterns of counts of ultrafine particles (UFPs, particles < 0.1 microm in aerodynamic diameter) and of particle-bound PAH (pPAH) concentrations were assessed by mobile monitoring in the neighborhood adjacent to the Peace Bridge plaza using portable instruments and Global Positioning System (GPS) tracking. The study was designed to assess differences in upwind and downwind concentrations of MSATs, in areas near the Peace Bridge plaza on the U.S. side of the border. The Buffalo Peace Bridge Study featured good access to monitoring locations proximate to the plaza and in the community, which are downwind with the dominant winds from the direction of Lake Erie and southern Ontario. Samples from the lakeside Great Lakes Center (GLC), which is upwind of the plaza with dominant winds, were used to characterize contaminants in regional air masses. On-site meteorologic measurements and hourly truck and car counts were used to assess the role of traffic on UFP counts and pPAH concentrations. The array of parallel and perpendicular residential streets adjacent to the plaza provided a grid on which to plot the spatial patterns of UFP counts and pPAH concentrations to determine the extent to which traffic emissions from the Peace Bridge plaza might extend into the neighboring community. For lake-wind conditions (southwest to northwest) 12-hour integrated daytime samples showed clear evidence that vehicle-related emissions at the Peace Bridge plaza were responsible for elevated downwind concentrations of PM2.5, EC, and benzene, toluene, ethylbenzene, and xylenes (BTEX), as well as 1,3-butadiene and styrene. The chlorinated VOCs and aldehydes were not differentially higher at the downwind site. Several metals (aluminum, calcium, iron, copper, and antimony) were two times higher at the site adjacent to the plaza as they were at the upwind GLC site on lake-wind sampling days. Other metals (beryllium, sodium, magnesium, potassium, titanium, manganese, cobalt, strontium, tin, cesium, and lanthanum) showed significant increases downwind as well. Sulfur, arsenic, selenium, and a few other elements appeared to be markers for regional transport as their upwind and downwind concentrations were correlated, with ratios near unity. Using positive matrix factorization (PMF), we identified the sources for PAHs at the three fixed sampling sites as regional, diesel, general vehicle, and asphalt volatilization. Diesel exhaust at the Peace Bridge plaza accounted for approximately 30% of the PAHs. The NPAH sources were identified as nitrate (NO3) radical reactions, diesel, and mixed sources. Diesel exhaust at the Peace Bridge plaza accounted for 18% of the NPAHs. Further evidence for the impact of the Peace Bridge plaza on local air quality was found when the differences in 10-minute average UFP counts and pPAH concentrations were calculated between pairs of sites and displayed by wind direction. With winds from approximately 160 degrees through 220 degrees, UFP counts adjacent to the plaza were 10,000 to 20,000 particles/cm3 higher than those upwind of the plaza. A similar pattern was displayed for pPAH concentrations adjacent to the plaza, which were between 10 and 20 ng/m3 higher than those at the upwind GLC site. Regression models showed better correlation with traffic variables for pPAHs than for UFPs. For pPAHs, truck counts and car counts had significant positive correlations, with similar magnitudes for the effects of trucks and cars, despite lower truck counts. Examining all traffic variables, including traffic counts and counts divided by wind speed, the multivariate regression analysis had an adjusted coefficient of determination (R2) of 0.34 for pPAHs, with all terms significant at P < 0.002. Study staff members traversed established routes in the neighborhood while carrying instruments to record continuous UFP and pPAH values. They also carried a GPS, which was used to provide location-specific time-stamped data. Analyses using a geographic information system (GIS) demonstrated that emissions at the Peace Bridge plaza, at times, affected ambient air quality over several blocks (a few hundred meters). Under lake-wind conditions, overall spatial patterns in UFP and pPAH levels were similar for summer and winter and for morning and afternoon sampling sessions. The Buffalo Peace Bridge Study demonstrated that a concentration of motor vehicles resulted in elevated levels of mobile-source-related emissions downwind, to distances of 300 m to 600 m. The study provides a unique data set to assess interrelationships among MSATs and to ascertain the impact of heavy-duty diesel vehicles on air quality.

Use of a total traffic count metric to investigate the impact of roadways on asthma severity: a case-control study

BACKGROUND

This study had two principal objectives: (i) to investigate the relationship between asthma severity and proximity to major roadways in Perth, Western Australia; (ii) to demonstrate a more accurate method of exposure assessment for traffic pollutants using an innovative GIS-based measure that fully integrates all traffic densities around subject residences.

METHODS

We conducted a spatial case-control study, in which 'cases' were defined as individuals aged under 19 years of age with more severe asthma (defined here as two or more emergency department contacts with asthma in a defined 5-year period) versus age- and gender-matched 'controls' with less severe asthma (defined here as one emergency department contact for asthma). Traffic exposures were measured using a GIS-based approach to determine the lengths of the roads falling within a buffer area, and then multiplying them by their respective traffic counts.

RESULTS

We examined the spatial relationship between emergency department contacts for asthma at three different buffer sizes: 50 metres, 100 metres and 150 metres. No effect was noted for the 50 metre buffer (OR = 1.07; 95% CI: 0.91-1.26), but elevated odds ratios were observed with for crude (unadjusted) estimates OR = 1.21 (95% CI: 1.00-1.46) for 100 metre buffers and OR = 1.25 (95% CI: 1.02-1.54) for 150 metre buffers. For adjusted risk estimates, only the 150 metre buffer yielded a statistically significant finding (OR = 1.24; 95% CI:1.00-1.52).

CONCLUSIONS

Our study revealed a significant 24% increase in the risk of experiencing multiple emergency department contacts for asthma for every log-unit of traffic exposure. This study provides support for the hypothesis that traffic related air pollution increases the frequency of health service contacts for asthma. This study used advanced GIS techniques to establish traffic-weighted buffer zones around the geocoded residential location of subjects to provide an accurate assessment of exposure to traffic emissions, thereby providing a quantification of the ranges over which pollutants may exert a health effect.

Asthma exacerbation and proximity of residence to major roads: a population-based matched case-control study among the pediatric Medicaid population in Detroit, Michigan

BACKGROUND

The relationship between asthma and traffic-related pollutants has received considerable attention. The use of individual-level exposure measures, such as residence location or proximity to emission sources, may avoid ecological biases.

METHOD

This study focused on the pediatric Medicaid population in Detroit, MI, a high-risk population for asthma-related events. A population-based matched case-control analysis was used to investigate associations between acute asthma outcomes and proximity of residence to major roads, including freeways. Asthma cases were identified as all children who made at least one asthma claim, including inpatient and emergency department visits, during the three-year study period, 2004-06. Individually matched controls were randomly selected from the rest of the Medicaid population on the basis of non-respiratory related illness. We used conditional logistic regression with distance as both categorical and continuous variables, and examined non-linear relationships with distance using polynomial splines. The conditional logistic regression models were then extended by considering multiple asthma states (based on the frequency of acute asthma outcomes) using polychotomous conditional logistic regression.

RESULTS

Asthma events were associated with proximity to primary roads with an odds ratio of 0.97 (95% CI: 0.94, 0.99) for a 1 km increase in distance using conditional logistic regression, implying that asthma events are less likely as the distance between the residence and a primary road increases. Similar relationships and effect sizes were found using polychotomous conditional logistic regression. Another plausible exposure metric, a reduced form response surface model that represents atmospheric dispersion of pollutants from roads, was not associated under that exposure model.

CONCLUSIONS

There is moderately strong evidence of elevated risk of asthma close to major roads based on the results obtained in this population-based matched case-control study.

Traffic exposure and incident venous thromboembolism in the Atherosclerosis Risk in Communities (ARIC) Study

BACKGROUND

Two recent case-control studies in Italy reported that long-term exposure to particulate air pollution or living near major traffic roads was associated with an increased risk of deep vein thrombosis (DVT). No prospective evidence exists on the possible association between long-term traffic-related air pollution and incident venous thromboembolism (VTE).

OBJECTIVES

To examine the association between long-term traffic exposure and incident VTE in a population-based prospective cohort study.

METHODS

We studied 13,143 middle-aged men and women in the Atherosclerosis Risk in Communities Study without a history of DVT or pulmonary embolism at baseline examination (1987-1989). The Geographical Information System-mapped traffic density and distance to major roads in the four study communities served as measures of traffic exposure. We examined the association between traffic exposure and incident VTE with proportional hazards regression models.

RESULTS

A total of 405 subjects developed VTE in 2005. Traffic density was not significantly associated with VTE. Relative to those in the lowest quartile of traffic density, the adjusted hazard ratios across increasing quartiles were 1.18 (95% confidence interval [CI] 0.88-1.57), 0.99 (95% CI 0.74-1.34) and 1.14 (95% CI 0.86-1.51) (P-value for trend across quartiles = 0.64). For residents living within 150 m of major roads, as compared with subjects living further away, the adjusted hazard ratio was 1.16 (95% CI 0.95-1.42, P = 0.14).

CONCLUSIONS

This first prospective study in the general population does not support an association between air pollution exposure or traffic proximity and risk of DVT. More data may be needed to clarify whether traffic or air pollution influences the risk of VTE.

Residential exposure to motor vehicle emissions and the risk of wheezing among 7-8 year-old schoolchildren: a city-wide cross-sectional study in Nicosia, Cyprus

BACKGROUND

Several studies have reported associations between respiratory outcomes in children and a range of self-reported, administrative or geographical indicators of traffic pollution. First-time investigation into the frequency of asthmatic symptoms among 7-8 year-old Cypriot children in 1999-2000 showed increased prevalence in the capital Nicosia compared to other areas. Geographical differences on an island the size of Cyprus may reflect environmental and/or lifestyle factors. This study investigates the relationship between self-reported symptoms and residential exposure to motor vehicle emissions among Nicosia schoolchildren.

METHODS

The addresses of children in the metropolitan area of Nicosia who participated in the original survey (N = 1,735) were geo-coded and the level of exposure of each child was assessed using distance- and emission-based indicators (i.e. estimated levels of particulate matter and nitrogen oxides emissions due to motor vehicles on main roads around the residence). Odds ratios of wheezing and asthma diagnosis in relation to levels of exposure were estimated in logistic regression models adjusting for person-based factors, co-morbidity and intra-school clustering.

RESULTS

We found an increased risk of wheezing at distances less than 50 m from a main road and/or only among those experiencing the highest levels of exposure. The strongest effect estimates were observed when exposure was defined in terms of the cumulative burden at all roads around the residence. Adjusted odds ratios for current wheezing were 2.33 (95% CI 1.27, 4.30) amongst the quartile of participants exposed to the highest levels of PM at all roads 50 m of their residence and 2.14 (95% CI 1.05, 4.35) for NOx, with no effect at intermediate levels of exposure. While the direction of effect was apparent at longer distances, differences were generally not statistically significant.

CONCLUSIONS

Children experiencing the highest burden of emissions in Nicosia seem to be at a higher risk of reporting asthmatic symptoms. Due to the small number of children residing at close proximity to main roads and lack of evidence of risk at intermediate levels of exposure or longer distances, the observed pattern alone does not explain the generally higher prevalence observed in urban Nicosia compared to other areas.

Predicting admissions for childhood asthma based on proximity to major roadways

PURPOSE

This retrospective study is an investigation of the relationship between traffic exposure and childhood asthma exacerbations in a previously unstudied geographic area. We hypothesized that, controlling for selected demographic and social factors, exposure to traffic emissions would allow the prediction of hospital utilization for children with asthma.

DESIGN

Using hospital and emergency department (ED) records, we investigated the relationship between proximity to major roadways and admissions for asthma exacerbations in the Fort Worth metropolitan area, designated as not attaining federal air health standards. The sample included 2,357 children from 1 to 12 years of age admitted for emergency or inpatient treatment in a 288-bed, nonprofit children's medical center in Fort Worth, Texas from January 1, 2004 to December 31, 2005. Data were analyzed using GIS mapping and logistic regression.

METHODS

Deidentification data were collected from hospital databases after IRB approval and waiver of parental permission or patient consent. Student's t test was used to compare groups with and without primary asthma diagnosis on admission in respect to distance from major roadways. Logistic regression was used to model relationships between asthma admission and patients' characteristics, exposure to traffic, and social environment.

FINDINGS

Controlling for several demographic factors, asthma occurrences were positively related to traffic exposures. On average, patients with asthma lived closer to major roadways than did patients who did not have asthma. Patients with asthma also tended to live in neighborhoods with more roads than did those who did not have asthma; 3/4 of the children admitted for asthma during the study period and less than 1/3 of the children admitted for nonasthma diagnoses lived within 1,500 meters of a major roadway (p=.0001). Controlling for other factors, every meter increase in proximity to major roadways produced 0.1% increase in likelihood of admission.

CLINICAL RELEVANCE

Knowledge of risk factors and their relative magnitudes enable nurses to better tailor symptom management for individual patients.

Spatial analysis of air pollution and childhood asthma in Hamilton, Canada: comparing exposure methods in sensitive subgroups

BACKGROUND

Variations in air pollution exposure within a community may be associated with asthma prevalence. However, studies conducted to date have produced inconsistent results, possibly due to errors in measurement of the exposures.

METHODS

A standardized asthma survey was administered to children in grades one and eight in Hamilton, Canada, in 1994-95 (N approximately 1467). Exposure to air pollution was estimated in four ways: (1) distance from roadways; (2) interpolated surfaces for ozone, sulfur dioxide, particulate matter and nitrous oxides from seven to nine governmental monitoring stations; (3) a kriged nitrogen dioxide (NO2) surface based on a network of 100 passive NO2 monitors; and (4) a land use regression (LUR) model derived from the same monitoring network. Logistic regressions were used to test associations between asthma and air pollution, controlling for variables including neighbourhood income, dwelling value, state of housing, a deprivation index and smoking.

RESULTS

There were no significant associations between any of the exposure estimates and asthma in the whole population, but large effects were detected the subgroup of children without hayfever (predominately in girls). The most robust effects were observed for the association of asthma without hayfever and NO2LUR OR = 1.86 (95%CI, 1.59-2.16) in all girls and OR = 2.98 (95%CI, 0.98-9.06) for older girls, over an interquartile range increase and controlling for confounders.

CONCLUSION

Our findings indicate that traffic-related pollutants, such as NO2, are associated with asthma without overt evidence of other atopic disorders among female children living in a medium-sized Canadian city. The effects were sensitive to the method of exposure estimation. More refined exposure models produced the most robust associations.

[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.

Traffic, outdoor air pollution, and asthma

The epidemiology of asthma and outdoor air pollution has shown that respiratory health effects can vary in relation to different emission sources, types of pollutants, underlying nutritional status, medication use, and genetic polymorphisms. Using sophisticated exposure assessment methods in conjunction with clinical tests and biomarkers that provide mechanistic information, the study of outdoor epidemiology and asthma has evolved into a complex multidisciplinary field. This article presents an overview of the mechanisms by which outdoor air pollution and traffic-related emissions lead to changes in respiratory health and lung function in subjects with asthma.

Traffic-related air pollution and asthma onset in children: a prospective cohort study with individual exposure measurement

BACKGROUND

The question of whether air pollution contributes to asthma onset remains unresolved.

OBJECTIVES

In this study, we assessed the association between asthma onset in children and traffic-related air pollution.

METHODS

We selected a sample of 217 children from participants in the Southern California Children's Health Study, a prospective cohort designed to investigate associations between air pollution and respiratory health in children 10-18 years of age. Individual covariates and new asthma incidence (30 cases) were reported annually through questionnaires during 8 years of follow-up. Children had nitrogen dioxide monitors placed outside their home for 2 weeks in the summer and 2 weeks in the fall-winter season as a marker of traffic-related air pollution. We used multilevel Cox models to test the associations between asthma and air pollution.

RESULTS

In models controlling for confounders, incident asthma was positively associated with traffic pollution, with a hazard ratio (HR) of 1.29 [95% confidence interval (CI), 1.07-1.56] across the average within-community interquartile range of 6.2 ppb in annual residential NO2. Using the total interquartile range for all measurements of 28.9 ppb increased the HR to 3.25 (95% CI, 1.35-7.85).

CONCLUSIONS

In this cohort, markers of traffic-related air pollution were associated with the onset of asthma. The risks observed suggest that air pollution exposure contributes to new-onset asthma.

Design issues in small-area studies of environment and health

BACKGROUND

Small-area studies are part of the tradition of spatial epidemiology, which is concerned with the analysis of geographic patterns of disease with respect to environmental, demographic, socioeconomic, and other factors. We focus on etiologic research, where the aim is to make inferences about spatially varying environmental factors influencing the risk of disease.

METHODS AND RESULTS

We illustrate the approach through three exemplars: a) magnetic fields from overhead electric power lines and the occurrence of childhood leukemia, which illustrates the use of geographic information systems to focus on areas with high exposure prevalence; b) drinking-water disinfection by-products and reproductive outcomes, taking advantage of large between- to within-area variability in exposures from the water supply; and c) chronic exposure to air pollutants and cardiorespiratory health, where issues of socioeconomic confounding are particularly important.

DISCUSSION

The small-area epidemiologic approach assigns exposure estimates to individuals based on location of residence or other geographic variables such as workplace or school. In this way, large populations can be studied, increasing the ability to investigate rare exposures or rare diseases. The approach is most effective when there is well-defined exposure variation across geographic units, limited within-area variation, and good control for potential confounding across areas.

CONCLUSIONS

In conjunction with traditional individual-based approaches, small-area studies offer a valuable addition to the armamentarium of the environmental epidemiologist. Modeling of exposure patterns coupled with collection of individual-level data on subsamples of the population should lead to improved risk estimates (i.e., less potential for bias) and help strengthen etiologic inference.

Impact and uncertainty of a traffic management intervention: population exposure to polycyclic aromatic hydrocarbons

In urban areas, road traffic is a major source of carcinogenic polycyclic aromatic hydrocarbons (PAH), thus any changes in traffic patterns are expected to affect PAH concentrations in ambient air. Exposure to PAH and other traffic-related air pollutants has often been quantified in a deterministic manner that disregards the various sources of uncertainty in the modelling systems used. In this study, we developed a generic method for handling uncertainty in population exposure models. The method was applied to quantify the uncertainty in population exposure to benzo[a]pyrene (BaP) before and after the implementation of a traffic management intervention. This intervention would affect the movement of vehicles in the studied area and consequently alter traffic emissions, pollutant concentrations and population exposure. Several models, including an emission calculator, a dispersion model and a Geographic Information System were used to quantify the impact of the traffic management intervention. We established four exposure zones defined by distance of residence postcode centroids from major road or intersection. A stochastic method was used to quantify the uncertainty in the population exposure model. The method characterises uncertainty using probability measures and propagates it applying Monte Carlo analysis. The overall model predicted that the traffic management scheme would lead to a minor reduction in mean population exposure to BaP in the studied area. However, the uncertainty associated with the exposure estimates was much larger than this reduction. The proposed method is generic and provides realistic estimates of population exposure to traffic-related pollutants, as well as characterises the uncertainty in these estimates. This method can be used within a decision support tool to evaluate the impact of alternative traffic management policies.

Development of ambient air quality population-weighted metrics for use in time-series health studies

A robust methodology was developed to compute population-weighted daily measures of ambient air pollution for use in time-series studies of acute health effects. Ambient data, including criteria pollutants and four fine particulate matter (PM) components, from monitors located in the 20-county metropolitan Atlanta area over the time period of 1999-2004 were normalized, spatially resolved using inverse distance-square weighting to Census tracts, denormalized using descriptive spatial models, and population-weighted. Error associated with applying this procedure with fewer than the maximum number of observations was also calculated. In addition to providing more representative measures of ambient air pollution for the health study population than provided by a central monitor alone and dampening effects of measurement error and local source impacts, results were used to evaluate spatial variability and to identify air pollutants for which ambient concentrations are poorly characterized. The decrease in correlation of daily monitor observations with daily population-weighted average values with increasing distance of the monitor from the urban center was much greater for primary pollutants than for secondary pollutants. Of the criteria pollutant gases, sulfur dioxide observations were least representative because of the failure of ambient networks to capture the spatial variability of this pollutant for which concentrations are dominated by point source impacts. Daily fluctuations in PM of particles less than 10 microm in aerodynamic diameter (PM10) mass were less well characterized than PM of particles less than 2.5 microm in aerodynamic diameter (PM2.5) mass because of a smaller number of PM10 monitors with daily observations. Of the PM2.5 components, the carbon fractions were less well spatially characterized than sulfate and nitrate both because of primary emissions of elemental and organic carbon and because of differences in measurement techniques used to assess these carbon fractions.

Comparison of regression models with land-use and emissions data to predict the spatial distribution of traffic-related air pollution in Rome

Spatial modeling of traffic-related air pollution typically involves either regression modeling of land-use and traffic data or dispersion modeling of emissions data, but little is known to what extent land-use regression models might be improved by incorporating emissions data. The aim of this study was to develop a land-use regression model to predict nitrogen dioxide (NO2) concentrations and compare its performance with a model including emissions data. The association between each land-use variable and NO2 concentrations at 68 locations in Rome in 1995 and 1996 was assessed by univariate linear regression and a multiple linear regression model that was constructed based on the importance of each variable. Traffic emissions (particulate matter, carbon monoxide, nitrogen oxides, and benzene) were estimated for 164 areas of the city based on vehicle type, traffic counts and driving patterns. Mean NO2 concentration across the 68 sites was 46.8 microg/m3 (SD 9.8 microg/m3; inter-quartile range 11.5 microg/m3; min 24 microg/m3; max 73 microg/m3). The most important predicting variables were the circular traffic zones (main ring road, green strip, inner ring road, traffic-limited zone), distance from busy streets, size of the census block, the inverse population density, and altitude. A multiple regression model including these variables resulted in an R2 of 0.686. The best-fitting model adding an emission term of benzene resulted in an R2 of 0.690, but was not significantly different from the model without emissions (P=0.147). In conclusion, these results suggest that a land-use regression model explains the traffic-related air pollution levels with reasonable accuracy and that emissions data do not significantly improve the model.

Particulate matter (PM(2.5), PM(10-2.5), and PM(10)) and children's hospital admissions for asthma and respiratory diseases: a bidirectional case-crossover study

Epidemiological studies reported adverse effects of air pollution on the prevalence of respiratory diseases in children. The purpose of this study was to examine the association between air pollution and admissions for asthma and other respiratory diseases among children who were younger than 15 yr of age. The study used data on respiratory hospital admissions and air pollutant concentrations, including thoracic particulate matter (PM(10)), fine (PM(2.5)), and coarse (PM(10-2.5)) particulate matter in Zonguldak, Turkey. A bidirectional case-crossover design was used to calculate odds ratios for the admissions adjusted for daily meteorological parameters. Significant increases were observed for hospital admissions in children for asthma, allergic rhinitis (AR), and upper (UPRD) and lower (LWRD) respiratory diseases. All fraction of PM in children showed significant positive associations with asthma admissions. The highest association noted was 18% rise in asthma admissions correlated with a 10-microg/m(3) increase in PM(10-2.5) on the same day of admissions. The adjusted odds ratios for exposure to PM(2.5) with an increment of 10 microg/m(3) were 1.15 and 1.21 for asthma and allergic rhinitis with asthma, respectively. PM(10) exerted significant effects on hospital admissions for all outcomes, including asthma, AR, UPRD, and LWRD. Our study suggested a greater effect of fine and coarse PM on asthma hospital admissions compared with PM(10) in children.

Traffic-related Exposures, Airway Function, Inflammation, and Respiratory Symptoms in Children

RATIONALE

Traffic-related emissions have been associated with respiratory symptoms in some studies. However, there is limited information on how traffic-related emissions relate to lung function and airway inflammation.

OBJECTIVES

To determine the differential association of traffic-related exposures with exhaled nitric oxide (NO) and lung volumes and symptoms in children with and without asthma.

METHODS

We performed a longitudinal study of 200 children from ages 6 to 12 years of whom half had physician-diagnosed asthma. Two-week NO(2) and 48-hour average levels of elemental carbon and particulate matter of less than 2.5 microm (PM(2.5)) were measured at participating schools. Road and traffic densities were determined at schools and at each participant's house.

MEASUREMENTS AND MAIN RESULTS

In children with asthma, an interquartile increase in road density within the 50-, 100-, and 200-m home buffer areas was associated with increased exhaled NO (50 m: 28%; P = 0.03; 95% confidence interval [CI], 3-60; 100 m: 27%; P = 0.005; 95% CI, 8-49; 200 m: 17%, P = 0.09, 95% CI, -2 to 40), and reduced FEV(1) (50 m: -0.091 L; P = 0.038; 95% CI, -0.174 to -0.007; 100 m: -0.072 L, P = -0.028, 95% CI, -0.134 to -0.009; 200 m: -0.106 L, P = 0.002, 95% CI, -0.171 to -0.041]). Exposure to NO(2) at schools was marginally associated with reduced FEV(1) (-0.020; P = 0.060; 95% CI, -0.042 to 0.001). We did not observe significant associations with PM(2.5) or elemental carbon on exhaled NO. We did not observe significant reductions in lung volumes or changes in exhaled NO among healthy children.

CONCLUSIONS

Vehicular traffic exposures are associated with increased levels of exhaled NO and reduced lung volumes in children with asthma.

Efficiency of two-phase methods with focus on a planned population-based case-control study on air pollution and stroke

BACKGROUND

We plan to conduct a case-control study to investigate whether exposure to nitrogen dioxide (NO2) increases the risk of stroke. In case-control studies, selective participation can lead to bias and loss of efficiency. A two-phase design can reduce bias and improve efficiency by combining information on the non-participating subjects with information from the participating subjects. In our planned study, we will have access to individual disease status and data on NO2 exposure on group (area) level for a large population sample of Scania, southern Sweden. A smaller sub-sample will be selected to the second phase for individual-level assessment on exposure and covariables. In this paper, we simulate a case-control study based on our planned study. We develop a two-phase method for this study and compare the performance of our method with the performance of other two-phase methods.

METHODS

A two-phase case-control study was simulated with a varying number of first- and second-phase subjects. Estimation methods: Method 1: Effect estimation with second-phase data only. Method 2: Effect estimation by adjusting the first-phase estimate with the difference between the adjusted and unadjusted second-phase estimate. The first-phase estimate is based on individual disease status and residential address for all study subjects that are linked to register data on NO2-exposure for each geographical area. Method 3: Effect estimation by using the expectation-maximization (EM) algorithm without taking area-level register data on exposure into account. Method 4: Effect estimation by using the EM algorithm and incorporating group-level register data on NO2-exposure.

RESULTS

The simulated scenarios were such that, unbiased or marginally biased (< 7%) odds ratio (OR) estimates were obtained with all methods. The efficiencies of method 4, are generally higher than those of methods 1 and 2. The standard errors in method 4 decreased further when the case/control ratio is above one in the second phase. For all methods, the standard errors do not become substantially reduced when the number of first-phase controls is increased.

CONCLUSION

In the setting described here, method 4 had the best performance in order to improve efficiency, while adjusting for varying participation rates across areas.

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.

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.

Proximity of schools in Detroit, Michigan to automobile and truck traffic

Exposure to traffic-related air pollutants, which has been associated with a range of adverse health effects, often is represented using indirect proxies or surrogate exposure measures, most commonly, the proximity to busy roads. This study examines the proximity of grade K-12 schools to high traffic roads in Wayne County, Michigan, an area including the industrialized city of Detroit as well as outlying urban and suburban communities. Unlike earlier studies, commercial and non-commercial traffic is distinguished, and effects of school type (public, charter, private), socio-economic variables, demographic factors, and mapping errors are evaluated. We find that total traffic flow, as measured by annual average daily traffic (AADT), does not reflect the substantial differences between trucking and commuting routes. Thus, AADT alone may inadequately capture traffic-related exposures, especially given the large differences between diesel and gasoline emissions. Based on close proximity (school-road distance < or = 150 m) to heavy traffic (AADT > or = 50,000), 4.9% of the 845 Wayne County schools are traffic exposed at school. In the urban core area, 7.2% of schools and 7.6% of students are traffic exposed at school. A larger proportion of grade 7-12 students in public schools are exposed than K-6 students. Considering truck emissions, 2.8% of the schools are within 150 m of roads with 5000 or more trucks per day. In Wayne County, students attending schools near high traffic roads are more likely to be Black or Hispanic, to be enrolled in a meal program, and to reside in a poor area. Many of these results are driven by the large minority population in the densely populated core area of Detroit. The findings show that a large fraction of children have high exposures to traffic-related pollutants, especially in Detroit, and the need for exposure measures that account for both the composition and volume of traffic.

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.

Association between reported exposure to road traffic and respiratory symptoms in children: evidence of bias

BACKGROUND

Many studies showing effects of traffic-related air pollution on health rely on self-reported exposure, which may be inaccurate. We estimated the association between self-reported exposure to road traffic and respiratory symptoms in preschool children, and investigated whether the effect could have been caused by reporting bias.

METHODS

In a random sample of 8700 preschool children in Leicestershire, UK, exposure to road traffic and respiratory symptoms were assessed by a postal questionnaire (response rate 80%). The association between traffic exposure and respiratory outcomes was assessed using unconditional logistic regression and conditional regression models (matching by postcode).

RESULTS

Prevalence odds ratios (95% confidence intervals) for self-reported road traffic exposure, comparing the categories 'moderate' and 'dense', respectively, with 'little or no' were for current wheezing: 1.26 (1.13-1.42) and 1.30 (1.09-1.55); chronic rhinitis: 1.18 (1.05-1.31) and 1.31 (1.11-1.56); night cough: 1.17 (1.04-1.32) and 1.36 (1.14-1.62); and bronchodilator use: 1.20 (1.04-1.38) and 1.18 (0.95-1.46). Matched analysis only comparing symptomatic and asymptomatic children living at the same postcode (thus exposed to similar road traffic) showed similar ORs, suggesting that parents of children with respiratory symptoms reported more road traffic than parents of asymptomatic children.

CONCLUSIONS

Our study suggests that reporting bias could explain some or even all the association between reported exposure to road traffic and disease. Over-reporting of exposure by only 10% of parents of symptomatic children would be sufficient to produce the effect sizes shown in this study. Future research should be based only on objective measurements of traffic exposure.

Nitrogen dioxide prediction in Southern California using land use regression modeling: potential for environmental health analyses

We modeled the intraurban distribution of nitrogen dioxide (NO(2)), a marker for traffic pollution, with land use regression, a promising new exposure classification technique. We deployed diffusion tubes to measure NO(2) levels at 39 locations in the fall of 2003 in San Diego County, CA, USA. At each sample location, we constructed circular buffers in a geographic information system and captured information on roads, traffic flow, land use, population and housing. Using multiple linear regression, we were able to predict 79% of the variation in NO(2) levels with four variables: traffic density within 40-300 m of the sampling location, traffic density within 300-1000 m, length of road within 40 m and distance to the Pacific coast. Applying this model to validation samples showed that the model predicted NO(2) levels within, on average, 2.1 p.p.b for 12 training sites initially excluded from the model. Our evaluation of this land use regression model showed that this method had excellent prediction and robustness in a North American context. These models may be useful tools in evaluating health effects of long-term exposure to traffic-related pollution.

Asthma and air pollution in the Bronx: methodological and data considerations in using GIS for environmental justice and health research

This paper examines methods of environmental justice assessment with Geographic Information Systems, using research on the spatial correspondence between asthma and air pollution in the Bronx, New York City as a case study. Issues of spatial extent and resolution, the selection of environmental burdens to analyze, data and methodological limitations, and different approaches to delineating exposure are discussed in the context of the asthma study, which, through proximity analysis, found that people living near (within specified distance buffers) noxious land uses were up to 66 percent more likely to be hospitalized for asthma, and were 30 percent more likely to be poor and 13 percent more likely to be a minority than those outside the buffers.

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.

Proximity of the home to roads and the risk of wheeze in an Ethiopian population

BACKGROUND

There is widespread public concern that exposure to road vehicle traffic pollution causes asthma, but epidemiological studies in developed countries have not generally confirmed a strong effect and may have underestimated the risk as a result of relatively high and widespread exposure to traffic in everyday life.

AIMS

To investigate the effect of living close to a traffic bearing road on the risk of wheezing in Jimma, Ethiopia where road traffic is generally low and restricted to a limited network of roads.

METHODS

Data have been previously collected on respiratory symptoms, allergic sensitisation, and numerous demographic and lifestyle factors in a systematic sample of inhabitants of Jimma town. In 2003 the homes of these people were retraced; the shortest distance to the nearest surfaced road, and traffic flows on these roads were measured.

RESULTS

Distance measurements were collected for 7609 (80%) individuals. The overall prevalence of wheeze was similar in those living within 150 m of a road compared to those living further away (3.9% v 3.7%), but among the 3592 individuals living within 150 m, the risk of wheeze increased significantly in linear relation to proximity to the road (adjusted odds ratio = 1.17 per 30 m proximity, 95% CI 1.01 to 1.36). This relation was stronger, though not significantly so, for roads with above median traffic flows.

CONCLUSION

These findings indicate that living in close proximity to road vehicle traffic is associated with an increased risk of wheeze, but that other environmental factors are also likely to be important.

Zone design for environment and health studies using pre-aggregated data

Many environment and health studies employ geographical areas as the units of analysis, either through choice or necessity. The design of these areas can greatly influence any observed spatial relationships or patterns-an effect known as the modifiable areal unit problem. In this paper we identify the phenomena and processes which are typically measured in environment and health studies and present a conceptualisation for their representation as data objects in spatial analysis. We discuss the circumstances under which we find ourselves using areas for representation and outline the application of zone design techniques for the creation of such areas in environment and health studies. An empirical study of the relationship between deprivation and limiting long-term illness in the former county of Avon, UK, is employed to demonstrate the potential usefulness of zone design techniques for creating zones with stable estimates and for exploring the sensitivity of relationships to changes in the zoning system. In particular, we illustrate the inappropriateness of the 1991 Census enumeration district and ward zoning systems for such an analysis and conclude that automatically designed aggregations may be a more appropriate basis for analysis than any pre-existing zoning system.

Traffic related pollutants in Europe and their effect on allergic disease

PURPOSE OF REVIEW

The prevalence and incidence of allergic diseases have increased in Europe during the last decades, as in most industrialized countries in other parts of the world. Persistent exposure to traffic related air pollution and especially particulate matter from motor vehicles has often been discussed as one of the factors responsible for this increase. This view seems to be supported by recent human and animal laboratory-based studies, which have shown that particulate pollutants, and in particular diesel exhaust particles, can enhance allergic inflammation and induce the development of allergic immune responses. However, the results from epidemiologic research provide a more complex picture.

RECENT FINDINGS

It has been clearly shown in many studies that traffic related air pollution contributes to increased mortality risk; in particular in relation to cardiopulmonary causes. Traffic related air pollution also increases the risk of non-allergic respiratory symptoms and disease. However, for allergic symptoms and illnesses like asthma, allergic rhinitis, atopic dermatitis, wheeze, and allergic sensitization less consistent results have been found. This is the reason why the World Health Organisation concludes cautiously that traffic related air pollution may increase the risk of allergy development and may exacerbate symptoms in particular in susceptible subgroups. This review concentrates on recent epidemiologic studies on the long-term effects of exposure to traffic related air pollution on allergic disease in Europe.

SUMMARY

In conclusion, the evidence for an increased risk for asthma and hay fever still is weak but seems to be strengthened a little. However, many questions are left open.

Secondhand smoke, dietary fruit intake, road traffic exposures, and the prevalence of asthma: a cross-sectional study in young children

The authors have investigated the independent effects of exposure to secondhand smoke, road vehicle traffic, and dietary fruit intake in a cross-sectional study of asthma in young children. They surveyed all children aged 4-6 years in 235 schools in the East Midlands and East of England regions of the United Kingdom in 2003. Data on respiratory symptoms, diagnoses and treatment, smoking in the home, and dietary fruit intake were collected by parental questionnaire. A geographic information system was used to map postcodes and determine the distance of the home from the nearest main road. Responses were obtained from 11,562 children. Wheeze in the past year and physician-diagnosed asthma were reported by 14.1% and 18.2%, respectively. Both of these outcomes were more common in children who lived with a smoker, and the prevalence of asthma increased with the number of smokers in the home. Asthma prevalence was not associated with proximity of the home to a main road or with dietary fruit intake. The authors conclude that, of the potential risk factors considered in this study, preventing secondhand smoke exposure may be the most effective way of preventing asthma.

Report of workshop on traffic, health, and infrastructure planning

Recent air pollutant measurement data document unique aspects of the air pollution mixture near roadways, and an expanding body of epidemiological data suggests increased risks for exacerbation of asthma and other respiratory diseases, premature mortality, and certain cancers and birth outcomes from air pollution exposures in populations residing in relatively close proximity to roadways. The Workshop on Traffic, Health, and Infrastructure Planning, held in February 2004, was convened to provide a forum for interdisciplinary discussion of motor vehicle emissions, exposures and potential health effects related to proximity to motor vehicle traffic. This report summarizes the workshop discussions and findings regarding the current science on this issue, identifies planning and policy issues related to localized motor vehicle emissions and health concerns, and provides recommendations for future research and policy directions.

A review and evaluation of intraurban air pollution exposure models

The development of models to assess air pollution exposures within cities for assignment to subjects in health studies has been identified as a priority area for future research. This paper reviews models for assessing intraurban exposure under six classes, including: (i) proximity-based assessments, (ii) statistical interpolation, (iii) land use regression models, (iv) line dispersion models, (v) integrated emission-meteorological models, and (vi) hybrid models combining personal or household exposure monitoring with one of the preceding methods. We enrich this review of the modelling procedures and results with applied examples from Hamilton, Canada. In addition, we qualitatively evaluate the models based on key criteria important to health effects assessment research. Hybrid models appear well suited to overcoming the problem of achieving population representative samples while understanding the role of exposure variation at the individual level. Remote sensing and activity-space analysis will complement refinements in pre-existing methods, and with expected advances, the field of exposure assessment may help to reduce scientific uncertainties that now impede policy intervention aimed at protecting public health.

Traffic air pollution and hospital admission for asthma: a case-control approach in a Turin (Italy) population

OBJECTIVES

This study investigated the relationship between traffic air pollution and asthma, using a case-control design applied to routinely collected data.

METHODS

Subjects resident in Turin during the period 1997-1999 and admitted for asthma were defined as cases; patients admitted for causes other than respiratory diseases or heart diseases were defined as controls. Nitrogen dioxide and total suspended particulate were considered as indicators of traffic air pollution. Statistical analysis were performed, separately for young (0-14 years), adult (15-64 years) and elderly (>64 years) patients, with a logistic regression model; results are expressed as percentage of risk modification for a 10 g/m(3) increase in exposure to pollutants.

RESULTS

The risk of emergency admissions for asthma rose significantly with increased exposure to nitrogen dioxide [2.4%, 95% Confidence Interval: 0.5%; 4.3%], and total suspended particulate [2.3%, 95% Confidence Interval: 1.1%-3.6%]. The significant association was evident, in particular, among young and elderly patients for both pollutants.

CONCLUSION

Using a case-control design both easy to use and manage, the study confirms the significant association between hospital emergency admissions for asthma and exposure to nitrogen dioxide and total suspended particulate pollutants.

Road-traffic pollution and asthma - using modelled exposure assessment for routine public health surveillance

Asthma is a common disease and appears to be increasing in prevalence. There is evidence linking air pollution, including that from road-traffic, with asthma. Road traffic is also on the increase. Routine surveillance of the impact of road-traffic pollution on asthma, and other diseases, would be useful in informing local and national government policy in terms of managing the environmental health risk.

Several methods for exposure assessment have been used in studies examining the association between asthma and road traffic pollution. These include comparing asthma prevalence in areas designated as high and low pollution areas, using distance from main roads as a proxy for exposure to road traffic pollution, using traffic counts to estimate exposure, using vehicular miles travelled and using modelling techniques. Although there are limitations to all these methods, the modelling approach has the advantage of incorporating several variables and may be used for prospective health impact assessment.

The modelling approach is already in routine use in the United Kingdom in support of the government's strategy for air quality management. Combining information from such models with routinely collected health data would form the basis of a routine public health surveillance system. Such a system would facilitate prospective health impact assessment, enabling policy decisions concerned with road-traffic to be made with knowledge of the potential implications. It would also allow systematic monitoring of the health impacts when the policy decisions and plans have been implemented.

Urban air pollution and asthma in children

This study investigated the relationship between atmospheric pollution and emergency hospital admission for asthma among children resident in Turin in the period 1997-1999, using a case-control design. On the basis of the primary diagnosis, pediatric patients (< 15 years old) resident in Turin and admitted for asthma were defined as cases (n(1) = 1,060); age-matched patients admitted for causes other than respiratory diseases or heart diseases were defined as controls (n(2) = 25,523). Nitrogen dioxide (NO(2) in microg/m(3)) and total suspended particulates (TSP in microg/m(3)) were considered as indicators of urban air pollution; sex and age of patient, seasonality, temperature, humidity, solar radiation, and day of admission were considered as principal confounders. Statistical analyses were performed using simple and multiple logistic regression models; the association between emergency admission for asthma and exposure was shown as percentage of risk modification for a 10 microg/m(3) increment of exposure to each pollutant and relative 95% confidence interval. The number of emergency admissions for respiratory causes rose significantly with increased exposure to each pollutant: 2.8% (95% CI, 0.7-4.9%) and 1.8% (95% CI, 0.3-3.2) for a 10 microg/m(3) increment of exposure to NO(2) and TSP, respectively. A significant association was found between increased number of hospital emergency admissions for respiratory causes and exposure to principal urban pollutants in Turin. The study confirms the results reported for other Italian and European cities, using a case-control design.

Self-reported traffic density and atopic disease in children. Results of the ISAAC Phase III survey in Muenster, Germany

Positive associations between traffic exposure and atopic respiratory disorders in children have been described in several studies. We analyzed data related to self-reported truck traffic density and several symptoms and diagnoses of asthma and hay fever (12-month wheezing and rhinitis symptoms, diagnoses of asthma and hay fever) from the ISAAC Phase III survey in Muenster, Germany, using core written and video questionnaires. Data were collected from representative school-based samples (n = 7345) of 6-7- and 13-14-yr-olds. In 13-14-yr-olds, according to exposure levels categorized into rare, frequent, and constant, with the 'never'-category used as reference, the sex-adjusted prevalence ratios were 1.29 (95% CI = 1.08-1.53), 1.58 (1.29-1.94), and 1.57 (1.18-2.10) for wheeze in the past 12 months, and 1.20 (1.06-1.34), 1.35 (1.17-1.55), and 1.69 (1.42-2.0) for rhinitis symptoms in the past 12 months. Prevalence ratios in 6-7-yr-olds and results for a diagnosis of asthma were less consistent while no positive association was detected between hay fever and truck traffic in both age groups. When analyses were based on a more general traffic indicator (self-reported traffic noise), no consistent associations were observed. Our data provide support for the hypothesis that residential exposure to truck traffic may adversely affect the health of 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.

Effects on respiratory health of a reduction in air pollution from vehicle exhaust emissions

AIMS

To determine whether residents of congested streets have a higher prevalence of respiratory symptoms than residents of nearby uncongested streets, and whether their respiratory health improves following a reduction in exposure to traffic related air pollutants.

METHODS

An area was identified where certain streets were subject to air pollution from heavy road traffic, which was likely to improve following the construction of a by-pass. A respiratory survey was conducted among the residents, together with the residents of nearby uncongested streets, at baseline and again a year after the by-pass opened. Measurements were made of air pollutant concentrations in both areas on both occasions.

RESULTS

Initial concentrations of PM10 and PM2.5 were substantially higher in the congested than in the uncongested streets. When the by-pass opened, the volume of heavy goods traffic fell by nearly 50%. PM10 decreased by 23% (8.0 microg/m3) in the congested streets and by 29% (3.4 microg/m3) in the uncongested streets, with similar proportionate falls in PM2.5. There were no clear or consistent differences between the residents of the two areas initially in terms of symptoms or peak flow variability. Repeat questionnaires were obtained from 165 and 283 subjects in the congested and uncongested areas respectively, and showed a tendency for most symptoms to improve in both areas. For chest symptoms, the improvement tended to be greater in the uncongested area, although the difference between the areas was not statistically significant. Rhinitis and rhinoconjunctivitis tended to improve to a greater extent in the congested streets; the difference between the areas was significant for the degree to which rhinitis interfered with daily activities. Peak flow variability tended to improve in the uncongested area.

CONCLUSIONS

The by-pass reduced pollutant levels to a degree that probably alleviates rhinitis and rhinoconjunctivitis but has little effect on lower respiratory symptoms.