Tom Bellander

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

Background. As part of a multicenter study relating traffic-related air pollution with incidence of asthma in three birth cohort studies (TRAPCA), we used a measurement and modelling procedure to estimate long-term average exposure to traffic-related particulate air pollution in communities throughout the Netherlands; in Munich, Germany; and in Stockholm County, Sweden. Methods. In each of the three locations, 40–42 measurement sites were selected to represent rural, urban background and urban traffic locations. At each site and fine particles and filter absorbance (a marker for diesel exhaust particles) were measured for four 2-week periods distributed over approximately 1-year periods between February 1999 and July 2000. We used these measurements to calculate annual average concentrations after adjustment for temporal variation. Traffic-related variables (eg, population density and traffic intensity) were collected using Geographic Information Systems and used in regression models predicting annual average concentrations. From these models we estimated ambient air concentrations at the home addresses of the cohort members. Results. Regression models using traffic-related variables explained 73%, 56% and 50% of the variability in annual average fine particle concentrations for the Netherlands, Munich and Stockholm County, respectively. For filter absorbance, the regression models explained 81%, 67% and 66% of the variability in the annual average concentrations. Cross-validation to estimate the model prediction errors indicated root mean squared errors of 1.1–1.6 &mgr;g/m3 for PM2.5 and 0.22–0.31 *10−5m−1 for absorbance. Conclusions. A substantial fraction of the variability in annual average concentrations for all locations was explained by traffic-related variables. This approach can be used to estimate individual exposures for epidemiologic studies and offers advantages over alternative techniques relying on surrogate variables or traditional approaches that utilize ambient monitoring data alone.

Urban air pollution and lung cancer in Stockholm.

We conducted a population-based case-control study among men 40–75 years of age encompassing all cases of lung cancer 1985–1990 among stable residents of Stockholm County 1950–1990. Questionnaires to subjects or next-of-kin (primarily wives or children) elicited information regarding smoking and other risk factors, including occupational and residential histories. A high response rate (>85%) resulted in 1,042 cases and 2,364 controls. We created retrospective emission databases for NOx/NO2 and SO2 as indicators of air pollution from road traffic and heating, respectively. We estimated local annual source-specific air pollution levels using validated dispersion models and we linked these levels to residential addresses using Geographical Information System (GIS) techniques. Average traffic-related NO2 exposure over 30 years was associated with a relative risk (RR) of 1.2 (95% confidence interval 0.8–1.6) for the top decile of exposure, adjusted for tobacco smoking, socioeconomic status, residential radon, and occupational exposures. The data suggested a considerable latency period; the RR for the top decile of average traffic-related NO2 exposure 20 years previously was 1.4 (1.0–2.0). Little association was observed for SO2. Occupational exposure to asbestos, diesel exhaust, and other combustion products also increased the risk of lung cancer. Our results indicate that urban air pollution increases lung cancer risk and that vehicle emissions may be particularly important.

Development of Land Use Regression Models for PM2.5, PM2.5 Absorbance, PM10 and PMcoarse in 20 European Study Areas; Results of the ESCAPE Project

Land Use Regression (LUR) models have been used increasingly for modeling small-scale spatial variation in air pollution concentrations and estimating individual exposure for participants of cohort studies. Within the ESCAPE project, concentrations of PM(2.5), PM(2.5) absorbance, PM(10), and PM(coarse) were measured in 20 European study areas at 20 sites per area. GIS-derived predictor variables (e.g., traffic intensity, population, and land-use) were evaluated to model spatial variation of annual average concentrations for each study area. The median model explained variance (R(2)) was 71% for PM(2.5) (range across study areas 35-94%). Model R(2) was higher for PM(2.5) absorbance (median 89%, range 56-97%) and lower for PM(coarse) (median 68%, range 32- 81%). Models included between two and five predictor variables, with various traffic indicators as the most common predictors. Lower R(2) was related to small concentration variability or limited availability of predictor variables, especially traffic intensity. Cross validation R(2) results were on average 8-11% lower than model R(2). Careful selection of monitoring sites, examination of influential observations and skewed variable distributions were essential for developing stable LUR models. The final LUR models are used to estimate air pollution concentrations at the home addresses of participants in the health studies involved in ESCAPE.

Traffic-related air pollution and respiratory health during the first 2 yrs of life

As part of an international collaborative study on the impact of Traffic-Related Air Pollution on Childhood Asthma (TRAPCA), the health effects associated with long-term exposure to particles with a 50% cut-off aerodynamic diameter of 2.5 µm (PM2.5), PM2.5 absorbance, and nitrogen dioxide (NO2) were analysed. The German part of the TRAPCA study used data from subpopulations of two ongoing birth cohort studies (German Infant Nutrition Intervention Programme (GINI) and Influences of Lifestyle Related Factors on the Human Immune System and Development of Allergies in Children (LISA)) based in the city of Munich. Geographic information systems (GIS)-based exposure modelling was used to estimate traffic-related air pollutants at the birth addresses of 1,756 infants. Logistic regression was used to analyse possible health effects and potential confounding factors were adjusted for. The ranges in estimated exposures to PM2.5, PM2.5 absorbance, and NO2 were 11.9–21.9 µg·m−3, 1.38–4.39×10−5 m−1, and 19.5–66.9 µg·m3, respectively. Significant associations between these pollutants and cough without infection (odds ratio (OR) (95% confidence interval (CI)): 1.34 (1.11–1.61), 1.32 (1.10–1.59), and 1.40 (1.12–1.75), respectively) and dry cough at night (OR (95% CI): 1.31 (1.07–1.60), 1.27 (1.04–1.55), and 1.36 (1.07–1.74), respectively) in the first year of life were found. In the second year of life, these effects were attenuated. There was some indication of an association between traffic-related air pollution and symptoms of cough. Due to the very young age of the infants, it was too early to draw definitive conclusions from this for the development of asthma.

Traffic-related air pollution and childhood respiratory symptoms, function and allergies.

Background: Urban air pollution can trigger asthma symptoms in children, but there is conflicting evidence on effects of long-term exposure on lung function, onset of airway disease and allergic sensitization. Methods: The spatial distribution of nitrogen oxides from traffic (traffic-NOx) and inhalable particulate matter from traffic (traffic-PM10) in the study area was assessed with emission databases and dispersion modeling. Estimated levels were used to assign first-year exposure levels for children in a prospective birth cohort (n = 4089), by linking to geocoded home addresses. Parents in 4 Swedish municipalities provided questionnaire data on symptoms and exposures when the children were 2 months and 1, 2, and 4-year-old. At 4 years, 73% of the children underwent clinical examination including peak expiratory flow and specific IgE measurements. Results: Exposure to air pollution from traffic during the first year of life was associated with an excess risk of persistent wheezing (odds ratio [OR] for 44 &mgr;g/m3 [5th–95th percentile] difference in traffic-NOx = 1.60; 95% confidence interval [CI] = 1.09–2.36). Similar results were found for sensitization (measured as specific IgE) to inhalant allergens, especially pollen (OR for traffic-NOx = 1.67; 95% CI = 1.10–2.53), at the age of 4 years. Traffic-related air pollution exposure during the first year of life was also associated with lower lung function at 4 years of age. Results were similar using traffic-NOx and traffic-PM10 as indicators. Conclusions: Exposure to moderate levels of locally emitted air pollution from traffic early in life appears to influence the development of airway disease and sensitization in preschool children.

Ambient Air Pollution Is Associated With Increased Risk of Hospital Cardiac Readmissions of Myocardial Infarction Survivors in Five European Cities

Background— Ambient air pollution has been associated with increases in acute morbidity and mortality. The objective of this study was to evaluate the short-term effects of urban air pollution on cardiac hospital readmissions in survivors of myocardial infarction, a potentially susceptible subpopulation. Methods and Results— In this European multicenter cohort study, 22 006 survivors of a first myocardial infarction were recruited in Augsburg, Germany; Barcelona, Spain; Helsinki, Finland; Rome, Italy; and Stockholm, Sweden, from 1992 to 2000. Hospital readmissions were recorded in 1992 to 2001. Ambient nitrogen dioxide, carbon monoxide, ozone, and mass of particles <10 &mgr;m (PM10) were measured. Particle number concentrations were estimated as a proxy for ultrafine particles. Short-term effects of air pollution on hospital readmissions for myocardial infarction, angina pectoris, and cardiac causes (myocardial infarction, angina pectoris, dysrhythmia, or heart failure) were studied in city-specific Poisson regression analyses with subsequent pooling. During follow-up, 6655 cardiac readmissions were observed. Cardiac readmissions increased in association with same-day concentrations of PM10 (rate ratio [RR] 1.021, 95% CI 1.004 to 1.039) per 10 &mgr;g/m3) and estimated particle number concentrations (RR 1.026 [95% CI 1.005 to 1.048] per 10 000 particles/cm3). Effects of similar strength were observed for carbon monoxide (RR 1.014 [95% CI 1.001 to 1.026] per 200 &mgr;g/m3 [0.172 ppm]), nitrogen dioxide (RR 1.032 [95% CI 1.013 to 1.051] per 8 &mgr;g/m3 [4.16 ppb]), and ozone (RR 1.026 [95% CI 1.001 to 1.051] per 15 &mgr;g/m3 [7.5 ppb]). Pooled effect estimates for angina pectoris and myocardial infarction readmissions were comparable. Conclusions— The results suggest that ambient air pollution is associated with increased risk of hospital cardiac readmissions of myocardial infarction survivors in 5 European cities.

Air pollution and inflammation (interleukin-6, C-reactive protein, fibrinogen) in myocardial infarction survivors.

Background Numerous studies have found that ambient air pollution has been associated with cardiovascular disease exacerbation. Objectives Given previous findings, we hypothesized that particulate air pollution might induce systemic inflammation in myocardial infarction (MI) survivors, contributing to an increased vulnerability to elevated concentrations of ambient particles. Methods A prospective longitudinal study of 1,003 MI survivors was performed in six European cities between May 2003 and July 2004. We compared repeated measurements of interleukin 6 (IL-6), fibrinogen, and C-reactive protein (CRP) with concurrent levels of air pollution. We collected hourly data on particle number concentrations (PNC), mass concentrations of particulate matter (PM) < 10 μm (PM10) and < 2.5 μm (PM2.5), gaseous pollutants, and meteorologic data at central monitoring sites in each city. City-specific confounder models were built for each blood marker separately, adjusting for meteorology and time-varying and time-invariant covariates. Data were analyzed with mixed-effects models. Results Pooled results show an increase in IL-6 when concentrations of PNC were elevated 12–17 hr before blood withdrawal [percent change of geometric mean, 2.7; 95% confidence interval (CI), 1.0–4.6]. Five day cumulative exposure to PM10 was associated with increased fibrinogen concentrations (percent change of arithmetic mean, 0.6; 95% CI, 0.1–1.1). Results remained stable for smokers, diabetics, and patients with heart failure. No consistent associations were found for CRP. Conclusions Results indicate an immediate response to PNC on the IL-6 level, possibly leading to the production of acute-phase proteins, as seen in increased fibrinogen levels. This might provide a link between air pollution and adverse cardiac events.

Comparison between different traffic-related particle indicators: elemental carbon (EC), PM2.5 mass, and absorbance.

Here we compare PM2.5 (particles with aerodynamic diameter less than 2.5 μm) mass and filter absorbance measurements with elemental carbon (EC) concentrations measured in parallel at the same site as well as collocated PM2.5 and PM10 (particles with aerodynamic diameter less than 10 μm) mass and absorbance measurements. The data were collected within the Traffic-Related Air Pollution on Childhood Asthma (TRAPCA) study in Germany, The Netherlands and Sweden. The study was designed to assess the health impact of spatial contrasts in long-term average concentrations. The measurement sites were distributed between background and traffic locations. Annual EC and PM2.5 absorbance measurements were at traffic sites on average 43–84% and 26–76% higher, respectively, compared to urban background sites. The contrast for PM2.5 mass measurements was lower (8–35%). The smaller contrast observed for PM2.5 mass in comparison with PM2.5 absorbance and EC documents that PM2.5 mass underestimates exposure contrasts related to motorized traffic emissions. The correlation between PM10 and PM2.5 was high, documenting that most of the spatial variation of PM10 was because of PM2.5. The measurement of PM2.5 absorbance was highly correlated with EC measurements and suggests that absorbance can be used as a simple, inexpensive and non-destructive method to estimate motorized traffic-related particulate air pollution. The EC/absorbance relation differed between countries and site type (background/traffic), supporting the need for site-specific calibrations of the simple absorbance method. While the ratio between PM2.5 and PM10 mass ranged from 0.54 to 0.68, the ratio of PM2.5 absorbance and PM10 absorbance was 0.96–0.97, indicating that PM2.5 absorbance captures nearly all of the particle absorbance.

Long-term exposure to urban air pollution and myocardial infarction.

Background: Cohort studies have reported increased risks of cardiopulmonary mortality from long-term air pollution exposure, but the evidence is limited and inconclusive. We studied the association between long-term exposure to source-specific air pollution and myocardial infarction (MI) in a case–control study of first-time MI cases and population controls age 45 to 70 years in Stockholm county in 1992 to 1994. Methods: Home addresses during several decades were combined with historical emission databases and dispersion models to obtain annual mean levels of pollutants from traffic and heating during 30 years for 1397 cases and 1870 controls. Nitrogen dioxide (NO2), carbon monoxide (CO), and particulate matter with an aerodynamic diameter less than 10 μm (PM10) were used as indicators of traffic emissions and sulfur dioxide (SO2) as an indicator of emissions from residential heating. Results: There was no association between long-term average air pollution exposure and overall MI, but an increased risk of fatal MI was suggested, especially for out-of-hospital death. After adjustment for cardiovascular risk factors, the odds ratio for fatal MI associated with a 5th to 95th percentile difference in 30-year average exposure was 1.51 (95% confidence interval = 0.96–2.16) for NO2, 1.22 (0.98–1.52) for CO, 1.39 (0.94–2.07) for PM10, and 1.24 (0.77–2.02) for SO2. For out-of-hospital death, the odds ratio related to NO2 exposure was 2.17 (1.05–4.51). Conclusions: This study provides some support for an association between long-term air pollution exposure and fatal cardiovascular disease.

Interactions between Glutathione S-Transferase P1, Tumor Necrosis Factor, and Traffic-Related Air Pollution for Development of Childhood Allergic Disease

Background Air pollutants may induce airway inflammation and sensitization due to generation of reactive oxygen species. The genetic background to these mechanisms could be important effect modifiers. Objective Our goal was to assess interactions between exposure to air pollution and single nucleotide polymorphisms (SNPs) in the β2-adrenergic receptor (ADRB2), glutathione S-transferase P1 (GSTP1), and tumor necrosis factor (TNF) genes for development of childhood allergic disease. Methods In a birth cohort originally of 4,089 children, we assessed air pollution from local traffic using nitrogen oxides (traffic NOx) as an indicator based on emission databases and dispersion modeling and estimated individual exposure through geocoding of home addresses. We measured peak expiratory flow rates and specific IgE for inhalant and food allergens at 4 years of age, and selected children with asthma symptoms up to 4 years of age (n = 542) and controls (n = 542) for genotyping. Results Interaction effects on allergic sensitization were indicated between several GSTP1 SNPs and traffic NOx exposure during the first year of life (pnominal < 0.001–0.06). Children with Ile105Val/Val105Val genotypes were at increased risk of sensitization to any allergen when exposed to elevated levels of traffic NOx (for a difference between the 5th and 95th percentile of exposure: odds ratio = 2.4; 95% confidence interval, 1.0–5.3). In children with TNF-308 GA/AA genotypes, the GSTP1–NOx interaction effect was even more pronounced. We observed no conclusive interaction effects for ADRB2. Conclusion The effect of air pollution from traffic on childhood allergy appears to be modified by GSTP1 and TNF variants, supporting a role of genes controlling the antioxidative system and inflammatory response in allergy.