Particulate Matter and Subclinical Atherosclerosis: Associations between Different Particle Sizes and Sources with Carotid Intima-Media Thickness in the SAPALDIA Study.

BACKGROUND: Subclinical atherosclerosis has been associated with long-term exposure to particulate matter (PM), but the relevance of particle size and sources of exposure remains unclear. OBJECTIVES: We investigated the association of long-term exposure to PM10 (≤ 10 µm), PM2.5 (≤ 2.5 µm: total mass, vehicular, and crustal sources), and ultrafine particles [UFP < 0.1 µm: particle number concentration (PNC) and lung-deposited surface area (LDSA)] with carotid intima-media thickness (CIMT). METHODS: We used data from 1,503 participants ≥ 50 years old who participated in the third examination of the Swiss SAPALDIA cohort. Exposures were obtained from dispersion models and land-use regression models. Covariate information, including previous cardiovascular risk factors, was obtained from the second and third SAPALDIA examinations. RESULTS: The adjusted percent difference in CIMT associated with an exposure contrast between the 10th and 90th percentile was 1.58% (95% CI: -0.30, 3.47%) for PM10, 2.10% (95% CI: 0.04, 4.16%) for PM2.5, 1.67% (95% CI: -0.13, 3.48%) for the vehicular source of PM2.5, -0.58% (95% CI: -3.95, 2.79%) for the crustal source of PM2.5, 2.06% (95% CI: 0.03, 4.10%) for PNC, and 2.32% (95% CI: 0.23, 4.40%) for LDSA. Stronger associations were observed among diabetics, subjects with low-educational level, and those at higher cardiovascular risk. CONCLUSIONS: CIMT was associated with exposure to PM10, PM2.5, and UFP. The PM2.5 source-specific analysis showed a positive association for the vehicular source but not for the crustal source. Although the effects of PNC and LDSA were similar in magnitude, two-pollutant and residual-based models suggested that LDSA may be a better marker for the health relevance of UFP. Citation: Aguilera I, Dratva J, Caviezel S, Burdet L, de Groot E, Ducret-Stich RE, Eeftens M, Keidel D, Meier R, Perez L, Rothe T, Schaffner E, Schmit-Trucksäss A, Tsai MY, Schindler C, Künzli N, Probst-Hensch N. 2016. Particulate matter and subclinical atherosclerosis: associations between different particle sizes and sources with carotid intima-media thickness in the SAPALDIA study. Environ Health Perspect 124:1700-1706; http://dx.doi.org/10.1289/EHP161.

Modeling indoor air pollution of outdoor origin in homes of SAPALDIA subjects in Switzerland.

Given the shrinking spatial contrasts in outdoor air pollution in Switzerland and the trends toward tightly insulated buildings, the Swiss Cohort Study on Air Pollution and Lung and Heart Diseases in Adults (SAPALDIA) needs to understand to what extent outdoor air pollution remains a determinant for residential indoor exposure. The objectives of this paper are to identify determining factors for indoor air pollution concentrations of particulate matter (PM), ultrafine particles in the size range from 15 to 300nm, black smoke measured as light absorbance of PM (PMabsorbance) and nitrogen dioxide (NO2) and to develop predictive indoor models for SAPALDIA. Multivariable regression models were developed based on indoor and outdoor measurements among homes of selected SAPALDIA participants in three urban (Basel, Geneva, Lugano) and one rural region (Wald ZH) in Switzerland, various home characteristics and reported indoor sources such as cooking. Outdoor levels of air pollutants were important predictors for indoor air pollutants, except for the coarse particle fraction. The fractions of outdoor concentrations infiltrating indoors were between 30% and 66%, the highest one was observed for PMabsorbance. A modifying effect of open windows was found for NO2 and the ultrafine particle number concentration. Cooking was associated with increased particle and NO2 levels. This study shows that outdoor air pollution remains an important determinant of residential indoor air pollution in Switzerland.

Land use regression models for crustal and traffic-related PM2.5 constituents in four areas of the SAPALDIA study.

Many studies have documented adverse health effects of long-term exposure to fine particulate matter (PM2.5), but there is still limited knowledge regarding the causal relationship between specific sources of PM2.5 and such health effects. The spatial variability of PM2.5 constituents and sources, as a exposure assessment strategy for investigating source contributions to health effects, has been little explored so far. Between 2011 and 2012, three measurement campaigns of PM and nitrogen dioxide (NO2) were performed in 80 sites across four areas of the Swiss Study on Air Pollution and Lung and heart Diseases in Adults (SAPALDIA). Reflectance analysis and energy dispersive X-ray fluorescence (XRF) were performed on PM2.5 filter samples to estimate light absorbance and trace element concentrations, respectively. Three air pollution source factors were identified using principal-component factor analysis: vehicular, crustal, and long-range transport. Land use regression (LUR) models were developed for temporally-adjusted scores of each factor, combining the four study areas. Model performance was assessed using two cross-validation methods. Model explained variance was high for the vehicular factor (R(2)=0.76), moderate for the crustal factor (R(2)=0.46), and low for the long-range transport factor (R(2)=0.19). The cross-validation methods suggested that models for the vehicular and crustal factors moderately accounted for both the between and within-area variability, and therefore can be applied to the four study areas to estimate long-term exposures within the SAPALDIA study population. The combination of source apportionment techniques and LUR modelling may help in identifying air pollution sources and disentangling their contribution to observed health effects in epidemiologic studies.

Differences in indoor versus outdoor concentrations of ultrafine particles, PM2.5, PMabsorbance and NO2 in Swiss homes.

Indoor air quality is a growing concern as we spend the majority of time indoors and as new buildings are increasingly airtight for energy saving purposes. For a better understanding of residential indoor air pollution in Switzerland we conducted repeated 1-2-week-long indoor and outdoor measurements of particle number concentrations (PNC), particulate matter (PM), light absorbance of PM2.5 (PMabsorbance) and nitrogen dioxide (NO2). Residents of all homes were enrolled in the Swiss Cohort Study on Air Pollution and Lung and Heart Diseases in Adults (SAPALDIA). Indoor levels were comparable in urban areas and generally low in rural homes. Average indoor levels were 7800 particles/cm(3) (interquartile range=7200); 8.7 µg/m(3) (6.5) PM2.5 and 10.2 µg/m(3) (11.2) NO2. All pollutants showed large variability of indoor/outdoor ratios between sites. We observed similar diurnal patterns for indoor and outdoor PNC. Nevertheless, the correlation of average indoor and outdoor PNC between sites as well as longitudinal indoor/outdoor correlations within sites were low. Our results show that a careful evaluation of home characteristics is needed when estimating indoor exposure to pollutants with outdoor origin.

Ambient air pollution and adult asthma incidence in six European cohorts (ESCAPE).

BACKGROUND: Short-term exposure to air pollution has adverse effects among patients with asthma, but whether long-term exposure to air pollution is a cause of adult-onset asthma is unclear. OBJECTIVE: We aimed to investigate the association between air pollution and adult onset asthma. METHODS: Asthma incidence was prospectively assessed in six European cohorts. Exposures studied were annual average concentrations at home addresses for nitrogen oxides assessed for 23,704 participants (including 1,257 incident cases) and particulate matter (PM) assessed for 17,909 participants through ESCAPE land-use regression models and traffic exposure indicators. Meta-analyses of cohort-specific logistic regression on asthma incidence were performed. Models were adjusted for age, sex, overweight, education, and smoking and included city/area within each cohort as a random effect. RESULTS: In this longitudinal analysis, asthma incidence was positively, but not significantly, associated with all exposure metrics, except for PMcoarse. Positive associations of borderline significance were observed for nitrogen dioxide [adjusted odds ratio (OR) = 1.10; 95% CI: 0.99, 1.21 per 10 µg/m3; p = 0.10] and nitrogen oxides (adjusted OR = 1.04; 95% CI: 0.99, 1.08 per 20 µg/m3; p = 0.08). Nonsignificant positive associations were estimated for PM10 (adjusted OR = 1.04; 95% CI: 0.88, 1.23 per 10 µg/m3), PM2.5 (adjusted OR = 1.04; 95% CI: 0.88, 1.23 per 5 µg/m3), PM2.5absorbance (adjusted OR = 1.06; 95% CI: 0.95, 1.19 per 10-5/m), traffic load (adjusted OR = 1.10; 95% CI: 0.93, 1.30 per 4 million vehicles × meters/day on major roads in a 100-m buffer), and traffic intensity (adjusted OR = 1.10; 95% CI: 0.93, 1.30 per 5,000 vehicles/day on the nearest road). A nonsignificant negative association was estimated for PMcoarse (adjusted OR = 0.98; 95% CI: 0.87, 1.14 per 5 µg/m3). CONCLUSIONS: Results suggest a deleterious effect of ambient air pollution on asthma incidence in adults. Further research with improved personal-level exposure assessment (vs. residential exposure assessment only) and phenotypic characterization is needed.

The relevance of commuter and work/school exposure in an epidemiological study on traffic-related air pollution.

Exposure during transport and at non-residential locations is ignored in most epidemiological studies of traffic-related air pollution. We investigated the impact of separately estimating NO2 long-term outdoor exposures at home, work/school, and while commuting on the association between this marker of exposure and potential health outcomes. We used spatially and temporally resolved commuter route data and model-based NO2 estimates of a population sample in Basel, Switzerland, to assign individual NO2-exposure estimates of increasing complexity, namely (1) home outdoor concentration; (2) time-weighted home and work/school concentrations; and (3) time-weighted concentration incorporating home, work/school and commute. On the basis of their covariance structure, we estimated the expectable relative differences in the regression slopes between a quantitative health outcome and our measures of individual NO2 exposure using a standard measurement error model. The traditional use of home outdoor NO2 alone indicated a 12% (95% CI: 11-14%) underestimation of related health effects as compared with integrating both home and work/school outdoor concentrations. Mean contribution of commuting to total weekly exposure was small (3.2%; range 0.1-13.5%). Thus, ignoring commute in the total population may not significantly underestimate health effects as compared with the model combining home and work/school. For individuals commuting between Basel-City and Basel-Country, ignoring commute may produce, however, a significant attenuation bias of 4% (95% CI: 4-5%). Our results illustrate the importance of including work/school locations in assessments of long-term exposures to traffic-related air pollutants such as NO2. Information on individuals' commuting behavior may further improve exposure estimates, especially for subjects having lengthy commutes along major transportation routes.

Cross-sectional associations between air pollution and chronic bronchitis: an ESCAPE meta-analysis across five cohorts.

BACKGROUND: This study aimed to assess associations of outdoor air pollution on prevalence of chronic bronchitis symptoms in adults in five cohort studies (Asthma-E3N, ECRHS, NSHD, SALIA, SAPALDIA) participating in the European Study of Cohorts for Air Pollution Effects (ESCAPE) project. METHODS: Annual average particulate matter (PM(10), PM(2.5), PM(absorbance), PM(coarse)), NO(2), nitrogen oxides (NO(x)) and road traffic measures modelled from ESCAPE measurement campaigns 2008-2011 were assigned to home address at most recent assessments (1998-2011). Symptoms examined were chronic bronchitis (cough and phlegm for ≥3 months of the year for ≥2 years), chronic cough (with/without phlegm) and chronic phlegm (with/without cough). Cohort-specific cross-sectional multivariable logistic regression analyses were conducted using common confounder sets (age, sex, smoking, interview season, education), followed by meta-analysis. RESULTS: 15 279 and 10 537 participants respectively were included in the main NO(2) and PM analyses at assessments in 1998-2011. Overall, there were no statistically significant associations with any air pollutant or traffic exposure. Sensitivity analyses including in asthmatics only, females only or using back-extrapolated NO(2) and PM10 for assessments in 1985-2002 (ECRHS, NSHD, SALIA, SAPALDIA) did not alter conclusions. In never-smokers, all associations were positive, but reached statistical significance only for chronic phlegm with PM(coarse) OR 1.31 (1.05 to 1.64) per 5 µg/m(3) increase and PM(10) with similar effect size. Sensitivity analyses of older cohorts showed increased risk of chronic cough with PM(2.5abs) (black carbon) exposures. CONCLUSIONS: Results do not show consistent associations between chronic bronchitis symptoms and current traffic-related air pollution in adult European populations.

Simulation of population-based commuter exposure to NO2 using different air pollution models.

We simulated commuter routes and long-term exposure to traffic-related air pollution during commute in a representative population sample in Basel (Switzerland), and evaluated three air pollution models with different spatial resolution for estimating commute exposures to nitrogen dioxide (NO2) as a marker of long-term exposure to traffic-related air pollution. Our approach includes spatially and temporally resolved data on actual commuter routes, travel modes and three air pollution models. Annual mean NO2 commuter exposures were similar between models. However, we found more within-city and within-subject variability in annual mean (±SD) NO2 commuter exposure with a high resolution dispersion model (40 ± 7 µg m(-3), range: 21-61) than with a dispersion model with a lower resolution (39 ± 5 µg m(-3); range: 24-51), and a land use regression model (41 ± 5 µg m(-3); range: 24-54). Highest median cumulative exposures were calculated along motorized transport and bicycle routes, and the lowest for walking. For estimating commuter exposure within a city and being interested also in small-scale variability between roads, a model with a high resolution is recommended. For larger scale epidemiological health assessment studies, models with a coarser spatial resolution are likely sufficient, especially when study areas include suburban and rural areas.

PM10 source apportionment in a Swiss Alpine valley impacted by highway traffic.

Although trans-Alpine highway traffic exhaust is one of the major sources of air pollution along the highway valleys of the Alpine regions, little is known about its contribution to residential exposure and impact on respiratory health. In this paper, source-specific contributions to particulate matter with an aerodynamic diameter < 10 µm (PM10) and their spatio-temporal distribution were determined for later use in a pediatric asthma panel study in an Alpine village. PM10 sources were identified by positive matrix factorization using chemical trace elements, elemental, and organic carbon from daily PM10 filters collected between November 2007 and June 2009 at seven locations within the village. Of the nine sources identified, four were directly road traffic-related: traffic exhaust, road dust, tire and brake wear, and road salt contributing 16 %, 8 %, 1 %, and 2 % to annual PM10 concentrations, respectively. They showed a clear dependence with distance to highway. Additional contributions were identified from secondary particles (27 %), biomass burning (18 %), railway (11 %), and mineral dust including a local construction site (13 %). Comparing these source contributions with known source-specific biomarkers (e.g., levoglucosan, nitro-polycyclic aromatic hydrocarbons) showed high agreement with biomass burning, moderate with secondary particles (in winter), and lowest agreement with traffic exhaust.

Role of highway traffic on spatial and temporal distributions of air pollutants in a Swiss Alpine valley.

Traffic-related air pollutants show high spatial variability near roads, posing a challenge to adequately assess exposures. Recent modeling approaches (e.g. dispersion models, land-use regression (LUR) models) have addressed this but mostly in urban areas where traffic is abundant. In contrast, our study area was located in a rural Swiss Alpine valley crossed by the main North-south transit highway of Switzerland. We conducted an extensive measurement campaign collecting continuous nitrogen dioxide (NO2), particulate number concentrations (PN), daily respirable particulate matter (PM10), elemental carbon (EC) and organic carbon (OC) at one background, one highway and seven mobile stations from November 2007 to June 2009. Using these measurements, we built a hybrid model to predict daily outdoor NO2 concentrations at residences of children participating in an asthma panel study. With the exception of OC, daily variations of the pollutants followed the temporal trends of heavy-duty traffic counts on the highway. In contrast, variations of weekly/seasonal means were strongly determined by meteorological conditions, e.g., winter inversion episodes. For pollutants related to primary exhaust emissions (i.e. NO2, EC and PN) local spatial variation strongly depended on proximity to the highway. Pollutant concentrations decayed to background levels within 150 to 200 m from the highway. Two separate daily NO2 prediction models were built using LUR approaches with (a) short-term traffic and weather data (model 1) and (b) subsequent addition of daily background NO2 to previous model (model 2). Models 1 and 2 explained 70% and 91% of the variability in outdoor NO2 concentrations, respectively. The biweekly averaged predictions from the final model 2 agreed very well with the independent biweekly integrated passive measurements taken at thirteen homes and nine community sites (validation R(2)=0.74). The excellent spatio-temporal performance of our model provides a very promising basis for the health effect assessment of the panel study.

Examining the representativeness of home outdoor PM(2.5), EC, and OC estimates for daily personal exposures in Southern California.

Recent studies have linked acute respiratory and cardiovascular outcomes to measurements or estimates of traffic-related air pollutants at homes or schools. However, few studies have evaluated these outdoor measurements and estimates against personal exposure measurements. We compared measured and modeled home outdoor concentrations with personal measurements of traffic-related air pollutants in the Los Angeles air basin (Whittier and Riverside). Personal exposure of 63 children with asthma and 15 homes were assessed for particulate matter with an aerodynamic diameter less than 2.5 µm (PM(2.5)), elemental carbon (EC), and organic carbon (OC) during sixteen 10-day monitoring runs. Regression models to predict daily home outdoor PM(2.5), EC, and OC were constructed using home outdoor measurements, geographical and meteorological parameters, as well as CALINE4 estimates at outdoor home sites, which represent the concentrations from local traffic sources. These home outdoor models showed the variance explained (R(2)) was 0.97 and 0.94 for PM(2.5), 0.91 and 0.83 for OC, and 0.76 and 0.87 for EC in Riverside and Whittier, respectively. The PM(2.5) outdoor estimates correlated well with the personal measurements (Riverside R(2) = 0.65 and Whittier R(2) = 0.69). However, excluding potentially inaccurate samples from Riverside, the correlation between personal exposure to carbonaceous species and home outdoor estimates in Whittier was moderate for EC (R(2) = 0.37) and poor for OC (R(2) = 0.08). The CALINE4 estimates alone were not correlated with personal measurements of EC or other pollutants. While home outdoor estimates provide good approximations for daily personal PM(2.5) exposure, they may not be adequate for estimating daily personal exposure to EC and OC. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11869-010-0099-y) contains supplementary material, which is available to authorized users.