Ming-Yi Tsai

Adult lung function and long-term air pollution exposure. ESCAPE: a multicentre cohort study and meta-analysis

The chronic impact of ambient air pollutants on lung function in adults is not fully understood. The objective of this study was to investigate the association of long-term exposure to ambient air pollution with lung function in adult participants from five cohorts in the European Study of Cohorts for Air Pollution Effects (ESCAPE). Residential exposure to nitrogen oxides (NO2, NOx) and particulate matter (PM) was modelled and traffic indicators were assessed in a standardised manner. The spirometric parameters forced expiratory volume in 1 s (FEV1) and forced vital capacity (FVC) from 7613 subjects were considered as outcomes. Cohort-specific results were combined using meta-analysis. We did not observe an association of air pollution with longitudinal change in lung function, but we observed that a 10 μg·m−3 increase in NO2 exposure was associated with lower levels of FEV1 (−14.0 mL, 95% CI −25.8 to −2.1) and FVC (−14.9 mL, 95% CI −28.7 to −1.1). An increase of 10 μg·m−3 in PM10, but not other PM metrics (PM2.5, coarse fraction of PM, PM absorbance), was associated with a lower level of FEV1 (−44.6 mL, 95% CI −85.4 to −3.8) and FVC (−59.0 mL, 95% CI −112.3 to −5.6). The associations were particularly strong in obese persons. This study adds to the evidence for an adverse association of ambient air pollution with lung function in adults at very low levels in Europe. The ESCAPE study finds that, even at very low levels, air pollution has adverse effects on lung function in adults http://ow.ly/A1ssB

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

BACKGROUNDnShort-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.nnnOBJECTIVEnWe aimed to investigate the association between air pollution and adult onset asthma.nnnMETHODSnAsthma 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.nnnRESULTSnIn 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).nnnCONCLUSIONSnResults 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.

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 (PM10, PM2.5, PMabsorbance, PMcoarse), NO2, nitrogen oxides (NOx) 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 ≥3u2005months of the year for ≥2u2005years), 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 15u2005279 and 10u2005537 participants respectively were included in the main NO2 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 NO2 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 PMcoarse OR 1.31 (1.05 to 1.64) per 5u2005µg/m3 increase and PM10 with similar effect size. Sensitivity analyses of older cohorts showed increased risk of chronic cough with PM2.5abs (black carbon) exposures. Conclusions Results do not show consistent associations between chronic bronchitis symptoms and current traffic-related air pollution in adult European populations.

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.

Socioeconomic position and outdoor nitrogen dioxide (NO2) exposure in Western Europe: A multi-city analysis.

BACKGROUNDnInconsistent associations between socioeconomic position (SEP) and outdoor air pollution have been reported in Europe, but methodological differences prevent any direct between-study comparison.nnnOBJECTIVESnAssess and compare the association between SEP and outdoor nitrogen dioxide (NO2) exposure as a marker of traffic exhaust, in 16 cities from eight Western European countries.nnnMETHODSnThree SEP indicators, two defined at individual-level (education and occupation) and one at neighborhood-level (unemployment rate) were assessed in three European multicenter cohorts. NO2 annual concentration exposure was estimated at participants addresses with land use regression models developed within the European Study of Cohorts for Air Pollution Effects (ESCAPE; http://www.escapeproject.eu/). Pooled and city-specific linear regressions were used to analyze associations between each SEP indicator and NO2. Heterogeneity across cities was assessed using the Higgins I-squared test (I2).nnnRESULTSnThe study population included 5692 participants. Pooled analysis showed that participants with lower individual-SEP were less exposed to NO2. Conversely, participants living in neighborhoods with higher unemployment rate were more exposed. City-specific results exhibited strong heterogeneity (I2>76% for the three SEP indicators) resulting in variation of the individual- and neighborhood-SEP patterns of NO2 exposure across cities. The coefficients from a model that included both individual- and neighborhood-SEP indicators were similar to the unadjusted coefficients, suggesting independent associations.nnnCONCLUSIONSnOur study showed for the first time using homogenized measures of outcome and exposure across 16 cities the important heterogeneity regarding the association between SEP and NO2 in Western Europe. Importantly, our results showed that individual- and neighborhood-SEP indicators capture different aspects of the association between SEP and exposure to air pollution, stressing the importance of considering both in air pollution health effects studies.

Air pollution modelling for birth cohorts: a time-space regression model.

BackgroundTo investigate air pollution effects during pregnancy or in the first weeks of life, models are needed that capture both the spatial and temporal variability of air pollution exposures.MethodsWe developed a time-space exposure model for ambient NO2 concentrations in Bern, Switzerland. We used NO2 data from passive monitoring conducted between 1998 and 2009: 101 rural sites (24,499 biweekly measurements) and 45 urban sites (4350 monthly measurements). We evaluated spatial predictors (land use; roads; traffic; population; annual NO2 from a dispersion model) and temporal predictors (meteorological conditions; NO2 from continuous monitoring station). Separate rural and urban models were developed by multivariable regression techniques. We performed ten-fold internal cross-validation, and an external validation using 57 NO2 passive measurements obtained at study participant’s homes.ResultsTraffic related explanatory variables and fixed site NO2 measurements were the most relevant predictors in both models. The coefficient of determination (R2) for the log transformed models were 0.63 (rural) and 0.54 (urban); cross-validation R2s were unchanged indicating robust coefficient estimates. External validation showed R2s of 0.54 (rural) and 0.67 (urban).ConclusionsThis approach is suitable for air pollution exposure prediction in epidemiologic research with time-vulnerable health effects such as those occurring during pregnancy or in the first weeks of life.

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.

Oxidative stress and inflammation mediate the effect of air pollution on cardio‐ and cerebrovascular disease: A prospective study in nonsmokers

Air pollution is associated with a broad range of adverse health effects, including mortality and morbidity due to cardio‐ and cerebrovascular diseases (CCVD), but the molecular mechanisms involved are not entirely understood. This study aims to investigate the involvement of oxidative stress and inflammation in the causal chain, and to identify intermediate biomarkers that are associated retrospectively with the exposure and prospectively with the disease. We designed a case‐control study on CCVD nested in a cohort of 18,982 individuals from the EPIC‐Italy study. We measured air pollution, inflammatory biomarkers, and whole‐genome DNA methylation in blood collected up to 17 years before the diagnosis. The study sample includes all the incident CCVD cases among former‐ and never‐smokers, with available stored blood sample, that arose in the cohort during the follow‐up. We identified enrichment of altered DNA methylation in “ROS/Glutathione/Cytotoxic granules” and “Cytokine signaling” pathways related genes, associated with both air pollution (multiple comparisons adjusted p for enrichment ranging from 0.01 to 0.03 depending on pollutant) and with CCVD risk (Pu2009=u20090.04 and Pu2009=u20090.03, respectively). Also, Interleukin‐17 was associated with higher exposure to NO2 (Pu2009=u20090.0004), NOx (Pu2009=u20090.0005), and CCVD risk (ORu2009=u20091.79; CI 1.04–3.11; Pu2009=u20090.04 comparing extreme tertiles). Our findings indicate that chronic exposure to air pollution can lead to oxidative stress, which in turn activates a cascade of inflammatory responses mainly involving the “Cytokine signaling” pathway, leading to increased risk of CCVD. Inflammatory proteins and DNA methylation alterations can be detected several years before CCVD diagnosis in blood samples, being promising preclinical biomarkers. Environ. Mol. Mutagen. 59:234–246, 2018.

Land use regression models for the oxidative potential of fine particles (PM2.5) in five European areas

Abstract Oxidative potential (OP) of particulate matter (PM) is proposed as a biologically‐relevant exposure metric for studies of air pollution and health. We aimed to evaluate the spatial variability of the OP of measured PM2.5 using ascorbate (AA) and (reduced) glutathione (GSH), and develop land use regression (LUR) models to explain this spatial variability. We estimated annual average values (m−3) of OPAA and OPGSH for five areas (Basel, CH; Catalonia, ES; London‐Oxford, UK (no OPGSH); the Netherlands; and Turin, IT) using PM2.5 filters. OPAA and OPGSH LUR models were developed using all monitoring sites, separately for each area and combined‐areas. The same variables were then used in repeated sub‐sampling of monitoring sites to test sensitivity of variable selection; new variables were offered where variables were excluded (p > .1). On average, measurements of OPAA and OPGSH were moderately correlated (maximum Pearsons maximum Pearsons R = = .7) with PM2.5 and other metrics (PM2.5absorbance, NO2, Cu, Fe). HOV (hold‐out validation) R2 for OPAA models was .21, .58, .45, .53, and .13 for Basel, Catalonia, London‐Oxford, the Netherlands and Turin respectively. For OPGSH, the only model achieving at least moderate performance was for the Netherlands (R2 = .31). Combined models for OPAA and OPGSH were largely explained by study area with weak local predictors of intra‐area contrasts; we therefore do not endorse them for use in epidemiologic studies. Given the moderate correlation of OPAA with other pollutants, the three reasonably performing LUR models for OPAA could be used independently of other pollutant metrics in epidemiological studies. Graphical abstract Figure. No Caption available. HighlightsOP moderately correlated (r ˜.6) with PM2.5 mass, NO2, and elemental constituents.OPAA and OPGSH LUR models were developed and evaluated for five areas.Three reasonably performing (R2: .45–.58) OPAA LUR models in hold‐out validation.OPGSH models were not robust to new coefficients derived against sub‐samples of sites.