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Background: The association between air pollution exposure and emotional and behavioural problems in children is unclear. We aimed to assess prenatal and postnatal exposure to several air pollutants and child's depressive and anxiety symptoms, and aggressive symptoms in children of 7-11 years. Methods: We analysed data of 13182 children from 8 European population-based birth cohorts. Concentrations of nitrogen dioxide (NO2), nitrogen oxides (NOx), particulate matter (PM) with diameters of

Evidence for the effects of air pollution exposure on lung function growth into adolescence is scarce. We investigated associations of air pollution exposure with lung function and lung function growth until age 16.We conducted both longitudinal (n=915) and cross-sectional (n=721) analyses of associations of air pollution exposure with forced expiratory volume in 1 s (FEV1) and forced vital capacity (FVC) growth from ages eight to 16 and FEV1 and FVC at age 16. We estimated residential concentrations of nitrogen dioxide (NO2), “soot” and particulate matter (PMx, where x is the 50% cut-off aerodynamic diameter in µm) with diameters of 2.5), 10) and 2.5–10 µm (PMcoarse) during the preschool, primary school and secondary school time windows by land use regression models. Associations with (growth in) FEV1 and FVC were analysed by linear (mixed effects) regression.Higher air pollution exposure was associated with reduced FEV1 growth (e.g. adjusted difference −0.26% (95% CI −0.49 to −0.03%) per interquartile range increase in secondary school PM2.5) and lower FEV1 (adjusted difference −2.36% (95% CI −3.76 to −0.94%)), but was not adversely associated with FVC. Associations with FEV1 were stronger in boys than girls and were not modified by asthma status.Higher air pollution exposure may lead to increased airway obstruction, but not reduced lung volume in adolescence.

Background Air pollution has been found to adversely affect children’s lung function. Forced expiratory volume in 1 s and forced vital capacity from spirometry have been studied most frequently, but measurements of airway resistance may provide additional information. We assessed associations of long-term air pollution exposure with airway resistance. Methods We measured airway resistance at age 8 with the interrupter resistance technique (Rint) in participants of the Dutch PIAMA birth cohort study. We linked Rint with estimated annual average air pollution concentrations [nitrogen oxides (NO2, NOx), PM2.5 absorbance (“soot”), and particulate matter

BACKGROUND: Land use regression (LUR) models are commonly used in environmental epidemiology to assign spatially resolved estimates of air pollution to study participants. In this setting, estimated LUR model parameters are assumed to be transportable to a main study (the ''transportability assumption''). We provide an empirical illustration of how violation of this assumption can affect exposure predictions and bias health-effect estimates. METHODS: We based our simulation on two existing LUR models, one for nitrogen dioxide, the other for particulate matter with aerodynamic diameter

Aims: Elevation of a child's blood pressure may cause possible health risks in later life. There is evidence for adverse effects of exposure to air pollution and noise on blood pressure in adults. Little is known about these associations in children. We investigated the associations of air pollution and noise exposure with blood pressure in 12-year-olds. Methods: Blood pressure was measured at age 12 years in 1432 participants of the PIAMA birth cohort study. Annual average exposure to traffic-related air pollution [NO2, mass concentrations of particulate matter with diameters of less than 2.5 μm (PM2.5) and less than 10 μm (PM10), and PM2.5 absorbance] at the participants' home and school addresses at the time of blood pressure measurements was estimated by land-use regression models. Air pollution exposure on the days preceding blood pressure measurements was estimated from routine air monitoring data. Long-term noise exposure was assessed by linking addresses to modelled equivalent road traffic noise levels. Associations of exposures with blood pressure were analysed by linear regression. Effects are presented for an interquartile range increase in exposure. Results: Long-term exposure to NO2 and PM2.5 absorbance were associated with increased diastolic blood pressure, in children who lived at the same address since birth [adjusted mean difference (95% confidence interval) [mmHg] 0.83 (0.06 to 1.61) and 0.75 (-0.08 to 1.58), respectively], but not with systolic blood pressure. We found no association of blood pressure with short-term air pollution or noise exposure. Conclusions: Long-term exposure to traffic-related air pollution may increase diastolic blood pressure in children.

BACKGROUND: Epidemiological evidence on the association between ambient air pollution and breast cancer risk is inconsistent. OBJECTIVE: We examined the association between long-term exposure to ambient air pollution and incidence of postmenopausal breast cancer in European women. METHODS: In 15 cohorts from nine European countries, individual estimates of air pollution levels at the residence were estimated by standardized land-use regression models developed within the European Study of Cohorts for Air Pollution Effects (ESCAPE) and Transport related Air Pollution and Health impacts - Integrated Methodologies for Assessing Particulate Matter (TRANSPHORM) projects: particulate matter (PM) ≤2:5 μm, ≤10 μm, and 2:5–10 μm in diameter (PM2:5, PM10, and PMcoarse, respectively); PM2:5 absorbance; nitrogen oxides (NO2 and NOx); traffic intensity; and elemental composition of PM. We estimated cohort-specific associations between breast cancer and air pollutants using Cox regression models, adjusting for major lifestyle risk factors, and pooled cohort-specific estimates using random-effects meta-analyses. RESULTS: Of 74,750 postmenopausal women included in the study, 3,612 developed breast cancer during 991,353 person-years of follow-up. We found positive and statistically insignificant associations between breast cancer and PM2:5 {hazard ratio (HR) =1:08 [95% confidence interval (CI): 0.77, 1.51] per 5 μg/m3 }, PM10 [1.07 (95% CI: 0.89, 1.30) per 10 μg/m3 ], PMcoarse [1.20 (95% CI: 0.96, 1.49 per 5 μg/m3 ], and NO2 [1.02 (95% CI: 0.98, 1.07 per 10 μg/m3 ], and a statistically significant association with NOx [1.04 (95% CI: 1.00, 1.08) per 20 μg/m3, p =0:04]. CONCLUSIONS: We found suggestive evidence of an association between ambient air pollution and incidence of postmenopausal breast cancer in European women. © 2017, Public Health Services, US Dept of Health and Human Services. All rights reserved. Chemicals/CAS: copper, 15158-11-9, 7440-50-8; iron, 14093-02-8, 53858-86-9, 7439-89-6; nickel, 7440-02-0; nitrogen oxide, 11104-93-1; potassium, 7440-09-7; silicon, 7440-21-3; sulfur, 13981-57-2, 7704-34-9; vanadium, 7440-62-2; zinc, 7440-66-6, 14378-32-6

Long-term ultrafine particle (UFP) exposure estimates at a fine spatial scale are needed for epidemiological studies. Land use regression (LUR) models were developed and evaluated for six European areas based on repeated 30 min monitoring following standardized protocols. In each area; Basel (Switzerland), Heraklion (Greece), Amsterdam, Maastricht, and Utrecht ("The Netherlands"), Norwich (United Kingdom), Sabadell (Spain), and Turin (Italy), 160-240 sites were monitored to develop LUR models by supervised stepwise selection of GIS predictors. For each area and all areas combined, 10 models were developed in stratified random selections of 90% of sites. UFP prediction robustness was evaluated with the intraclass correlation coefficient (ICC) at 31-50 external sites per area. Models from Basel and The Netherlands were validated against repeated 24 h outdoor measurements. Structure and model R2 of local models were similar within, but varied between areas (e.g., 38-43% Turin; 25-31% Sabadell). Robustness of predictions within areas was high (ICC 0.73-0.98). External validation R2 was 53% in Basel and 50% in The Netherlands. Combined area models were robust (ICC 0.93-1.00) and explained UFP variation almost equally well as local models. In conclusion, robust UFP LUR models could be developed on short-term monitoring, explaining around 50% of spatial variance in longer-term measurements.

Several studies have indicated weakly increased risk for kidney cancer among occupational groups exposed to gasoline vapors, engine exhaust, polycyclic aromatic hydrocarbons and other air pollutants, although not consistently. It was the aim to investigate possible associations between outdoor air pollution at the residence and the incidence of kidney parenchyma cancer in the general population. We used data from 14 European cohorts from the ESCAPE study. We geocoded and assessed air pollution concentrations at baseline addresses by land-use regression models for particulate matter (PM10 , PM2.5 , PMcoarse , PM2.5 absorbance (soot)) and nitrogen oxides (NO2 , NOx ), and collected data on traffic. We used Cox regression models with adjustment for potential confounders for cohort-specific analyses and random effects models for meta-analyses to calculate summary hazard ratios (HRs). The 289,002 cohort members contributed 4,111,908 person-years at risk. During follow-up (mean 14.2 years) 697 incident cancers of the kidney parenchyma were diagnosed. The meta-analyses showed higher HRs in association with higher PM concentration, e.g. HR=1.57 (95%CI: 0.81-3.01) per 5μg/m(3) PM2.5 and HR=1.36 (95%CI: 0.84-2.19) per 10(-5) m(-1) PM2.5 absorbance, albeit never statistically significant. The HRs in association with nitrogen oxides and traffic density on the nearest street were slightly above one. Sensitivity analyses among participants who did not change residence during follow-up showed stronger associations, but none were statistically significant. This study provides suggestive evidence that exposure to outdoor PM at the residence may be associated with higher risk for kidney parenchyma cancer; the results should be interpreted cautiously as associations may be due to chance. This article is protected by copyright. All rights reserved.

Background: Few studies have examined the link between air pollution exposure and behavioural problems and learning disorders during late childhood and adolescence. Objectives: To determine whether traffic-related air pollution exposure is associated with hyperactivity/inattention, dyslexia and dyscalculia up to age 15 years using the German GINIplus and LISAplus birth cohorts (recruitment 1995–1999). Methods: Hyperactivity/inattention was assessed using the German parent-completed (10 years) and self-completed (15 years) Strengths and Difficulties Questionnaire. Responses were categorized into normal versus borderline/abnormal. Parent-reported dyslexia and dyscalculia (yes/no) at age 10 and 15 years were defined using parent-completed questionnaires. Individual-level annual average estimates of nitrogen dioxide (NO2), particulate matter (PM)10 mass, PM2.5 mass and PM2.5 absorbance concentrations were assigned to each participant's birth, 10 year and 15 year home address. Longitudinal associations between the air pollutants and the neurodevelopmental outcomes were assessed using generalized estimation equations, separately for both study areas, and combined in a random-effects meta-analysis. Odds ratios and 95% confidence intervals are given per interquartile range increase in pollutant concentration. Results: The prevalence of abnormal/borderline hyperactivity/inattention scores and parental-reported dyslexia and dyscalculia at 15 years of age was 12.9%, 10.5% and 3.4%, respectively, in the combined population (N = 4745). In the meta- analysis, hyperactivity/inattention was associated with PM2.5 mass estimated to the 10 and 15 year addresses (1.12 [1.01, 1.23] and 1.11 [1.01, 1.22]) and PM2.5 absorbance estimated to the 10 and 15 year addresses (1.14 [1.05, 1.25] and 1.13 [1.04, 1.23], respectively). Conclusions: We report associations suggesting a potential link between air pollution exposure and hyperactivity/inattention scores, although these findings require replication. Keywords: Adolescents, Air pollution, Hyperactivity, Inattention, Neurodevelopment

Background Land Use Regression (LUR) is a popular method to explain and predict spatial contrasts in air pollution concentrations, but LUR models for ultrafine particles, such as particle number concentration (PNC) are especially scarce. Moreover, no models have been previously presented for the lung deposited surface area (LDSA) of ultrafine particles. The additional value of ultrafine particle metrics has not been well investigated due to lack of exposure measurements and models. Methods Air pollution measurements were performed in 2011 and 2012 in the eight areas of the Swiss SAPALDIA study at up to 40 sites per area for NO2 and at 20 sites in four areas for markers of particulate air pollution. We developed multi-area LUR models for biannual average concentrations of PM2.5, PM2.5 absorbance, PM10, PMcoarse, PNC and LDSA, as well as alpine, non-alpine and study area specific models for NO2, using predictor variables which were available at a national level. Models were validated using leave-one-out cross-validation, as well as independent external validation with routine monitoring data. Results Model explained variance (R2) was moderate for the various PM mass fractions PM2.5 (0.57), PM10 (0.63) and PMcoarse (0.45), and was high for PM2.5 absorbance (0.81), PNC (0.87) and LDSA (0.91). Study-area specific LUR models for NO2 (R2 range 0.52–0.89) outperformed combined-area alpine (R2 = 0.53) and non-alpine (R2 = 0.65) models in terms of both cross-validation and independent external validation, and were better able to account for between-area variability. Predictor variables related to traffic and national dispersion model estimates were important predictors. Conclusions LUR models for all pollutants captured spatial variability of long-term average concentrations, performed adequately in validation, and could be successfully applied to the SAPALDIA cohort. Dispersion model predictions or area indicators served well to capture the between area variance. For NO2, applying study-area specific models was preferable over applying combined-area alpine/non-alpine models. Correlations between pollutants were higher in the model predictions than in the measurements, so it will remain challenging to disentangle their health effects. Electronic supplementary material The online version of this article (doi:10.1186/s12940-016-0137-9) contains supplementary material, which is available to authorized users.

Background: Particulate matter (PM) air pollution is a human lung carcinogen; however, the components responsible have not been identified. We assessed the associations between PM components and lung cancer incidence. Methods: We used data from 14 cohort studies in eight European countries. We geocoded baseline addresses and assessed air pollution with land-use regression models for eight elements (Cu, Fe, K, Ni, S, Si, V and Zn) in size fractions of PM2.5 and PM10. We used Cox regression models with adjustment for potential confounders for cohort-specific analyses and random effect models for meta-analysis. Results: The 245,782 cohort members contributed 3,229,220 person–years at risk. During follow-up (mean, 13.1 years), 1878 incident cases of lung cancer were diagnosed. In the meta-analyses, elevated hazard ratios (HRs) for lung cancer were associated with all elements except V; none was statistically significant. In analyses restricted to participants who did not change residence during follow-up, statistically significant associations were found for PM2.5 Cu (HR, 1.25; 95% CI, 1.01–1.53 per 5 ng/m3), PM10 Zn (1.28; 1.02–1.59 per 20 ng/m3), PM10 S (1.58; 1.03–2.44 per 200 ng/m3), PM10 Ni (1.59; 1.12–2.26 per 2 ng/m3) and PM10 K (1.17; 1.02–1.33 per 100 ng/m3). In two-pollutant models, associations between PM10 and PM2.5 and lung cancer were largely explained by PM2.5 S. Conclusions: This study indicates that the association between PM in air pollution and lung cancer can be attributed to various PM components and sources. PM containing S and Ni might be particularly important. Keywords: Air pollution, Particulate matter, Sulfur, Nickel, Cohort study, Lung cancer

Summary Background Previous published analyses have focused on the effect of air pollution on asthma and rhinoconjunctivitis throughout early and middle childhood. However, the role of exposure to air pollution in the development of childhood and adolescent asthma and rhinoconjunctivitis remains unclear. We aimed to assess the longitudinal associations between exposure to air pollution and development of asthma and rhinoconjunctivitis throughout childhood and adolescence. Methods We did a population-based birth cohort study of 14 126 participants from four prospective birth cohort studies from Germany, Sweden, and the Netherlands with 14–16 years of follow-up. We linked repeated questionnaire reports of asthma and rhinoconjunctivitis with annual average air pollution concentrations (nitrogen dioxide [NO 2 ], particulate matter [PM] with a diameter of less than 2·5 μm [PM 2·5 ], less than 10 μm [PM 10 ], and between 2·5 μm and 10 μm [PM coarse ], and PM 2·5 absorbance [indicator of soot]) at the participants' home addresses. We analysed longitudinal associations of air pollution exposure at participants' birth addresses and addresses at the time of follow-up with asthma and rhinoconjunctivitis incidence and prevalence in cohort-specific analyses, with subsequent meta-analysis and pooled analyses. Findings Overall, the risk of incident asthma up to age 14–16 years increased with increasing exposure to NO 2 (adjusted meta-analysis odds ratio [OR] 1·13 per 10 μg/m 3 [95% CI 1·02–1·25]) and PM 2·5 absorbance (1·29 per 1 unit [1·00–1·66]) at the birth address. A similar, albeit non-significant, trend was shown for PM 2·5 and incident asthma (meta-analysis OR 1·25 per 5 μg/m 3 [95% CI 0·94–1·66]). These associations with asthma were more consistent after age 4 years than before that age. There was no indication of an adverse effect of air pollution on rhinoconjunctivitis. Interpretation Exposure to air pollution early in life might contribute to the development of asthma throughout childhood and adolescence, particularly after age 4 years, when asthma can be more reliably diagnosed. Reductions in levels of air pollution could help to prevent the development of asthma in children. Funding The European Union.

Background: Childhood blood pressure is an important predictor of hypertension and cardiovascular disease in adulthood. Evidence for an association between ambient particulate matter (PM) exposure and blood pressure is increasing, but little is known about the relevance of different PM constituents. Objectives: We investigated the association between particulate matter composition and blood pressure at age 12 years. Methods: Annual average concentrations of copper, iron, potassium, nickel, sulfur, silicon, vanadium, and zinc in particles with diameters of less than 2.5 μm (PM2.5) and 10 μm (PM10) were estimated by land-use regression modeling for the home addresses of the participants of the prospective PIAMA birth cohort study. Associations between element concentrations and blood pressure measurements performed at age 12 years were investigated by linear regression with and without adjustment for confounders. Results: After adjustment for potential confounders we found statistically significant positive associations of diastolic blood pressure with iron, silicon, and potassium in PM10 in children who lived at the same address since birth [mean difference (95% confidence interval) 0.67 (0.02;1.31) mm Hg, 0.85 (0.18;1.52) mm Hg, and 0.75 (0.09;1.41) mm Hg, respectively, per interquartile range increase in exposure]. Also, we found marginally significant (p

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.

Background: ambient particulate matter (PM) exposure is associated with children's respiratory health. little is known about the importance of different PM constituents. We investigated the effects of PM constituents on asthma, allergy, and lung function until the age of 11-12 years. Methods: For 3,702 participants of a prospective birth cohort study, questionnaire-reported asthma and hay fever and measurements of allergic sensitization and lung function were linked with annual average concentrations of copper, iron, potassium, nickel, sulfur, silicon, vanadium, and zinc in particles with diameters of less than 2.5 and 10 μm (PM2.5 and PM10) at birth addresses and current addresses from land-use regression models. exposure-health relations were analyzed by multiple (repeated measures) logistic and linear regressions. Results: asthma incidence and prevalence of asthma symptoms and rhinitis were positively associated with zinc in PM10 at the birth address (odds ratio [95% confidence interval] per interquartile range increase in exposure 1.13 [1.02, 1.25], 1.08 [1.00, 1.17], and 1.16 [1.04, 1.30], respectively). Moreover, asthma symptoms were positively associated with copper in PM10 at the current address (1.06 [1.00, 1.12]). allergic sensitization was positively associated with copper and iron in PM10 at the birth address (relative risk [95% con-fidence interval] 1.07 [1.01, 1.14] and 1.10 [1.03, 1.18]) and current address. Forced expiratory volume in 1 second was negatively associated with copper and iron in PM2.5 (change [95% confidence interval]-2.1% [-1.1,-0.1%] and-1.0% [-2.0,-0.0%]) and FeF75-50 with copper in PM10 at the current address (-2.3% [-4.3,-0.3%]). Conclusion: PM constituents, in particular iron, copper, and zinc, reflecting poorly regulated non-tailpipe road traffic emissions, may increase the risk of asthma and allergy in schoolchildren.

The aim of this study was to determine the effect of six traffic-related air pollution metrics (nitrogen dioxide, nitrogen oxides, particulate matter with an aerodynamic diameter 10), PM2.5, coarse particulate matter and PM2.5 absorbance) on childhood asthma and wheeze prevalence in five European birth cohorts: MAAS (England, UK), BAMSE (Sweden), PIAMA (the Netherlands), GINI and LISA (both Germany, divided into north and south areas).Land-use regression models were developed for each study area and used to estimate outdoor air pollution exposure at the home address of each child. Information on asthma and current wheeze prevalence at the ages of 4–5 and 8–10 years was collected using validated questionnaires. Multiple logistic regression was used to analyse the association between pollutant exposure and asthma within each cohort. Random-effects meta-analyses were used to combine effect estimates from individual cohorts.The meta-analyses showed no significant association between asthma prevalence and air pollution exposure (e.g. adjusted OR (95%CI) for asthma at age 8–10 years and exposure at the birth address (n=10377): 1.10 (0.81–1.49) per 10 μg·m-3 nitrogen dioxide; 0.88 (0.63–1.24) per 10 μg·m-3 PM10; 1.23 (0.78–1.95) per 5 μg·m-3 PM2.5). This result was consistently found in initial crude models, adjusted models and further sensitivity analyses.This study found no significant association between air pollution exposure and childhood asthma prevalence in five European birth cohorts.