Spatial variability of nitrogen dioxide and formaldehydeand residential exposure of children in the industrial area of Viadana, Northern Italy

Chipboard production is a source of ambient air pollution. We assessed the spatial variability of outdoor pollutants and residentialexposure of children living in proximity to the largest chipboard industry in Italy and evaluated the reliability of exposureestimates obtained from a number of available models. We obtained passive sampling data on NO2and formaldehyde collectedby the Environmental Protection Agency of Lombardy region at 25 sites in the municipality of Viadana during 10 weeks (2017-2018) and compared NO2measurements with average weekly concentrations from continuous monitors. We compared interpo-lated NO2and formaldehyde surfaces with previous maps for 2010. We assessed the relationship between residential proximity tothe industry and pollutant exposures assigned using these maps, as well as other available countrywide/continental models basedon routine data on NO2, PM10, andPM2.5. The correlation between NO2concentrations from continuous and passive samplingwas high (Pearson'sr= 0.89), although passive sampling underestimated NO2especially during winter. For both 2010 and 2017-2018, we observed higher NO2and formaldehyde concentrations in the south of Viadana, with hot-spots in proximity to theindustry. PM10and PM2.5exposures were higher for children at 3.5 km to theindustry, whereas NO2exposure was higher at 1-1.7 km to the industry. Road and population densities were also higher close tothe industry. Findings from a variety of exposure models suggest that children living in proximity to the chipboard industry inViadana are more exposed to air pollution and that exposure gradients are relatively stable over time

Association between Asthma Control and Exposure to Greenness and Other Outdoor and Indoor Environmental Factors: A Longitudinal Study on a Cohort of Asthmatic Children

Achieving and maintaining asthma control (AC) is the main goal of asthma management. Indoor and outdoor environmental factors may play an important role on AC. The aim of this longitudinal study was to evaluate the association between AC and exposure to greenness and other outdoor or indoor environmental factors in a cohort of asthmatic children. This study involved 179 asthmatic children (5–16 years). Parents were interviewed through a modified version of the SIDRIA questionnaire. AC was assessed at each visit. Exposure to greenness was measured using the normalized difference vegetation index (NDVI). A logistic regression model was applied for assessing risk factors for uncontrolled asthma (UA). Low NDVI exposure was a risk factor for UA (OR: 2.662, 95% CI (1.043–6.799)); children exposed to passive smoke during pregnancy had a higher risk of UA than those non-exposed to passive smoke during pregnancy (OR: 3.816, 95% CI (1.114–13.064)); and a unit increase in the crowding index was associated with an increased risk of UA (OR: 3.376, 95% CI (1.294–8.808)). In conclusion, the current study provided a comprehensive assessment of urban-related environmental exposures on asthma control in children, using multiple indicators of greenness and other outdoor or indoor environmental factors

Air pollution exposure during pregnancy and childhood autistic traits in four European population-based cohort studies : the ESCAPE project

Background: Prenatal exposure to air pollutants has been suggested as a possible etiologic factor for the occurrence of autism spectrum disorder. Objectives: We aimed to assess whether prenatal air pollution exposure is associated with childhood autistic traits in the general population. Methods: Ours was a collaborative study of four European population-based birth/child cohorts— CATSS (Sweden), Generation R (the Netherlands), GASPII (Italy), and INMA (Spain). Nitrogen oxides (NO2, NOx) and particulate matter (PM) with diameters of ≤ 2.5 μm (PM2.5), ≤ 10 μm (PM10), and between 2.5 and 10 μm (PMcoarse), and PM2.5 absorbance were estimated for birth addresses by land-use regression models based on monitoring campaigns performed between 2008 and 2011. Levels were extrapolated back in time to exact pregnancy periods. We quantitatively assessed autistic traits when the child was between 4 and 10 years of age. Children were classified with autistic traits within the borderline/clinical range and within the clinical range using validated cut-offs. Adjusted cohort-specific effect estimates were combined using random-effects meta-analysis. Results: A total of 8,079 children were included. Prenatal air pollution exposure was not associated with autistic traits within the borderline/clinical range (odds ratio = 0.94; 95% CI: 0.81, 1.10 per each 10‑μg/m3 increase in NO2 pregnancy levels). Similar results were observed in the different cohorts, for the other pollutants, and in assessments of children with autistic traits within the clinical range or children with autistic traits as a quantitative score. Conclusions: Prenatal exposure to NO2 and PM was not associated with autistic traits in children from 4 to 10 years of age in four European population-based birth/child cohort studies.NonePublishe

Air Pollution Exposure during Pregnancy and Childhood Autistic Traits in Four European Population-Based Cohort Studies: The ESCAPE Project

Background: Prenatal exposure to air pollutants has been suggested as a possible etiologic factor for the occurrence of autism spectrum disorder. Objectives: We aimed to assess whether prenatal air pollution exposure is associated with childhood autistic traits in the general population. Methods: Ours was a collaborative study of four European population-based birth/child cohorts—CATSS (Sweden), Generation R (the Netherlands), GASPII (Italy), and INMA (Spain). Nitrogen oxides (NO2, NOx) and particulate matter (PM) with diameters of ≤ 2.5 μm (PM2.5), ≤ 10 μm (PM10), and between 2.5 and 10 μm (PMcoarse), and PM2.5 absorbance were estimated for birth addresses by land-use regression models based on monitoring campaigns performed between 2008 and 2011. Levels were extrapolated back in time to exact pregnancy periods. We quantitatively assessed autistic traits when the child was between 4 and 10 years of age. Children were classified with autistic traits within the borderline/clinical range and within the clinical range using validated cut-offs. Adjusted cohort-specific effect estimates were combined using random-effects meta-analysis. Results: A total of 8,079 children were included. Prenatal air pollution exposure was not associated with autistic traits within the borderline/clinical range (odds ratio = 0.94; 95% CI: 0.81, 1.10 per each 10-μg/m3 increase in NO2 pregnancy levels). Similar results were observed in the different cohorts, for the other pollutants, and in assessments of children with autistic traits within the clinical range or children with autistic traits as a quantitative score. Conclusions: Prenatal exposure to NO2 and PM was not associated with autistic traits in children from 4 to 10 years of age in four European population-based birth/child cohort studies.Funding was provided as follows: ESCAPE Project— European Community’s Seventh Framework Program (FP7/2007-2011-GA#211250). CATSS, Sweden— Swedish Research Council for Health, Working Life and Welfare (FORTE), Swedish Research Council (VR) Formas, in partner hip with FORTE and VINNOVA (cross-disciplinary research program concerning children’s and young people’s mental health); VR through the Swedish Initiative for Research on Microdata in the Social And Medical Sciences (SIMSAM) framework grant 340-2013-5867; HKH Kronprinsessan Lovisas förening för barnasjukvård; and the Strategic Research Program in Epidemiology at Karolinska Institutet. Generation R, the Netherlands—The Generation R Study is conducted by the Erasmus University Medical Center in close collaboration with the School of Law and Faculty of Social Sciences of the Erasmus University Rotterdam; the Municipal Health Service Rotterdam area, Rotterdam; the Rotterdam Homecare foundation, Rotterdam; and the Stichting Trombosedienst & Artsenlaboratorium Rijnmond (STAR-MDC), Rotterdam. The general design of the Generation R Study is made possible by financial support from the Erasmus University Medical Center, Rotterdam; the Erasmus University Rotterdam; the Netherlands Organization for Health Research and Development (ZonMw); the Netherlands Organization for Scientific Research (NWO); and the Ministry of Health, Welfare and Sport. The Netherlands Organisation for Applied Scientific Research (TNO) received funding from the Netherlands Ministry of Infrastructure and the Environment to support exposure assessment. GASPII, Italy—grant from the Italian Ministry of Health (ex art.12, 2001). INMA, Spain— grants from Instituto de Salud Carlos III (Red INMA G03/176 and CB06/02/0041 FIS-FEDER 03/1615, 04/1509, 04/1112, 04/1931, 05/1079, 05/1052, 06/1213, 07/0314, 09/02647, 11/01007, 11/02591, CP11/00178, FIS-PI041436, FIS-PI081151, FIS-PI06/0867, FIS-PS09/00090), PI13/1944, PI13_02032, PI14/0891, PI14/1687, MS13/00054, UE (FP7-ENV-2011 cod 282957, and HEALTH.2010.2.4.5-1); Generalitat de Catalunya-CIRIT 1999SGR 00241; La Fundació La Marató de TV3 (090430); Conselleria de Sanitat Generalitat Valenciana; Department of Health of the Basque Government (2005111093 and 2009111069); and Provincial Government of Gipuzkoa (DFG06/004 and DFG08/001). V.W.V.J. received an additional grant from the Netherlands Organization for Health Research and Development (ZonMw 90700303, 916.10159). A.G.’s work was supported by a research grant from the European Community’s 7th Framework Programme (FP7/2008–2013-GA#212652). A full roster of the INMA project investigators can be found online (http://www. proyectoinma.org/presentacion-inma/listado-investigadores/ en_listado-investigadores.html)

Особливості державного регулювання інвестиційно-інноваційної діяльності, в сфері екології

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/m(3)), PM10 Zn (1.28; 1.02-1.59 per 20 ng/m(3)), PM10 S (1.58; 1.03-2.44 per 200 ng/m(3)), PM10 Ni (1.59; 1.12-2.26 per 2 ng/m(3)) and PM10 K (1.17; 1.02-1.33 per 100 ng/m(3)). 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