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Objectives We aimed to evaluate cardiovascular (CV) risk in patients with idiopathic inflammatory myopathies (IIM) compared with healthy controls (HC) and to assess its association with disease-specific features. Methods Ninety IIM patients and 180 age-/sex-matched HC were included. Subjects with a history of CV disease (angina pectoris, myocardial infarction and cerebrovascular/peripheral arterial vascular events) were excluded. All participants were prospectively recruited and underwent examinations of carotid intima–media thickness (CIMT), pulse wave velocity (PWV), ankle-brachial index (ABI), and body composition. The risk of fatal CV events was evaluated by the Systematic COronary Risk Evaluation (SCORE) and its modifications. Results Compared with HC, IIM patients had a significantly higher prevalence of traditional CV risk factors, carotid artery disease (CARD), abnormal ABI and PWV. After propensity score matching (using traditional CV risk factors), the prevalence of CARD and pathological PWV remained significantly higher in IIM than HC. No significant difference in SCORE was observed. The most unfavourable CV risk profile was observed in patients with necrotizing myopathy, especially in statin-induced anti-HMGCR+ patients. The calculated CV risk scores by SCORE, SCORE2 and SCORE multiplied by the coefficient 1.5 (mSCORE) were reclassified according to CIMT and the presence of carotid plaques. SCORE was demonstrated to be most inaccurate in predicting CV risk in IIM. Age, disease activity, lipid profile, body composition parameters and blood pressure were the most significant predictors of CV risk in IIM patients. Conclusion Significantly higher prevalence of traditional risk factors and subclinical atherosclerosis was observed in IIM patients compared with HC. [ABSTRACT FROM AUTHOR]

As part of the ICARUS (Integrated Climate forcing and Air pollution Reduction in Urban Systems) H2020 EU project, sampling campaigns took place in seven European cities (Athens, Basel, Brno, Ljubljana, Madrid, Milan, Thessaloniki), aiming to characterize urban population exposure to air pollutants, altogether with over 600 participants from over 250 households. By combining spatio-temporal information on air pollution and activity data of individuals, we were able to identify individual exposure profiles and to aggregate information according to specific micro-environments and activity. Personal exposure reports were then prepared and distributed to all participants. In this paper the overall experience gained conducting sampling campaigns in all seven cities is summarised, focusing on the following aspects: sensors selection and evaluation, development of the overall study design, data harmonisation and building of supporting ICT infrastructure, as well as overall feasibility evaluation including user experience as reported by both participants and field workers. [ABSTRACT FROM AUTHOR]

In this study, the emission changes for the city of Brno in the Czech Republic following the implementation of four policy measures focused on transport and energy were assessed simultaneously for nine air pollutants and three greenhouse gases (GHGs). The policy measure related to the reduction of the motorised vehicles in the city and subsequent increase in use of soft transport was the one with the highest emission reduction potential for most of the compounds investigated (e.g. up to 13% decrease for PM2.5 and NOx). Such type of measures, which have a higher positive effect on human health and climate change than those on low-carbon vehicles, are difficult to implement as they require a behavioral change. Therefore, they should be implemented along additional measures which can be easily implemented such as those on the replacement of old coal-fired boilers. This study highlighted the need for an integrated impact assessment of policy measures, considering both air pollutants and GHGs. [ABSTRACT FROM AUTHOR]

A total number of 471 soil samples collected during the period of 1996-2006 from the agricultural and forest areas of the Czech Republic were analyzed for their content of persistent organic pollutants (POPs). Spatial variability of the POP concentrations was assessed using an IDW spatial GIS model analysis. For every grid of the network, resulting modeled levels of contamination allowed for estimation of the total burden of POPs in soils. Potential risks associated with contaminated soils were assessed as well. Database of the old ecological burdens counting 3061 sampling sites was used to adjust the model and incorporate the risks of heavily contaminated sites. The high levels of health risks were only found at less than 1% of the area of interest. The IDW modeling proved to be a useful tool for screening of the health risks in the large areas with scarce monitoring data. Presented approach can be applied in the risk management, to support an efficient targeting of the risk reduction measures, or to improve a design of the national monitoring.