Suchergebnisse

BACKGROUND: Road traffic is the main source of environmental noise in European cities and one of the main environmental risks to health and wellbeing. In this study we aimed to provide an in-depth assessment of available road traffic noise data and to estimate population exposure and health impacts for cities in Europe. METHODS: We conducted the analysis for 724 cities and 25 greater cities in 25 European countries. We retrieved road traffic strategic noise maps delivered under the Environmental Noise Directive (END) or available from local sources. We assessed noise exposure using the 24 h day-evening-night noise level indicator (Lden) starting at exposure levels of 55 dB Lden - based on data availability - for the adult population aged 20 and over (n = 123,966,346). For the adults exposed to noise levels above 55 dB Lden we estimated the health impacts of compliance with the World Health Organization (WHO) recommendation of 53 dB Lden. Two primary health outcomes were assessed: high noise annoyance and Ischemic Heart Disease (IHD), using mortality from IHD causes as indicator. Exposure Response Functions (ERFs) relating road traffic noise exposure to annoyance and IHD mortality were retrieved from the literature. Uncertainties in input parameters were propagated using Monte Carlo simulations to obtain point estimates and empirical 95% Confidence Intervals (CIs). Lastly, the noise maps were categorized as high, moderate and low quality following a qualitative approach. RESULTS: Strategic noise map data was delivered in three distinct formats (i.e. raster, polygon or polyline) and had distinct noise ranges and levels of categorization. The majority of noise maps (i.e. 83.2%) were considered of moderate or low quality. Based on the data provided, almost 60 million adults were exposed to road traffic noise levels above 55 dB Lden, equating to a median of 42% (Interquartile Range (IQR): 31.8-64.8) of the adult population across the analysed cities. We estimated that approximately 11 million adults were highly annoyed by road traffic noise and that 3608 deaths from IHD (95% CI: 843-6266) could be prevented annually with compliance of the WHO recommendation. The proportion of highly annoyed adults by city had a median value of 7.6% (IQR: 5.6-11.8) across the analysed cities, while the number preventable deaths had a median of 2.2 deaths per 100,000 population (IQR: 1.4-3.1). CONCLUSIONS: Based on the provided strategic noise maps a considerable number of adults in European cities are exposed to road traffic noise levels harmful for health. Efforts to standardize the strategic noise maps and to increase noise and disease data availability at the city level are needed. These would allow for a more accurate and comprehensive assessment of the health impacts and further help local governments to address the adverse health effects of road traffic noise.

Background: Road traffic is the main source of environmental noise in European cities and one of the main environmental risks to health and wellbeing. In this study we aimed to provide an in-depth assessment of available road traffic noise data and to estimate population exposure and health impacts for cities in Europe. Methods: We conducted the analysis for 724 cities and 25 greater cities in 25 European countries. We retrieved road traffic strategic noise maps delivered under the Environmental Noise Directive (END) or available from local sources. We assessed noise exposure using the 24 h day-evening-night noise level indicator (Lden) starting at exposure levels of 55 dB Lden - based on data availability - for the adult population aged 20 and over (n = 123,966,346). For the adults exposed to noise levels above 55 dB Lden we estimated the health impacts of compliance with the World Health Organization (WHO) recommendation of 53 dB Lden. Two primary health outcomes were assessed: high noise annoyance and Ischemic Heart Disease (IHD), using mortality from IHD causes as indicator. Exposure Response Functions (ERFs) relating road traffic noise exposure to annoyance and IHD mortality were retrieved from the literature. Uncertainties in input parameters were propagated using Monte Carlo simulations to obtain point estimates and empirical 95% Confidence Intervals (CIs). Lastly, the noise maps were categorized as high, moderate and low quality following a qualitative approach. Results: Strategic noise map data was delivered in three distinct formats (i.e. raster, polygon or polyline) and had distinct noise ranges and levels of categorization. The majority of noise maps (i.e. 83.2%) were considered of moderate or low quality. Based on the data provided, almost 60 million adults were exposed to road traffic noise levels above 55 dB Lden, equating to a median of 42% (Interquartile Range (IQR): 31.8-64.8) of the adult population across the analysed cities. We estimated that approximately 11 million adults were highly annoyed by road traffic noise and that 3608 deaths from IHD (95% CI: 843-6266) could be prevented annually with compliance of the WHO recommendation. The proportion of highly annoyed adults by city had a median value of 7.6% (IQR: 5.6-11.8) across the analysed cities, while the number preventable deaths had a median of 2.2 deaths per 100,000 population (IQR: 1.4-3.1). Conclusions: Based on the provided strategic noise maps a considerable number of adults in European cities are exposed to road traffic noise levels harmful for health. Efforts to standardize the strategic noise maps and to increase noise and disease data availability at the city level are needed. These would allow for a more accurate and comprehensive assessment of the health impacts and further help local governments to address the adverse health effects of road traffic noise.

Background: Multiple omics technologies are increasingly applied to detect early, subtle molecular responses to environmental stressors for future disease risk prevention. However, there is an urgent need for further evaluation of stability and variability of omics profiles in healthy individuals, especially during childhood. Methods: We aimed to estimate intra-, inter-individual and cohort variability of multi-omics profiles (blood DNA methylation, gene expression, miRNA, proteins and serum and urine metabolites) measured 6 months apart in 156 healthy children from five European countries. We further performed a multi-omics network analysis to establish clusters of co-varying omics features and assessed the contribution of key variables (including biological traits and sample collection parameters) to omics variability. Results: All omics displayed a large range of intra- and inter-individual variability depending on each omics feature, although all presented a highest median intra-individual variability. DNA methylation was the most stable profile (median 37.6% inter-individual variability) while gene expression was the least stable (6.6%). Among the least stable features, we identified 1% cross-omics co-variation between CpGs and metabolites (e.g. glucose and CpGs related to obesity and type 2 diabetes). Explanatory variables, including age and body mass index (BMI), explained up to 9% of serum metabolite variability. Conclusions: Methylation and targeted serum metabolomics are the most reliable omics to implement in single time-point measurements in large cross-sectional studies. In the case of metabolomics, sample collection and individual traits (e.g. BMI) are important parameters to control for improved comparability, at the study design or analysis stage. This study will be valuable for the design and interpretation of epidemiological studies that aim to link omics signatures to disease, environmental exposures, or both. ; The study has received funding from the European Community's Seventh Framework Programme (FP7/2007-206) under grant agreement no 308333 (HELIX project) and the H2020-EU.3.1.2. - Preventing Disease Programme under grant agreement no 874583 (ATHLETE project). Additionally, BiB received core infrastructure funding from the Wellcome Trust (WT101597MA) and a joint grant from the UK Medical Research Council (MRC) and Economic and Social Science Research Council (ESRC) (MR/N024397/1). INMA data collections were supported by grants from the Instituto de Salud Carlos III, CIBERESP, and the Generalitat de Catalunya-CIRIT. KANC was funded by the grant of the Lithuanian Agency for Science Innovation and Technology (6-04-2014_31V-66). The Rhea project was financially supported by European projects (EU FP6-2003-Food-3-NewGeneris, EU FP6. STREP Hiwate, EU FP7 ENV.2007.1.2.2.2. Project No 211250 Escape, EU FP7-2008-ENV- 1.2.1.4 Envirogenomarkers, EU FP7-HEALTH-2009- single stage CHICOS, EU FP7 ENV.2008.1.2.1.6. Proposal No 226285 ENRIECO, EU- FP7- HEALTH-2012 Proposal No 308333 HELIX), and the Greek Ministry of Health (Program of Prevention of obesity and neurodevelopmental disorders in preschool children, in Heraklion district, Crete, Greece: 2011- 2014; "Rhea Plus": Primary Prevention Program of Environmental Risk Factors for Reproductive Health, and Child Health: 2012-15). The CRG/UPF Proteomics Unit is part of the Spanish Infrastructure for Omics Technologies (ICTS OmicsTech) and it is a member of the ProteoRed PRB3 consortium which is supported by grant PT17/0019 of the PE I+D+i 2013-2016 from the Instituto de Salud Carlos III (ISCIII) and ERDF. We acknowledge support from the Spanish Ministry of Science and Innovation and State Research Agency through the "Centro de Excelencia Severo Ochoa 2019-2023" Program (CEX2018-000806-S), and support from the Generalitat de Catalunya through the CERCA Program. MV-U and CR-A were supported by a FI fellowship from the Catalan Government (FI-DGR 2015 and #016FI_B 00272). MC received funding from Instituto Carlos III (Ministry of Economy and Competitiveness) (MS16/00128). LM is funded by a Juan de la Cierva-Incorporación fellowship (IJC2018-035394-I) awarded by the Spanish Ministerio de Economía, Industria y Competitividad.