37 research outputs found

    Hypertension and Exposure to Noise near Airports (HYENA): Study Design and Noise Exposure Assessment

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    An increasing number of people live near airports with considerable noise and air pollution. The Hypertension and Exposure to Noise near Airports (HYENA) project aims to assess the impact of airport-related noise exposure on blood pressure (BP) and cardiovascular disease using a cross-sectional study design. We selected 6,000 persons (45–70 years of age) who had lived at least 5 years near one of six major European airports. We used modeled aircraft noise contours, aiming to maximize exposure contrast. Automated BP instruments are used to reduce observer error. We designed a standardized questionnaire to collect data on annoyance, noise disturbance, and major confounders. Cortisol in saliva was collected in a subsample of the study population (n = 500) stratified by noise exposure level. To investigate short-term noise effects on BP and possible effects on nighttime BP dipping, we measured 24-hr BP and assessed continuous night noise in another sub-sample (n = 200). To ensure comparability between countries, we used common noise models to assess individual noise exposure, with a resolution of 1 dB(A). Modifiers of individual exposure, such as the orientation of living and bedroom toward roads, window-opening habits, and sound insulation, were assessed by the questionnaire. For four airports, we estimated exposure to air pollution to explore modifying effects of air pollution on cardiovascular disease. The project assesses exposure to traffic-related air pollutants, primarily using data from another project funded by the European Union (APMoSPHERE, Air Pollution Modelling for Support to Policy on Health and Environmental Risks in Europe)

    Hypertension and Exposure to Noise Near Airports: the HYENA Study

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    We compare two approaches for high-level power estimation of DSP components implemented in FPGAs for different sets of data streams from real-world applications. The first model is a power macro-model based on the Hamming distance of input signals. The second model is an analytical high-level power model based on switching activity computation and knowledge about the component’s internal structure, which has been improved to also consider additional information on the signal distribution of two consecutive input vectors. The results show that the accuracy of both models is, in most cases, within 10% of the low-level power estimates given by the tool XPower when cycle-bycycle input signal distributions are taken into account, and that the difference between the model accuracies depends significantly on the nature of the signals. Additionally, the effort required for the characterization and construction of the models for different component structures is discussed in detail

    Updated exposure-response relationship between road traffic noise and coronary heart diseases: A meta-analysis

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    A meta-analysis of 14 studies (17 individual effect estimates) on the association between road traffic noise and coronary heart diseases was carried out. A significant pooled estimate of the relative risk of 1.08 (95% confidence interval: 1.04, 1.13) per increase of the weighted day-night noise level L DN of 10 dB (A) was found within the range of approximately 52-77 dB (A) (5 dB-category midpoints). The results gave no statistically significant indication of heterogeneity between the results of individual studies. However, stratified analyses showed that the treatment of gender in the studies, the lowest age of study subjects and the lowest cut-off of noise levels had an impact on the effect estimates of different studies. The result of the meta-analysis complies quantitatively with the result of a recent meta-analysis on the association between road traffic noise and hypertension. Road traffic noise is a significant risk factor for cardiovascular diseases

    Cardiovascular effects of noise

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