Auditory and non-auditory effects of noise on health

Noise is pervasive in everyday life and can cause both auditory and non-auditory health eff ects. Noise-induced hearing loss remains highly prevalent in occupational settings, and is increasingly caused by social noise exposure (eg, through personal music players). Our understanding of molecular mechanisms involved in noise-induced haircell and nerve damage has substantially increased, and preventive and therapeutic drugs will probably become available within 10 years. Evidence of the non-auditory eff ects of environmental noise exposure on public health is growing. Observational and experimental studies have shown that noise exposure leads to annoyance, disturbs sleep and causes daytime sleepiness, aff ects patient outcomes and staff performance in hospitals, increases the occurrence of hypertension and cardiovascular disease, and impairs cognitive performance in schoolchildren. In this Review, we stress the importance of adequate noise prevention and mitigation strategies for public health.

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Auditory and non-auditory eff ects of noise on health

The health impacts of environmental noise are a growing concern. At least one million healthy life years are lost every year from traffic-related noise in the western part of Europe. This publication summarises the evidence on the relationship between environmental noise and health effects, including cardiovascular disease, cognitive impairment, sleep disturbance, tinnitus, and annoyance. For each one, the environmental burden of disease methodology, based on exposure-response relationship, exposure distribution, background prevalence of disease and disability weights of the outcome, is applied to calculate the burden of disease in terms of disability-adjusted life-years. Data are still lacking for the rest of the WHO European Region. This publication provides policy-makers and their advisers with technical support in their quantitative risk assessment of environmental noise. International, national and local authorities can use the procedure for estimating burdens presented here to prioritize and plan environmental and public health policies.

Burden of Disease from Environmental Noise: Quantification of Healthy Life Years Lost in Europe

Improving health through policies that promote active travel: a review of evidence to support integrated health impact assessment

The role of noise as an environmental pollutant and its impact on health are being increasingly recognized. Beyond its effects on the auditory system, noise causes annoyance and disturbs sleep, and it impairs cognitive performance. Furthermore, evidence from epidemiologic studies demonstrates that environmental noise is associated with an increased incidence of arterial hypertension, myocardial infarction, and stroke. Both observational and experimental studies indicate that in particular night-time noise can cause disruptions of sleep structure, vegetative arousals (e.g. increases of blood pressure and heart rate) and increases in stress hormone levels and oxidative stress, which in turn may result in endothelial dysfunction and arterial hypertension. This review focuses on the cardiovascular consequences of environmental noise exposure and stresses the importance of noise mitigation strategies for public health.

https://www.klein-winternheim.de/lokale-agenda/d43d5e550c96630fc05d6c66ec88f0f4_Elsner-eurheartj.ehu030.full.pdf

Cardiovascular effects of environmental noise exposure

We present a model of the distribution of noise annoyance with the mean varying as a function of the noise exposure. Day-night level (DNL) and day-evening-night level (DENL) were used as noise descriptors. Because the entire annoyace distribution has been modeled, any annoyance measure that summarizes this distribution can be calculated from the model. We fitted the model to data from noise annoyance studies for aircraft, road traffic, and railways separately. Polynomial approximations of relationships implied by the model for the combinations of the following exposure and annoyance measures are presented: DNL or DENL, and percentage "highly annoyed" (cutoff at 72 on a scale of 0-100), percentage "annoyed" (cutoff at 50 on a scale of 0-100), or percentage (at least) "a little annoyed" (cutoff at 28 on a scale of 0-100). These approximations are very good, and they are easier to use for practical calculations than the model itself, because the model involves a normal distribution. Our results are based on the same data set that was used earlier to establish relationships between DNL and percentage highly annoyed. In this paper we provide better estimates of the confidence intervals due to the improved model of the relationship between annoyance and noise exposure. Moreover, relationships using descriptors other than DNL and percentage highly annoyed, which are presented here, have not been established earlier on the basis of a large dataset.

Annoyance from transportation noise: Relationships with exposure metrics DNL and DENL and their confidence intervals

Summary A computationally efficient way to generate an initial model for 3D full waveform inversion is to first invert for 1D velocity profiles, exploiting Hankel transform properties to speed up modeling. The inverse Hankel transform is an improper integral, and knowing at which wavenumbers to sample to numerically evaluate it with sufficient accuracy is non-trivial. In this work, we split the inverse Hankel transform into two integrals. A definite integral which is approximated with numerical integration, and a second improper integral which is treated as a convergent series using the extrema of the integral. The series can be forced to converge quicker via the method of repeated averaging. The location of the extrema correspond to the roots of the Bessel function, which are known and can be compiled into a wavenumber list. The forward modelling for each wavenumber can be then independently carried out, in a massively parallel fashion, on CPU or GPU cores. This way only the number of integration nodes and number of extrema need to be specified a-priori for accurate modeling. This is beneficial in inversion schemes where quality control of the forward modeling steps is impractical. Numerical results using only ten extrema already give low relative errors. 

Catharina G. M. Oudshoorn

Papers

Annoyance from transportation noise: Relationships with exposure metrics DNL and DENL and their confidence intervals

Accurate and parallelizable inverse Hankel transform for full waveform inversion