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

Sleep and circadian rhythm disruption are frequently observed in patients with psychiatric disorders and neurodegenerative disease. The abnormal sleep that is experienced by these patients is largely assumed to be the product of medication or some other influence that is not well defined. However, normal brain function and the generation of sleep are linked by common neurotransmitter systems and regulatory pathways. Disruption of sleep alters sleep-wake timing, destabilizes physiology and promotes a range of pathologies (from cognitive to metabolic defects) that are rarely considered to be associated with abnormal sleep. We propose that brain disorders and abnormal sleep have a common mechanistic origin and that many co-morbid pathologies that are found in brain disease arise from a destabilization of sleep mechanisms. The stabilization of sleep may be a means by which to reduce the symptoms of--and permit early intervention of--psychiatric and neurodegenerative disease.

Sleep and circadian rhythm disruption in psychiatric and neurodegenerative disease

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

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

Study Objectives: Traffic noise disturbs sleep and may impair recuperation. There is limited information on single and combined effects of air, road and rail traffic noise on sleep and recuperation.
Design: Repeated measures
Setting: Polysomnographic laboratory study
Participants: 72 healthy subjects, mean ± standard deviation 40 ± 13 years, range 18-71 years, 32 male
Interventions: Exposure to 40, 80, or 120 rail, road, and/or air traffic noise events
Measurements and Results: Subjects were investigated for 11 consecutive nights, which included eight noise exposure nights and one noise-free control night. Noise effects on sleep structure and continuity were subtle, even in nights with combined exposure, most likely due to habituation and an increase in arousal thresholds both within and across nights. However, cardiac arousals did not habituate across nights. Noise exposure significantly affected subjective assessments of sleep quality and recuperation, whereas objective performance was unaffected, except for a small increase in mean PVT reaction time (+4 ms, adjusted P 3 kHz) noise event components.
Conclusions: Road, rail, and air traffic noise differentially affect objective and subjective assessments of sleep. Differences in the degree of noise-induced sleep fragmentation between traffic modes were explained by the specific spectral and temporal composition of noise events, indicating potential targets for active and passive noise control. Field studies are needed to validate our findings in a setting with higher ecologic validity.

http://www.laermorama.ch/m6_machtlaermkrank/pdf/03_Basner2011_Air,%20Road,%20Rail%20and%20Sleep.pdf

Single and combined effects of air, road, and rail traffic noise on sleep and recuperation.

Objectives: EEG arousals are associated with autonomic activations. Visual EEG arousal scoring is time consuming and suffers from low interob-server agreement. We hypothesized that information on changes in heart rate alone suffice to predict the occurrence of cortical arousal. Methods: Two visual AASM EEG arousal scorings of 56 healthy subject nights (mean age 37.0 ± 12.8 years, 26 male) were obtained. For each of 5 heartbeats following the onset of 3581 consensus EEG arousals and of an equal number of control conditions, differences to a moving median were calculated and used to estimate likelihood ratios (LRs) for 10 categories of heartbeat differences. Comparable to 5 consecutive diagnostic tests, these LRs were used to calculate the probability of heart rate responses being associated with cortical arousals. Results: EEG and ECG arousal indexes agreed well across a wide range of decision thresholds, resulting in a receiver operating characteristic (ROC) with an area under the curve of 0.91. For the decision threshold chosen for the final analyses, a sensitivity of 68.1% and a specificity of 95.2% were obtained. ECG and EEG arousal indexes were poorly correlated (r = 0.19, P <0.001, ICC = 0.186), which could in part be attributed to 3 outliers. The Bland-Altman plot showed an unbiased estimation of EEG arousal indexes by ECG arousal indexes with a standard deviation of ± 7.9 arousals per hour sleep. In about two-thirds of all cases, ECG arousal scoring was matched by at least one (22.2%) or by both (42.5%) of the visual scorings. Sensitivity of the algorithm increased with increasing duration of EEG arousals. The ECG algorithm was also successfully validated with 30 different nights of 10 subjects (mean age 35.3 □ 13.6 years, 5 male). Conclusions: In its current version, the ECG algorithm cannot replace visual EEG arousal scoring. Sensitivity for detecting <10-s EEG arousals needs to be improved. However, in a nonclinical population, it may be valuable to supplement visual EEG arousal scoring by this automatic, objective, reproducible, cheap, and time-saving method.

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An ECG-based Algorithm for the Automatic Identification of Autonomic Activations Associated with Cortical Arousal

Noise exposure prediction models for health effect studies normally estimate free field exposure levels outside. However, to assess the noise exposure inside dwellings, an estimate of indoor sound levels is necessary. To date, little field data is available about the difference between indoor and outdoor noise levels and factors affecting the damping of outside noise. This is a major cause of uncertainty in indoor noise exposure prediction and may lead to exposure misclassification in health assessments. This study aims to determine sound level differences between the indoors and the outdoors for different window positions and how this sound damping is related to building characteristics. For this purpose, measurements were carried out at home in a sample of 102 Swiss residents exposed to road traffic noise. Sound pressure level recordings were performed outdoors and indoors, in the living room and in the bedroom. Three scenarios-of open, tilted, and closed windows-were recorded for three minutes each. For each situation, data on additional parameters such as the orientation towards the source, floor, and room, as well as sound insulation characteristics were collected. On that basis, linear regression models were established. The median outdoor-indoor sound level differences were of 10 dB(A) for open, 16 dB(A) for tilted, and 28 dB(A) for closed windows. For open and tilted windows, the most relevant parameters affecting the outdoor-indoor differences were the position of the window, the type and volume of the room, and the age of the building. For closed windows, the relevant parameters were the sound level outside, the material of the window frame, the existence of window gaskets, and the number of windows.

https://www.mdpi.com/1660-4601/15/1/149/pdf

Uwe Müller

Papers

Single and combined effects of air, road, and rail traffic noise on sleep and recuperation.

An ECG-based Algorithm for the Automatic Identification of Autonomic Activations Associated with Cortical Arousal

Differences between Outdoor and Indoor Sound Levels for Open, Tilted, and Closed Windows

Practical guidance for risk assessment of traffic noise effects on sleep

The influence of acoustical and non-acoustical factors on short-term annoyance due to aircraft noise in the field - The COSMA study.