Long-term road traffic noise exposure is associated with an increase in morning tiredness

A study on road traffic noise exposure and prevalence of insomnia

The potential of the nocturnal traffic noise to affect the quality and the quantity of sleep makes it a serious threat to public health. The present study is an attempt to provide insights into the ways through which nocturnal traffic noise causes insomnia. A total of 4525 respondents participated in the study. Modelled nocturnal noise levels were used, and the assessment of insomnia-related symptoms was done using the Jenkins sleep problem scale. A directed acyclic graph was used to obtain the minimum set of confounders that need to be adjusted for obtaining unbiased estimates. DASS-21 item scale was used to evaluate the mental health of respondents. The study reported significant associations between traffic noise exposure and all insomnia-related symptoms. For the total study population, the highest risk occurred for difficulty in falling asleep symptom (OR = 1.45; 95% CI = 1.01 - 2.07). Based on the sensitivity analysis, respondents with bedrooms facing the road were found to have higher risks as compared to the overall sample with the highest risks occurring for difficulty in maintaining the sleep symptom (OR = 1.65; 95% CI = 1.08 - 2.51). Severity levels of mental disorders showed an increasing trend with the increasing noise levels. Females were found to have a higher risk as compared to males (OR = 1.75; 95% CI = 1.14 - 2.69). No significant association was found between traffic noise exposure and sleep medication usage. Future research on large populations can help in minimizing the impacts of nocturnal noise on public health.

Quantifying traffic noise pollution levels: a cross-sectional survey in South Africa

Despite the alarming increase in environmental noise pollution, particularly road traffic noise, in developing countries, there seems to be no awareness regarding the long-term impacts of noise, specifically traffic noise, on the health outcomes of individuals exposed to excessive noise. Additionally, there is a dearth of studies on noise and its effects utilising the pollution modelling technique known as Pollution Standard Index (PSI) to analyse the impact of noise pollution on exposed individuals. The aim of this study was to investigate the noise levels commuters are exposed to and to apply PSI to determine the level of exposure. We conducted a cross-sectional study at two taxi ranks, over 28 days. Eighty-four noise measurements were collected using a sound level meter and a dosimeter at different times of the day and month, peak vs off-peak hours and busy days vs quiet days. Data were collected between April and July 2019. We used the Pollution Standard Index to analyse the data. Noise levels were above the permissible commercial noise levels as they fell within the extremely dangerous noise sensitivity zone as determined by the PSI. Furthermore, the noise levels fell below the WHO maximum permissible level of 90 dB. There was no statistical difference between the means of the open and closed ranks. Dosimeter noise level recordings fell within the satisfactory zone as measurements were below 300 PSI, which is considered unhealthy. There is a need to raise awareness on the dangers and effects of noise pollution in developing countries, as their populations are exposed to road traffic noise.

Optimized Sensors Network and Dynamical Maps for Monitoring Traffic Noise in a Large Urban Zone

We review a Dynamap European Life project whose main scope was the design, commissioning, and actual implementation of “real-time” acoustic maps in a district of the city of Milan (District 9, or Z9, composed of about 2000 road stretches), by employing a small number of noise monitoring stations within the urban zone. Dynamap is based on the idea of finding suitable sets of roads displaying similar daily traffic noise behavior, so that one can group them together into single dynamical noise maps. The Dynamap sensor network has been built upon twenty-four monitoring stations, which have been permanently installed in appropriate locations within the pilot zone Z9, by associating four sensors to each one of the six group of roads considered. In order to decide which road stretches belong to a group, a non-acoustic parameter is used, which is obtained from a traffic flow model of the city, developed and tested over the years by the “Enviroment, Mobility and Territory Agency” of Milan (EMTA). The fundamental predictive equation of Dynamap, for the local equivalent noise level at a given site, can be built by using real-time data provided by the monitoring sensors. In addition, the corresponding contributions of six static traffic noise maps, associated with the six group of roads, are required. The static noise maps can be calculated from the Cadna noise model, based on EMTA road traffic data referred to the ‘rush-hour’ (8:00–9:00 a.m.), when the road traffic flow is maximum and the model most accurate. A further analysis of road traffic noise measurements, performed over the whole city of Milan, has provided a more accurate description of road traffic noise behavior by using a clustering approach. It is found that essentially just two mean cluster hourly noise profiles are sufficient to represent the noise profile at any site location within the zone. In order words, one can use the 24 monitoring stations data to estimate the local noise variations at a single site in real time. The different steps in the construction of the network are described in detail, and several validation tests are presented in support of the Dynamap performance, leading to an overall error of about 3 dB. The present work ends with a discussion of how to improve the design of the network further, based on the calculation of the cross-correlations between monitoring stations’ noise data.

Nighttime road traffic noise exposure at the least and most exposed façades and sleep medication prescription redemption-a Danish cohort study

STUDY OBJECTIVES

Traffic noise has been associated with poor sleep quality and short sleep duration. This study investigates the association between nighttime road traffic noise at the least and most exposed façades of the residence and redemption of sleep medication.

METHODS

In a cohort of 44,438 Danes, aged 50-64 at baseline (1993-1997), we identified all addresses from 1987 to 2015 from a national registry and calculated nighttime road traffic noise at the most and least exposed façades. Using Cox Proportional Hazard Models we investigated the association between residential traffic noise over 1, 5, and 10 years before redemption of the first sleep medication prescription in the Danish National Prescription Registry. During a median follow-up time of 18.5 years, 13,114 persons redeemed a prescription.

RESULTS

We found that 10-year average nighttime exposure to road traffic noise at the most exposed façade was associated with a hazard ratio (HR) of 1.05, 95% confidence interval (CI) (1.00 to 1.10) for Ln greater than 55 as compared to not more than 45 dB, which when stratified by sex was confined to men (HR 1.16, 95% CI 1.08 to 1.25). For the least exposed façade the HR for Ln >45 vs ≤35 dB was 1.00, 95% CI (0.95 to 1.05). For the most exposed façade, the overall association was strongest in smokers and physically inactive.

CONCLUSIONS

Long-term residential nighttime noise exposure at the most exposed façade may be associated with a higher likelihood of redeeming prescriptions for sleep medication, especially among men, smokers, and physically inactive.

Exposure assessment to road traffic noise levels and health effects in an arid urban area

Road traffic noise exposures have been recognized as serious environmental health concerns, especially in most developing countries with arid climate conditions, rapid increase in vehicle population, and limited traffic management systems. The excessive noise exposure level is associated with increase in the incidence of cardiovascular diseases and anxiety, including annoyance. This study aimed at determining traffic noise levels in residential areas, including the assessment of its annoyance and health effects based on the people's perception and reportage. To do so, field measurement and traffic noise modeling were carried out in six road points to estimate the current noise levels along various roads close to human inhabitants in Muscat Governorate, Sultanate of Oman. The detailed measured noise levels in urban residential areas across the selected roads showed that noise levels have exceeded the local and international threshold limits at all locations during the entire day. The high sound levels (48.0-56.3 dBA) were observed using the US Federal Highway Administration's Traffic Noise Model (TNM, version 2.5) results, which were in agreement with the observed (56.3-60.4 dBA) data. To assess health implication to residents through interviews (n = 208), annoyance at home was found to be little (32%), moderate (28%), and high (9%) in comparison with workplace settings of 42%, 43%, and 15%, respectively. Nineteen percent of the interviewees had difficulties in sleeping, while 19.8% experienced stress due to road traffic noise exposures. Moreover, a strong association (p < 0.05) was established between the use and objection of noise barriers. The study revealed high noise levels and the prevalence of annoyance and health effects among the exposed population. Therefore, immediate action is required to tackle the current noise levels.

Urban Noise and Psychological Distress: A Systematic Review

Chronic exposure to urban noise is harmful for auditory perception, cardiovascular, gastrointestinal and nervous systems, while also causing psychological annoyance. Around 25% of the EU population experience a deterioration in the quality of life due to annoyance and about 5-15% suffer from sleep disorders, with many disability-adjusted life years (DALYs) lost annually. This systematic review highlights the main sources of urban noise, the relevant principal clinical disorders and the most effected countries. This review included articles published on the major databases (PubMed, Cochrane Library, Scopus), using a combination of some keywords. The online search yielded 265 references; after selection, the authors have analyzed 54 articles (5 reviews and 49 original articles). From the analysis, among the sources of exposure, we found the majority of items dealing with airports and wind turbines, followed by roads and trains; the main disorders that were investigated in different populations dealt with annoyance and sleep disorders, sometimes associated with cardiovascular symptoms. Regarding countries, studies were published from all over the world with a slight prevalence from Western Europe. Considering these fundamental health consequences, research needs to be extended in such a way as to include new sources of noise and new technologies, to ensure a health promotion system and to reduce the risk of residents being exposed.

Analysis of urban road traffic noise exposure of residential buildings in hong kong over the past decade

Introduction:

With the development of transportation system and the economy, the rapidly increasing number of automobiles brings the associated problem of road traffic noise, especially in metropolitan and densely populated high-rise cities like Hong Kong. In Hong Kong, approximately one million people are affected by severe road traffic noise. Excessive noise exposure is hazardous to the health and wellbeing of people and therefore has drawn progressively more attention in Hong Kong. The Calculation of Road Traffic Noise (CRTN) has been adopted as the sole tool to evaluate road traffic noise in the form of descriptor L_A10. The accuracy and suitability of the CRTN method for predicting road traffic noise in Hong Kong were evaluated in this study by comparing the prediction results and measured traffic noise levels. The results show that the CRTN method was able to provide adequate predictions with correlation coefficients of 0.8032 and 0.7626 between the predicted and measured L_A10 for 2007 and 2017 respectively. The predicted traffic noise levels on different floors of seven selected residential buildings in 2017 were compared with those predictions for the same buildings in 2007. The worsening traffic noise exposure in these residential buildings was analysed and some suggestions and counter-measures to alleviate the traffic noise problems are put forward. Since the situation of Hong Kong is an example of what may happen in other cities, the present longitudinal study of the road traffic noise in Hong Kong hopes to contribute to a better urban acoustic environment worldwide.

Context:

Excessive noise exposure is hazardous to the health and wellbeing of people and therefore has drawn progressively more attention in Hong Kong. The urban road traffic noise exposure of residential buildings in Hong Kong over the past decade has been analysed.

Aims:

This study aims to assess the road traffic noise exposure of residential buildings over the past decade.

Settings and Design:

Measurements of traffic noise levels at some selected residential buildings were first conducted in 2007, and then repeated at the same buildings in 2017.

Material and Methods:

The CRTN was adopted to predict the traffic noise levels based on the recorded traffic flow data.

Results:

The exposure of these buildings to road traffic noise is higher in 2017 than in 2007. The study illustrates that the deterioration of the urban acoustic environment may not be caused by an increased total number of vehicles, but that heavy vehicles are dominantly responsible for the increased traffic noise levels. Restriction of vehicle velocity for urban street canyons is useless for road traffic noise control.

Conclusions:

This study shows the deterioration of traffic noise levels is mainly due to the increased heavy vehicles instead of the increased total number of vehicles. The alleviation of traffic noise levels by velocity restriction may not be obvious for urban street canyons and may only work with a certain velocity range.

Research on Noise Reduction Scheme of Heat Pump Unit in a Square

Heat pump unit is a host device located in the central air-conditioning terminal, providing cold and hot water. Heat pump unit has the advantages of energy saving, environmental protection, easy maintenance, and so on. It is adopted to solve the problems of refrigeration and heating in ventilation and air conditioning from many engineering projects in China. When the equipment is turned on, however, the high noise generated by the heat pump unit has a very negative impact on the life and work of the surrounding residents. Therefore, noise reduction is needed to improve the environment quality. In this paper, the noise of the air-cooled heat pump unit of the square area in Shanghai was detected, the noise source was analyzed, and the corresponding noise reduction scheme was proposed. After the completion of the scheme, measurements indicate that A-weighted sound pressure level is less than or equal to 60 dB (A) during the day and less than or equal to 50 dB (A) at night, which meets the relevant national noise limit emission standards and conforms to the second-class quality standard of the acoustic environment.

Accuracy of the Dynamic Acoustic Map in a Large City Generated by Fixed Monitoring Units

DYNAMAP, a European Life project, aims at giving a real image of the noise generated by vehicular traffic in urban areas developing a dynamic acoustic map based on a limited number of low-cost permanent noise monitoring stations. The system has been implemented in two pilot areas located in the agglomeration of Milan (Italy) and along the Motorway A90 (Rome-Italy). The paper reports the final assessment of the system installed in the pilot area of Milan. Traffic noise data collected by the monitoring stations, each one representative of a number of roads (groups) sharing similar characteristics (e.g., daily traffic flow), are used to build-up a “real-time” noise map. In particular, we focused on the results of the testing campaign (21 sites distributed over the pilot area and 24 h duration of each recording). It allowed evaluating the accuracy and reliability of the system by comparing the predicted noise level of DYNAMAP with field measurements in randomly selected sites. To this end, a statistical analysis has been implemented to determine the error associated with such prediction, and to optimize the system by developing a correction procedure aimed at keeping the error below some acceptable threshold. The steps and the results of this procedure are given in detail. It is shown that it is possible to describe a complex road network on the basis of a statistical approach, complemented by empirical data, within a threshold of 3 dB provided that the traffic flow model achieves a comparable accuracy within each single groups of roads in the network.

Artificial intelligence based ensemble model for prediction of vehicular traffic noise

Vehicular traffic noise is the main source of noise pollution in major cities around the globe. A reliable and accurate method for the estimation of vehicular traffic noise is therefore essential for creating a healthy noise-free environment. In this study, 2 linear (simple average and weighted average) and 2-nonlinear (neural network and neuro-fuzzy) ensemble models were developed by combining the outputs of three Artificial Intelligence (AI) based non-linear models; Adaptive Neuro Fuzzy Inference System (ANFIS), Feed Forward Neural Network (FFNN), Support Vector Regression (SVR) and one Multilinear regression (MLR) model to enhance the performance of the single black box models in predicting vehicular traffic noise of Nicosia city, North Cyprus. In this way, first a nonlinear sensitivity analysis was applied to select the most relevant and dominant input parameters of the traffic data obtained from 12 observation points in the study area. The most dominant parameters in order of their importance were determined to be number of cars, number of van/pickups, number of trucks, average speed and number of buses. Classifying the number of vehicles into five categories before feeding the traffic data into the AI models was observed to improve performance of the single models up to 29% in the verification phase. Out of the four ensembles models developed, the nonlinear ANFIS ensemble was found to be the most robust by improving the performance of ANFIS, FFNN, SVR and MLR models in the verification stage by 11%, 19%, 21% and 31%, respectively.

Influence of translational vehicle dynamics on heavy vehicle noise emission

Vehicle dynamics can play a significant role in the noise emission from heavy vehicles. In this work, a heavy vehicle noise emission model is presented to study the influence of translational vehicle dynamics on the sound power level emitted by heavy-duty trucks. Vehicle speed and acceleration are calculated using an analytical approximation that describes the tractive and retarding forces acting on a heavy vehicle on grade. Heavy vehicle noise emission associated with rolling noise is defined with reference to the Nordic traffic noise model that takes into account the number of axles for different articulated trucks. An expression for engine noise emission in terms of vehicle speed, weight, engine power, aerodynamic properties and road grade is derived. The individual and combined effects of engine noise and rolling noise for different vehicle mass combinations are examined. The influence of road grade on vehicle kinematics and noise emission is also investigated.

Simulation and Analysis of Road Traffic Noise among Urban Buildings Using Spatial Subdivision-Based Beam Tracing Method

In order to realize the simulation and evaluation of road traffic noise among urban buildings, a spatial subdivision-based beam-tracing method is proposed in this study. First, the road traffic source is divided into sets of point sources and described with the help of vehicle emission model. Next, for each pair of source and receiver, spatial subdivision-based beam-tracing method is used in noise paths generation. At last, noise distribution can be got by noise calculation of all receivers considering the complex transmission among urban buildings. A measurement experiment with a point source is carried out to validate the accuracy of the method; the 0.8 m height and 2.5-m height average errors are about 0.9 dB and 1.2 dB, respectively. Moreover, traffic noise analysis under different building layouts and heights are presented by case applications and conclusions can be reached: (1) Different patterns result in different noise distributions and patterns designed as self-protective can lead to an obvious noise abatement for rear buildings. Noise differences between the front and rear buildings are about 7–12 dB with different patterns. (2) Noise value might not show a linear variation along with the height as shielding of different layers is various in reality.

Dynamic Noise Mapping in the Suburban Area of Rome (Italy)

A “real-time” noise mapping project, named DYNAMAP, has been developed in the framework of a Life+ 2013 program and cofunded by the European Commission. The project aims at giving a real picture of the noise generated by vehicular traffic. To this purpose, a dedicated platform has been developed to elaborate the information from distributed noise monitoring stations. The methodology has been implemented along the ring road encircling the city of Rome (Italy). A detailed description of the system is given together with a report on the testing campaign that allowed evaluation of the accuracy and reliability of the system. From the monitoring campaign satisfactory results have been achieved, showing an average overall prediction error of ~1.5 dB.

The role of the physical environment in adolescent mental health

The existing literature suggests an association between the physical environment and mental health but also complex relationships between the social and the physical environment as well as between objective and subjective measures of the environment. In this study, we attempted to explore the role of the residential neighbourhood's physical environment in adolescent mental health, taking this complexity into account. Using data on 3683 ten- to 15-year-olds from England and Wales who participated in Understanding Society, we investigated the role of neighbourhood greenspace and air pollution in adolescent mental health (measured with the Strengths and Difficulties Questionnaire) while controlling for measures of neighbourhood and family socio-economic disadvantage as well as subjective perceptions of social cohesion, crime, safety, and noise in the neighbourhood. In linear regression models, greenspace and air pollution could not predict mental health. However, fear of being a victim of crime was a consistent predictor of mental health and behaviour, indicating the essential role of young people's subjective experience of their neighbourhoods for their mental health and well-being.

Environmental Noise around Hospital Areas: A Case Study

Due to the particular characteristics of hospitals, these buildings are highly sensitive to environmental noise. However, they are usually located close or within urban agglomerations. Hence, hospitals are, in many cases, exposed to high levels of environmental noise. A study of one of the main hospitals in the Extremadura region (Spain) is presented here to allow a global assessment of the acoustic impact of outdoor sound sources. Both long- and short-term measurements were carried out, and a software model was developed. The measured values exceed the World Health Organisation reference value of 50 dBA for daytime and evening, and are even higher than the 55 dBA limit at which severe annoyance is generated. Taking into account the results obtained, the noise impact on this hospital is primarily influenced by three sound sources: road traffic, cooling towers of the hospital and the emergency helicopter. Their relative importance depends on the facade under consideration. It can therefore be concluded that the overall situation of the hospital needs to be improved. Thus, a series of solutions are proposed for a possible action plan based on interventions regarding the main sound sources and the location of the most sensitive areas to environmental noise.

Acute Effects of Air Pollution and Noise from Road Traffic in a Panel of Young Healthy Adults

Panel studies are an efficient means to assess short-term effects of air pollution and other time-varying environmental exposures. Repeated examinations of volunteers allow for an in-depth analysis of physiological responses supporting the biological interpretation of environmental impacts. Twenty-four healthy students walked for 1 h at a minimum of four separate occasions under each of the following four settings: along a busy road, along a busy road wearing ear plugs, in a park, and in a park but exposed to traffic noise (65 dB) through headphones. Particle mass (PM_2.5, PM₁), particle number, and noise levels were measured throughout each walk. Lung function and exhaled nitrogen oxide (NO) were measured before, immediately after, 1 h after, and approximately 24 h after each walk. Blood pressure and heart rate variability were measured every 15 min during each walk. Recorded air pollution levels were found to correlate with reduced lung function. The effects were clearly significant for end-expiratory flows and remained visible up to 24 h after exposure. While immediate increases in airway resistance could be interpreted as protective (muscular) responses to particulate air pollution, the persisting effects indicate an induced inflammatory reaction. Noise levels reduced systolic blood pressure and heart rate variability. Maybe due to the small sample size, no effects were visible per specific setting (road vs. park).

Learning Wireless Sensor Networks for Source Localization

Source localization and target tracking are among the most challenging problems in wireless sensor networks (WSN). Most of the state-of-the-art solutions are complicated and do not meet the processing and memory limitations of the existing low-cost sensor nodes. In this paper, we propose computationally-cheap solutions based on the support vector machine (SVM) and twin SVM (TWSVM) learning algorithms in which network nodes firstly detect the desired signal. Then, the network is trained to specify the nodes in the vicinity of the source (or target); hence, the region of event is detected. Finally, the centroid of the event region is considered as an estimation of the source location. The efficiency of the proposed methods is shown by simulations.

Recent Developments in Sonic Crystals as Barriers for Road Traffic Noise Mitigation

Noise barriers are the most widespread solution to mitigate noise produced by the continuous growth of vehicular traffic, thus reducing the large number of people exposed to it and avoiding unpleasant effects on health. However, conventional noise barriers present the well-known issues related to the diffraction at the edges which reduces the net insertion loss, to the reflection of sound energy in the opposite direction, and to the complaints of citizens due to the reduction of field of view, natural light, and air flow. In order to avoid these shortcomings and maximize noise abatement, recent research has moved toward the development of sonic crystals as noise barriers. A previous review found in the literature was focused on the theoretical aspects of the propagation of sound through crystals. The present work on the other hand reviews the latest studies concerning the practical application of sonic crystal as noise barriers, especially for road traffic noise mitigation. The paper explores and compares the latest developments reported in the scientific literature, focused on integrating Bragg’s law properties with other mitigation effects such as hollow scatterers, wooden or recycled materials, or porous coating. These solutions could increase the insertion loss and frequency band gap, while inserting the noise mitigation action in a green and circular economy. The pros and cons of sonic crystal barriers will also be discussed, with the aim of finding the best solution that is actually viable, as well as stimulating future research on the aspects requiring improvement.

Traffic noise, noise annoyance and psychotropic medication use

BACKGROUND

Road-traffic noise can induce stress, which may contribute to mental health disorders. Mental health problems have not received much attention in noise research. People perceive noise differently, which may affect the extent to which noise contributes to poor mental health at the individual level. This paper aims to assess the relationships between outdoor traffic noise and noise annoyance and the use of psychotropic medication.

METHODS

We conducted a survey to assess noise annoyance and psychotropic medication among residents of the Helsinki Capital Region of Finland. We also assessed the associations of annoyance and road-traffic noise with sleep disorders, anxiety and depression. Respondents were randomly sampled from the Finnish Population registry, and data was collected using a self-administered questionnaire. Outdoor traffic noise was modelled using the Nordic prediction model. Associations between annoyance and modelled façade-noise levels with mental health outcome indicators were assessed using a binary logistic regression while controlling for socioeconomic, lifestyle and exposure-related factors.

RESULTS

A total of 7321 respondents returned completed questionnaires. Among the study respondents, 15%, 7% and 7% used sleep medication, anxiolytic and antidepressant medications, respectively, in the year preceding the study. Noise annoyance was associated with anxiolytic drug use, OR = 1.41 (95% CI: 1.02-1.95), but not with sedative or antidepressant use. There was suggestive association between modelled noise at levels higher than 60 dB and anxiolytic or antidepressant use. In respondents whose bedroom windows faced the street, modelled noise was definitively associated with antidepressant use. Noise sensitivity did not modify the effect of noise but was associated with an increased use of psychotropic medication.

CONCLUSION

We observed suggestive associations between high levels of road-traffic noise and psychotropic medication use. Noise sensitivity was associated with psychotropic medication use.

The Public Health Impact of Road-Traffic Noise in a Highly-Populated City, Republic of Korea: Annoyance and Sleep Disturbance

Sustainable transportation is an essential part of a sustainable city; however, modern transportation systems with internal-combustion engines emits unacceptably high level of air-pollutants and noise. It is recognized widely that road-traffic noise has negative health impacts (such as annoyance and sleep disturbance) on exposed population in highly-populated cities. These harmful effects should be removed or at least reduced to guarantee the sustainability of modern cities. The estimation of pollutant levels at a specific location and the extent of the damage is therefore important for policy makers. This study presents a procedure to determine the levels of road-traffic noise at both day and night, and an assessment of the adverse health effects across Gwangju Metropolitan City (GMC), Republic of Korea (ROK). Road-traffic noise maps in 2-D and 3-D were generated, in order to find spatial distribution of noise levels across the city and noise level at the façade of a building-floor, respectively. The adoption of existing assessment models for the highly-annoyed (%HA) and highly-sleep-disturbed (%HSD) leads to building-based estimation of the affected population and spatial distribution of the road networks of the city. Very high noise levels were found to exist along major roads in the day and at night, with little difference between them. As a result, approximately 10% and 5% of the total population (n = 1,471,944) were estimated to experience high-level annoyance and sleep disturbance, respectively.

Optimal Questions for Sleep in Epidemiological Studies: Comparisons of Subjective and Objective Measures in Laboratory and Field Studies

Epidemiological studies on sleep often use questionnaires, and measurement of validity provides necessary guidance in selection of valid single sleep questions. Twenty-five items assessing different aspects of sleep, including overall sleep quality, specific sleep parameters, nocturnal restoration, and exposure-related questions, were tested. This involved coherence with objective polysomnographic (PSG) laboratory measurements of sleep in 47 participants and application of selected items under field conditions in over 3,000 participants. Items on overall sleep quality correlated significantly with PSG data. For specific sleep parameter questions, tiredness in the morning, time to fall asleep, difficulties to sleep and estimated number of awakenings were correlated to PSG data. Questions asking specifically about the effect of potential sleep disturbances correlated poorly with PSG data, but showed highest effects between environmental exposure (noise and vibration) and control nights in the laboratory and highest correlation with the dose of exposure in the field. In conclusion, healthy participants seem to be able to access their sleep reliably; and sleep questions asking about specific sleep parameters can be recommended for the assessment of sleep.

A Population-Based Study on Nighttime Road Traffic Noise and Insomnia

Study Objectives

The aims of the present study were to investigate how nighttime road traffic noise relates to self-reported symptoms of insomnia and sleep medication use.

Methods

We used questionnaire data from the population-based study Health and Environment in Oslo (HELMILO) (2009-2010; n = 13019). The insomnia symptoms difficulties falling asleep, awakenings during the night, and waking up too early in the morning as well as self-reported sleep medication use were included as outcomes. Modeled noise levels (Lnight) were assigned to each participant's home address. For selecting covariates to the statistical model, we used a directed acyclic graph. The associations between noise and sleep were analyzed using logistic regression models.

Results

After adjustment for potential confounders, we found an odds ratio (OR) of 1.05 (95% confidence interval [CI]: 1.01-1.09) for the association between traffic noise and difficulties falling asleep, in the total study population. For the association between traffic noise and awakenings during the night, the OR was 1.04 (95% CI: 1.00-1.08) and for waking up too early, the OR was 1.06 (95% CI: 1.02-1.11). The effect estimates are given per 5-dB increase in traffic noise level (Lnight). Self-reported sleep medication use was not statistically significantly associated with traffic noise exposure.

Conclusions

In an adult population from Oslo, traffic noise was associated with difficulties falling asleep and waking up too early. These findings indicate that sleep quantity may be compromised for individuals living in areas highly exposed to nighttime traffic noise.

Road traffic noise and registry based use of sleep medication

BACKGROUND

Road traffic noise has been associated with adverse health effects including sleep disturbances. Use of sleep medication as an indicator of sleeping problems has rarely been explored in studies of the effects of traffic noise. Furthermore, using registry data on sleep medications provides an opportunity to study the effects of noise on sleep where attribution of sleep problems to noise is not possible.

METHODS

We used questionnaire data from the population-based study Health and Environment in Oslo (HELMILO) (2009-10) (n = 13,019). Individual data on sleep medications was obtained from the Norwegian Prescription Database (NorPD). Noise levels (L _night) were modeled for the most exposed façade of the building at each participant's home address. Logistic regression models adjusted for potential confounders were used to analyze the association between traffic noise and sleep medication use both for one whole year and for the summer season. The results were reported as changes in the effect estimate per 5 decibel (dB) increase in noise level.

RESULTS

We observed no association between traffic noise and sleep medication use during one year [odds ratio (OR) = 1.00; 95% confidence interval (CI): 0.96, 1.04]. For sleep medication use in the summer season, there was a positive, however non-significant association (OR = 1.04; 95% CI: 0.99, 1.10). Among individuals sleeping with the bedroom window open, the association increased slightly and was borderline statistically significant (OR = 1.06; 95% CI: 1.00, 1.12).

CONCLUSIONS

We found no evidence of an association between traffic noise and sleep medication use during one year. However, for the summer season, there was some suggestive evidence of an association. These findings indicate that season may play a role in the association between traffic noise and sleep, possibly because indoor traffic noise levels are likely to be higher during summer due to more frequent window opening. More studies are, however, necessary in order to confirm this.

Physiological effects of railway vibration and noise on sleep

This paper evaluates the relative contribution of vibration and noise from railway on physiological sleep outcomes. Vibration from railway freight often accompanies airborne noise, yet is almost totally absent in the existing literature. In an experimental investigation, 23 participants, each sleeping for six nights in the laboratory, were exposed to 36 simulated railway freight pass-bys per night with vibration alone (a_Wd,max = 0.0204 ms^-2), noise alone (L_AF,max = 49.8 dB), or both vibration and noise simultaneously. A fourth exposure night involved 52 pass-bys with concurrent vibration and noise. Sleep was measured with polysomnography. Cardiac activity was measured with electrocardiography. The probability of cortical arousals or awakenings was greater following all exposures, including vibration alone, than spontaneous reaction probability (p < 0.05). The effects of vibration exposure and noise exposure on changes of sleep stage and arousals were directly additive. Vibration and noise exposure both induced heart rate acceleration above spontaneously expected fluctuations at baseline. The results indicate that vibration and noise are processed in the brain separately yet in parallel, with both contributing towards the likelihood of sleep disruption. The findings show that vibration is of importance when considering the impact of railway freight on sleep.

Neighborhood Factors as Predictors of Poor Sleep in the Sueño Ancillary Study of the Hispanic Community Health Study/Study of Latinos

Study Objectives

To evaluate whether an adverse neighborhood environment has higher prevalence of poor sleep in a US Hispanic/Latino population.

Methods

A cross-sectional analysis was performed in 2156 US Hispanic/Latino participants aged 18-64 years from the Sueño ancillary study of the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). Participants completed surveys of neighborhood environment including perceived safety, violence and noise, the Insomnia Severity Index (ISI), and 7 days of wrist actigraphy.

Results

In age and sex-adjusted analyses, short sleep, low sleep efficiency, and late sleep midpoint were all more prevalent among those living in an unsafe neighborhood. After adjustment for background, site, nativity, income, employment, depressive symptoms, and sleep apnea, the absolute risk of sleeping <6 hours was 7.7 (95% CI [0.9, 14.6]) percentage points greater in those living in an unsafe compared to a safe neighborhood. There were no differences in the prevalence of insomnia by level of safety or violence. Insomnia was more prevalent among those living in a noisy neighborhood. In adjusted analysis, the absolute risk of insomnia was 4.4 (95% CI [0.4, 8.4]) percentage points greater in those living in noisy compared to non-noisy neighborhoods.

Conclusion

Using validated measures of sleep duration and insomnia, we have demonstrated the existence of a higher prevalence of short sleep and insomnia by adverse neighborhood factors. An adverse neighborhood environment is an established risk factor for a variety of poor health outcomes. Our findings suggest negative effects on sleep may represent one pathway by which neighborhood environment influences health.

Health effects from low-frequency noise and infrasound in the general population: Is it time to listen? A systematic review of observational studies

A systematic review of observational studies was conducted to assess the association between everyday life low-frequency noise (LFN) components, including infrasound and health effects in the general population. Literature databases Pubmed, Embase and PsycInfo and additional bibliographic sources such as reference sections of key publications and journal databases were searched for peer-reviewed studies published from 2000 to 2015. Seven studies met the inclusion criteria. Most of them examined subjective annoyance as primary outcome. The adequacy of provided information in the included papers and methodological quality of studies was also addressed. Moreover, studies were screened for meta-analysis eligibility. Some associations were observed between exposure to LFN and annoyance, sleep-related problems, concentration difficulties and headache in the adult population living in the vicinity of a range of LFN sources. However, evidence, especially in relation to chronic medical conditions, was very limited. The estimated pooled prevalence of high subjective annoyance attributed to LFN was about 10%. Epidemiological research on LFN and health effects is scarce and suffers from methodological shortcomings. Low frequency noise in the everyday environment constitutes an issue that requires more research attention, particularly for people living in the vicinity of relevant sources.

How Might People Near National Roads Be Affected by Traffic Noise as Electric Vehicles Increase in Number? A Laboratory Study of Subjective Evaluations of Environmental Noise

We face a likely shift to electric vehicles (EVs) but the environmental and human consequences of this are not yet well understood. Simulated auditory traffic scenes were synthesized from recordings of real conventional and EVs. These sounded similar to what might be heard by a person near a major national road. Versions of the simulation had 0%, 20%, 40%, 60%, 80% and 100% EVs. Participants heard the auditory scenes in random order, rating each on five perceptual dimensions such as pleasant–unpleasant and relaxing–stressful. Ratings of traffic noise were, overall, towards the negative end of these scales, but improved significantly when there were high proportions of EVs in the traffic mix, particularly when there were 80% or 100% EVs. This suggests a shift towards a high proportion of EVs is likely to improve the subjective experiences of people exposed to traffic noise from major roads. The effects were not a simple result of EVs being quieter: ratings of bandpass-filtered versions of the recordings suggested that people’s perceptions of traffic noise were specifically influenced by energy in the 500–2000 Hz band. Engineering countermeasures to reduce noise in this band might be effective for improving the subjective experience of people living or working near major roads, even for conventional vehicles; energy in the 0–100 Hz band was particularly associated with people identifying sound as ‘quiet’ and, again, this might feed into engineering to reduce the impact of traffic noise on people.

Impact of overnight traffic noise on sleep quality, sleepiness, and vigilant attention in long-haul truck drivers: Results of a pilot study

This study aimed to evaluate the impact of traffic noise along the motorway on sleep quality, sleepiness, and vigilant attention in long-haul truck drivers. This was a randomized, crossover, within-subject controlled study. Healthy long-haul truck drivers spent 6 consecutive nights in a real truck berth with full sleep laboratory equipment. During 3 nights, subjects were exposed to replayed traffic noise alongside motorways, whereas the other 3 nights were without traffic noise. Polysomnography was recorded during the nights and numerous sleepiness tests and vigilance examinations were performed during the following standardized working day. Outcome measures were compared between noisy and silent nights using the paired Wilcoxon test. Ten healthy long-haul truck drivers with a mean age of 36.3 ± 7.3 years completed the study as planned. On noisy nights, subjects had greater latencies to the rapid eye movement (REM) phase (90 ± 32 min vs 69 ± 16 min, P = 0.074) and higher percentages of sleep stage 1 (13.7 ± 5.5% vs 11.2 ± 4.4%; P = 0.059). Subjects also rated their sleep quality as having been better during nights without noise (28.1 ± 3.7 vs 30.3 ± 6.2, P = 0.092). The impact of these differences on daytime sleepiness and vigilance was rather low; however, mean Karolinska Sleepiness Scale (KSS) scores measured during the course of the following day were higher on six out of eight occasions after noisy nights. The effects of overnight traffic noise on sleep quality are detectable but unlikely to have any major impact on the vigilant attention and driving performance of long haul-truck drivers with low nocturnal noise sensitivity. This might not be true for subgroups prone to sleeping disorders.

Musculoskeletal Symptoms and Risk of Burnout in Child Care Workers - A Cross-Sectional Study

Objectives

German child care workers' job satisfaction is influenced by the consequences of unfavourable underlying conditions. Child care workers tend to suffer from psychosocial stress, as they feel that their work is undervalued. The objective of the present study is to investigate how the psychosocial factors of the effort-reward imbalance (ERI) model influence musculoskeletal symptoms (MS) and the risk of burnout. To our knowledge this is the first study investigating the association between the factors of the ERI model and MS in child care workers.

Methods and Findings

Data from 199 child care workers were examined in a cross-sectional study. Psychosocial factors were recorded with the ERI questionnaire. MS was recorded with the Nordic Questionnaire and risk of burnout with the Personal Burnout scale of the Copenhagen Burnout Inventory. Multivariate analysis was performed using linear and logistic regression models. The response rate was 57%. In most of the sample (65%), an effort-reward imbalance was observed. 56% of the child care workers were at risk of burnout and 58% reported MS. Factors associated with risk of burnout were subjective noise exposure (OR: 4.4, 95%CI: 1.55–12.29) and overcommitment (OR: 3.4; 95%CI: 1.46–7.75). There were statistically significant associations between MS and overcommitment (low back pain—OR: 2.2, 95%CI: 1.04–4.51), low control (overall MS OR: 3.8; 95%CI: 1.68–3.37) and risk of burnout (overall MS OR: 2.3, 95%CI: 1.01–5.28). For ERI no statistically significant associations were found with reference to risk of burnout or MS.

Conclusion

Overcommitment in child care workers is related to MS and risk of burnout. There is also evidence that low control is associated with MS and subjective noise exposure with risk of burnout. Effort-reward imbalance is not related to either outcome. This occupational health risk assessment identifies changeable working factors in different types of facilities.

Modeling environmental noise exceedances using non-homogeneous Poisson processes

In this work a non-homogeneous Poisson model is considered to study noise exposure. The Poisson process, counting the number of times that a sound level surpasses a threshold, is used to estimate the probability that a population is exposed to high levels of noise a certain number of times in a given time interval. The rate function of the Poisson process is assumed to be of a Weibull type. The presented model is applied to community noise data from Messina, Sicily (Italy). Four sets of data are used to estimate the parameters involved in the model. After the estimation and tuning are made, a way of estimating the probability that an environmental noise threshold is exceeded a certain number of times in a given time interval is presented. This estimation can be very useful in the study of noise exposure of a population and also to predict, given the current behavior of the data, the probability of occurrence of high levels of noise in the near future. One of the most important features of the model is that it implicitly takes into account different noise sources, which need to be treated separately when using usual models.

Associations of neighborhood characteristics with sleep timing and quality: the Multi-Ethnic Study Of Atherosclerosis

STUDY OBJECTIVES

To investigate the associations of specific neighborhood features (disorder, safety, social cohesion, physical environment, and socioeconomic status) with sleep duration and quality.

DESIGN

Cross-sectional. One wave of a population-based study (Multi-Ethnic Study of Atherosclerosis).

SETTING

Community-dwelling participants in New York, NY and Los Angeles, CA.

PARTICIPANTS

There were 1,406 participants (636 males, 770 females).

INTERVENTIONS

NA.

MEASUREMENTS AND RESULTS

Sleep was assessed using reported hours of sleep, the Epworth Sleepiness Scale, and insomnia symptoms. Neighborhood characteristics were assessed via questionnaires administered to neighbors of study participants and were aggregated to the neighborhood (census tract) level using empirical Bayes estimation. An adverse social environment (characterized by high disorder, and low safety and social cohesion) was associated with shorter sleep duration after adjustment for the physical environment, neighborhood and individual-level socioeconomic status (SES), and other short sleep risk factors (mean difference per standard deviation increase in summary social environment scale 0.24 h 95% confidence interval 0.08, 0.43). Adverse neighborhood social and physical environments, and neighborhood SES were associated with greater sleepiness, but associations with physical environments were no longer statistically significant after adjustment for sociodemographic characteristics. Neighborhood SES was a weaker and less consistent predictor of specific measures of neighborhood social and physical environments. Neighborhood characteristics were not associated with insomnia.

CONCLUSIONS

Shortened sleep related to adverse social environments represents one potential pathway through which neighborhoods may influence health.

Cohort Profile: Understanding socioeconomic inequalities in health and health behaviours: the GLOBE study

The main aim of the Gezondheid en Levens Omstandigheden Bevolking Eindhoven en omstreken (GLOBE) study (the letters of whose name represent the first letters of the Dutch acronym for Health and Living Conditions of the Population of Eindhoven and surroundings) is to quantitatively assess mechanisms and factors explaining socio-economic inequalities in health in the Netherlands. Baseline data for the study were collected by postal survey in 1991 among 18,973 respondents ranging in age from 15-75 years from the city of Eindhoven and its surrounding municipalities. Subsamples (total N=5667) were interviewed and/or surveyed in 1991, 1997, 2004 (also including a new sample), and most recently in 2011. Information was asked on indicators of socio-economic position, a range of potential explanatory factors (material, behavioural, psychosocial, and environmental) and health outcomes. From 2004 onwards, special emphasis was given to the identification of physical, social, and cultural environmental factors in the explanation of socio-economic inequalities in health behaviours. Information from the baseline postal survey onwards can and has been linked to several registries of causes of death, hospital admissions, and cancer. Researchers are cordially invited to contact the project leader (f.vanlenthe@erasmusmc.nl) to propose research based on the data.

Effect of nocturnal road traffic noise exposure and annoyance on objective and subjective sleep quality

BACKGROUND

Various epidemiological studies have found an association between noise exposure and sleep quality, but the mediating role of annoyance is unclear for this association.

OBJECTIVES

To investigate the effects of both objectively modeled road traffic noise exposure as well as noise annoyance on subjective and objective sleep quality measures.

METHODS

1375 randomly selected participants from Basel, Switzerland, were enrolled in a questionnaire survey in 2008 with follow-up one year later (1122 participants). We assessed sleep quality by using a standardized sleep disturbance score, as well as the level of annoyance with road traffic noise at home. Objective sleep efficiency data was collected in a nested diary study by means of actigraphy from 119 subjects for 1551 nights. Residential nocturnal exposure to road traffic noise was modeled using validated models. Data were analyzed with random intercept mixed-effects regression models.

RESULTS

In the main study, self-reported sleep quality was strongly related to noise annoyance (p for trend<0.001) but only moderately correlated with modeled noise exposure (p=0.07). In the nested diary study objectively measured sleep efficiency was not related to annoyance (p=0.25) but correlated with modeled noise exposure (p=0.02). Strikingly, noise induced decreased sleep efficiency was even more significant for study participants who were not annoyed with traffic noise (p=0.001).

CONCLUSIONS

This study indicates that effects of nocturnal traffic noise on objective sleep quality are independent of perceived noise annoyance, whereas the association between self-reported sleep quality and noise is mediated by noise annoyance.

On the influence of freight trains on humans: a laboratory investigation of the impact of nocturnal low frequency vibration and noise on sleep and heart rate

Background

A substantial increase in transportation of goods on railway may be hindered by public fear of increased vibration and noise leading to annoyance and sleep disturbance. As the majority of freight trains run during night time, the impact upon sleep is expected to be the most serious adverse effect. The impact of nocturnal vibration on sleep is an area currently lacking in knowledge. We experimentally investigated sleep disturbance with the aim to ascertain the impact of increasing vibration amplitude.

Methodology/Principal Findings

The impacts of various amplitudes of horizontal vibrations on sleep disturbance and heart rate were investigated in a laboratory study. Cardiac accelerations were assessed using a combination of polysomnography and ECG recordings. Sleep was assessed subjectively using questionnaires. Twelve young, healthy subjects slept for six nights in the sleep laboratory, with one habituation night, one control night and four nights with a variation of vibration exposures whilst maintaining the same noise exposure. With increasing vibration amplitude, we found a decrease in latency and increase in amplitude of heart rate as well as a reduction in sleep quality and increase in sleep disturbance.

Conclusions/Significance

We concluded that nocturnal vibration has a negative impact on sleep and that the impact increases with greater vibration amplitude. Sleep disturbance has short- and long-term health consequences. Therefore, it is necessary to define levels that protect residents against sleep disruptive vibrations that may arise from night time railway freight traffic.

Road traffic noise: annoyance, sleep disturbance, and public health implications

BACKGROUND

The WHO has recognized environmental noise as harmful pollution that causes adverse psychosocial and physiologic effects (i.e., annoyance and sleep disturbance) on human health. In Europe, noise-related health studies have been actively conducted, but the U.S. has lagged behind in this research field.

PURPOSE

This research predicted ambient levels of road traffic noise for a highly urbanized area: Fulton County GA. Assessment was made of noise impacts on the population, focusing on annoyance and sleep disturbance.

METHODS

All the data sets were collected during 2009-2011, and data analysis was performed in 2010-2011. The study used a sound-propagation model for noise-level prediction and derived noise-impact indicators for annoyance and sleep disturbance from exposure-response models. Then, annoyed and sleep-disturbed populations were predicted with the use of each noise-impact indicator.

RESULTS

It was predicted that 109,967 people would be at risk of being highly annoyed, with 19,621 people at risk for high sleep disturbance for Fulton County GA. Noise-impact indicators such as the percentage of those who were highly annoyed and who had high levels of sleep disturbance were expected to be valuable metrics to compare noise equity among urban communities.

CONCLUSIONS

Many residents of the greater Atlanta area may be exposed to noise levels that put them at risk of being highly annoyed or having high levels of sleep disturbance. These results, if generalized to other urban areas with high levels of road traffic, indicate that it may be important for the public's health to update existing noise-related policies or develop new ones to control and abate noise concerns in urban communities.

On the outdoor annoyance from scooter and motorbike noise in the urban environment

The health impacts of environmental noise are a growing concern amongst both the general public and policy-makers in Europe. Environmental noise - especially from road transportation - is widely accepted as an important environmental impact factor that can be taken as a start for the process of evaluating the impact of annoyance on the exposed urban population. Extensive urbanisation and the increase of road transport define the main driving forces for the environmental noise exposure of the population. In urban conditions, it is rather common, regarding road transportation noise, to hear from people that, especially, PTW (Powered Two Wheelers) are annoying, and many times are actually the most annoying environmental noise sources introducing a degradation of the urban environment. In this research, in Athens city centre, both scooters and motorbikes operation patterns are analysed, in the basis of their environmental impact through ad-hoc tests to establish if specific features of their emitted noise are annoying and affect the quality of life. It resulted that PTW are a relevant cause of specific environmental annoyance on pedestrians when low background noise levels and sparse traffic flow allow identifying the PTW. Based on the results of a measurement campaign, both L(max) and roughness indices are identified as characteristic noise signatures of the PTW. Results are compared to laboratory studies on annoyance found in literature and to a specific set of interviews with a large number of pedestrians in selected sites. Annoyance caused by scooters and motorbikes is analysed in the findings and conclusions.

Impact of wind turbine sound on annoyance, self-reported sleep disturbance and psychological distress

PURPOSE OF THE RESEARCH

The present government in the Netherlands intends to realize a substantial growth of wind energy before 2020, both onshore and offshore. Wind turbines, when positioned in the neighborhood of residents may cause visual annoyance and noise annoyance. Studies on other environmental sound sources, such as railway, road traffic, industry and aircraft noise show that (long-term) exposure to sound can have negative effects other than annoyance from noise. This study aims to elucidate the relation between exposure to the sound of wind turbines and annoyance, self-reported sleep disturbance and psychological distress of people that live in their vicinity. Data were gathered by questionnaire that was sent by mail to a representative sample of residents of the Netherlands living in the vicinity of wind turbines

PRINCIPAL RESULTS

A dose-response relationship was found between immission levels of wind turbine sound and selfreported noise annoyance. Sound exposure was also related to sleep disturbance and psychological distress among those who reported that they could hear the sound, however not directly but with noise annoyance acting as a mediator. Respondents living in areas with other background sounds were less affected than respondents in quiet areas.

MAJOR CONCLUSIONS

People living in the vicinity of wind turbines are at risk of being annoyed by the noise, an adverse effect in itself. Noise annoyance in turn could lead to sleep disturbance and psychological distress. No direct effects of wind turbine noise on sleep disturbance or psychological stress has been demonstrated, which means that residents, who do not hear the sound, or do not feel disturbed, are not adversely affected.

Air pollution exposure estimation using dispersion modelling and continuous monitoring data in a prospective birth cohort study in The Netherlands

Previous studies suggest that pregnant women and children are particularly vulnerable to the adverse effects of air pollution. A prospective cohort study in pregnant women and their children enables identification of the specific effects and critical periods. This paper describes the design of air pollution exposure assessment for participants of the Generation R Study, a population-based prospective cohort study from early pregnancy onwards in 9778 women in The Netherlands. Individual exposures to PM10 and NO2 levels at the home address were estimated for mothers and children, using a combination of advanced dispersion modelling and continuous monitoring data, taking into account the spatial and temporal variation in air pollution concentrations. Full residential history was considered. We observed substantial spatial and temporal variation in air pollution exposure levels. The Generation R Study provides unique possibilities to examine effects of short- and long-term air pollution exposure on various maternal and childhood outcomes and to identify potential critical windows of exposure.

[Influence of environmental noise on sleep quality and sleeping disorders-implications for health]

Environmental noise is a well-known risk factor influencing sleep-wake behavior and sleep quality. Epidemiologic studies have shown that environmental noise is regarded as the most annoying environmental factor. Noise causes modifications in physiologic and mental functions and may result in health outcomes like elevated blood pressure and ischemic heart disease. Reactions to high sound levels during sleep are decreased sleep intensity, arousals, and increased stress hormone secretion. Effects of poor sleep quality are reduced cognitive performance, tiredness, and psychosomatic symptoms. Long-term consequences of recurrent sleep loss due to environmental noise may be heart disease and increased medication intake. Arousals occur especially due to single noise events and intermittent noise. Laboratory and field studies showed no habituation of physiologic parameters to high sound levels. Sleep is especially sensitive to noise; therefore, sound levels during nighttime should be much lower than during daytime.

Urban road traffic noise and annoyance: the effect of a quiet façade

Road traffic noise in urban areas is a major source of annoyance. A quiet façade has been hypothesized to beneficially affect annoyance. However, only a limited number of studies investigated this hypothesis, and further quantification is needed. This study investigates the effect of a relatively quiet façade on the annoyance response. Logistic regression was performed in a large population based study (GLOBE, N~18,000), to study the association between road traffic noise exposure at the most exposed dwelling façade (L(den)) and annoyance in: (1) The subgroup with a relatively quiet façade (large difference in road traffic noise level between most and least exposed façade (Q>10 dB); (2) the subgroup without a relatively quiet façade (Q<10 dB). Questionnaire data were linked to individual exposure assessment based on detailed spatial data (GIS) and standard modeling techniques. Annoyance was less likely (OR(Q) (>10)<OR(Q) (<10)) in the subgroup with relatively quiet façade compared to the subgroup without relatively quiet façade. The difference in response between groups seemed to increase with increasing Q and L(den). Results indicate that residents may benefit from a quiet façade to the dwelling.