Association between occupational noise exposure level and pure-tone audiometry abnormalities among Metropolitan Manila Development Authority employees: A cross-sectional study

Traffic enforcers are exposed to various occupational health and safety hazards, including noise pollution, which may lead to occupational hearing loss. This cross-sectional study aimed to estimate the prevalence of hearing loss and to assess the relationship between occupational noise exposure level (ONEL) and abnormalities in air conduction thresholds among Metropolitan Manila Development Authority (MMDA) employees along Epifanio delos Santos Avenue, Philippines. Eight-hour ONELs were measured among 108 participants working with greater than 5 years of service. Participants had hearing evaluations using pure tone audiometry (PTA) to calculate the prevalence of hearing loss. Generalized linear models with a Poisson distribution were fitted to estimate the association between ONEL and audiologic abnormalities, controlling for confounding factors. Approximately 16% of employees had hearing loss. The prevalence of hearing loss was higher with ONEL exposures greater than 85 A-weighted decibels (dBA), with traffic enforcers exposed to higher ONELs than office workers. ONELs greater than 85 dBA were related to audiologic abnormalities at different frequencies in PTA. The prevalence of audiologic abnormalities at 4000 Hz and 6000 Hz was 48% higher (adjusted prevalence ratio [aPR], 1.48; 95% CI, 1.12-1.96) and 25% higher (aPR, 1.25; 95% CI, 1.00-1.55), respectively, among participants with ONELs greater than 85 dBA than with ONELs less than or equal to 85 dBA. Participants exposed to ONELs greater than 85 dBA, more likely traffic enforcers, may have increased risk of audiologic abnormalities. Regular ONEL monitoring is warranted for occupational risk assessment of traffic enforcers. A hearing conservation program may need to be considered for this population. Additional studies are needed to determine trends in hearing deterioration among traffic enforcers.

Long-Term Exposure to Road Traffic Noise and Incident Heart Failure: Evidence From UK Biobank

BACKGROUND

Evidence on road traffic noise and heart failure (HF) is limited, and little is known on the potential mediation roles of acute myocardial infarction (AMI), hypertension, or diabetes.

OBJECTIVES

The purpose of this study was to evaluate the impacts of long-term road traffic noise exposure on the risk of incident HF considering air pollution, and explore the mediations of the previously mentioned diseases.

METHODS

This prospective study included 424,767 participants without HF at baseline in UK Biobank. The residential-level noise and air pollution exposure was estimated, and the incident HF was identified through linkages with medical records. Cox proportional hazard models were used to estimate HRs. Furthermore, time-dependent mediation was performed.

RESULTS

During a median 12.5 years of follow-up, 12,817 incident HF were ascertained. The HRs were 1.08 (95% CI: 1.00-1.16) per 10 dB[A] increase in weighted average 24-hour road traffic noise level (Lden), and 1.15 (95% CI: 1.02-1.31) for exposure to Lden >65 dB[A] compared with the reference category (Lden ≤55 dB[A]), respectively. Furthermore, the strongest combined effects were found in those with both high exposures to road traffic noise and air pollution including fine particles and nitrogen dioxide. Prior AMI before HF within 2 years' time interval mediated 12.5% of the association of road traffic noise with HF.

CONCLUSIONS

More attention should be paid and a preventive strategy should be considered to alleviate the disease burden of HF related to road traffic noise exposure, especially in participants who survived AMI and developed HF within 2 years.

Advanced Noise Indicator Mapping Relying on a City Microphone Network

In this work, a methodology is presented for city-wide road traffic noise indicator mapping. The need for direct access to traffic data is bypassed by relying on street categorization and a city microphone network. The starting point for the deterministic modeling is a previously developed but simplified dynamic traffic model, the latter necessary to predict statistical and dynamic noise indicators and to estimate the number of noise events. The sound propagation module combines aspects of the CNOSSOS and QSIDE models. In the next step, a machine learning technique-an artificial neural network in this work-is used to weigh the outcomes of the deterministic predictions of various traffic parameter scenarios (linked to street categories) to approach the measured indicators from the microphone network. Application to the city of Barcelona showed that the differences between predictions and measurements typically lie within 2-3 dB, which should be positioned relative to the 3 dB variation in street-side measurements when microphone positioning relative to the façade is not fixed. The number of events is predicted with 30% accuracy. Indicators can be predicted as averages over day, evening and night periods, but also at an hourly scale; shorter time periods do not seem to negatively affect modeling accuracy. The current methodology opens the way to include a broad set of noise indicators in city-wide environmental noise impact assessment.

Road Traffic Noise and Incidence of Primary Hypertension: A Prospective Analysis in UK Biobank

Background

The quality of evidence regarding the associations between road traffic noise and hypertension is low due to the limitations of cross-sectional study design, and the role of air pollution remains to be further clarified.

Objectives

The purpose of this study was to evaluate the associations of long-term road traffic noise exposure with incident primary hypertension; we conducted a prospective population-based analysis in UK Biobank.

Methods

Road traffic noise was estimated at baseline residential address using the common noise assessment method model. Incident hypertension was ascertained through linkage with medical records. Cox proportional hazard models were used to estimate hazard ratios (HRs) for association in an analytical sample size of over 240,000 participants free of hypertension at baseline, adjusting for covariates determined via directed acyclic graph.

Results

During a median of 8.1 years follow-up, 21,140 incident primary hypertension (International Classification of Diseases-10th Revision [ICD-10]: I10) were ascertained. The HR for a 10 dB[A] increment in mean weighted average 24-hour road traffic noise level (L den ) exposure was 1.07 (95% CI: 1.02-1.13). A dose-response relationship was found, with HR of 1.13 (95% CI: 1.03-1.25) for L den >65 dB[A] vs ≤55 dB[A] (P for trend <0.05). The associations were all robust to adjustment for fine particles (PM2.5) and nitrogen dioxide (NO2). Furthermore, high exposure to both road traffic noise and air pollution was associated with the highest hypertension risk.

Conclusions

Long-term exposure to road traffic noise was associated with increased incidence of primary hypertension, and the effect estimates were stronger in presence of higher air pollution.

Noise Emission Models of Electric Vehicles Considering Speed, Acceleration, and Motion State

Electric vehicles, known for their low-noise emission, are popular and widespread in metropolises in China, and they provide an opportunity for a reduction in environmental noise from vehicles. To understand the noise from electric vehicles better, this study develops noise emission models considering speed, acceleration, and motion state. The model construction is based on the data collected from a pass-by noise measurement experiment in Guangzhou, China. The models describe a linear relationship between the noise level, the logarithm of speed, and the acceleration for multiple motion states (i.e., the constant-speed state, the acceleration state, and the deceleration state). From the spectrum analysis, the low-frequency noise is barely affected by the speed and acceleration, but the noise at a certain frequency is most sensitive to them. Compared to other models, the proposed ones have the highest accuracy and the greatest ability for extrapolation and generalization.

How Do Road Traffic Noise and Residential Greenness Correlate with Noise Annoyance and Long-Term Stress? Protocol and Pilot Study for a Large Field Survey with a Cross-Sectional Design

Urban areas are continuously growing, and densification is a frequent strategy to limit urban expansion. This generally entails a loss of green spaces (GSs) and an increase in noise pollution, which has negative effects on health. Within the research project RESTORE (Restorative potential of green spaces in noise-polluted environments), an extended cross-sectional field study in the city of Zurich, Switzerland, is conducted. The aim is to assess the relationship between noise annoyance and stress (self-perceived and physiological) as well as their association with road traffic noise and GSs. A representative stratified sample of participants from more than 5000 inhabitants will be contacted to complete an online survey. In addition to the self-reported stress identified by the questionnaire, hair cortisol and cortisone probes from a subsample of participants will be obtained to determine physiological stress. Participants are selected according to their dwelling location using a spatial analysis to determine exposure to different road traffic noise levels and access to GSs. Further, characteristics of individuals as well as acoustical and non-acoustical attributes of GSs are accounted for. This paper presents the study protocol and reports the first results of a pilot study to test the feasibility of the protocol.

Associations of road traffic noise and its frequency spectrum with prevalent depression in Taichung, Taiwan

Introduction

Exposure to road traffic noise has been reported to be associated with depression in many epidemiological studies, but the association between noise frequency spectrum and depression remains unclear. This community-based study investigated the associations between road traffic noise exposure and its frequency components with prevalent depression.

Methods

A total of 3,191 residents living in Taichung who participated in the Taiwan Biobank between 2010 and 2017, were included as study participants. The land-use regression models were used to evaluate individual annual average values of A-weighted equivalent sound level over 24 h (L_eq,24h) and particulate matter with an aerodynamic diameter <2.5 μm (PM_2.5) using the geographic information system. Multiple logistic regression was applied to estimate the odds ratios (ORs) for depression after adjusting for potential risk factors and PM_2.5.

Results

An interquartile range increase in L_eq,24h at full frequency (4.7 dBA), 1,000 Hz (5.2 dB), and 2,000 Hz (4.8 dB) was significantly associated with an elevated risk for depression with ORs of 1.62 (95% confidence interval [CI]: 1.03, 2.55), 1.58 (95% CI: 1.05, 2.37), and 1.58 (95% CI:1.03, 2.43), respectively, by controlling for PM_2.5. The high-exposure group (≥3rd quartile median of noise levels) at full frequency, 1,000 Hz, and 2,000 Hz had an increased risk for depression with ORs of 2.65 (95% CI: 1.16-6.05), 2.47 (95% CI: 1.07-5.70), and 2.60 (95% CI: 1.10-6.12), respectively, compared with the reference group (<1st quartile of noise levels) after adjustment for PM_2.5. Significant exposure-response trends were observed between the prevalent depression and noise exposure by quartiles at full frequency, 1,000 Hz, and 2,000 Hz (all p < 0.05).

Conclusion

Exposure to road traffic noise may be associated with an increased prevalence of depression, particularly at 1,000 and 2,000 Hz.

Statistical Pass-By for Unattended Road Traffic Noise Measurement in an Urban Environment

Low-noise surfaces have become a common mitigation action in the last decade, so much so that different methods for feature extraction have been established to evaluate their efficacy. Among these, the Close Proximity Index (CPX) evaluates the noise emissions by means of multiple runs at different speeds performed with a vehicle equipped with a reference tire and with acoustic sensors close to the wheel. However, signals acquired with CPX make it source oriented, and the analysis does not consider the real traffic flow of the studied site for a receiver-oriented approach. These aspects are remedied by Statistical Pass-By (SPB), a method based on sensor feature extraction with live detection of events; noise and speed acquisitions are performed at the roadside in real case scenarios. Unfortunately, the specific SPB requirements for its measurement setup do not allow an evaluation in urban context unless a special setup is used, but this may alter the acoustical context in which the measurement was performed. The present paper illustrates the testing and validation of a method named Urban Pass-By (U-SPB), developed during the LIFE NEREiDE project. U-SPB originates from standard SPB, exploits unattended measurements and develops an in-lab feature detection and extraction procedure. The U-SPB extends the evaluation in terms of before/after data comparison of the efficiency of low-noise laying in an urban context while combining the estimation of long-term noise levels and traffic parameters for other environmental noise purposes, such as noise mapping and action planning.

Experimental Study on the Effect of Urban Road Traffic Noise on Heart Rate Variability of Noise-Sensitive People

Epidemiological studies have confirmed that long-term exposure to road traffic noise can cause cardiovascular diseases (CDs), and when noise exposure reaches a certain level, the risk of related CDs significantly increases. Currently, a large number of Chinese residents are exposed to high noise exposure, which could greatly increase the risk of cardiovascular disease. On the other hand, relevant studies have found that people with high noise sensitivity are more susceptible to noise. And it is necessary to pay more attention to the high noise-sensitive people. This study investigated the acute physiological effect of different noise-sensitive groups by indoor-level noise stimulus experiments under laboratory conditions, by observing heart rate variability (HRV) indicators, including standard deviation of NN intervals (SDNN), low frequency/high frequency (LF/HF), and heart rate (HR). The results showed that (a) there was no significant difference in HRV between the high-sensitive group and the low-sensitive group at the physiological baseline and the different stimulating noise levels. (b) Then, based on the theory of cumulative effect of noise proposed by WHO Regional Office for Europe, non-significant but observable differences between groups were further discussed. By analyzing differences of the variation trends and the within-group significant changes of SDNN and HR between the two groups, the results tended to show that the high-sensitive group is more affected by road traffic noise. In addition, the values of SDNN and HR showed observable between-group differences at 55 dB (A) and 65 dB (A) which corresponding to the SPL associated with a significantly increased risk of cardiovascular disease concerned by epidemiological studies. According to the cumulative effect theory (WHO), these differences in HRV caused by short-term noise stimulation may have the potential to produce physiological response and lead to between-groups differences in prevalence after long-term recurrent effect, and deserve attention and further research.

Long-Term Exposure to Air Pollution, Road Traffic Noise, and Heart Failure Incidence: The Danish Nurse Cohort

Background We examined the association of long-term exposure to air pollution and road traffic noise with incident heart failure (HF). Methods And Results Using data on female nurses from the Danish Nurse Cohort (aged >44 years), we investigated associations between 3-year mean exposures to air pollution and road traffic noise and incident HF using Cox regression models, adjusting for relevant confounders. Incidence of HF was defined as the first hospital contact (inpatient, outpatient, or emergency) between cohort baseline (1993 or 1999) and December 31, 2014, based on the Danish National Patient Register. Annual mean levels of particulate matter with a diameter <2.5 µm since 1990 and NO₂ and road traffic noise since 1970 were estimated at participants' residences. Of the 22 189 nurses, 484 developed HF. We detected associations with all 3 pollutants, with hazard ratios (HRs) of 1.17 (95% CI, 1.01-1.36), 1.10 (95% CI, 0.99-1.22), and 1.12 (95% CI, 0.99-1.26) per increase of 5.1 µg/m³ in particulate matter with a diameter <2.5 µm, 8.6 µg/m³ in NO₂, and 9.3 dB in road traffic noise, respectively. We observed an enhanced risk of HF incidence for those exposed to high levels of the 3 pollutants; however, the effect modification of coexposure was not statistically significant. Former smokers and nurses with hypertension showed the strongest associations with particulate matter with a diameter <2.5 µm (P_{effect modification}<0.05). Conclusions We found that long-term exposures to air pollution and road traffic noise were independently associated with HF.

Effects of Exposure to Road, Railway, Airport and Recreational Noise on Blood Pressure and Hypertension

Noise is one of the most diffused environmental stressors affecting modern life. As such, the scientific community is committed to studying the main emission and transmission mechanisms aiming at reducing citizens' exposure, but is also actively studying the effects that noise has on health. However, scientific literature lacks data on multiple sources of noise and cardiovascular outcomes. The present cross-sectional study aims to evaluate the impact that different types of noise source (road, railway, airport and recreational) in an urban context have on blood pressure variations and hypertension. 517 citizens of Pisa, Italy, were subjected to a structured questionnaire and five measures of blood pressure in one day. Participants were living in the same building for at least 5 years, were aged from 37 to 72 years old and were exposed to one or more noise sources among air traffic, road traffic, railway and recreational noise. Logistic and multivariate linear regression models have been applied in order to assess the association between exposures and health outcomes. The analyses showed that prevalence of high levels of diastolic blood pressure (DBP) is consistent with an increase of 5 dB (A) of night-time noise (β = 0.50 95% CI: 0.18-0.81). Furthermore, increased DBP is also positively associated with more noise sensitive subjects, older than 65 years old, without domestic noise protection, or who never close windows. Among the various noise sources, railway noise was found to be the most associated with DBP (β = 0.68; 95% CI: -1.36, 2.72). The obtained relation between DBP and night-time noise levels reinforces current knowledge.

Modeling and Mapping of Combined Noise Annoyance for Aircraft and Road Traffic Based on a Partial Loudness Model

Complex transportation systems often produce combined exposure to aircraft and road noise. Depending on the noise source, the annoyance response is different, and a masking effect occurs between the noise sources within the combined noise. Considering these characteristics, partial loudness was adopted to evaluate noise annoyance. First, a partial loudness model incorporating binaural inhibition was proposed and validated. Second, short- and long-term annoyance models were developed using partial loudness. Finally, the annoyance of combined noise was visualized as a map. These models can evaluate the annoyance by considering both the intensity and frequency characteristics of the noise. In addition, it is possible to quantify the masking effect that occurs between noise sources. Combined noise annoyance maps depict the degree of annoyance of residents and show the background noise effect, which is not seen on general noise maps.

Short-Term Annoyance Due to Night-Time Road, Railway, and Air Traffic Noise: Role of the Noise Source, the Acoustical Metric, and Non-Acoustical Factors

Field studies on traffic noise-induced annoyance have predominantly used estimated outside noise levels. We intended to complement existing knowledge with exposure–response relationships that are based on precise indoor noise measurements. Acoustic recordings inside the bedrooms of nightly road traffic and annoyance ratings in the following morning were obtained from 40 suburban residents (mean age 29.1 years ± 11.7; 26 females). We derived exposure–response functions for the probability to be “annoyed at least a little” (%LA). Further analyses compared data from the current study with those from two earlier studies on railway and aircraft noise. Annoyance increased with the number of traffic events and the equivalent sound pressure level. The inclusion of non-acoustical factors (such as assessment of road transport) improved the prediction considerably. When comparing the different traffic noise sources, %LA was higher for road than for air traffic at a given L_Aeq,night, but higher for road and railway than for air traffic at a given number of noise events. Acoustical as well as non-acoustical factors impact short-term annoyance induced by road, railway, and air traffic. Annoyance varies across noise sources, which may be due to differences in acoustical characteristics or in the temporal noise distribution throughout the night.

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.

[Estimation of Health Risk Posed by Road Traffic Noise in Japan Based on the Environmental Noise Guidelines for the European Region]

OBJECTIVES

Traffic noise exposure is associated with adverse health effects such as environmental sleep disorder, ischaemic heart disease (IHD), stroke and diabetes. The health risks posed by traffic noise were estimated to be quite high in European countries. However, in Japan, no estimation has ever been conducted. In the present study, we estimated the health risk posed by road traffic noise in Japan.

METHODS

We estimated the risks of environmental sleep disorder (high sleep disturbance) and IHD caused by road traffic noise in Japan as of 2015 on the basis of existing noise-exposure estimates, vital statistics of deaths, and patient survey with exposure-response relationships proposed by the Environmental Noise Guidelines for the European Region issued in 2018. We employed old information on noise exposure in 1994 because it is the only information currently available in Japan. We also estimated the health risks of noise exposure levels that were equivalent to the Japanese environmental quality standards.

RESULTS

The estimated numbers of patients with environmental sleep disorder and IHD caused by road traffic noise were approximately 1,200,000 and 9,000, respectively. The estimated number of mortalities from IHD was approximately 1,700. The noise exposure level equivalent to the Japanese noise standards caused a lifetime mortality rate of more than 10^-2, which was extremely high as an environmental health risk.

CONCLUSIONS

As in European countries, road traffic noise was one of the most important environmental risk factors in Japan. However, the current Japanese noise standards are insufficient for the protection of public health.

Traffic Noise and Mental Health: A Systematic Review and Meta-Analysis

Recent evidence suggests that traffic noise may negatively impact mental health. However, existing systematic reviews provide an incomplete overview of the effects of all traffic noise sources on mental health. We conducted a systematic literature search and summarized the evidence for road, railway, or aircraft noise-related risks of depression, anxiety, cognitive decline, and dementia among adults. We included 31 studies (26 on depression and/or anxiety disorders, 5 on dementia). The meta-analysis of five aircraft noise studies found that depression risk increased significantly by 12% per 10 dB L_DEN (Effect Size = 1.12, 95% CI 1.02–1.23). The meta-analyses of road (11 studies) and railway traffic noise (3 studies) indicated 2–3% (not statistically significant) increases in depression risk per 10 dB L_DEN. Results for road traffic noise related anxiety were similar. We did not find enough studies to meta-analyze anxiety and railway or aircraft noise, and dementia/ cognitive impairment and any traffic noise. In conclusion, aircraft noise exposure increases the risk for depression. Otherwise, we did not detect statistically significant risk increases due to road and railway traffic noise or for anxiety. More research on the association of cognitive disorders and traffic noise is required. Public policies to reduce environmental traffic noise might not only increase wellness (by reducing noise-induced annoyance), but might contribute to the prevention of depression and anxiety disorders.

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.

Association Between Road Traffic Noise and Incidence of Diabetes Mellitus and Hypertension in Toronto, Canada: A Population-Based Cohort Study

Background Exposure to road traffic noise has been linked to cardiometabolic complications, such as elevated blood pressure and glucose dysregulation. However, epidemiologic evidence linking road traffic noise to diabetes mellitus and hypertension remains scarce. We examined associations between road traffic noise and the incidence of diabetes mellitus and hypertension in Toronto, Canada. Methods and Results Using the Ontario Population Health and Environment Cohort, we conducted a retrospective, population-based cohort study of long-term residents of Toronto, aged 35 to 100 years, who were registered for provincial publicly funded health insurance, and were without a history of hypertension (n=701 174) or diabetes mellitus (n=914 607). Road traffic noise exposure levels were assessed by the equivalent continuous A-weighted sound pressure level (dBA) for the 24-hour day and the equivalent continuous A-weighted sound pressure level for the night (11 pm-7am). Noise exposures were assigned to subjects according to their annual residential postal codes during the 15-year follow-up. We used random-effect Cox proportional hazards models adjusting for personal and area-level characteristics. From 2001 to 2015, each interquartile range increase in the equivalent continuous A-weighted sound pressure level (dBA) for the 24-hour day (10.0 dBA) was associated with an 8% increase in incident diabetes mellitus (95% CI, 1.07-1.09) and a 2% increase in hypertension (95% CI, 1.01-1.03). We obtained similar estimates with the equivalent continuous A-weighted sound pressure level for the night (11 pm-7am). These results were robust to all sensitivity analyses conducted, including further adjusting for traffic-related air pollutants (ultrafine particles and nitrogen dioxide). For both hypertension and diabetes mellitus, we observed stronger associations with the equivalent continuous A-weighted sound pressure level (dBA) for the 24-hour day among women and younger adults (aged <60 years). Conclusions Long-term exposure to road traffic noise was associated with an increased incidence of diabetes mellitus and hypertension in Toronto.

Effects of Motorcycle Noise on Annoyance-A Cross-Sectional Study in the Alps

Motorcycle noise is an increasing noise problem, especially in Alpine valleys with winding roads and low environmental noise. The annoyance response to motorcycle engine noise is extraordinarily high in comparison to other traffic noise and cannot be explained by standard noise assessment curves. Therefore, the Tyrolean state government decided to initiate a multi-purpose study. Exposures were calculated based on sound-measurements taken across the entire district of Reutte in the western part of the State of Tyrol and a telephone survey (n = 545) was conducted with regional participants. The influence of demographic characteristics; sensitivity to noise; attitudes towards motorcycles and background noise on the annoyance was examined using bivariate analyses. In addition; exposure-response curves and their 95% confidence intervals with cut-off points of 60% and 72% for “highly annoyed” were created. The exposure annoyance response curves for motorcycle noise show a shift of more than 30 dB in annoyance reaction compared to other road traffic noise. The annoyance response to motorcycle noise in this Alpine region is concentrated on summer Sundays and Saturdays and is independent of the background exposure caused by other road traffic

On the Temporal Stability of People's Annoyance with Road Traffic Noise

Sixty-one social surveys on annoyance caused by road traffic noise conducted world-wide over a period of forty-five years have been re-analyzed by various means for possible temporal trends. Eighteen of these surveys were conducted after 2000. People's reactions to road traffic noise seem to have been stable across the study period. No indications were found that would warrant revision of the current EU reference curve for predicting the annoyance from road traffic noise.

Aggregate Impact of Anomalous Noise Events on the WASN-Based Computation of Road Traffic Noise Levels in Urban and Suburban Environments

Environmental noise can be defined as the accumulation of noise pollution caused by sounds generated by outdoor human activities, Road Traffic Noise (RTN) being the main source in urban and suburban areas. To address the negative effects of environmental noise on public health, the European Environmental Noise Directive requires EU member states to tailor noise maps and define the corresponding action plans every five years for major agglomerations and key infrastructures. Noise maps have been hitherto created from expert-based measurements, after cleaning the recorded acoustic data of undesired acoustic events, or Anomalous Noise Events (ANEs). In recent years, Wireless Acoustic Sensor Networks (WASNs) have become an alternative. However, most of the proposals focus on measuring global noise levels without taking into account the presence of ANEs. The LIFE DYNAMAP project has developed a WASN-based dynamic noise mapping system to analyze the acoustic impact of road infrastructures in real time based solely on RTN levels. After studying the bias caused by individual ANEs on the computation of the A-weighted equivalent noise levels through an expert-based dataset obtained before installing the sensor networks, this work evaluates the aggregate impact of the ANEs on the RTN measurements in a real-operation environment. To that effect, 304 h and 20 min of labeled acoustic data collected through the two WASNs deployed in both pilot areas have been analyzed, computing the individual and aggregate impacts of ANEs for each sensor location and impact range (low, medium and high) for a 5 min integration time. The study shows the regular occurrence of ANEs when monitoring RTN levels in both acoustic environments, which are especially common in the urban area. Moreover, the results reveal that the aggregate contribution of low- and medium-impact ANEs can become as critical as the presence of high-impact individual ANEs, thus highlighting the importance of their automatic removal to obtain reliable WASN-based RTN maps in real-operation environments.

Evidence for Environmental Noise Effects on Health for the United Kingdom Policy Context: A Systematic Review of the Effects of Environmental Noise on Mental Health, Wellbeing, Quality of Life, Cancer, Dementia, Birth, Reproductive Outcomes, and Cognition

This systematic review commissioned by the UK Department for the Environment, Food and Rural Affairs (Defra), considers how the evidence base for noise effects on health has changed following the recent reviews undertaken for the WHO Environmental Noise Guidelines. This systematic review assesses the quality of the evidence for environmental noise effects on mental health, wellbeing, and quality of life; birth and reproductive outcomes; and cognition for papers published since the WHO reviews (mid-2015 to March 2019), as well as for cancer and dementia (January 2014 to March 2019). Using the GRADE methodology (Grading of Recommendations Assessment, Development and Evaluation) most evidence was rated as low quality as opposed to very low quality in the previous reviews. There is now low-quality evidence for a harmful effect of road traffic noise on medication use and interview measures of depression and anxiety and low quality evidence for a harmful effect of road traffic noise, aircraft noise, and railway noise on some cancer outcomes. Many other conclusions from the WHO evidence reviews remain unchanged. The conclusions remain limited by the low number of studies for many outcomes. The quantification of health effects for other noise sources including wind turbine, neighbour, industrial, and combined noise remains a research priority.

Application of the Intermittency Ratio Metric for the Classification of Urban Sites Based on Road Traffic Noise Events

Human hearing adapts to steady signals, but remains very sensitive to fluctuations as well as to prominent, salient noise events. The higher these fluctuations are, the more annoying a sound is possibly perceived. To quantify these fluctuations, descriptors have been proposed in the literature and, among these, the intermittency ratio (IR) has been formulated to quantify the eventfulness of an exposure from transportation noise. This paper deals with the application of IR to urban road traffic noise data, collected in terms of 1 s A-weighted sound pressure level (SPL), without being attended, monitored continuously for 24 h in 90 sites in the city of Milan. IR was computed on each hourly data of the 251 time series available (lasting 24 h each), including different types of roads, from motorways to local roads with low traffic flow. The obtained hourly IR values have been processed by clustering methods to extract the most significant temporal pattern features of IR in order to figure out a criterion to classify the urban sites taking into account road traffic noise events, which potentially increase annoyance. Two clusters have been obtained and a “non-acoustic” parameter x, determined by combination of the traffic flow rate in three hourly intervals, has allowed to associate each site with the cluster membership. The described methodology could be fruitfully applied on road traffic noise data in other cities. Moreover, to have a more detailed characterization of noise exposure, IR, describing SPL short-term temporal variations, has proved to be a useful supplementary metric accompanying L_Aeq, which is limited to measure the energy content of the noise exposure.

Self-Reported Sleep Disturbance from Road, Rail and Aircraft Noise: Exposure-Response Relationships and Effect Modifiers in the SiRENE Study

This survey investigates the cross-sectional association between nighttime road, rail and aircraft noise exposure and the probability to be highly sleep disturbed (%HSD), as measured by self-report in postal and online questionnaires. As part of the Swiss SiRENE study, a total of 5592 survey participants in the entire country were selected based on a stratified random sample of their dwelling. Self-reported sleep disturbance was measured using an ICBEN-style 5-point verbal scale. The survey was carried out in four waves at different times of the year. Source-specific noise exposure was calculated for several façade points for each dwelling. After adjustment for potential confounders, all three noise sources showed a statistically significant association between the nighttime noise level LNight at the most exposed façade point and the probability to report high sleep disturbance, as determined by logistic regression. The association was strongest for aircraft noise and weakest for road traffic noise. We a priori studied the role of a range of effect modifiers, including the “eventfulness” of noise exposure, expressed as the Intermittency Ratio (IR) metric, bedroom window position, bedroom orientation towards the closest street, access to a quiet side of the dwelling, degree of urbanization, sleep timing factors (bedtime and sleep duration), sleep medication intake, survey season and night air temperature. While bedroom orientation exhibited a strong moderating effect, with an Leq-equivalent of nearly 20 dB if the bedroom faces away from the nearest street, the LNight-%HSD associations were not affected by bedroom window position, sleep timing factors, survey season, or temperature.

Associations of Various Nighttime Noise Exposure Indicators with Objective Sleep Efficiency and Self-Reported Sleep Quality: A Field Study

It is unclear which noise exposure time window and noise characteristics during nighttime are most detrimental for sleep quality in real-life settings. We conducted a field study with 105 volunteers wearing a wrist actimeter to record their sleep during seven days, together with concurrent outdoor noise measurements at their bedroom window. Actimetry-recorded sleep latency increased by 5.6 min (95% confidence interval (CI): 1.6 to 9.6 min) per 10 dB(A) increase in noise exposure during the first hour after bedtime. Actimetry-assessed sleep efficiency was significantly reduced by 2%-3% per 10 dB(A) increase in measured outdoor noise (Leq, 1h) for the last three hours of sleep. For self-reported sleepiness, noise exposure during the last hour prior to wake-up was most crucial, with an increase in the sleepiness score of 0.31 units (95% CI: 0.08 to 0.54) per 10 dB(A) Leq,1h. Associations for estimated indoor noise were not more pronounced than for outdoor noise. Taking noise events into consideration in addition to equivalent sound pressure levels (Leq) only marginally improved the statistical models. Our study provides evidence that matching the nighttime noise exposure time window to the individual's diurnal sleep-wake pattern results in a better estimate of detrimental nighttime noise effects on sleep. We found that noise exposure at the beginning and the end of the sleep is most crucial for sleep quality.