Adverse impact of nocturnal transportation noise on glucose regulation in healthy young adults: Effect of different noise scenarios

Long-term exposure to transportation noise and diabetes mellitus mortality: a national cohort study and updated meta-analysis

BACKGROUND

Long-term exposure to transportation noise is related to cardio-metabolic diseases, with more recent evidence also showing associations with diabetes mellitus (DM) incidence. This study aimed to evaluate the association between transportation noise and DM mortality within the Swiss National Cohort.

METHODS

During 15 years of follow-up (2001-2015; 4.14 million adults), over 72,000 DM deaths were accrued. Source-specific noise was calculated at residential locations, considering moving history. Multi-exposure, time-varying Cox regression was used to derive hazard ratios (HR, and 95%-confidence intervals). Models included road traffic, railway and aircraft noise, air pollution, and individual and area-level covariates including socio-economic position. Analyses included exposure-response modelling, effect modification, and a subset analysis around airports. The main findings were integrated into meta-analyses with published studies on mortality and incidence (separately and combined).

RESULTS

HRs were 1.06 (1.05, 1.07), 1.02 (1.01, 1.03) and 1.01 (0.99, 1.02) per 10 dB day evening-night level (Lden) road traffic, railway and aircraft noise, respectively (adjusted model, including NO2). Splines suggested a threshold for road traffic noise (~ 46 dB Lden, well below the 53 dB Lden WHO guideline level), but not railway noise. Substituting for PM2.5, or including deaths with type 1 DM hardly changed the associations. HRs were higher for males compared to females, and in younger compared to older adults. Focusing only on type 1 DM showed an independent association with road traffic noise. Meta-analysis was only possible for road traffic noise in relation to mortality (1.08 [0.99, 1.18] per 10 dB, n = 4), with the point estimate broadly similar to that for incidence (1.07 [1.05, 1.09] per 10 dB, n = 10). Combining incidence and mortality studies indicated positive associations for each source, strongest for road traffic noise (1.07 [1.05, 1.08], 1.02 [1.01, 1.03], and 1.02 [1.00, 1.03] per 10 dB road traffic [n = 14], railway [n = 5] and aircraft noise [n = 5], respectively).

CONCLUSIONS

This study provides new evidence that transportation noise is associated with diabetes mortality. With the growing evidence and large disease burden, DM should be viewed as an important outcome in the noise and health discussion.

Aircraft and road traffic noise, insulin resistance, and diabetes: The role of neighborhood socioeconomic status in San Diego County

Evidence linking traffic noise to insulin resistance and diabetes is limited and unanswered questions remain regarding the potential effect modification by neighborhood socioeconomic status (nSES). We aimed to assess socioeconomic inequalities in noise exposure, whether road and aircraft noise exposures were associated with insulin resistance or diabetes, and whether nSES modified these relationships. Among the Community of Mine Study in San Diego County, road and aircraft noise exposure at enrollment was calculated based on the static (participant's administrative boundary, and circular buffer around participant homes), and dynamic (mobility data by global positioning system, GPS) spatio-temporal aggregation methods. Associations of noise with insulin resistance (HOMA-IR) or type 2 diabetes (T2DM) were quantified using generalized estimating equation models adjusted for sex, age, ethnicity, individual income, and air pollution (nitrogen dioxide) exposure. Additive interaction between noise and nSES was assessed. Among 573 participants (mean age 58.7 y), participants living in low nSES were exposed to higher levels of aircraft and road noise using noise level at the census tract, circular buffer, or Kernel Density Estimation (KDE) of GPS data. Participants exposed to road noise greater or equal to the median (53 dB(A)) at the census tract and living in low nSES had an increased level of insulin resistance (β = 0.15, 95%CI: -0.04, 0.34) and higher odds of T2DM (Odds Ratio = 2.34, 95%CI: 1.12, 4.90). A positive additive interaction was found as participants living in low nSES had higher odds of T2DM. The impact of noise exposure on insulin resistance and T2DM differs substantially by nSES. Public health benefits of reducing exposure to road or aircraft noise would be larger in individuals living in low nSES.

Effects of noise on pedestrians in urban environments where road traffic is the main source of sound

Research combining the measurement of objective variables with surveys of people's perception of noise on city streets is useful in terms of understanding the impact of urban noise on the population and improving the environment. Although previous investigations have analysed the factors that may influence the noise annoyance of citizens, it is usually considered as a global aspect. This paper presents research based on in situ surveys and objective variables (urban, meteorological and noise indicators) to evaluate some specific effects of noise on pedestrians in urban environments where road traffic is the main source of sound. The results show significant relationships of the effects of noise and perceptions of how noisy urban environments are with variables such as building height, road category and temperature, with correlation coefficients ranging from 0.37 to 0.64. Significant correlations between these subjective variables and the acoustic variables were also found, with explanations of variability that reached values of up to 50 %. A multivariate analysis revealed that both urban variables (especially the category of street) and environmental variables can be an alternative or a complement to models predicting the effects and perception of environmental noise based only on acoustic variables.

Automated identification and assessment of environmental noise sources

Noise pollution is one of the major health risks in urban life. The approach to measurement and identification of noise sources needs to be improved and enhanced to reduce high costs. Long measurement times and the need for expensive equipment and trained personnel must be automated. Simplifying the identification of main noise sources and excluding residual and background noise allows more effective measures. By spatially filtering the acoustic scene and combining unsupervised learning with psychoacoustic features, this paper presents a prototype system capable of automated calculation of the contribution of individual noise sources to the total noise level. Pilot measurements were performed at three different locations in the city of Ljubljana, Slovenia. Equivalent sound pressure levels obtained with the device were compared to the results obtained by manually marking individual parts of each of the three measurements. The proposed approach correctly identified the main noise sources in the vicinity of the measurement points.

Railway noise and diabetes among residents living close to the railways in Västra Götaland, Sweden: Cross-sectional mediation analysis on obesity indicators

Railway noise is expected to increase in Europe and Sweden as well, following recommendations for a more sustainable transportation mode. This forecasted increase might lead to higher level of noise exposure, higher population exposure and potentially increased night-time exposure. Evidence supports an effect of transportation noise on several health outcomes, including metabolic conditions such as diabetes. However, few studies were directed to railway noise; present studies on railway noise and diabetes so far show ambiguous results while some studies report an association between railway noise and obesity. The aim of this study is to investigate the relationship between railway noise and diabetes prevalence and to assess whether obesity might be a mediator in this association. The study population (N = 5381) was randomly selected from residents living within 1 km of a trafficked railway in Västra Götaland, Sweden. Survey data was combined with modelled exposures and health register data (ICD10 codes for diabetes). The study uses a cross sectional design, logistic regression analysis and a counterfactual mediation analysis. We found an increase in the prevalence of diabetes associated with the exposure to railway noise: OR = 1.33 per 10 dB increase L_den (95% CI 1.09-1.63) accounting for sociodemographic and lifestyle factors. BMI and waist circumference partially mediate the association between railway noise and diabetes. This is the first study to report an association between railway noise and diabetes in Sweden. BMI and waist circumference seem to be a potential mediators in this association. Still, future studies should further explore the mechanisms from noise to diabetes, considering different pathways in relation to obesity but also exploring other potential mediators.

Health impact assessment of transportation noise in two Estonian cities

Transportation noise is a growing public health concern worldwide, especially in urban areas, causing annoyance, sleep disturbance, cardiovascular diseases and other health effects. Recently, European Commission (EC) has developed a mutual methodology for assessing health impacts of transportation noise in European Union using strategic noise mapping. Applying this methodology, our aim was to quantify the health effects of road, rail and aircraft noise in two Estonian cities, Tallinn and Tartu. We also aimed to assess sensitivity of this methodology, while implementing lower threshold values and employing additional health outcomes. The proportion of highly annoyed residents due to road traffic noise was 11.6% in Tallinn, and 9.2% in Tartu; around 2.5% residents in both cities could have high sleeping disturbances. As exposure to railway and aircraft noise was relatively low in both cities, people with high annoyance and high sleep disturbance caused by railway and aircraft noise was below 1%. Ischemic heart disease (IHD) cases attributable to road traffic noise was estimated to be 122.6 in Tallinn and 21.5 in Tartu. Altogether transportation noise was estimated to cause 1807 disability adjusted life years (DALYs) in Tallinn and 370 DALYs in Tartu. The health costs were calculated as €126.5 and €25.9 million annually, respectively in the two cities. When we included higher number of health outcomes (stroke incidence, IHD deaths) and lowered exposure threshold by 5 dB, the annual burden of disease was doubled. As the latest epidemiological studies showed transportation noise having larger number of effects on lower noise levels, the results with the currently applied European Commission health impact assessment (HIA) methodology were rather conservative. Despite of uncertainties associated to applied methodology, transportation noise, especially road traffic noise, is an important environmental risk factor, that leads to considerable loss of healthy life years and causes large health costs in urban areas.

Variability of traffic noise pollution levels as a function of city size variables

Noise levels measured in 27 cities with different areas (from 0.6 km² to 59.27 km²) and populations (from approximately 2000 to 70,000 inhabitants) were compared with respect to five different urban characteristics (population, area, total street length, density, and linear density). Comparisons were conducted for both overall city noise levels and noise registered on five types of roads with different functionality using the Categorisation Method. The results showed that four of the five cities' characteristics presented a significant correlation with the noise levels (all except for density). The calculated correlations were better for noise levels in the different categories than the overall noise values, with higher explained variability on the streets with more traffic. Therefore, the road categorisation method can be used not only to assess the noise variations within cities, but also to better explain the effect of noise on the analysed city characteristics. The results of the calculated relationships enable the estimation of noise levels both currently and in future urban developments of noise values on different types of streets.

Residential Green and Blue Spaces and Type 2 Diabetes Mellitus: A Population-Based Health Study in China

Evidence on the health benefits of green space in residential environments is still limited, and few studies have investigated the potential association between blue space and type 2 diabetes mellitus (T2DM) prevalence. This study included 39,019 participants who had completed the baseline survey from the Henan Rural Cohort Study, 2015-2017. The Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) were employed to characterize the residential green space, and the distance from the participant's residential address to the nearest water body was considered to represent the residential blue space. Mixed effect models were applied to evaluate the associations of the residential environment with T2DM and fasting blood glucose (FBG) levels. An interquartile range (IQR) increase in NDVI and EVI was significantly associated with a 13.4% (odds ratio (OR): 0.866, 95% Confidence interval (CI): 0.830,0.903) and 14.2% (OR: 0.858, 95% CI: 0.817,0.901) decreased risk of T2DM, respectively. The residential green space was associated with lower fasting blood glucose levels in men (%change, -2.060 in men vs. -0.972 in women) and the elderly (%change, -1.696 in elderly vs. -1.268 in young people). Additionally, people who lived more than 5 km from the water body had a 15.7% lower risk of T2DM (OR: 0.843, 95% CI: 0.770,0.923) and 1.829% lower fasting blood glucose levels (95% CI: -2.335%,-1.320%) than those who lived closer to the blue space. Our findings suggest that residential green space was beneficially associated with T2DM and fasting blood glucose levels. However, further research is needed to explore more comprehensively the relationship between residential blue space and public health.

The impact of aircraft noise on vascular and cardiac function in relation to noise event number: a randomized trial

Aims

Nighttime aircraft noise exposure has been associated with increased risk of hypertension and myocardial infarction, mechanistically linked to sleep disturbance, stress, and endothelial dysfunction. It is unclear, whether the most widely used metric to determine noise exposure, equivalent continuous sound level (L_eq), is an adequate indicator of the cardiovascular impact induced by different noise patterns.

Methods and results

In a randomized crossover study, we exposed 70 individuals with established cardiovascular disease or increased cardiovascular risk to two aircraft noise scenarios and one control scenario. Polygraphic recordings, echocardiography, and flow-mediated dilation (FMD) were determined for three study nights. The noise patterns consisted of 60 (Noise60) and 120 (Noise120) noise events, respectively, but with comparable L_eq, corresponding to a mean value of 45 dB. Mean value of noise during control nights was 37 dB. During the control night, FMD was 10.02 ± 3.75%, compared to 7.27 ± 3.21% for Noise60 nights and 7.21 ± 3.58% for Noise120 nights (P < 0.001). Sleep quality was impaired after noise exposure in both noise scenario nights (P < 0.001). Serial echocardiographic assessment demonstrated an increase in the E/E′ ratio, a measure of diastolic function, within the three exposure nights, with a ratio of 6.83 ± 2.26 for the control night, 7.21 ± 2.33 for Noise60 and 7.83 ± 3.07 for Noise120 (P = 0.043).

Conclusions

Nighttime exposure to aircraft noise with similar L_eq, but different number of noise events, results in a comparable worsening of vascular function. Adverse effects of nighttime aircraft noise exposure on cardiac function (diastolic dysfunction) seemed stronger the higher number of noise events.

Research: Replacing Overhead Paging with Smartphones to Reduce Hospital Noise

Hospital noise is associated with adverse effects on patients and staff. Communication through overhead paging is a major contributor to hospital noise. Replacing overhead paging with smartphones through a clinical mobility platform has the potential to reduce transitory noises in the hospital setting, though this result has not been described. The current study evaluated the impact of replacing overhead paging with a smartphone-based clinical mobility platform on transitory noise levels in a labor and delivery unit. Transitory noises were defined as sound levels greater than 10 dB above baseline, as recorded by a sound level meter. Prior to smartphone implementation, 77% of all sound levels at or above 60 dB were generated by overhead paging. Overhead pages occurred at an average rate of 3.17 per hour. Following smartphone implementation, overhead pages were eliminated and transitory noises decreased by two-thirds (P < 0.001). The highest recorded sound level decreased from 76.54 to 57.34 dB following implementation. The percent of sounds that exceeded the thresholds recommended by the Environmental Protection Agency and International Noise Council decreased from 31.2% to 0.2% following implementation (P < 0.001). Replacement of overhead paging with a clinical mobility platform that utilized smartphones was associated with a significant reduction in transitory noise. Clinical mobility implementation, as part of a noise reduction strategy, may be effective in other inpatient settings.

The Association between Noise Exposure and Metabolic Syndrome: A Longitudinal Cohort Study in Taiwan

Metabolic syndrome is becoming more common worldwide. Studies suggest environmental pollution, including traffic noise, might be linked with metabolic syndrome. This study sought to evaluate how noise exposure is linked to the development of metabolic syndrome and its components in Taiwan. Using data from a cohort of 42,509 participants and Cox proportional hazards regression models, the effects of noise exposure on metabolic syndrome and its components were quantified. After adjustment for covariates (age, gender, body mass index, and physical activity), the hazard ratio for metabolic syndrome was 1.13 (95% CI: 1.04–1.22) for medium noise exposure and 1.24 (95% CI: 1.13–1.36) for high noise exposure. Noise exposure was also positively associated with all of metabolic syndrome’s components. This finding suggests noise exposure might contribute to metabolic syndrome and its components. Policies aiming to reduce noise pollution might reduce the risks of metabolic syndrome and its components.

Transportation noise impairs cardiovascular function without altering sleep: The importance of autonomic arousals

AIMS

Chronic exposure to nocturnal transportation noise has been linked to cardiovascular disorders with sleep impairment as the main mediator. Here we examined whether nocturnal transportation noise affects the main stress pathways, and whether it relates to changes in the macro and micro structure of sleep.

METHODS AND RESULTS

Twenty-six young healthy participants (12 women, 24.6 ± 0.7 years, mean ± SE) spent five consecutive 24-h days and one last morning in the laboratory. The first (baseline) and last (recovery) nights comprised a quiet ambient scenario. In-between, four different noise scenarios (low/medium/high intermittent road or rail scenarios with an identical equivalent continuous sound level of 45 dB) were randomly presented during the 8-h nights. Participants felt more annoyed from the transportation noise scenarios compared to the quiet ambient scenario played back during the baseline and recovery nights (F_5,117 = 10.2, p < 0.001). Nocturnal transportation noise did not significantly impact polysomnographically assessed sleep macrostructure, blood pressure, nocturnal catecholamine levels and morning cytokine levels. Evening cortisol levels increased after sleeping with highly intermittent road noise compared to baseline (p = 0.002, noise effect: F_4,83 = 4.0, p = 0.005), a result related to increased cumulative duration of autonomic arousals during the noise nights (F_5,106 = 3.4, p < 0.001; correlation: r_pearson = 0.64, p = 0.006).

CONCLUSION

Under controlled laboratory conditions, highly intermittent nocturnal road noise exposure at 45 dB increased the cumulative duration of autonomic arousals during sleep and next-day evening cortisol levels. Our results indicate that, without impairing sleep macrostructure, nocturnal transportation noise of 45 dB is a physiological stressor that affects the hypothalamic-pituitary-adrenal axis during the following day in healthy young good sleepers.

Adverse Cardiovascular Effects of Traffic Noise with a Focus on Nighttime Noise and the New WHO Noise Guidelines

Exposure to traffic noise is associated with stress and sleep disturbances. The World Health Organization (WHO) recently concluded that road traffic noise increases the risk for ischemic heart disease and potentially other cardiometabolic diseases, including stroke, obesity, and diabetes. The WHO report focused on whole-day noise exposure, but new epidemiological and translational field noise studies indicate that nighttime noise, in particular,is an important risk factor for cardiovascular disease (CVD) through increased levels of stress hormones and vascular oxidative stress, leading to endothelial dysfunction and subsequent development of various CVDs. Novel experimental studies found noise to be associated with oxidative stress-induced vascular and brain damage, mediated by activation of the NADPH oxidase, uncoupling of endothelial and neuronal nitric oxide synthase, and vascular/brain infiltration with inflammatory cells. Noise-induced pathophysiology was more pronounced in response to nighttime as compared with daytime noise. This review focuses on the consequences of nighttime noise.

Exposure to traffic noise and gestational weight gain and postpartum weight retention: a cohort study

OBJECTIVES

Transportation noise has been associated with markers of obesity. We aimed to investigate whether road traffic and railway noise were associated with weight gain during and after pregnancy.

METHODS

Among the women participating in the Danish National Birth Cohort, 74 065 reported on weight before and during the pregnancy (gestational week 30) and 52 661 reported on weight before and 18 months after pregnancy. Residential address history from conception to 18 months after pregnancy was obtained in national registers, and road traffic and railway noise were modelled for all addresses. Associations between noise and gestational weight gain (GWG) and postpartum weight retention (PPWR) were analysed using the linear and log-binomial regression.

RESULTS

A 10 dB(A) higher road traffic noise was associated with an increase in GWG of 3.8 g/week (95% CI 2.3 to 5.3) and PPWR of 0.09 kg (95% CI 0.02 to 0.16). For PPWR, this association seemed confined to women who were overweight (0.17 kg, 95% CI 0.02 to 0.32) or obese (0.49 kg, 95% CI 0.26 to 0.73) before pregnancy. Further adjustment by nitrogen dioxide reduced GWG risk estimates and slightly increased PPWR risk estimates. Railway noise ≥65 dB(A) was associated with an increase in GWG of 4.5 g/week (95% CI -2.7 to 11.6) and PPWR of 0.26 kg (95% CI -0.09 to 0.60) compared with levels <55 dB(A).

CONCLUSIONS

Our findings suggest that road traffic noise is associated with weight gain during and after the pregnancy, which adds to the literature linking transportation noise to adiposity.

Silicon dioxide nanoparticles induce insulin resistance through endoplasmic reticulum stress and generation of reactive oxygen species

Background

Silicon dioxide nanoparticles (SiO₂ NPs) are one of the most widely utilized NPs in various food sectors. However, the potential endocrine toxicity of SiO₂ NPs has not been characterized.

Results

In the present study, mice were orally administered a series of doses of SiO₂ NPs. All doses of SiO₂ NPs were absorbed into the blood, liver, and pancreas of the mice. Administration of 100 mg/kg bw (body weight) of SiO₂ NPs significantly increased blood glucose levels in mice. However, the same dose of SiO₂ fine-particles (FPs) did not result in altered blood glucose. Whole-genome analysis showed that SiO₂ NPs affected the expression of genes associated with reactive oxygen species (ROS) production and endoplasmic reticulum (ER) stress. In addition, we showed that SiO₂ NPs activated xenobiotic metabolism, resulting in ER stress. Endoplasmic reticulum stress resulted in increased ROS production, which activated the NF-κB pathway leading to expression of inflammatory cytokines. Increased inflammatory cytokine expression resulted in serine phosphorylation of IRS1, which induced insulin resistance (IR). Furthermore these inflammatory cytokines activated the MAPK pathway, which further promoted the serine phosphorylation of IRS1. Insulin resistance resulted in elevated blood glucose. The ER stress inhibitor 4-phenylbutyric acid (4-PBA) inhibited SiO₂ NP-induced ROS production. The ROS scavenger N-acetylcysteine (NAC) did not affect SiO₂ NP-induced ER stress, but inhibited SiO₂ NP-induced activation of the NF-κB and MAPK pathways, expression of inflammatory cytokines, SiO₂ NP-induced serine phosphorylation of IRS1, and SiO2 NP-induced elevations of blood glucose.

Conclusion

Silicon dioxide NPs induced IR through ER stress and generation of ROS, but SiO₂ FPs did not. Therefore, lifelong exposure of humans to SiO₂ NPs may result in detrimental effects on blood glucose. The results of this study strongly suggested that non-nanoformed SiO₂ should be used as food additives.

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.

A Study of Noise Pollution Measurements and Possible Effects on Public Health in Ota Metropolis, Nigeria

BACKGROUND:

Noise pollution has become a major environmental problem leading to nuisances and health issues.

AIM:

This paper aims to study and analyse the noise pollution levels in major areas in Ota metropolis. A probability model which is capable of predicting the noise pollution level is also determined.

METHODS:

Datasets on the noise pollution level in 41 locations across Ota metropolis were used in this research. The datasets were collected thrice per day; morning, afternoon and evening. Descriptive statistics were performed, and analysis of variance was also conducted using Minitab version 17.0 software. Easy fit software was however used to select the appropriate probability model that would best describe the dataset.

RESULTS:

The noise levels are way far from the WHO recommendations. Also, there is no significant difference in the effects of the noise pollution level for all the times of the day considered. The log-logistic distribution provides the best fit to the dataset based on the Kolmogorov Smirnov goodness of fit test.

CONCLUSION:

The fitted probability model can help in the prediction of noise pollution and act as a yardstick in the reduction of noise pollution, thereby improving the public health of the populace.

A survey on exposure-response relationships for road, rail, and aircraft noise annoyance: Differences between continuous and intermittent noise

The aim of the present study is to establish exposure-response relationships reflecting the percentage highly annoyed (%HA) as functions of road traffic, railway, and aircraft noise exposure, measured as day-evening-night level (Lden), as well as to elucidate the degree to which the acoustic indicator Intermittency Ratio (IR), which reflects the "eventfulness" of a noise situation, predicts noise annoyance. We conducted a mixed-mode representative population survey in a stratified random sample of 5592 residents exposed to transportation noise all over Switzerland. Source-specific noise exposure was calculated for each floor and each façade based on comprehensive traffic data. Noise annoyance was measured using the ICBEN 11-point scale. The survey was carried out in 4 waves at different times of the year. We hypothesized that in addition to Lden, the effects of noise on annoyance can be better explained when also considering the intensity of short-term variations of noise level over time. We therefore incorporated the acoustic indicator IR in the statistical models. For all noise sources, results revealed significant associations between Lden and %HA after controlling for confounders and independent predictors such as IR (measured over 24 h), exposure to other transportation noise sources, sex and age, language, home ownership, education level, living duration, temperature, and access to a quiet side of the dwelling. Aircraft noise annoyance scored markedly higher than annoyance to railway and road traffic noise at the same Lden level. Railway noise elicited higher percentages of highly annoyed persons than road traffic noise. Results furthermore suggest that for road traffic noise, IR has an additional effect on %HA and can explain shifts of the exposure-response curve of up to about 6 dB between low IR and high IR exposure situations, possibly due to the effect of different durations of noise-free intervals between events. For railway and aircraft noise annoyance, the predictive value of IR was limited.

Comparing the Effects of Road, Railway, and Aircraft Noise on Sleep: Exposure⁻Response Relationships from Pooled Data of Three Laboratory Studies

Objectives: Air, road, and railway traffic, the three major sources of traffic noise, have been reported to differently impact on annoyance. However, these findings may not be transferable to physiological reactions during sleep which are considered to decrease nighttime recovery and might mediate long-term negative health effects. Studies on awakenings from sleep indicate that railway noise, while having the least impact on annoyance, may have the most disturbing properties on sleep compared to aircraft noise. This study presents a comparison between the three major traffic modes and their probability to cause awakenings. In combining acoustical and polysomnographical data from three laboratory studies sample size and generalizability of the findings were increased. Methods: Data from three laboratory studies were pooled, conducted at two sites in Germany (German Aerospace Center, Cologne, and Leibniz Research Centre for Working Environment and Human Factors, Dortmund). In total, the impact of 109,836 noise events on polysomnographically assessed awakenings was analyzed in 237 subjects using a random intercept logistic regression model. Results: The best model fit according to the Akaike Information Criterion (AIC) included different acoustical and sleep parameters. After adjusting for these moderators results showed that the probability to wake up from equal maximum A-weighted sound pressure levels (SPL) increased in the order aircraft < road < railway noise, the awakening probability from road and railway noise being not significantly different (p = 0.988). At 70 dB SPL, it was more than 7% less probable to wake up due to aircraft noise than due to railway noise. Conclusions: The three major traffic noise sources differ in their impact on sleep. The order with which their impact increased was inversed compared to the order that was found in annoyance surveys. It is thus important to choose the correct concept for noise legislation, i.e., physiological sleep metrics in addition to noise annoyance for nighttime noise protection.