Long-term exposure to road traffic noise and incident diabetes: a cohort study

Race, historical redlining, and contemporary transportation noise disparities in the United States

BACKGROUND

Legacies of discriminatory federal housing practices-e.g., racialized property appraisal by the Home Owners' Loan Corporation (HOLC) and institutionalized redlining by the Federal Housing Administration-include disparate present-day environmental health outcomes. Noise pollution is health-harming, but just one study has associated contemporary noise with redlining in some HOLC-mapped United States (US) cities, while two national studies found associations between greater neighborhood-level people of color composition and increased noise. No studies have examined noise pollution exposure disparities across all HOLC-mapped cities or based on the intersection of race/ethnicity and redlining.

OBJECTIVE

We address three objectives: (1) Assess disparities in fine-scale, per person transportation noise exposures by historical redlining status across all HOLC-mapped cities. (2) Quantify disparities in noise exposures by race/ethnicity nationwide. (3) Explore interactions between redlining status and race/ethnicity in noise exposures.

METHODS

We analyzed three data sources: (1) complete digital HOLC maps of ordered investment risk grades (A-D), (2) fine-scale (30 m) estimates of transportation noise levels (year-2020), and (3) sociodemographic characteristics of individuals in year-2020 census blocks.

RESULTS

We find an approximately monotonic association for excess transportation noise with HOLC grade, marked by a pronounced exposure increase (17.4 dBA or 3× loudness) between contemporary residents of grade A (highest-graded) and D (lowest-graded) neighborhoods, a pattern consistent across HOLC-mapped cities. People of color experience ~7 dBA greater (2× louder) excess transportation noise exposures than White people nationwide, a pattern consistent across US counties. Noise exposure disparities are larger by HOLC grade than by race/ethnicity. However, contemporary racial/ethnic noise exposure disparities persist within each HOLC grade at levels approximating those disparities existing in ungraded areas, indicating that historical redlining is one of multiple discriminatory practices shaping contemporary national soundscape injustices.

SIGNIFICANCE

Findings illustrate how historical redlining and broader racialized inequalities in US society have shaped environmental injustices nationwide.

IMPACT STATEMENT

Excessive noise exposures harm human health. Communities of color in the United States experience disparate noise exposures, although previous studies are limited by reliance upon aggregated data. They are also disproportionately concentrated in historically redlined areas. Legacies of redlining include persistent racial and economic inequalities and environmental health disparities. Here, we conduct the first complete national examination of contemporary noise pollution disparities with respect to historical redlining and race/ethnicity. Findings advance understanding of the historical roots and enduring salience of race-based disparities in noise pollution exposures and can inform efforts to address these disparities through noise pollution policy-making.

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 noise exposure and body mass index among female participants in two Nurses' Health Study prospective cohorts living around 90 airports in the United States

OBJECTIVE

Aircraft noise exposure is linked to cardiovascular disease risk. One understudied candidate pathway is obesity. This study investigates the association between aircraft noise and obesity among female participants in two prospective Nurses' Health Study (NHS and NHSII) cohorts.

METHODS

Aircraft day-night average sound levels (DNL) were estimated at participant residential addresses from modeled 1 dB (dB) noise contours above 44 dB for 90 United States (U.S.) airports in 5-year intervals 1995-2010. Biennial surveys (1994-2017) provided information on body mass index (BMI; dichotomized, categorical) and other individual characteristics. Change in BMI from age 18 (BMI18; tertiles) was also calculated. Aircraft noise exposures were dichotomized (45, 55 dB), categorized (<45, 45-54, ≥55 dB) or continuous for exposure ≥45 dB. Multivariable multinomial logistic regression using generalized estimating equations were adjusted for individual characteristics and neighborhood socioeconomic status, greenness, population density, and environmental noise. Effect modification was assessed by U.S. Census region, climate boundary, airline hub type, hearing loss, and smoking status.

RESULTS

At baseline, the 74,848 female participants averaged 50.1 years old, with 83.0%, 14.8%, and 2.2% exposed to <45, 45-54, and ≥55 dB of aircraft noise, respectively. In fully adjusted models, exposure ≥55 dB was associated with 11% higher odds (95% confidence interval [95%CI]: -1%, 24%) of BMIs ≥30.0, and 15% higher odds (95%CI: 3%, 29%) of membership in the highest tertile of BMI18 (ΔBMI 6.7 to 71.6). Less-pronounced associations were observed for the 2nd tertile of BMI18 (ΔBMI 2.9 to 6.6) and BMI 25.0-29.9 as well as exposures ≥45 versus <45 dB. There was evidence of DNL-BMI trends (ptrends ≤ 0.02). Stronger associations were observed among participants living in the West, arid climate areas, and among former smokers.

DISCUSSION

In two nationwide cohorts of female nurses, higher aircraft noise exposure was associated with higher BMI, adding evidence to an aircraft noise-obesity-disease pathway.

Pathogenesis of PM2.5-Related Disorders in Different Age Groups: Children, Adults, and the Elderly

The effects of PM2.5 on human health fluctuate greatly among various age groups, influenced by a range of physiological and immunological reactions. This paper compares the pathogenesis of the disease caused by PM2.5 in people of different ages, focusing on how children, adults, and the elderly are each susceptible to it because of differences in their bodies. Regarding children, exposure to PM2.5 is linked to many negative consequences. These factors consist of inflammation, oxidative stress, and respiratory problems, which might worsen pre-existing conditions and potentially cause neurotoxicity and developmental issues. Epigenetic changes can affect the immune system and make people more likely to get respiratory diseases. On the other hand, exposures during pregnancy can change how the cardiovascular and central nervous systems develop. In adults, the inhalation of PM2.5 is associated with a wide range of health problems. These include respiratory difficulties, reduced pulmonary function, and an increased susceptibility to illnesses such as asthma, chronic obstructive pulmonary disease (COPD), and lung cancer. In addition, exposure to PM2.5 induces systemic inflammation, cardiovascular diseases, insulin resistance, and neurotoxic consequences. Evident disturbances in the immune system and cognitive function demonstrate the broad impact of PM2.5. The elderly population is prone to developing respiratory and cardiovascular difficulties, which worsen their pre-existing health issues and raise the risk of cognitive decline and neurological illnesses. Having additional medical conditions, such as peptic ulcer disease, significantly increases the likelihood of being admitted to hospital.

Association of greenspaces exposure with cardiometabolic risk factors: a systematic review and meta-analysis

BACKGROUND

Cardiometabolic conditions are major contributors to the global burden of disease. An emerging body of evidence has associated access to and surrounding public open spaces (POS) and greenspace with cardiometabolic risk factors, including obesity, body mass index (BMI), hypertension (HTN), blood glucose (BG), and lipid profiles. This systematic review aimed to synthesize this evidence.

METHODS

This systematic review was conducted based on the PRISMA guidelines. Four electronic databases including Web of Science, PubMed, Scopus, and Google Scholar were searched for eligible articles published until July 2023. All observational studies which assessed the association of greenspace and POS with cardiometabolic risk factors including obesity, BMI, HTN, BG, and lipid profiles were included and reviewed by two authors independently. Heterogeneity between studies was assessed using the I2 index and Cochrane's Q test. Random/fixed effect meta-analyses were used to combine the association between greenspace exposure with cardiometabolic risk factors.

RESULTS

Overall, 118 relevant articles were included in our review. The majority of the articles were conducted in North America or Europe. In qualitative synthesis, access or proximity to greenspaces or POS impacts BMI and blood pressure or HTN, BG, and lipid profiles via various mechanisms. According to the random effect meta-analysis, more access to greenspace was significantly associated with lower odds of HTN (odds ratio (OR): 0.81, 95% confidence intervals (CIs): 0.61-0.99), obesity (OR: 0.83, 95% CIs: 0.77-0.90), and diabetes (OR:0.79, 95% CI: 0.67,0.90).

CONCLUSIONS

Findings of this systematic review and meta-analysis suggested that greenspace accessibility is associated with some cardiometabolic risk factors. Improving greenspace accessibility could be considered as one of the main strategies to reduce cardiometabolic risk factors at population level.

Health position paper and redox perspectives - Disease burden by transportation noise

Transportation noise is a ubiquitous urban exposure. In 2018, the World Health Organization concluded that chronic exposure to road traffic noise is a risk factor for ischemic heart disease. In contrast, they concluded that the quality of evidence for a link to other diseases was very low to moderate. Since then, several studies on the impact of noise on various diseases have been published. Also, studies investigating the mechanistic pathways underlying noise-induced health effects are emerging. We review the current evidence regarding effects of noise on health and the related disease-mechanisms. Several high-quality cohort studies consistently found road traffic noise to be associated with a higher risk of ischemic heart disease, heart failure, diabetes, and all-cause mortality. Furthermore, recent studies have indicated that road traffic and railway noise may increase the risk of diseases not commonly investigated in an environmental noise context, including breast cancer, dementia, and tinnitus. The harmful effects of noise are related to activation of a physiological stress response and nighttime sleep disturbance. Oxidative stress and inflammation downstream of stress hormone signaling and dysregulated circadian rhythms are identified as major disease-relevant pathomechanistic drivers. We discuss the role of reactive oxygen species and present results from antioxidant interventions. Lastly, we provide an overview of oxidative stress markers and adverse redox processes reported for noise-exposed animals and humans. This position paper summarizes all available epidemiological, clinical, and preclinical evidence of transportation noise as an important environmental risk factor for public health and discusses its implications on the population level.

Association between residential proximity to major roadways and chronic multimorbidity among Chinese older adults: a nationwide cross-sectional study

BACKGROUND

Multiple negative health outcomes were linked to residential proximity to major roadways. Nevertheless, there is limited knowledge regarding the association between residential proximity to major roadways and chronic multimorbidity.

METHODS

We used data from the 2018 wave of the Chinese Longitudinal Healthy Longevity Survey, which included 12,214 individuals aged ≥ 60. We derived the residential proximity to major roadways from self-reported data, defining chronic multimorbidity as the presence of two or more concurrent chronic diseases. A binary logistic regression model was utilized to investigate the association between residential proximity to major roadways and chronic multimorbidity. The model accounted for some demographic features, socioeconomic conditions, social participation, and health conditions. Subsequently, we conducted subgroup analyses to examine potential interaction effects.

RESULTS

Residential proximity to major roadways was associated with chronic multimorbidity, even after adjusting for confounding factors. Compared with those living > 300 m from major roadways, the OR for those living 201-300 m, 101-200 m, 50-100 m, and < 50 m were increased. When subgroup analyses were conducted using a cutoff point of 200 m, the risk of chronic multimorbidity associated with residential proximity to major roadways was stronger in participants with education levels > 6 years (P = 0.017).

CONCLUSION

Our findings provide important implications for improving residential area siting, transportation policies, and environmental regulations to reduce the risk of chronic multimorbidity caused by traffic-related exposure.

Effects of aircraft noise cessation on blood pressure, cardio- and cerebrovascular endothelial function, oxidative stress, and inflammation in an experimental animal model

Large epidemiological studies have shown that traffic noise promotes the development of cardiometabolic diseases. It remains to be established how long these adverse effects of noise may persist in response to a noise-off period. We investigated the effects of acute aircraft noise exposure (mean sound level of 72 dB(A) applied for 4d) on oxidative stress and inflammation mediating vascular dysfunction and increased blood pressure in male C57BL/6 J mice. 1, 2 or 4d of noise cessation after a 4d continuous noise exposure period completely normalized noise-induced endothelial dysfunction of the aorta (measured by acetylcholine-dependent relaxation) already after a 1d noise pause. Vascular oxidative stress and the increased blood pressure were partially corrected, while markers of inflammation (VCAM-1, IL-6 and leukocyte oxidative burst) showed a normalization within 4d of noise cessation. In contrast, endothelial dysfunction, oxidative stress, and inflammation of the cerebral microvessels of noise-exposed mice did not improve at all. These data demonstrate that the recovery from noise-induced damage is more complex than expected demonstrating a complete restoration of large conductance vessel function but persistent endothelial dysfunction of the microcirculation. These findings also imply that longer noise pauses are required to completely reverse noise-induced vascular dysfunction including the resistance vessels.

The Impact of Neighborhoods on Diabetes Risk and Outcomes: Centering Health Equity

Neighborhood environments significantly influence the development of diabetes risk factors, morbidity, and mortality throughout an individual's life. The social, economic, and physical environments of a neighborhood all affect the health risks of individuals and communities and also affect population health inequities. Factors such as access to healthy food, green spaces, safe housing, and transportation options can impact the health outcomes of residents. Social factors, including social cohesion and neighborhood safety, also play an important role in shaping neighborhood environments and can influence the development of diabetes. Therefore, understanding the complex relationships between neighborhood environments and diabetes is crucial for developing effective strategies to address health disparities and promote health equity. This review presents landmark findings from studies that examined associations between neighborhood socioeconomic, built and physical, and social environmental factors and diabetes-related risk and outcomes. Our framework emphasizes the historical context and structural and institutional racism as the key drivers of neighborhood environments that ultimately shape diabetes risk and outcomes. To address health inequities in diabetes, we propose future research areas that incorporate health equity principles and place-based interventions.

Spatial assessment of the attributable burden of disease due to transportation noise in England

BACKGROUND

Noise pollution from transportation is one of the leading contributors to the environmental disease burden in Europe. We provide a novel assessment of spatial variations of these health impacts within a country, using England as an example.

METHODS

We estimated the burden of annoyance (highly annoyed), sleep disturbance (highly sleep disturbed), ischemic heart disease (IHD), stroke, and diabetes attributable to long-term transportation noise exposures in England for the adult population in 2018 down to local authority level (average adult population: 136,000). To derive estimates, we combined literature-informed exposure-response relationships, with population data on noise exposures, disease, and mortalities. Long-term average noise exposures from road, rail and aircraft were sourced from strategic noise mapping, with a lower exposure threshold of 50 dB (decibels) Lden and Lnight.

RESULTS

40 %, 4.5 % and 4.8 % of adults in England were exposed to road, rail, and aircraft noise exceeding 50 dB Lden. We estimated close to a hundred thousand (∼97,000) disability adjusted life years (DALY) lost due to road-traffic, ∼13,000 from railway, and ∼ 17,000 from aircraft noise. This excludes some noise-outcome pairs as there were too few studies available to provide robust exposure-response estimates. Annoyance and sleep disturbance accounted for the majority of the DALYs, followed by strokes, IHD, and diabetes. London, the South East, and North West regions had the greatest number of road-traffic DALYs lost, while 63 % of all aircraft noise DALYs were found in London. The strategic noise mapping did not include all roads, which may still have significant traffic flows. In sensitivity analyses using modelled noise from all roads in London, the DALYs were 1.1x to 2.2x higher.

CONCLUSION

Transportation noise exposures contribute to a significant and unequal environmental disease burden in England. Omitting minor roads from the noise exposure modelling leads to underestimation of the disease burden.

The co-benefits of electric mobility in reducing traffic noise and chemical air pollution: Insights from a transit-oriented city

Traffic noise is a growing threat to the urban population. Prolonged exposure to traffic noise has been linked to negative health consequences such as annoyance, sleep disturbances and cardiovascular diseases. While electric vehicles are known to have lower noise profiles, the impacts of electric mobility on traffic noise, especially for electrified heavy-duty vehicles, have not been thoroughly examined. This study aims to examine the impacts of both electric light-duty vehicles and electric buses on traffic noise levels in a highly urbanized city. Traffic noise along the source line and pedestrian network was first estimated and mapped to illustrate its spatiotemporal variations. Then, scenario analysis was used to compare the impacts. Population potentially benefiting from reduced traffic noise in the neighbourhoods and the associated health impacts were also estimated. Results indicate that electric buses have a greater potential to reduce traffic noise, with a maximum reduction of 4.4 dBA during daytime in the urban cores. With all bus fleet electrified, around 60% of the population can benefit from a reduction of 1 dBA at the street environment, 15.3% for 1-2 dBA, and 4.3% for more than 2 dBA. The estimated reduction of preventable deaths and preventable cases of diseases per 100,000 population are 4.15 and 112.99 respectively. The findings shed important insights into prioritizing bus routes to be electrified in urban areas for maximizing health co-benefits.

Assessing the impact of aircraft arrival on ambient ultrafine particle number concentrations in near-airport communities in Boston, Massachusetts

Aircraft emissions contribute to overall ambient air pollution, including ultrafine particle (UFP) concentrations. However, accurately ascertaining aviation contributions to UFP is challenging due to high spatiotemporal variability along with intermittent aviation emissions. The objective of this study was to evaluate the impact of arrival aircraft on particle number concentration (PNC), a proxy for UFP, across six study sites 3-17 km from a major arrival aircraft flight path into Boston Logan International Airport by utilizing real-time aircraft activity and meteorological data. Ambient PNC at all monitoring sites was similar at the median but had greater variation at the 95th and 99th percentiles with more than two-fold increases in PNC observed at sites closer to the airport. PNC was elevated during the hours with high aircraft activity with sites closest to the airport exhibiting stronger signals when downwind from the airport. Regression models indicated that the number of arrival aircraft per hour was associated with measured PNC at all six sites, with a maximum contribution of 50% of total PNC at a monitor 3 km from the airport during hours with arrival activity on the flight path of interest (26% across all hours). Our findings suggest strong but intermittent contributions from arrival aircraft to ambient PNC in communities near airports.

Mediation of metabolic syndrome in the association between long-term co-exposure to road traffic noise, air pollution and incident type 2 diabetes

OBJECTIVES

Recent studies have linked exposure to road traffic noise or air pollution with incident type 2 diabetes (T2D), but investigation on their co-exposure was limited and underlying mechanisms remain unclear. We hypothesized that long-term co-exposure to road traffic noise and air pollution increases the risk of incident T2D via the development of metabolic syndrome (MetS).

METHODS

This prospective study included 390,834 participants in UK Biobank. Cumulative risk index (CRI), the health-based weighted levels of multiple exposures, was applied to characterize the co-exposure to 24-hour road traffic noise (L_den), particulate matter with aerodynamic diameter ≤ 2.5 µm (PM_2.5), and nitrogen dioxide (NO₂). L_den was modeled by the Common Noise Assessment Methods in Europe and air pollutant levels were measured by the Land Use Regression model at participants' residential addresses. Incident T2D was ascertained through linkages to inpatient hospital records. MetS was defined by five (central obesity, triglycerides, HDL cholesterol, glucose, and blood pressure) or six factors (C-reactive protein additionally). Cox proportional hazard models were used to assess the association between environmental exposures and incident T2D, and mediation analyses were applied to investigate the role of MetS.

RESULTS

After a median of 10.9 years of follow-up, 13,214 (3.4%) incident T2D cases were ascertained. The exposure to L_den, PM_2.5, and NO₂, as well as their co-exposure, were significantly associated with an elevated risk of incident T2D, with HRs of 1.03 (95%CI: 1.00, 1.05) per 3.5 dB(A) increase in L_den, 1.05 (95%CI: 1.01, 1.10) per 1.3 μg/m³ increase in PM_2.5, 1.07 (95%CI: 1.02, 1.11) per 9.8 μg/m³ increase in NO₂, and 1.06 (95%CI: 1.02, 1.09) per interquartile range increase in CRI. MetS significantly mediated 43.5%- 54.7% of the CRI-T2D relationship.

CONCLUSIONS

Long-term co-exposure to road traffic noise and air pollution is associated with an elevated risk of incident T2D, which may partly be mediated by MetS.

Health impact assessment of road traffic noise exposure based on different densification scenarios in Malmö, Sweden

While urbanization provides many opportunities to those arriving in thriving urban areas, a greater number of residents necessitates the expansion of housing and infrastructure. This is often achieved through densification, which can lead to increased noise, particularly through increased road traffic. A key challenge of promoting healthy urban planning is to understand potential health effects, especially on the local level. The aim of the present study is, therefore, to estimate and compare the health impacts of road traffic noise exposure for various urban densification scenarios within a neighborhood (Lorensborg) in Malmö, Sweden. The three scenarios include 1) Present-day, representing the study area as it is presently organized; 2) Planned municipal strategy (the city of Malmö's own densification plans) and 3) Health-centred, which involves major structural alterations and reflects an effort prioritize a health-centred approach. Noise was modelled using the Nordic prediction method for road traffic. Health outcomes included noise annoyance, adverse sleep disturbance, ischemic heart disease (IHD) incidence and mortality. Within all scenarios, a large proportion of the study population was exposed above the WHO's health-based guideline value (L_den 53 dB): >80% for Present-day and Planned municipal strategy scenarios, and almost 50% in the Health-centred scenario. Still, densifying Lorensborg (population ≈9,600) according to the Health-centred scenario could prevent 549 cases of highly annoyed, 193 cases of adverse sleep disturbance, 4.7 new cases of IHD (8.9% of total cases), and 1.5 deaths due to IHD (17.8% of IHD mortality) annually. The results demonstrated that it is possible to considerably lower the health impact with a more health-centred densification strategy. Important co-benefits for public and environmental health include air pollution reduction and green space creation, although their health effects were not quantified in the present study. Urban planning initiatives must be more ambitious in order to create healthy, sustainable cities.

Changes in the Global Epidemiology of Type 1 Diabetes in an Evolving Landscape of Environmental Factors: Causes, Challenges, and Opportunities

The worldwide incidence of type 1 diabetes mellitus (T1DM) has increased in recent decades. The reasons behind this phenomenon are not yet fully understood. Early life infections, prenatal and perinatal factors, and diet composition have been associated with the triggering of autoimmunity and the risk of presentation of T1DM. However, the rapid increase in new cases of the disease raises the hypothesis that lifestyle factors, which have traditionally been associated with type 2 diabetes, such as obesity and unhealthy eating patterns could also play a role in the genesis of autoimmune diabetes. This article aims to highlight the changing epidemiology of T1DM and the importance of properly recognizing the environmental factors behind it, as well as the connections with the pathogenesis of the disorder and the need to prevent or delay T1DM and its long-term complications.

The association between road traffic noise and type 2 diabetes: a systematic review and meta-analysis of cohort studies

The association between road traffic noise and type 2 diabetes (T2DM) was inconsistent. To address this, we have synthesized available cohort studies about their association by meta-analysis. PubMed, Web of Science, EBSCO, Cochrane Library, EMBASE, and Scopus databases were searched up to July 2022. The Quality-effect model (QE) was used to incorporate the results of included studies. The possibility of publication bias was assessed by the Doi plots and Luis Furuya-Kanamori index. Sensitivity analyses included leave-one-out meta-analysis, subgroup meta-analysis, and meta-regressions. The Recommendations for Assessment, Development, and Evaluation (GRADE) guidelines were conducted to evaluate the overall quality of evidence. Eight cohort studies with 4,989,846 participants and 416,799 diabetes cases were included. Based on the fully adjusted models from 8 cohort studies (10 estimates; Lden range ≈ 15-98.5 dB(A)), we found "high" evidence of RR per 10 dB(A) = 1.07 (1.05, 1.10), high heterogeneity (I2 = 0.91%, p < 0.001), and high publication bias (LKF index = 4.55). Sensitivity analyses showed stable model results, and the GRADE assessment suggested the current overall quality of evidence is high. Comprehensive evidence from cohort studies supports that increasing exposure to road traffic noise may be associated with higher risk of T2DM.

Dose-response association between transportation noise exposure and type 2 diabetes: A systematic review and meta-analysis of prospective cohort studies

AIMS

To examine the longitudinal association between transportation noise exposure (road traffic, aircraft, and railway noise) and T2D in a meta-analysis.

MATERIALS AND METHODS

We systematically searched PubMed, Embase, Scopus, Cochrane, and Web of Science published up to February 2022. The GRADE approach was used to evaluate the study quality, and the pooled effect estimate was calculated by the fixed-effects model or the random-effects model.

RESULTS

We included 10 prospective studies with a total of 4,994,171 participants and 417,332 T2D cases in the meta-analysis. According to the Navigation guide, 8 studies out of 10 were rated as having a probably high or high risk of bias. For road noise, the pooled relative risk (RR) per 10 dB higher L_den for developing T2D was 1.06 (95% CI:1.03, 1.09) with high heterogeneity (I²  = 90.1%, p < 0.001). Similar associations were also observed in aircraft and railway noise: the pooled RR were separately were: 1.01 (1.00, 1.01) and 1.02 (1.01, 1.03) separately. A 'dose-response' analysis found a similar linear association between road noise exposure and the risk of T2D.

CONCLUSIONS

An overall 6% increase in the risk of T2D per 10 dB increase in road exposure was observed. Further studies are needed to confirm our findings, especially for aircraft and railway noise, and to identify the mechanisms involved.

Long-term exposure to transportation noise and risk of type 2 diabetes: A cohort study

BACKGROUND

Some studies have found transportation noise to be associated with higher diabetes risk. This includes studies based on millions of participants, relying entirely on register-based confounder adjustment, which raises concern about residual lifestyle confounding. We aimed to investigate associations between noise and type 2 diabetes (T2D), including investigation of effects of increasing confounder adjustment for register-data and lifestyle.

METHODS

In a cohort of 286,151 participants randomly selected across Denmark in 2010-2013 and followed up until 2017, we identified 7574 incident T2D cases. Based on residential address-history for all participants linked with exposure assessment of high spatial resolution, we calculated 10-year time-weighted mean road and railway noise at the most (LdenMax) and least (LdenMin) exposed façades and air pollution (PM_2.5). We used Cox models to calculate hazard ratios (HR) with increasing adjustment for individual- and area-level register-based sociodemographic covariates, self-reported lifestyle and air pollution.

RESULTS

We found that a 10 dB increase in 10-year mean road LdenMin was associated with HRs (95% CI) of 1.06 (1.02-1.10) after adjustment for age, sex and year, 1.08 (1.04-1.13) after further adjustment for register-based sociodemographic covariates, 1.07 (1.03-1.12) after further lifestyle adjustment (e.g. smoking, diet and alcohol) and 1.06 (1.02-1.11) after further PM_2.5 adjustment. For road LdenMax, the corresponding HRs were 1.07 (1.04-1.10), 1.05 (1.02-1.08), 1.04 (1.01-1.07) and 1.03 (1.00-1.06). Railway noise was associated with HRs of 1.04 (0.98-1.11) for LdenMax and 1.02 (0.92-1.12) for LdenMin after adjustment for sociodemographic and lifestyle covariates and PM_2.5.

CONCLUSIONS

Long-term exposure to road traffic noise was associated with T2D, which together with previous literature indicates that T2D should be considered when calculating health impacts of noise. After sociodemographic adjustment, further lifestyle adjustment only changed HRs slightly, suggesting that large register-based studies with adjustment for key sociodemographic covariates can produce reliable results.

Analysing Interlinked Frequency Dynamics of the Urban Acoustic Environment

As sustainable metropolitan regions require more densely built-up areas, a comprehensive understanding of the urban acoustic environment (AE) is needed. However, comprehensive datasets of the urban AE and well-established research methods for the AE are scarce. Datasets of audio recordings tend to be large and require a lot of storage space as well as computationally expensive analyses. Thus, knowledge about the long-term urban AE is limited. In recent years, however, these limitations have been steadily overcome, allowing a more comprehensive analysis of the urban AE. In this respect, the objective of this work is to contribute to a better understanding of the time-frequency domain of the urban AE, analysing automatic audio recordings from nine urban settings over ten months. We compute median power spectra as well as normalised spectrograms for all settings. Additionally, we demonstrate the use of frequency correlation matrices (FCMs) as a novel approach to access large audio datasets. Our results show site-dependent patterns in frequency dynamics. Normalised spectrograms reveal that frequency bins with low power hold relevant information and that the AE changes considerably over a year. We demonstrate that this information can be captured by using FCMs, which also unravel communities of interlinked frequency dynamics for all settings.

The Association between Duration of Noise Exposure in the Workplace and Glucose Metabolism Status: Evidence from the Korea National Health and Nutrition Examination Survey

BACKGROUND

This study aimed to evaluate the association between the duration of workplace noise exposure and glucose metabolism status in a nationally representative Korean sample.

METHODS

This cross-sectional study included 3,534 participants aged ≥40 years without tinnitus or hearing loss from the Korea National Health and Nutrition Examination Survey (2018). The primary exposure was noise in the workplace and its duration. We divided the noise exposure group into four groups according to the duration of noise exposure (<3 years, 3-10 years, 10-20 years, and ≥20 years). The primary outcomes were fasting blood sugar (FBS), hemoglobin A1c (HbA1c), and pre-diabetes and diabetes diagnosed using FBS. Logistic and linear regression analyses were used to test the association between noise exposure and glycemic status.

RESULTS

After adjustment, HbA1c levels were significantly higher in the noise exposure than in the non-noise exposure group. HbA1c levels were significantly higher in those exposed to occupational noise for more than 20 years than in others. In the subgroup analysis among those who had been exposed to noise for >20 years, the non-aerobic physical activity group had significantly higher HbA1c levels than the physical activity group. Furthermore, among those who had been exposed to noise for >20 years, the without hearing protection group had significantly higher HbA1c levels than those using hearing protection.

CONCLUSION

The association between noise exposure and the prevalence of diabetes is unclear. However, our study clearly suggests that there is a relationship between elevated HbA1c levels and workplace noise exposure and that a long period of workplace noise exposure, no physical activity, and not wearing a hearing protection device could increase the risk of diabetes.

Road Traffic Noise, Obesity, and the Risk of Incident Type 2 Diabetes: A Cohort Study in UK Biobank

Objectives: To assess the association of road traffic noise exposure with Type 2 Diabetes (T2D) risk, and to explore the potential moderation effect of obesity. Methods: A total of 305,969 participants from the UK Biobank Cohort - an open access cohort of 500,000 participants recruited in the United Kingdom (UK) between 2006 and 2010 - were included in the study. A Cox proportional hazard model was fitted to assess the association between road traffic noise exposure and T2D. Results: A total of 19,303 participants were diagnosed with T2D during the 11.9-year median follow-up period. For every 10 dB increase in road traffic noise, there was a 4% increase in T2D risk (HR = 1.04, 95%CI: 1.01, 1.07). Besides, a significant positive interaction was observed between obesity and road traffic noise (P interaction <0.001) for the risk of T2D. The association of road traffic noise with T2D was stronger in overweight and obese participants (HR = 1.04, 95% CI: 1.01-1.08), but not significant among lean ones (HR = 0.96, 95% CI: 0.86-1.07). Conclusion: Our study observed a longitudinal association of road traffic noise exposure with T2D risk, which was stronger among overweight and obese individuals than the lean ones.

Redox Regulatory Changes of Circadian Rhythm by the Environmental Risk Factors Traffic Noise and Air Pollution

Significance: Risk factors in the environment such as air pollution and traffic noise contribute to the development of chronic noncommunicable diseases. Recent Advances: Epidemiological data suggest that air pollution and traffic noise are associated with a higher risk for cardiovascular, metabolic, and mental disease, including hypertension, heart failure, myocardial infarction, diabetes, arrhythmia, stroke, neurodegeneration, depression, and anxiety disorders, mainly by activation of stress hormone signaling, inflammation, and oxidative stress. Critical Issues: We here provide an in-depth review on the impact of the environmental risk factors air pollution and traffic noise exposure (components of the external exposome) on cardiovascular health, with special emphasis on the role of environmentally triggered oxidative stress and dysregulation of the circadian clock. Also, a general introduction on the contribution of circadian rhythms to cardiovascular health and disease as well as a detailed mechanistic discussion of redox regulatory pathways of the circadian clock system is provided. Future Directions: Finally, we discuss the potential of preventive strategies or "chrono" therapy for cardioprotection. Antioxid. Redox Signal. 37, 679-703.

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.

Recent Insights into Particulate Matter (PM2.5)-Mediated Toxicity in Humans: An Overview

Several epidemiologic and toxicological studies have commonly viewed ambient fine particulate matter (PM_2.5), defined as particles having an aerodynamic diameter of less than 2.5 µm, as a significant potential danger to human health. PM_2.5 is mostly absorbed through the respiratory system, where it can infiltrate the lung alveoli and reach the bloodstream. In the respiratory system, reactive oxygen or nitrogen species (ROS, RNS) and oxidative stress stimulate the generation of mediators of pulmonary inflammation and begin or promote numerous illnesses. According to the most recent data, fine particulate matter, or PM_2.5, is responsible for nearly 4 million deaths globally from cardiopulmonary illnesses such as heart disease, respiratory infections, chronic lung disease, cancers, preterm births, and other illnesses. There has been increased worry in recent years about the negative impacts of this worldwide danger. The causal associations between PM_2.5 and human health, the toxic effects and potential mechanisms of PM_2.5, and molecular pathways have been described in this review.

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.

Long-term aircraft noise exposure and risk of hypertension in the Nurses' Health Studies

BACKGROUND

Aircraft noise can affect populations living near airports. Chronic exposure to aircraft noise has been associated with cardiovascular disease, including hypertension. However, previous studies have been limited in their ability to characterize noise exposures over time and to adequately control for confounders.

OBJECTIVES

The aim of this study was to examine the association between aircraft noise and incident hypertension in two cohorts of female nurses, using aircraft noise exposure estimates with high spatial resolution over a 20-year period.

METHODS

We obtained contour maps of modeled aircraft noise levels over time for 90 U.S. airports and linked them with geocoded addresses of participants in the Nurses' Health Study (NHS) and Nurses' Health Study II (NHS II) to assign noise exposure for 1994-2014 and 1995-2013, respectively. We used time-varying Cox proportional hazards models to estimate hypertension risk associated with time-varying noise exposure (dichotomized at 45 and 55 dB(A)), adjusting for fixed and time-varying confounders. Results from both cohorts were pooled via random effects meta-analysis.

RESULTS

In meta-analyses of parsimonious and fully-adjusted models with aircraft noise dichotomized at 45 dB(A), hazard ratios (HR) for hypertension incidence were 1.04 (95% CI: 1.00, 1.07) and 1.03 (95% CI: 0.99, 1.07), respectively. When dichotomized at 55 dB(A), HRs were 1.10 (95% CI: 1.01, 1.19) and 1.07 (95% CI: 0.98, 1.15), respectively. After conducting fully-adjusted sensitivity analyses limited to years in which particulate matter (PM) was obtained, we observed similar findings. In NHS, the PM-unadjusted HR was 1.01 (95% CI: 0.90, 1.14) and PM-adjusted HR was 1.01 (95% CI: 0.89, 1.14); in NHS II, the PM-unadjusted HR was 1.08 (95% CI: 0.96, 1.22) and the PM-adjusted HR was 1.08 (95% CI: 0.95, 1.21). Overall, in these cohorts, we found marginally suggestive evidence of a positive association between aircraft noise exposure and hypertension.

Road transportation green productivity and its threshold effects from environmental regulation

This paper uses the global Malmquist-Luenberger index to investigate changes in road transportation green productivity from 2010 to 2017, incorporating undesirable outputs into the analytical framework. Furthermore, the relationship between environmental regulation and green productivity is tested by the panel threshold model. At the area level, the improvement of green productivity in western China benefits from a catch-up effect and improved scale efficiency. Moreover, the driving factor improving green productivity in China's central and eastern areas is mainly the scale economy, and technology regress is the hindering factor. Research and development investment and government fiscal expenditure both show a single-threshold effect on green productivity. That is, their values in relation to thresholds cause differences in the impact of environmental regulation on green productivity. Our analysis shows that economic development can significantly promote green productivity, while highway density can significantly hinder it. Based on the evidence presented, we put forward practical suggestions for improving green productivity.

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.

Environmental Factors as Diabetic Mediators: A Mechanistic Approach

Despite substantial investment in research and treatment options, diabetes mellitus remains a pressing public health concern with potential epidemic proportions globally. There are reports that by the end of 2040, 642 million people will be suffering from diabetes. Also, according to an estimation, 1.6 million deaths were caused directly by diabetes in 2016. Diabetes is a metabolic disorder characterized by impaired glucose regulation in the body due to the destruction of pancreatic β-cells or insulin resistance. Genetic propensity, unhealthy and imbalanced diet, obesity and increasing urbanization are the common risk factors for diabetes. Besides this, it has been reported that environmental pollutants like organic pesticides, heavy metals, and air pollutants act as strong predisposing factors for diabetes owing to their highly bio-accumulative nature. These pollutants disturb glucose homeostasis either by up-regulating or down-regulating the expression of diabetic marker genes like insulin (INS) and glucokinase (GCK). Unfortunately, the molecular mechanism of the role of pollutants in causing diabetes is not very clear. This mechanistic review provides evidence of different environmental determinants, including persistent organic pollutants (POPs), air pollutants, toxic metals, etc., in inducing diabetes and proposes a framework for the possible mechanisms involved. It also illuminates the current status and future challenges, which will not only broaden our understanding but can also be a reasonable platform for further investigation.

Association between occupational or environmental noise exposure and renal function among middle-aged and older Korean adults: a cross-sectional study

Exposure to occupational and environmental noise is closely linked to various auditory system diseases. Few studies have focused on the effect of noise exposure on the extra auditory system, especially the urinary system. We analyzed 17,154 participants aged 40–79 years from the Korea National Health and Nutrition Examination Survey between 2013 and 2018. A self-reported questionnaire was used to assess occupational or environmental noise exposure. Logistic regression was used to determine the differences in the prevalence of chronic kidney disease (CKD) based on noise exposure characteristics. For participants with noise exposure, linear regression was performed to determine relationship of the noise exposure period and estimated glomerular filtration rate (eGFR). In the noise exposure group, a higher CKD prevalence was associated with females who experienced long-term occupational noise (≥ 240 months) (adjusted OR 2.72, 95% CI 1.11–6.66). An increase of one month of occupational noise exposure was associated with a 0.0106 mL/min/1.73 m² decrease in eGFR in females aged < 60 years. Overall, noise exposure may be a risk factor for reduced renal function, especially long-term occupational noise exposure. More precise studies should determine (1) the relationship between noise and renal function and (2) the underlying mechanisms.

Redox Switches in Noise-Induced Cardiovascular and Neuronal Dysregulation

Environmental exposures represent a significant health hazard, which cumulatively may be responsible for up to 2/3 of all chronic non-communicable disease and associated mortality (Global Burden of Disease Study and The Lancet Commission on Pollution and Health), which has given rise to a new concept of the exposome: the sum of environmental factors in every individual’s experience. Noise is part of the exposome and is increasingly being investigated as a health risk factor impacting neurological, cardiometabolic, endocrine, and immune health. Beyond the well-characterized effects of high-intensity noise on cochlear damage, noise is relatively well-studied in the cardiovascular field, where evidence is emerging from both human and translational experiments that noise from traffic-related sources could represent a risk factor for hypertension, ischemic heart disease, diabetes, and atherosclerosis. In the present review, we comprehensively discuss the current state of knowledge in the field of noise research. We give a brief survey of the literature documenting experiments in noise exposure in both humans and animals with a focus on cardiovascular disease. We also discuss the mechanisms that have been uncovered in recent years that describe how exposure to noise affects physiological homeostasis, leading to aberrant redox signaling resulting in metabolic and immune consequences, both of which have considerable impact on cardiovascular health. Additionally, we discuss the molecular pathways of redox involvement in the stress responses to noise and how they manifest in disruptions of the circadian rhythm, inflammatory signaling, gut microbiome composition, epigenetic landscape and vessel function.

Plasma metabolomic profiling in workers with noise-induced hearing loss: a pilot study

Noise-induced hearing loss (NIHL) remains a leading occupational related disease and is a serious public health problem. Hence, the identification of potential biomarkers for NIHL prevention and diagnosis has become an urgent work. To discover potential metabolic biomarkers of NIHL, plasma metabolomics analysis in 62 NIHL patients and 62 normal hearing controls was performed using ultrahigh-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry (UHPLC-Q-TOF MS). Orthogonal partial least square-discriminant analysis (OPLS-DA) model was applied to distinguish metabolite profile alterations in plasma samples between the two groups. The metabolites with a variable importance of projection (VIP) value > 1 and P value < 0.05 were considered to be potential metabolic biomarkers. KEGG database was performed to explore the involved pathways of potential biomarkers. Three autophagy-related genes (PI3K, AKT, and ATG5) were selected for further verification, and mRNA levels were detected using RT-qPCR analysis. Twenty plasma metabolites with VIP > 1 and P < 0.05 were significantly altered between the two groups. Totally, seven metabolic pathways involving the glycerophospholipid metabolism, glycosylphosphatidylinositol (GPI)-anchor biosynthesis, autophagy pathway, choline metabolism, the alpha-linolenic acid metabolism and linoleic acid metabolism, and retrograde endocannabinoid pathway were significantly related to NIHL. Furthermore, verification by RT-qPCR suggested that the mRNA expression levels of PI3K and AKT along with ATG5 were significantly lower in the NIHL patients compared with controls. In summary, the present study provides the first evidence that the identified aberrantly altered metabolites may be the potentially valuable biomarkers of NIHL for occupational noise-exposed workers. Autophagy signal pathway may be involved in the occurrence and development of NIHL. Moreover, this present study may be helpful to further better understand the metabolic changes in NIHL and be helpful for the understanding of pathogenic mechanism.

Long-Term Exposure to Transportation Noise and Risk for Type 2 Diabetes in a Nationwide Cohort Study from Denmark

BACKGROUND

Epidemiologic studies have linked transportation noise to increased morbidity and mortality, particularly for cardiovascular outcomes. However, studies investigating metabolic outcomes such as diabetes are limited and have focused only on noise exposures estimated for the loudest residential façade.

OBJECTIVES

We aimed to examine the influence of long-term residential exposure to transportation noise at the loudest and quietest residential façades and the risk for type 2 diabetes.

METHODS

Road traffic and railway noise exposures (Lden) at the most and least exposed façades were estimated for all dwellings in Denmark during 1990-2017. Aircraft noise was estimated in 5-dB categories. Ten-year time-weighted mean noise exposures were estimated for 3.56 million individuals ≥35 years of age. From 2000 to 2017, 233,912 incident cases of type 2 diabetes were identified using hospital and prescription registries, with a mean follow-up of 12.9 y. We used Cox proportional hazards models adjusting for individual- and area-level covariates and long-term residential air pollution. The population-attributable fraction (PAF) was also computed.

RESULTS

Hazard ratios (HRs) and 95% confidence intervals (CIs) for type 2 diabetes in association with 10-dB increases in 10-y mean road traffic noise at the most and least exposed façades, respectively, were 1.05 (95% CI: 1.04, 1.05) and 1.09 (95% CI: 1.08, 1.10). Following subsequent adjustment for fine particulate matter [particulate matter ≤2.5μm in aerodynamic diameter] (10-y mean), the HRs (CIs) were 1.03 (95% CI: 1.03, 1.04) and 1.08 (95% CI: 1.07, 1.09), respectively. For railway noise, the HRs per 10-dB increase in 10-y mean exposure were 1.03 (95% CI: 1.02, 1.04) and 1.02 (95% CI: 1.01, 1.04) for the most and least exposed façades, respectively. Categorical models supported a linear exposure-outcome relationship for road traffic noise and, to a lesser extent, for railway noise. Aircraft noise >45 dB was associated with a 1-4% higher likelihood of type 2 diabetes compared with those who were unexposed. We found road traffic and railway noise associated with a PAF of 8.5% and 1.4%, respectively, of the diabetes cases.

DISCUSSION

Long-term exposure to road, railway, and possibly aircraft traffic noise was associated with an increased risk of type 2 diabetes in a nationwide cohort of Danish adults. Our findings suggest that diabetes should be included when estimating the burden of disease due to transportation noise. https://doi.org/10.1289/EHP9146.

Urban Noise Exposure and Cardiometabolic Diseases: An Exploratory Cross-Sectional Study in Lisbon

Introduction: Urban noise pollution has been associated with an increased risk of developing metabolic syndrome. Nevertheless, existing observational studies relating to noise exposure and metabolic syndrome are based on non-generalizable cohorts. Lisbon remains a noisy city where this association has not been evaluated, and for this reason, we studied the relationship between exposure to urban noise and the prevalence of type 2 diabetes mellitus, obesity, and hypertension. Methods: Diurnal, evening and nocturnal noise emission levels were obtained for each street in the city from the Lisbon noise map. After allocation of all roads to the respective parish of Lisbon, the noise emission for each parish was averaged for each day period. The number of adult patients with type 2 diabetes mellitus, obesity and hypertension in 2014, 2015 and 2016 in each parish of Lisbon was obtained from the Regional Health Administration of Lisbon and Tagus Valley. Prevalence as a percentage of the population was determined using the number of residents in each parish determined in the 2011 population census. Spearman’s non-parametric correlation coefficient was used due to the non-normal distribution of the variables, at the 5% significance level (α = 0.05). Results: No correlations were found between daytime, afternoon or night-time noise exposure and the prevalence of type 2 diabetes mellitus, obesity or hypertension, although correlations were found between the cardiometabolic variables. Nevertheless, noise levels in Lisbon were above the legally established limit and the World Health Organization guidelines for environmental noise exposure in the European region. Conclusion: Our results do not agree with previous studies and should be faced as preliminary due to a strong biological plausibility for an association between noise exposure and cardiometabolic diseases and to encourage further studies, with longitudinal cohorts.

Acute cardiovascular effects of traffic-related air pollution (TRAP) exposure in healthy adults: A randomized, blinded, crossover intervention study

Exposure to traffic-related air pollution (TRAP) may enhance the risk of cardiovascular disease. However, the short-term effects of TRAP components on the cardiovascular system are not well understood. We conducted a randomized, double-blinded, crossover intervention study in which 39 healthy university students spent 2 h next to a busy road. Participants wore a powered air-purifying respirator (PAPR) or an N95 mask. PAPRs were equipped with a filter for particulate matter (PM), a PM and volatile organic compounds (VOCs) filter or a sham filter. Participants were blinded to PAPR filter type and underwent randomized exposures four times, once for each intervention mode. Blood pressure (BP), heart rate (HR) and heart rate variability (HRV) were measured before, during and for 6 h after the roadside exposure. Linear mixed-effect models were used to evaluate the effects of the interventions relative to baseline controlling for other covariates. All HRV measures increased during and following exposure for all intervention modes. Some HRV measures (SDNN and rMSSD during exposure and SDNN after exposure) were marginally affected by PM filtration. Wearing the N95 mask affected VLF power and rMSSD responses to traffic exposure differently than the PAPR interventions. Both systolic and diastolic BP increased slightly during exposure, but then were generally lower than baseline after exposure for the sham and filter interventions. HR, which fell during exposure and mostly remained lower than baseline after exposure, was lower yet with all filter interventions compared to the sham mode following exposure. Therefore, short-term exposure to traffic acutely affects HRV, BP and HR, but N95 mask and PAPR interventions generally show little efficacy in reducing these effects. Removing the PM component of TRAP has some limited effects on HRV responses to exposure but exaggerates the traffic-related decrease in HR. HRV findings from N95 mask interventions need to be interpreted cautiously.

Long-term PM2.5 exposure and survival among cardiovascular disease patients in Beijing, China

Previous studies have proved that particulate air pollution was related to adverse cardiovascular effects. However, most studies focused on the acute effects of short-term fine particulate matter (PM_2.5) exposure and the general population. Evidence from long-term cohort studies based on the cardiovascular disease (CVD) patients was scarce. Our study aimed to explore the impact of long-term exposure to PM_2.5 on the mortality among post-CVD patients. This is a cohort study that involved 5143 post-CVD patients in Beijing, China. We collected records of CVD patients from hospitals in Beijing, China from 1 January 2012 to 31 December 2012 and followed up these patients from hospital admission until December 31, 2016. The vital status of the patients was determined using the National Death Surveillance Point System (DSPs). The PM_2.5 concentrations were obtained from the Atmospheric Composition Analysis Group. The Cox regression models were used for data analyses. Our findings suggested that increased mortality of CVD patients with an HR of 1.43 (95% CI: 1.24, 1.63) was related to long-term exposure to PM_2.5. The association was stronger for cardiovascular-related mortality, especially for mortality from myocardial infarction (MI). The HR for any CVD mortality was 1.57 (95% CI: 1.27, 1.94), HR for MI mortality was 1.82 (95% CI: 1.16, 2.83). Long-term PM_2.5 exposure may significantly affect the survival of CVD patients. Compared with the general population, patients with CVD are more susceptible to PM_2.5 exposure. Increased attention to the management of CVD patients is warranted.

Mortality and Morbidity Effects of Long-Term Exposure to Low-Level PM2.5, BC, NO2, and O3: An Analysis of European Cohorts in the ELAPSE Project

INTRODUCTION

Epidemiological cohort studies have consistently found associations between long-term exposure to outdoor air pollution and a range of morbidity and mortality endpoints. Recent evaluations by the World Health Organization and the Global Burden of Disease study have suggested that these associations may be nonlinear and may persist at very low concentrations. Studies conducted in North America in particular have suggested that associations with mortality persisted at concentrations of particulate matter with an aerodynamic diameter of less than 2.5 μm (PM2.5) well below current air quality standards and guidelines. The uncertainty about the shape of the concentration-response function at the low end of the concentration distribution, related to the scarcity of observations in the lowest range, was the basis of the current project. Previous studies have focused on PM2.5, but increasingly associations with nitrogen dioxide (NO2) are being reported, particularly in studies that accounted for the fine spatial scale variation of NO2. Very few studies have evaluated the effects of long-term exposure to low concentrations of ozone (O3). Health effects of black carbon (BC), representing primary combustion particles, have not been studied in most large cohort studies of PM2.5. Cohort studies assessing health effects of particle composition, including elements from nontailpipe traffic emissions (iron, copper, and zinc) and secondary aerosol (sulfur) have been few in number and reported inconsistent results. The overall objective of our study was to investigate the shape of the relationship between long-term exposure to four pollutants (PM2.5, NO2, BC, and O3) and four broad health effect categories using a number of different methods to characterize the concentration-response function (i.e., linear, nonlinear, or threshold). The four health effect categories were (1) natural- and cause-specific mortality including cardiovascular and nonmalignant as well as malignant respiratory and diabetes mortality; and morbidity measured as (2) coronary and cerebrovascular events; (3) lung cancer incidence; and (4) asthma and chronic obstructive pulmonary disease (COPD) incidence. We additionally assessed health effects of PM2.5 composition, specifically the copper, iron, zinc, and sulfur content of PM2,5.

METHODS

We focused on analyses of health effects of air pollutants at low concentrations, defined as less than current European Union (EU) Limit Values, U.S. Environmental Protection Agency (U.S. EPA), National Ambient Air Quality Standards (NAAQS), and/or World Health Organization (WHO) Air Quality Guideline values for PM2.5, NO2, and O3. We address the health effects at low air pollution levels by performing new analyses within selected cohorts of the ESCAPE study (European Study of Cohorts for Air Pollution Effects; Beelen et al. 2014a) and within seven very large European administrative cohorts. By combining well-characterized ESCAPE cohorts and large administrative cohorts in one study the strengths and weaknesses of each approach can be addressed. The large administrative cohorts are more representative of national or citywide populations, have higher statistical power, and can efficiently control for area-level confounders, but have fewer possibilities to control for individual-level confounders. The ESCAPE cohorts have detailed information on individual confounders, as well as country-specific information on area-level confounding. The data from the seven included ESCAPE cohorts and one additional non-ESCAPE cohort have been pooled and analyzed centrally. More than 300,000 adults were included in the pooled cohort from existing cohorts in Sweden, Denmark, Germany, the Netherlands, Austria, France, and Italy. Data from the administrative cohorts have been analyzed locally, without transfer to a central database. Privacy regulations prevented transfer of data from administrative cohorts to a central database. More than 28 million adults were included from national administrative cohorts in Belgium, Denmark, England, the Netherlands, Norway, and Switzerland as well as an administrative cohort in Rome, Italy. We developed central exposure assessment using Europewide hybrid land use regression (LUR) models, which incorporated European routine monitoring data for PM2.5, NO2, and O3, and ESCAPE monitoring data for BC and PM2.5 composition, land use, and traffic data supplemented with satellite observations and chemical transport model estimates. For all pollutants, we assessed exposure at a fine spatial scale, 100 × 100 m grids. These models have been applied to individual addresses of all cohorts including the administrative cohorts. In sensitivity analyses, we applied the PM2.5 models developed within the companion HEI-funded Canadian MAPLE study (Brauer et al. 2019) and O3 exposures on a larger spatial scale for comparison with previous studies. Identification of outcomes included linkage with mortality, cancer incidence, hospital discharge registries, and physician-based adjudication of cases. We analyzed natural-cause, cardiovascular, ischemic heart disease, stroke, diabetes, cardiometabolic, respiratory, and COPD mortality. We also analyzed lung cancer incidence, incidence of coronary and cerebrovascular events, and incidence of asthma and COPD (pooled cohort only). We applied the Cox proportional hazard model with increasing control for individual- and area-level covariates to analyze the associations between air pollution and mortality and/or morbidity for both the pooled cohort and the individual administrative cohorts. Age was used as the timescale because of evidence that this results in better adjustment for potential confounding by age. Censoring occurred at the time of the event of interest, death from other causes, emigration, loss to follow-up for other reasons, or at the end of follow-up, whichever came first. A priori we specified three confounder models, following the modeling methods of the ESCAPE study. Model 1 included only age (time axis), sex (as strata), and calendar year of enrollment. Model 2 added individual-level variables that were consistently available in the cohorts contributing to the pooled cohort or all variables available in the administrative cohorts, respectively. Model 3 further added area-level socioeconomic status (SES) variables. A priori model 3 was selected as the main model. All analyses in the pooled cohort were stratified by subcohort. All analyses in the administrative cohorts accounted for clustering of the data in neighborhoods by adjusting the variance of the effect estimates. The main exposure variable we analyzed was derived from the Europewide hybrid models based on 2010 monitoring data. Sensitivity analyses were conducted using earlier time periods, time-varying exposure analyses, local exposure models, and the PM2.5 models from the Canadian MAPLE project. We first specified linear single-pollutant models. Two-pollutant models were specified for all combinations of the four main pollutants. Two-pollutant models for particle composition were analyzed with PM2.5 and NO2 as the second pollutant. We then investigated the shape of the concentration-response function using natural splines with two, three, and four degrees of freedom; penalized splines with the degrees of freedom determined by the algorithm and shape-constrained health impact functions (SCHIF) using confounder model 3. Additionally, we specified linear models in subsets of the concentration range, defined by removing concentrations above a certain value from the analysis, such as for PM2.5 25 μg/m3 (EU limit value), 20, 15, 12 μg/m3 (U.S. EPA National Ambient Air Quality Standard), and 10 μg/m3 (WHO Air Quality Guideline value). Finally, threshold models were evaluated to investigate whether the associations persisted below specific concentration values. For PM2.5, we evaluated 10, 7.5, and 5 μg/m3 as potential thresholds. Performance of threshold models versus the corresponding no-threshold linear model were evaluated using the Akaike information criterion (AIC).

RESULTS

In the pooled cohort, virtually all subjects in 2010 had PM2.5 and NO2 annual average exposures below the EU limit values (25 μg/m3 and 40 μg/m3, respectively). More than 50,000 had a residential PM2.5 exposure below the U.S. EPA NAAQS (12 μg/m3). More than 25,000 subjects had a residential PM2.5 exposure below the WHO guideline (10 μg/m3). We found significant positive associations between PM2.5, NO2, and BC and natural-cause, respiratory, cardiovascular, and diabetes mortality. In our main model, the hazard ratios (HRs) (95% [confidence interval] CI) were 1.13 (CI = 1.11, 1.16) for an increase of 5 μg/m3 PM2.5, 1.09 (CI = 1.07, 1.10) for an increase of 10 μg/m3 NO2, and 1.08 (CI = 1.06, 1.10) for an increase of 0.5 × 10-5/m BC for natural-cause mortality. The highest HRs were found for diabetes mortality. Associations with O3 were negative, both in the fine spatial scale of the main ELAPSE model and in large spatial scale exposure models. For PM2.5, NO2, and BC, we generally observed a supralinear association with steeper slopes at low exposures and no evidence of a concentration below which no association was found. Subset analyses further confirmed that these associations remained at low levels: below 10 μg/m3 for PM2.5 and 20 μg/m3 for NO2. HRs were similar to the full cohort HRs for subjects with exposures below the EU limit values for PM2.5 and NO2, the U.S. NAAQS values for PM2.5, and the WHO guidelines for PM2.5 and NO2. The mortality associations were robust to alternative specifications of exposure, including different time periods, PM2.5 from the MAPLE project, and estimates from the local ESCAPE model. Time-varying exposure natural spline analyses confirmed associations at low pollution levels. HRs in two-pollutant models were attenuated but remained elevated and statistically significant for PM2.5 and NO2. In two-pollutant models of PM2.5 and NO2 HRs for natural-cause mortality were 1.08 (CI = 1.05, 1.11) for PM2.5 and 1.05 (CI = 1.03, 1.07) for NO2. Associations with O3 were attenuated but remained negative in two-pollutant models with NO2, BC, and PM2.5. We found significant positive associations between PM2.5, NO2, and BC and incidence of stroke and asthma and COPD hospital admissions. Furthermore, NO2 was significantly related to acute coronary heart disease and PM2.5 was significantly related to lung cancer incidence. We generally observed linear to supralinear associations with no evidence of a threshold, with the exception of the association between NO2 and acute coronary heart disease, which was sublinear. Subset analyses documented that associations remained even with PM2.5 below 20 μg/m3 and possibly 12 μg/m3. Associations remained even when NO2 was below 30 μg/m3 and in some cases 20 μg/m3. In two-pollutant models, NO2 was most consistently associated with acute coronary heart disease, stroke, asthma, and COPD hospital admissions. PM2.5 was not associated with these outcomes in two-pollutant models with NO2. PM2.5 was the only pollutant that was associated with lung cancer incidence in two-pollutant models. Associations with O3 were negative though generally not statistically significant. In the administrative cohorts, virtually all subjects in 2010 had PM2.5 and NO2 annual average exposures below the EU limit values. More than 3.9 million subjects had a residential PM2.5 exposure below the U.S. EPA NAAQS (12 μg/m3) and more than 1.9 million had residential PM2.5 exposures below the WHO guideline (10 μg/m3). We found significant positive associations between PM2.5, NO2, and BC and natural-cause, respiratory, cardiovascular, and lung cancer mortality, with moderate to high heterogeneity between cohorts. We found positive but statistically nonsignificant associations with diabetes mortality. In our main model meta-analysis, the HRs (95% CI) for natural-cause mortality were 1.05 (CI = 1.02, 1.09) for an increase of 5 μg/m3 PM2.5, 1.04 (CI = 1.02, 1.07) for an increase of 10 μg/m3 NO2, and 1.04 (CI = 1.02, 1.06) for an increase of 0.5 × 10-5/m BC, and 0.95 (CI = 0.93, 0.98) for an increase of 10 μg/m3 O3. The shape of the concentration-response functions differed between cohorts, though the associations were generally linear to supralinear, with no indication of a level below which no associations were found. Subset analyses documented that these associations remained at low levels: below 10 μg/m3 for PM2.5 and 20 μg/m3 for NO2. BC and NO2 remained significantly associated with mortality in two-pollutant models with PM2.5 and O3. The PM2.5 HR attenuated to unity in a two-pollutant model with NO2. The negative O3 association was attenuated to unity and became nonsignificant. The mortality associations were robust to alternative specifications of exposure, including time-varying exposure analyses. Time-varying exposure natural spline analyses confirmed associations at low pollution levels. Effect estimates in the youngest participants (<65 years at baseline) were much larger than in the elderly (>65 years at baseline). Effect estimates obtained with the ELAPSE PM2.5 model did not differ from the MAPLE PM2.5 model on average, but in individual cohorts, substantial differences were found.

CONCLUSIONS

Long-term exposure to PM2.5, NO2, and BC was positively associated with natural-cause and cause-specific mortality in the pooled cohort and the administrative cohorts. Associations were found well below current limit values and guidelines for PM2.5 and NO2. Associations tended to be supralinear, with steeper slopes at low exposures with no indication of a threshold. Two-pollutant models documented the importance of characterizing the ambient mixture with both NO2 and PM2.5. We mostly found negative associations with O3. In two-pollutant models with NO2, the negative associations with O3 were attenuated to essentially unity in the mortality analysis of the administrative cohorts and the incidence analyses in the pooled cohort. In the mortality analysis of the pooled cohort, significant negative associations with O3 remained in two-pollutant models. Long-term exposure to PM2.5, NO2, and BC was also positively associated with morbidity outcomes in the pooled cohort. For stroke, asthma, and COPD, positive associations were found for PM2.5, NO2, and BC. For acute coronary heart disease, an increased HR was observed for NO2. For lung cancer, an increased HR was found only for PM2.5. Associations mostly showed steeper slopes at low exposures with no indication of a threshold.

Transportation noise pollution and cardiovascular disease

Epidemiological studies have found that transportation noise increases the risk of cardiovascular morbidity and mortality, with high-quality evidence for ischaemic heart disease. According to the WHO, ≥1.6 million healthy life-years are lost annually from traffic-related noise in Western Europe. Traffic noise at night causes fragmentation and shortening of sleep, elevation of stress hormone levels, and increased oxidative stress in the vasculature and the brain. These factors can promote vascular dysfunction, inflammation and hypertension, thereby elevating the risk of cardiovascular disease. In this Review, we focus on the indirect, non-auditory cardiovascular health effects of transportation noise. We provide an updated overview of epidemiological research on the effects of transportation noise on cardiovascular risk factors and disease, discuss the mechanistic insights from the latest clinical and experimental studies, and propose new risk markers to address noise-induced cardiovascular effects in the general population. We also explain, in detail, the potential effects of noise on alterations of gene networks, epigenetic pathways, gut microbiota, circadian rhythm, signal transduction along the neuronal-cardiovascular axis, oxidative stress, inflammation and metabolism. Lastly, we describe current and future noise-mitigation strategies and evaluate the status of the existing evidence on noise as a cardiovascular risk factor.

Associations between ambient air pollutants and blood pressure among children and adolescents: A systemic review and meta-analysis

OBJECTIVE

Numerous epidemiological studies have investigated the effects of short-term and long-term exposure to ambient air pollution on hypertension and blood pressure among children and adolescents. However, the results were controversial. To provide researchers reliable evidence, this meta-analysis was performed.

METHODS

We searched all published studies in four databases examining the effects of particulate matter (PM₁₀, PM_2.5 and PM_1.0), nitrogen oxide (NO₂), sulfur dioxide (SO₂), ozone (O₃) and carbon monoxide (CO) on hypertension and blood pressure in children and adolescents. Overall risk estimates associated with per 10 μg/m³ increase of air pollution were analyzed by a random-effect model for articles with significant heterogeneity, otherwise, a fixed-effect model was applied. Subgroup analysis was conducted for studies with significant heterogeneity.

RESULTS

Of 3918 identified literatures, 154 were evaluated in-depth with 15 satisfying inclusion criteria. Increased risk of hypertension was associated with long-term PM₁₀ exposure (OR = 1.17, 95% confidence interval [CI]:1.13, 1.21). For systolic blood pressure (SBP), significant results were found for short-term PM₁₀ (β = 0.26, 95% CI: -0.00, 0.53) exposure, long-term PM_2.5 (β = 1.80, 95% CI: 0.94, 2.65) and PM₁₀ (β = 0.50, 95% CI: 0.19, 0.81) exposure. The corresponding estimates of diastolic blood pressure (DBP) were 0.32 mmHg (95% CI: 0.19, 0.45) for short-term PM₁₀ exposure, 1.06 mmHg (95% CI: 0.32, 1.80), 0.34 mmHg (95% CI: 0.11, 0.57) and 0.44 mmHg (95% CI: 0.25, 0.63) for long-term PM_2.5, PM₁₀ and NO₂ exposure, respectively. Stratified analyses showed stronger effects of PM₁₀ on blood pressure among studies with ≥50% boys' percentage (0.57 mmHg [95% CI: 0.44, 0.70] for SBP, 0.44 mmHg, [95% CI: 0.34, 0.54] for DBP, respectively) and articles using models to estimate exposure (0.90 mmHg [95% CI: 0.20 1.59] for SBP).

CONCLUSION

Ambient air pollution was associated with higher hypertension prevalence and elevated blood pressure in children and adolescents.

A neurobiological link between transportation noise exposure and metabolic disease in humans

BACKGROUND

Chronic transportation noise exposure associates with cardiovascular events through a link involving heightened stress-associated neurobiological activity (as amygdalar metabolic activity, AmygA) on ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG-PET/CT). Increased AmygA also associates with greater visceral adipose tissue (VAT) and type 2 diabetes mellitus (DM). While relationships between noise exposure and VAT and DM have been reported, the underlying mechanisms remain incompletely understood. We tested whether: (1) transportation noise exposure associates with greater (a) baseline and gains in VAT and (b) DM risk, and (2) heightened AmygA partially mediates the link between noise exposure and these metabolic diseases.

METHODS

VAT was measured in a retrospective cohort (N = 403) who underwent clinical ¹⁸F-FDG-PET/CT. AmygA was measured in those with brain imaging (N = 238). Follow-up VAT was remeasured on available imaging (N = 67). Among individuals (N = 224) without baseline DM, incident DM was adjudicated over 2 years from clinical records. Noise (24-h average) was modeled at each individual's home address. Linear regression, survival, and mediation analyses were employed.

RESULTS

Higher noise exposure (upper tertile vs. others) associated with greater: baseline VAT (standardized β [95% confidence interval (CI)]= 0.230 [0.021, 0.438], p = 0.031), gains in VAT (0.686 [0.185, 1.187], p = 0.008 adjusted for baseline VAT), and DM (hazard ratio [95% CI]=2.429 [1.031, 5.719], p = 0.042). The paths of: ↑noise exposure→↑AmygA→↑baseline VAT and ↑noise exposure→↑AmygA→↑subsequent DM were significant (p < 0.05).

CONCLUSIONS

Increased transportation noise exposure associates with greater VAT and DM. This relationship is partially mediated by stress-associated neurobiological activity. These findings suggest altered neurobiology contributes to noise exposure's link to metabolic diseases.

Land use regression modelling of community noise in São Paulo, Brazil

Noise pollution has negative health consequences, which becomes increasingly relevant with rapid urbanization. In low- and middle-income countries research on health effects of noise is hampered by scarce exposure data and noise maps. In this study, we developed land use regression (LUR) models to assess spatial variability of community noise in the Western Region of São Paulo, Brazil.We measured outdoor noise levels continuously at 42 homes once or twice for one week in the summer and the winter season. These measurements were integrated with various geographic information system variables to develop LUR models for predicting average A-weighted (dB(A)) day-evening-night equivalent sound levels (L_den) and night sound levels (L_night). A supervised mixed linear regression analysis was conducted to test potential noise predictors for various buffer sizes and distances between home and noise source. Noise exposure levels in the study area were high with a site average L_den of 69.3 dB(A) ranging from 60.3 to 82.3 dB(A), and a site average L_night of 59.9 dB(A) ranging from 50.7 to 76.6 dB(A). LUR models had a good fit with a R² of 0.56 for L_den and 0.63 for L_night in a leave-one-site-out cross validation. Main predictors of noise were the inverse distance to medium roads, count of educational facilities within a 400 m buffer, mean Normalized Difference Vegetation Index (NDVI) within a 100 m buffer, residential areas within a 50 m (L_den) or 25 m (L_night) buffer and slum areas within a 400 m buffer. Our study suggests that LUR modelling with geographic predictor data is a promising and efficient approach for noise exposure assessment in low- and middle-income countries, where noise maps are not available.

Modelling road traffic Noise under heterogeneous traffic conditions using the graph-theoretic approach

A traffic noise system involves several subsystems like road traffic subsystem, human subsystem, environment subsystem, traffic network subsystem, and urban prosperity subsystem. The study's main aim was to develop road traffic noise models using a graph theory approach involving the parameters related to road traffic subsystem. The road traffic subsystem variables selected for the modeling purposes included vehicular speed, traffic volume, carriageway width, number of heavy vehicles, and number of honking events. The interaction of the selected variables considered in the form of permanent noise function is given in the matrix form. Eigenvalues and corresponding eigenvectors are calculated for removing any human judgmental error. The permanent noise function matrix was then updated using the eigenvectors, which was ultimately utilized for obtaining the permanent noise index. Data regarding the selected variables were collected for three months, and the noise parameters included in the study were equivalent noise level (Leq,1h), maximum noise level (L10,1h), and background noise level (L90,1h). A logarithmic transformation was applied to the permanent noise index and linear regression models were developed for Leq,1h , L90,1h , and L10,1h respectively. The models were validated using the data collected from the same locations for nine months. The models were found to provide satisfactory results, although the results were somewhat overestimated. The method can prove beneficial for estimating future noise levels, given the expected changes in values for the independent variables considered in the study.

Noise annoyance, sociodemographic and health patterns, and neighborhood perceptions in a Brazilian metropolis: BH Health Study

OBJECTIVE

The present study aims to analyze the association of noise annoyance with individual and sociodemographic factors and self-perception of the neighborhood in an urban center.

METHODS

Data were collected through a population-based cross-sectional study held in two of the nine health districts in the city of Belo Horizonte, Minas Gerais, Brazil, from 2008 to 2009. The study included 3,934 individuals of both genders, aged 18 years and older. The response variable was the self-perception of noise, investigated by the question: "In your neighborhood, does the noise bother you?" The explanatory variables were grouped into the following domains: sociodemographic, social determinants, self-rated health, and self-reported diseases.

RESULTS

The prevalence of noise annoyance was 47% for women and 39.8% for men. For both genders, noise annoyance was independently associated with bad traffic and the presence of loud music, discussions, and late-night parties.

CONCLUSION

Gender differences were identified in the association of noise annoyance with sociodemographic characteristics and self-reported morbidity. Traffic and social customs were the main sources of noise in the regions under study.

Insomnia associated with traffic noise and proximity to traffic-a cross-sectional study of the Respiratory Health in Northern Europe III population

STUDY OBJECTIVES

Exposure to traffic noise increases the risk of sleeping disturbance, but little is known about the effect of traffic-related air pollution on insomnia symptoms. We aimed to investigate the separate associations of self-reported proximity to traffic and traffic noise with insomnia.

METHODS

This is a cross-sectional study of the population included in the Respiratory Health in Northern Europe study, consisting of randomly selected men and women born between 1945 and 1973, from 7 Northern European centers. Hearing traffic noise in the bedroom, bedroom window proximity to traffic, and insomnia symptoms were self-reported. Bedroom window proximity to traffic was used as a surrogate for exposure to traffic-related air pollution. The following insomnia symptoms were assessed: difficulty initiating sleep, difficulty maintaining sleep, and early morning awakening.

RESULTS

A total of 12,963 individuals was included. Traffic noise was positively associated with all three insomnia symptoms: difficulty initiating sleep (odds ratio [OR] = 3.54; 95% confidence interval [CI]: 1.85, 6.76), difficulty maintaining sleep (OR = 2.95; 95% CI: 1.62, 5.37), and early morning awakening (OR = 3.25; 95% CI: 1.97, 5.37). Proximity to traffic without disturbing noise was associated with difficulty initiating sleep (OR = 1.62; 95% CI: 1.45, 1.82).

CONCLUSIONS

This study adds further support to the identification of traffic noise as a risk factor for insomnia. Proximity to traffic without being exposed to noise was associated with an increased risk of difficulty initiating sleep. Our findings indicate that insomnia may be associated with both traffic noise and traffic-related air pollution.

Integrating random forests and propagation models for high-resolution noise mapping

The adverse effects of long-term exposure to environmental noise on human health are of increasing concern. Noise mapping methods such as spatial interpolation and land use regression cannot capture complex relationships between environmental conditions and noise propagation or attenuation in a three-dimension (3D) built environment. In this study, we developed a hybrid approach by combining a traffic propagation model and random forests (RF) machine learning algorithm to map the total environment noise levels for daily average, daytime, nighttime, and day-evening-nighttime at 30 m × 30 m resolution for the island of Montreal, Canada. The propagation model was used to predict traffic noise surfaces using road traffic flow, 3D building information, and a digital elevation model. The traffic noise estimates were compared with ground-based sound-level measurements at 87 points to extract residuals between total environmental noise and traffic noise. Residuals at these points were fit to RF models with multiple environmental and geographic predictor variables (e.g., vegetation index, population density, brightness of nighttime lights, land use types, and distances to noise contour around the airport, bus stops, and road intersections). Using the sound-level measurements as baseline data, the prediction errors, i.e., mean error, mean absolute error, and root mean squared error of daily average noise levels estimated by our hybrid approach was -0.03 dB(A), 2.67 dB(A), and 3.36 dB(A). Combining deterministic and stochastic models can provide accurate total environmental noise estimates for large geographic areas where sound-level measurements are available.

Theoretical Comparison of the Effects of Different Traffic Conditions on Urban Road Environmental External Costs

External costs that are associated with air pollution, climate change linked to greenhouse gas emissions (GHG), and noise are among the most important environmental externalities that are generated by road transport, which have been well monetized. This paper theoretically investigates the effects of different traffic conditions on the environmental external costs of urban roads where traffic flow is more complicated than un-interrupted traffic flows. A Monte Carlo method is used to theoretically simulate traffic speed in different traffic conditions. Subsequently, the emitted carbon dioxide (CO2), nitrogen oxides (NOx), carbon monoxide (CO), particulate matter (PM), sulfur dioxide (SO2), and noise were estimated in each of the theoretically simulated traffic conditions. Finally, the environmental external costs in each traffic condition were calculated taking the EU average costs values into account. The results showed that, when compared to free-flow condition, the total air pollutant and GHG external costs (€2010) have been increased by 6%, 31%, 44%, 50%, and 93% in under-saturated flow, accelerated flow, decelerated flow, congestion, and over-saturated congestion, respectively. Furthermore, the total noise cost (€2010/year/person exposed), as compared to free-flow condition, has been decreased by 2%, 11%, 12%, 36%, and 69% in accelerated flow, under-saturated flow, congestion, over-saturated congestion, and decelerated flow, respectively.

Occupational Noise Exposure and Diabetes Risk

Introduction

Noise is one of the most common worldwide environmental pollutants, especially in occupational fields. As a stressor, it affects not only the ear but also the entire body. Its physiological and psychological impacts have been well established in many conditions such as cardiovascular diseases. However, there is a dearth of evidence regarding diabetes risk related to noises.

Aim

To evaluate the relationship between occupational exposure to noise and the risk of developing diabetes.

Methods

This is a cross-sectional analytical study enrolling two groups of 151 workers each. The first group (noise exposed group: EG) included the employees of a Tunisian power plant, who worked during the day shift and had a permanent position. The second group (unexposed to noise group: NEG) included workers assigned to two academic institutions, who were randomly selected in the Occupational Medicine Department of the Farhat Hached University Hospital in Sousse, during periodical fitness to work visits. Both populations (exposed and unexposed) were matched by age and gender. Data collection was based on a preestablished questionnaire, a physical examination, a biological assessment, and a sonometric study.

Results

The mean equivalent continuous sound level was 89 dB for the EG and 44.6 dB for the NEG. Diabetes was diagnosed in 24 workers from EG (15.9%) and 14 workers from NEG (9.3%), with no statistically significant difference (p=0.08). After multiple binary logistic regression, including variables of interest, noise did not appear to be associated with diabetes.

Conclusion

Our results did not reveal a higher risk of developing diabetes in workers exposed to noise. Further studies assessing both level and duration of noise exposure are needed before any definitive conclusion.