Long-term exposure to traffic noise and mortality: A systematic review and meta-analysis of epidemiological evidence between 2000 and 2020

Disentangling associations between multiple environmental exposures and all-cause mortality: an analysis of European administrative and traditional cohorts

Background

We evaluated the independent and joint effects of air pollution, land/built environment characteristics, and ambient temperature on all-cause mortality as part of the EXPANSE project.

Methods

We collected data from six administrative cohorts covering Catalonia, Greece, the Netherlands, Rome, Sweden, and Switzerland and three traditional cohorts in Sweden, the Netherlands, and Germany. Participants were linked to spatial exposure estimates derived from hybrid land use regression models and satellite data for: air pollution [fine particulate matter (PM2.5), nitrogen dioxide (NO₂), black carbon (BC), warm season ozone (O3)], land/built environment [normalized difference vegetation index (NDVI), distance to water, impervious surfaces], and ambient temperature (the mean and standard deviation of warm and cool season temperature). We applied Cox proportional hazard models accounting for several cohort-specific individual and area-level variables. We evaluated the associations through single and multiexposure models, and interactions between exposures. The joint effects were estimated using the cumulative risk index (CRI). Cohort-specific hazard ratios (HR) were combined using random-effects meta-analyses.

Results

We observed over 3.1 million deaths out of approximately 204 million person-years. In administrative cohorts, increased exposure to PM2.5, NO2, and BC was significantly associated with all-cause mortality (pooled HRs: 1.054, 1.033, and 1.032, respectively). We observed an adverse effect of increased impervious surface and mean season-specific temperature, and a protective effect of increased O3, NDVI, distance to water, and temperature variation on all-cause mortality. The effects of PM2.5 were higher in areas with lower (10th percentile) compared to higher (90th percentile) NDVI levels [pooled HRs: 1.054 (95% confidence interval (CI) 1.030-1.079) vs. 1.038 (95% CI 0.964-1.118)]. A similar pattern was observed for NO2. The CRI of air pollutants (PM2.5 or NO2) plus NDVI and mean warm season temperature resulted in a stronger effect compared to single-exposure HRs: [PM2.5 pooled HR: 1.061 (95% CI 1.021-1.102); NO2 pooled HR: 1.041 (95% CI 1.025-1.057)]. Non-significant effects of similar patterns were observed in traditional cohorts.

Discussion

The findings of our study not only support the independent effects of long-term exposure to air pollution and greenness, but also highlight the increased effect when interplaying with other environmental exposures.

Geographic uncertainties in external exposome studies: A multi-scale approach to reduce exposure misclassification

BACKGROUND

Many studies on environment-health associations have emphasized that the selected buffer size (i.e., the scale of the geographic context when exposures are assigned at people's address location) may affect estimated effect sizes. However, there is limited methodological progress in addressing these buffer size-related uncertainties.

AIM

We aimed to 1) develop a statistical multi-scale approach to address buffer-related scale effects in cohort studies, and 2) investigate how environment-health associations differ between our multi-scale approach and ad hoc selected buffer sizes.

METHODS

We used lacunarity analyses to determine the largest meaningful buffer size for multiple high-resolution exposure surfaces (i.e., fine particulate matter [PM2.5], noise, and the normalized difference vegetation index [NDVI]). Exposures were linked to 7.7 million Dutch adults at their home addresses. We assigned exposure estimates based on buffers with fine-grained distance increments until the lacunarity-based upper limit was reached. Bayesian Cox model averaging addressed geographic uncertainties in the estimated exposure effect sizes within the exposure-specific upper buffer limits on mortality. Z-tests assessed statistical differences between averaged effect sizes and those obtained through pre-selected 100, 300, 1200, and 1500 m buffers.

RESULTS

The estimated lacunarity curves suggested exposure-specific upper buffer size limits; the largest was for NDVI (960 m), followed by noise (910 m) and PM2.5 (450 m). We recorded 845,229 deaths over eight years of follow-up. Our multi-scale approach indicated that higher values of NDVI were health-protectively associated with mortality risk (hazard ratio [HR]: 0.917, 95 % confidence interval [CI]: 0.886-0.948). Increased noise exposure was associated with an increased risk of mortality (HR: 1.003, 95 % CI: 1.002-1.003), while PM2.5 showed null associations (HR:0.998, 95 % CI: 0.997-1.000). Effect sizes of NDVI and noise differed significantly across the averaged and prespecified buffers (p < 0.05).

CONCLUSIONS

Geographic uncertainties in residential-based exposure assessments may obscure environment-health associations or risk spurious ones. Our multi-scale approach produced more consistent effect estimates and mitigated contextual uncertainties.

Modelling variations of emergency attendances using data on community mobility, climate and air pollution

Air pollution is associated with morbidity and mortality worldwide. We investigated the impact of improved air quality during the economic lockdown during the SARS-Cov2 pandemic on emergency room (ER) admissions in Germany. Weekly aggregated clinical data from 33 hospitals were collected in 2019 and 2020. Hourly concentrations of nitrogen and sulfur dioxide (NO2, SO2), carbon and nitrogen monoxide (CO, NO), ozone (O3) and particulate matter (PM10, PM2.5) measured by ground stations and meteorological data (ERA5) were selected from a 30 km radius around the corresponding ED. Mobility was assessed using aggregated cell phone data. A linear stepwise multiple regression model was used to predict ER admissions. The average weekly emergency numbers vary from 200 to over 1600 cases (total n = 2,216,217). The mean maximum decrease in caseload was 5 standard deviations. With the enforcement of the shutdown in March, the mobility index dropped by almost 40%. Of all air pollutants, NO2 has the strongest correlation with ER visits when averaged across all departments. Using a linear stepwise multiple regression model, 63% of the variation in ER visits is explained by the mobility index, but still 6% of the variation is explained by air quality and climate change.

The built environment and cardiovascular disease: an umbrella review and meta-meta-analysis

AIMS

To provide a comprehensive overview of the current evidence on objectively measured neighbourhood built environment exposures in relation to cardiovascular disease (CVD) events in adults.

METHODS AND RESULTS

We searched seven databases for systematic reviews on associations between objectively measured long-term built environmental exposures, covering at least one domain (i.e. outdoor air pollution, food environment, physical activity environment like greenspace and walkability, urbanization, light pollution, residential noise, and ambient temperature), and CVD events in adults. Two authors extracted summary data and assessed the risk of bias independently. Robustness of evidence was rated based on statistical heterogeneity, small-study effect, and excess significance bias. Meta-meta-analyses were conducted to combine the meta-analysis results from reviews with comparable exposure and outcome within each domain. From the 3304 initial hits, 51 systematic reviews were included, covering 5 domains and including 179 pooled estimates. There was strong evidence of the associations between increased air pollutants (especially PM2.5 exposure) and increased residential noise with greater risk of CVD. Highly suggestive evidence was found for an association between increased ambient temperature and greater risk of CVD. Systematic reviews on physical activity environment, food environment, light pollution, and urbanization in relation to CVD were scarce or lacking.

CONCLUSION

Air pollutants, increased noise levels, temperature, and greenspace were associated with CVD outcomes. Standardizing design and exposure assessments may foster the synthesis of evidence. Other crucial research gaps concern the lack of prospective study designs and lack of evidence from low-to-middle-income countries (LMICs).

REGISTRATION

PROSPERO: CRD42021246580.

The Long-Term Mortality Effects Associated with Exposure to Particles and NOx in the Malmö Diet and Cancer Cohort

In this study, the long-term mortality effects associated with exposure to PM10 (particles with an aerodynamic diameter smaller than or equal to 10 µm), PM2.5 (particles with an aerodynamic diameter smaller than or equal to 2.5 µm), BC (black carbon), and NOx (nitrogen oxides) were analyzed in a cohort in southern Sweden during the period from 1991 to 2016. Participants (those residing in Malmö, Sweden, born between 1923 and 1950) were randomly recruited from 1991 to 1996. At enrollment, 30,438 participants underwent a health screening, which consisted of questionnaires about lifestyle and diet, a clinical examination, and blood sampling. Mortality data were retrieved from the Swedish National Cause of Death Register. The modeled concentrations of PM10, PM2.5, BC, and NOx at the cohort participants' home addresses were used to assess air pollution exposure. Cox proportional hazard models were used to estimate the associations between long-term exposure to PM10, PM2.5, BC, and NOx and the time until death among the participants during the period from 1991 to 2016. The hazard ratios (HRs) associated with an interquartile range (IQR) increase in each air pollutant were calculated based on the exposure lag windows of the same year (lag0), 1-5 years (lag1-5), and 6-10 years (lag6-10). Three models were used with varying adjustments for possible confounders including both single-pollutant estimates and two-pollutant estimates. With adjustments for all covariates, the HRs for PM10, PM2.5, BC, and NOx in the single-pollutant models at lag1-5 were 1.06 (95% CI: 1.02-1.11), 1.01 (95% CI: 0.95-1.08), 1.07 (95% CI: 1.04-1.11), and 1.11 (95% CI: 1.07-1.16) per IQR increase, respectively. The HRs, in most cases, decreased with the inclusion of a larger number of covariates in the models. The most robust associations were shown for NOx, with statistically significant positive HRs in all the models. An overall conclusion is that road traffic-related pollutants had a significant association with mortality in the cohort.

Measuring environmental exposures in people's activity space: The need to account for travel modes and exposure decay

BACKGROUND

Accurately quantifying people's out-of-home environmental exposure is important for identifying disease risk factors. Several activity space-based exposure assessments exist, possibly leading to different exposure estimates, and have neither considered individual travel modes nor exposure-related distance decay effects.

OBJECTIVE

We aimed (1) to develop an activity space-based exposure assessment approach that included travel modes and exposure-related distance decay effects and (2) to compare the size of such spaces and the exposure estimates derived from them across typically used activity space operationalizations.

METHODS

We used 7-day-long global positioning system (GPS)-enabled smartphone-based tracking data of 269 Dutch adults. People's GPS trajectory points were classified into passive and active travel modes. Exposure-related distance decay effects were modeled through linear, exponential, and Gaussian decay functions. We performed cross-comparisons on these three functional decay models and an unweighted model in conjunction with four activity space models (i.e., home-based buffers, minimum convex polygons, two standard deviational ellipses, and time-weighted GPS-based buffers). We applied non-parametric Kruskal-Wallis tests, pair-wise Wilcoxon signed-rank tests, and Spearman correlations to assess mean differences in the extent of the activity spaces and correlations across exposures to particulate matter (PM2.5), noise, green space, and blue space.

RESULTS

Participants spent, on average, 42% of their daily life out-of-home. We observed that including travel modes into activity space delineation resulted in significantly more compact activity spaces. Exposure estimates for PM2.5 and blue space were significantly (p < 0.05) different between exposure estimates that did or did not account for travel modes, unlike noise and green space, for which differences did not reach significance. While the inclusion of distance decay effects significantly affected noise and green space exposure assessments, the decay functions applied appear not to have had any impact on the results. We found that residential exposure estimates appear appropriate for use as proxy values for the overall amount of PM2.5 exposure in people's daily lives, while GPS-based assessments are suitable for noise, green space, and blue space.

SIGNIFICANCE

For some exposures, the tested activity space definitions, although significantly correlated, exhibited differing exposure estimate results based on inclusion or exclusion of travel modes or distance decay effect. Results only supported using home-based buffer values as proxies for individuals' daily short-term PM2.5 exposure.

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.

Long-term exposure to residential transportation noise and mortality: A nationwide cohort study

Studies have indicated that transportation noise is associated with higher cardiovascular mortality, whereas evidence of noise as a risk factor for respiratory and cancer mortality is scarce and inconclusive. Also, knowledge on effects of low-level noise on mortality is very limited. We aimed to investigate associations between road and railway noise and natural-cause and cause-specific mortality in the Danish population. We estimated address-specific road and railway noise at the most (LdenMax) and least (LdenMin) exposed façades for all residential addresses in Denmark from 1990 to 2017 using high-quality exposure models. Using these data, we calculated 10-year time-weighted mean noise exposure for 2.6 million Danes aged >50 years, of whom 600,492 died from natural causes during a mean follow-up of 11.7 years. We analyzed data using Cox proportional hazards models with adjustment for individual and area-level sociodemographic variables and air pollution (PM_2.5 and NO₂). We found that a 10-year mean exposure to road LdenMax and road LdenMin per 10 dB were associated with hazard ratios (95% confidence intervals) of, respectively, 1.09 (1.09; 1.10) and 1.10 (1.10; 1.11) for natural-cause mortality, 1.09 (1.08; 1.10) and 1.09 (1.08; 1.10) for cardiovascular mortality, 1.13 (1.12; 1.14) and 1.17 (1.16; 1.19) for respiratory mortality and 1.03 (1.02; 1.03) and 1.06 (1.05; 1.07) for cancer mortality. For LdenMax, the associations followed linear exposure-response relationships from 35 dB to 60-<65 dB, after which the function levelled off. For LdenMin, exposure-response relationships were linear from 35 dB and up, with some levelling off at high noise levels for natural-cause and cardiovascular mortality. Railway noise did not seem associated with higher mortality in an exposure-response dependent manner. In conclusion, road traffic noise was associated with higher mortality and the increase in risk started well below the current World Health Organization guideline limit for road traffic noise of 53 dB.

Joint associations and pathways from greenspace, traffic-related air pollution, and noise to poor self-rated general health: A population-based study in Sofia, Bulgaria

BACKGROUND

Little is still known of how multiple urban exposures interact as health determinants. This study investigated various ways in which greenspace, traffic-related air pollution, and noise could operate together, influencing general health status.

METHODS

In 2022, a cross-sectional population-based survey was conducted in Sofia, Bulgaria. Included were 917 long-term adult residents who completed questionnaires on poor self-rated health (PSRH), total time spent in physical activity (PA), home garden presence, time spent in urban greenspace and nature, and sociodemographics. Residential greenspace was operationalized using the normalized difference vegetation index (NDVI), tree cover density, number of trees, and access to local greenspace and parks. Nitrogen dioxide (NO₂) was modeled for the study area. Road traffic, railway, and aircraft day-evening-night sound levels (L_den) were extracted from EU noise maps. Area-level income and urbanicity were considered. Analyses included multivariate ordinal regressions, interactions, and structural equation modeling (SEM).

RESULTS

Associations with PSRH were per 0.10 NDVI _300 m: OR = 0.65 (0.42-1.01), home garden: OR = 0.72 (0.49-1.07), per 5 μg/m³ NO₂: OR = 1.57 (1.00-2.48), per 5 dB(A) L_den road traffic: OR = 1.06 (0.91-1.23), railway: OR = 1.11 (1.03-1.20), and aircraft: OR = 1.22 (1.11-1.34). Spending >30 min/week in nature related to better health. In multi-exposure models, only associations with aircraft and railway L_den persisted. People with lower education and financial difficulties or living in poorer districts experienced some exposures stronger. In SEM, time spent in nature and PA mediated the effect of greenspace.

CONCLUSIONS

Greenspace was associated with better general health, with time spent in nature and PA emerging as intermediate pathways. NO₂, railway, and aircraft noise were associated with poorer general health. These results could inform decision-makers, urban planners, and civil society organizations facing urban development problems. Mitigation and abatement policies and measures should target socioeconomically disadvantaged citizens.

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.

Environmental noise-induced cardiovascular, metabolic and mental health disorders: a brief review

BACKGROUND

Environmental noise is a pervasive pollutant that is one of the greatest environmental threats to mental, physiological and psychological well-being and has a significant global health burden associated with it. Many epidemiological studies indicate long-term relationship of noise pollution with wide range of metabolic, cardio-vascular and respiratory disorders and diseases.

OBJECTIVE

The goal of this study was to thoroughly analyse available literature on public health implications and various underlying biological mechanisms associated with ambient noise exposure, taking into account both objective and subjective measures of noise exposure.

METHODS

A search of literature for review on environmental noise and associated cardiovascular, mental health and metabolic implications on human health was done using Web of Science, Google Scholar and PubMed databases.

DISCUSSION

Experimental studies indicate that noise exposure leads to endocrine effects, increased incidence of diabetes, impairment of cognitive performance, sleep disturbance and annoyance. Epidemiological evidence indicates that high levels of noise, particularly at night, may cause arterial hypertension and endothelial dysfunction due to higher level of stress hormones and oxidative stress. An increased incidence of cardio-vascular diseases like myocardial infarction, heart rate, ischemic heart disease, stroke and heart failure is associated with noise-induced mental stress. Furthermore, psychological and mental health issues like anxiety and depression are also related with exposure to noise pollution.

CONCLUSION

This article summarises a comprehensive and systematic knowledge established in recent noise research with the spotlight on cardiovascular, metabolic and mental health disorders of environmental noise, providing unique understanding into underlying mechanisms.

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.

Rural-urban gradients and all-cause, cardiovascular and cancer mortality in Spain using individual data

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The literature reporting on rural-urban health status disparities remains inconclusive.

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We analyzed data from a longitudinal population-based study using individual observations.

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Our results show that the risks of all-cause and cancer mortality are greater in large cities than in other municipalities, with no clear urban-rural gradient.

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Not differences were found among territories in cardiovascular mortality.

Investigating the association of environmental exposures and all-cause mortality in the UK Biobank using sparse principal component analysis

Multicollinearity refers to the presence of collinearity between multiple variables and renders the results of statistical inference erroneous (Type II error). This is particularly important in environmental health research where multicollinearity can hinder inference. To address this, correlated variables are often excluded from the analysis, limiting the discovery of new associations. An alternative approach to address this problem is the use of principal component analysis. This method, combines and projects a group of correlated variables onto a new orthogonal space. While this resolves the multicollinearity problem, it poses another challenge in relation to interpretability of results. Standard hypothesis testing methods can be used to evaluate the association of projected predictors, called principal components, with the outcomes of interest, however, there is no established way to trace the significance of principal components back to individual variables. To address this problem, we investigated the use of sparse principal component analysis which enforces a parsimonious projection. We hypothesise that this parsimony could facilitate the interpretability of findings. To this end, we investigated the association of 20 environmental predictors with all-cause mortality adjusting for demographic, socioeconomic, physiological, and behavioural factors. The study was conducted in a cohort of 379,690 individuals in the UK. During an average follow-up of 8.05 years (3,055,166 total person-years), 14,996 deaths were observed. We used Cox regression models to estimate the hazard ratio (HR) and 95% confidence intervals (CI). The Cox models were fitted to the standardised environmental predictors (a) without any transformation (b) transformed with PCA, and (c) transformed with SPCA. The comparison of findings underlined the potential of SPCA for conducting inference in scenarios where multicollinearity can increase the risk of Type II error. Our analysis unravelled a significant association between average noise pollution and increased risk of all-cause mortality. Specifically, those in the upper deciles of noise exposure have between 5 and 10% increased risk of all-cause mortality compared to the lowest decile.

Long-term exposure to road traffic noise and all-cause and cause-specific mortality: a Danish Nurse Cohort study

BACKGROUND

Long-term road traffic noise exposure is linked to cardio-metabolic disease morbidity, whereas evidence on mortality remains limited.

OBJECTIVES

We investigated association of long-term exposure to road traffic noise with all-cause and cause-specific mortality.

METHODS

We linked 22,858 females from the Danish Nurse Cohort (DNC), recruited into the Danish Register of Causes of Death up to 2014. Road traffic noise levels since 1970 were modelled by Nord2000 as the annual mean of a weighted 24 h average (L_den). Cox regression models examined the associations between L_den (5-year and 23-year means) and all-cause and cause-specific mortalities, adjusting for lifestyle and exposure to PM_2.5 (particulate matter with diameter < 2.5 μm) and NO₂ (nitrogen dioxide).

RESULTS

During follow-up (mean 17.4 years), 3902 nurses died: 1622 from cancer, 922 from CVDs (289 from stroke), 338 from respiratory diseases (186 from chronic obstructive pulmonary disease, 114 from lower respiratory tract infections [ALRIs]), 234 from dementia, 95 from psychiatric disorders, and 79 from diabetes. Hazard ratios (95% confidence intervals) for all-cause mortality from fully-adjusted models were 1.06 (1.01, 1.11) and 1.09 (1.03, 1.15) per 10 dB of 5-year and 23-year mean L_den, respectively, which attenuated slightly in our main model (fully-adjusted plus PM_2.5: 1.04 [1.00, 1.10]; 1.08 [1.02, 1.13]). Main model estimates suggested the strongest associations between 5-year mean L_den and diabetes (1.14: 0.81, 1.61), ALRIs (1.13: 0.84, 1.54), dementia (1.12: 0.90, 1.38), and stroke (1.10: 0.91, 1.31), whereas associations with 23-year mean L_den were suggested for respiratory diseases (1.15: 0.95, 1.39), psychiatric disorders (1.11: 0.78, 1.59), and all cancers (1.08: 0.99, 1.17).

DISCUSSION

Among the female nurses from the DNC, we observed that long-term exposure to road traffic noise led to premature mortality, independently of air pollution, and its adverse effects may extend well beyond those on the cardio-metabolic system to include respiratory diseases, cancer, neurodegenerative and psychiatric disorders.

Impact of road traffic noise on annoyance and preventable mortality in European cities: A health impact assessment

BACKGROUND

Road traffic is the main source of environmental noise in European cities and one of the main environmental risks to health and wellbeing. In this study we aimed to provide an in-depth assessment of available road traffic noise data and to estimate population exposure and health impacts for cities in Europe.

METHODS

We conducted the analysis for 724 cities and 25 greater cities in 25 European countries. We retrieved road traffic strategic noise maps delivered under the Environmental Noise Directive (END) or available from local sources. We assessed noise exposure using the 24 h day-evening-night noise level indicator (L_den) starting at exposure levels of 55 dB L_den - based on data availability - for the adult population aged 20 and over (n = 123,966,346). For the adults exposed to noise levels above 55 dB L_den we estimated the health impacts of compliance with the World Health Organization (WHO) recommendation of 53 dB L_den. Two primary health outcomes were assessed: high noise annoyance and Ischemic Heart Disease (IHD), using mortality from IHD causes as indicator. Exposure Response Functions (ERFs) relating road traffic noise exposure to annoyance and IHD mortality were retrieved from the literature. Uncertainties in input parameters were propagated using Monte Carlo simulations to obtain point estimates and empirical 95% Confidence Intervals (CIs). Lastly, the noise maps were categorized as high, moderate and low quality following a qualitative approach.

RESULTS

Strategic noise map data was delivered in three distinct formats (i.e. raster, polygon or polyline) and had distinct noise ranges and levels of categorization. The majority of noise maps (i.e. 83.2%) were considered of moderate or low quality. Based on the data provided, almost 60 million adults were exposed to road traffic noise levels above 55 dB L_den, equating to a median of 42% (Interquartile Range (IQR): 31.8-64.8) of the adult population across the analysed cities. We estimated that approximately 11 million adults were highly annoyed by road traffic noise and that 3608 deaths from IHD (95% CI: 843-6266) could be prevented annually with compliance of the WHO recommendation. The proportion of highly annoyed adults by city had a median value of 7.6% (IQR: 5.6-11.8) across the analysed cities, while the number preventable deaths had a median of 2.2 deaths per 100,000 population (IQR: 1.4-3.1).

CONCLUSIONS

Based on the provided strategic noise maps a considerable number of adults in European cities are exposed to road traffic noise levels harmful for health. Efforts to standardize the strategic noise maps and to increase noise and disease data availability at the city level are needed. These would allow for a more accurate and comprehensive assessment of the health impacts and further help local governments to address the adverse health effects of road traffic noise.

Environmental Influences on Sleep in the California Teachers Study Cohort

Only two-thirds of Americans meet the recommended 7 hours of sleep nightly. Insufficient sleep and circadian disruption have been associated with adverse health outcomes, including diabetes and cardiovascular disease. Several environmental disruptors of sleep have been reported, such as artificial light at night (ALAN) and noise. These studies tended to evaluate exposures individually. We evaluated several spatially derived environmental exposures (ALAN, noise, green space, and air pollution) and self-reported sleep outcomes obtained in 2012-2015 in a large cohort of 51,562 women in the California Teachers Study. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated for sleep duration and latency. After adjusting for age, race/ethnicity, chronotype, use of sleep medication, and self-reported trouble sleeping, ALAN (per 5 millicandela (mcd)/m2 luminance, OR = 1.13, 95% CI: 1.07, 1.20) and air pollution (per 5 μg/m3 PM2.5, OR = 1.06, 95% CI: 1.04, 1.09) were associated with shorter sleep duration (<7 hours), and noise was associated with longer latency (>15 minutes) (per 10 decibels, OR = 1.05, 95% CI: 1.01, 1.10). Green space was associated with increased duration (per 0.1 units, OR = 0.41, 95% CI: 0.28, 0.60) and decreased latency (per 0.1 units, OR = 0.55, 95% CI: 0.39, 0.78). Further research is necessary to understand how these and other exposures (e.g., diet) perturb an individuals' inherited sleep patterns and contribute to downstream health outcomes.

Environmental risk factors and cardiovascular diseases: a comprehensive review

Noncommunicable diseases (NCDs) are fatal for more than 38 million people each year and are thus the main contributors to the global burden of disease accounting for 70% of mortality. The majority of these deaths are caused by cardiovascular disease. The risk of NCDs is strongly associated with exposure to environmental stressors such as pollutants in the air, noise exposure, artificial light at night and climate change, including heat extremes, desert storms and wildfires. In addition to the traditional risk factors for cardiovascular disease such as diabetes, arterial hypertension, smoking, hypercholesterolemia and genetic predisposition, there is a growing body of evidence showing that physicochemical factors in the environment contribute significantly to the high NCD numbers. Furthermore, urbanization is associated with accumulation and intensification of these stressors. This comprehensive expert review will summarize the epidemiology and pathophysiology of environmental stressors with a focus on cardiovascular NCDs. We will also discuss solutions and mitigation measures to lower the impact of environmental risk factors with focus on cardiovascular disease.

The influence of a signal's time structure on the perceived noise annoyance of road traffic noise

PURPOSE

Road traffic noise is the most common source of noise in modern cities. The noise indicators used to manage noise do not take into account its temporal structure. However, in cities the traffic flow varies during the day, peaking due to congestion and more fluent periods. In this research we sought to analyze how people (giving answers on a numerical ICBEN scale) perceive noise stimuli with the same L_AeqT values but different time structures (more/less noise events, different amplitude envelopes).

METHODS

31 people with normal hearing took part in an experiment conducted in an anechoic chamber. Participants listened to 18 different noise recordings and rated each of them using the numerical ICBEN scale regarding noise annoyance.

RESULTS

The results showed that only sound level was a statistically significant factor. However, based on people's remarks about noise, we can also say that the more intermittent the noise is, the more negative feelings it evokes in people.

CONCLUSIONS

Time structure does not have a significant influence on people's judgments about noise annoyance. However, people tend to have a preference for a steady noise rather than an intermittent one.

An ecological study of the relationship between urban built environment and cardiovascular hospital admissions (2004-2016) in an Asian developing country

This study aims to evaluate the relationship between urban built environment and hospital admissions from cardiovascular diseases in Kuala Lumpur, Malaysia. Hospital admission data from 2004 to 2016 for cardiovascular diseases were used with patient residential postcodes as the unit of analysis. Data was split into 2004-2009 (12,551 cases) and 2010-2016 (17,154 cases) periods corresponding to land use data. We used generalized linear mixed model to analyse population density, property value, entropy index, and the kernel density (800 m) of specific land use, bus and rail stations, and road junctions, with time period and postcodes as the random effects to generate incidence rate ratios (IRRs). Results indicated that entropy index and recreational area density were associated with fewer hypertensive disease and ischemic heart disease hospital admissions (IRR range: 0.49-0.68, 95%CI: 0.27, 0.97). Population density and property value were associated with fewer cerebrovascular disease hospital admissions (IRR range: 0.29-0.34, 95%CI: 0.11, 0.75). Contrarily, density of road junctions was associated with 2.5-6.3 times more hospital admissions for cardiovascular disease hospital admissions (IRR range: 2.53-6.34, 95%CI: 1.07,17.91). There were no significant association between hospital admission and density of residential area, undeveloped land, rail and bus stations. The shapes of relationships for all attributes were non-linear, and changed markedly at the third quartile except for recreational area density. The findings suggest that land use attributes have some protective effects on the cardiovascular disease admission cases as compared to the transport attributes. These findings have important merits for integrating health into urban planning.