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.

Environmental noise is an important environmental exposure that can affect health. An association between transportation noise and breast cancer incidence has been suggested, although current evidence is limited. We investigated the pooled association between long-term exposure to transportation noise and breast cancer incidence.
Pooled data from eight Nordic cohorts provided a study population of 111,492 women. Road, railway, and aircraft noise were modelled at residential addresses. Breast cancer incidence (all, estrogen receptor (ER) positive, and ER negative) was derived from cancer registries. Hazard ratios (HR) were estimated using Cox Proportional Hazards Models, adjusting main models for sociodemographic and lifestyle variables together with long-term exposure to air pollution.
A total of 93,859 women were included in the analyses, of whom 5,875 developed breast cancer. The median (5th-95th percentile) 5-year residential road traffic noise was 54.8 (40.0-67.8) dB Lden, and among those exposed, the median railway noise was 51.0 (41.2-65.8) dB Lden. We observed a pooled HR for breast cancer (95 % confidence interval (CI)) of 1.03 (0.99-1.06) per 10 dB increase in 5-year mean exposure to road traffic noise, and 1.03 (95 % CI: 0.96-1.11) for railway noise, after adjustment for lifestyle and sociodemographic covariates. HRs remained unchanged in analyses with further adjustment for PM2.5 and attenuated when adjusted for NO2 (HRs from 1.02 to 1.01), in analyses using the same sample. For aircraft noise, no association was observed. The associations did not vary by ER status for any noise source. In analyses using <60 dB as a cutoff, we found HRs of 1.08 (0.99-1.18) for road traffic and 1.19 (0.95-1.49) for railway noise.
We found weak associations between road and railway noise and breast cancer risk. More high-quality prospective studies are needed, particularly among those exposed to railway and aircraft noise before conclusions regarding noise as a risk factor for breast cancer can be made.

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.
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.
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.
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 combined health impact of concurrent railway noise and railway vibration exposure is not yet well understood.
This systematic review gives an overview of epidemiological studies on health effects from railway vibration, aiming to quantify this association with exposure-effect curves. Moreover, the combined health effects of vibration and concurrent noise were investigated.
We converted the vibration metric to an equivalent noise level and calculated an overall noise level by energetically summing the equivalent and railway noise level. The combined health effect was determined by using published evidence-based exposure-effect formulas.
Studies included in this systematic review predominately investigated annoyance and self-reported sleep disturbances; no studies on manifest diseases were identified. For the combined effects of vibration and noise on \"total\" annoyance, the results based on the pooled analysis of CargoVibes project are recommended as conservative approach.
Converting railway vibration into equivalent noise levels in dB may offer a pragmatic approach to assess the combined health effects of railway noise and railway vibration exposure. Future studies should include cardiovascular and mental diseases in addition to vibration-induced annoyance and sleep disturbances. Furthermore, future studies should include in-depth investigations of the interaction between railway noise and railway vibration to allow for a more accurate assessment of the railway-induced burden of disease.

BACKGROUND: Environmental noise is of increasing concern for public health. Quantification of associated health impacts is important for regulation and preventive strategies.
OBJECTIVE: To estimate the burden of disease (BoD) due to road traffic and railway noise in four Nordic countries and their capitals, in terms of DALYs (Disability-Adjusted Life Years), using comparable input data across countries.
METHODS: Road traffic and railway noise exposure was obtained from the noise mapping conducted according to the Environmental Noise Directive (END) as well as nationwide noise exposure assessments for Denmark and Norway. Noise annoyance, sleep disturbance and ischaemic heart disease were included as the main health outcomes, using exposure-response functions from the WHO, 2018 systematic reviews. Additional analyses included stroke and type 2 diabetes. Country-specific DALY rates from the Global Burden of Disease (GBD) study were used as health input data.
RESULTS: Comparable exposure data were not available on a national level for the Nordic countries, only for capital cities. The DALY rates for the capitals ranged from 329 to 485 DALYs/100,000 for road traffic noise and 44 to 146 DALY/100,000 for railway noise. Moreover, the DALY estimates for road traffic noise increased with up to 17% upon inclusion of stroke and diabetes. DALY estimates based on nationwide noise data were 51 and 133% higher than the END-based estimates, for Norway and Denmark, respectively.
CONCLUSIONS: Further harmonization of noise exposure data is required for between-country comparisons. Moreover, nationwide noise models indicate that DALY estimates based on END considerably underestimate national BoD due to transportation noise. The health-related burden of traffic noise was comparable to that of air pollution, an established risk factor for disease in the GBD framework. Inclusion of environmental noise as a risk factor in the GBD is strongly encouraged.

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 (PM2.5 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.

Urban environment noise is a complex mixture of transportation, industrial, household, and recreational noise, which is identified as an emerging environmental threat. Present study monitors and evaluates a noise pollution hotspot: a railway level crossing, where several activities related to transportation noise were involved. Train honking, train movement, road vehicles, and pedestrians contribute to the noise level at a railway level crossing. Train horns are generally performed as train approach railway level crossings and they are mandatorily used to alert road users. However, the train horns are regarded as nuisance to the nearby residents. A detailed evaluation of train horn effectiveness is very much essential in the current contemporary environment. Thus, the main objective of this study is to measure noise levels emanating from train horns at a level crossing with due consideration to train types and climatic conditions. A comprehensive noise monitoring survey was conducted at an access-controlled level crossing. Furthermore, an artificial neural network (ANN)-based railway noise prediction model was developed to forecast maximum ([Formula: see text]) and equivalent (Leq) noise levels. Results revealed that train horn produced impulsive sound signals which fall under high frequency one-third octave bands causing severe irritation to trackside inhabitants. The proposed ANN models produced accurate results for [Formula: see text] and Leq noise levels and this model is identified as a vital tool for railway noise abatement. The results from this study are helpful to the urban planning and development authorities to implement strategic laws and policies to eradicate the urban environment noise.

Background Colon cancer incidence is rising globally, and factors pertaining to urbanization have been proposed involved in this development. Traffic noise may increase colon cancer risk by causing sleep disturbance and stress, thereby inducing known colon cancer risk-factors, e.g. obesity, diabetes, physical inactivity, and alcohol consumption, but few studies have examined this. Objectives The objective of this study was to investigate the association between traffic noise and colon cancer (all, proximal, distal) in a pooled population of 11 Nordic cohorts, totaling 155,203 persons. Methods We identified residential address history and estimated road, railway, and aircraft noise, as well as air pollution, for all addresses, using similar exposure models across cohorts. Colon cancer cases were identified through national registries. We analyzed data using Cox Proportional Hazards Models, adjusting main models for harmonized sociodemographic and lifestyle data. Results During follow-up (median 18.8 years), 2757 colon cancer cases developed. We found a hazard ratio (HR) of 1.05 (95% confidence interval (CI): 0.99-1.10) per 10-dB higher 5-year mean time-weighted road traffic noise. In sub-type analyses, the association seemed confined to distal colon cancer: HR 1.06 (95% CI: 0.98-1.14). Railway and aircraft noise was not associated with colon cancer, albeit there was some indication in sub-type analyses that railway noise may also be associated with distal colon cancer. In interaction-analyses, the association between road traffic noise and colon cancer was strongest among obese persons and those with high NO2-exposure. Discussion A prominent study strength is the large population with harmonized data across eleven cohorts, and the complete address-history during follow-up. However, each cohort estimated noise independently, and only at the most exposed façade, which may introduce exposure misclassification. Despite this, the results of this pooled study suggest that traffic noise may be a risk factor for colon cancer, especially of distal origin.

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

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.
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 (PM2.5). 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.
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 PM2.5 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 PM2.5.
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.