Insights of infected Schwann cells extinction and inherited randomness in a stochastic model of leprosy.

Investigating disease progression, transmission of infection and impacts of Multidrug Therapy (MDT) to inhibit demyelination in leprosy involves a certain amount of difficulty in terms of the in-built uncertain complicated and complex intracellular cell dynamical interactions. To tackle this scenario and to elucidate a more realistic, rationalistic approach of examining the infection mechanism and associated drug therapeutic interventions, we propose a four-dimensional ordinary differential equation-based model. Stochastic processes has been employed on this deterministic system by formulating the Kolmogorov forward equation introducing a transition state and the quasi-stationary distribution, exact distribution analysis have been investigated which allow us to estimate an expected time to extinction of the infected Schwann cells into the human body more prominently. Additionally, to explore the impact of uncertainty in the key intracellular factors, the stochastic system is investigated incorporating random perturbations and environmental noises in the disease dissemination, proliferation and reinfection rates. Rigorous numerical simulations validating the analytical outcomes provide us significant novel insights on the progression of leprosy and unravelling the existing major treatment complexities. Analytical experiments along with the simulations utilizing Monte-Carlo method and Euler-Maruyama scheme involving stochasticity predicts that the bacterial density is underestimated due to the recurrence of infection and suggests that maintaining a drug-efficacy rate in the range 0.6-0.8 would be substantially efficacious in eradicating leprosy.

Features for Evaluating Source Localization Effectiveness in Sound Maps from Acoustic Cameras.

Acoustic cameras (ACs) have become very popular in the last decade as an increasing number of applications in environmental acoustics are observed, which are mainly used to display the points of greatest noise emission of one or more sound sources. The results obtained are not yet certifiable because the beamforming algorithms or hardware behave differently under different measurement conditions, but at present, not enough studies have been dedicated to clarify the issues. The present study aims to provide a methodology to extract analytical features from sound maps obtained with ACs, which are generally only visual information. Based on the inputs obtained through a specific measurement campaign carried out with an AC and a known sound source in free field conditions, the present work elaborated a methodology for gathering the coordinates of the maximum emission point on screen, its distance from the real position of the source and the uncertainty associated with this position. The results obtained with the proposed method can be compared, thus acting as a basis for future comparison studies among calculations made with different beamforming algorithms or data gathered with different ACs in all real case scenarios. The method can be applicable to any other sector interested in gathering data from intensity maps not related to sound.

Depressive symptoms of people living in areas with high exposure to environmental noise: a multilevel analysis.

Exposure and damage caused by noise have been reported in many countries around the world. However, few nationwide studies explored the association of residential environmental noise with depressive symptoms, this study aims to examine this association. The Korean Community Health Survey at the individual-level and the Korean Environmental Noise Measurement Database at the regional-level were used. A total of 30,630 individuals were eligible for the analysis. Multilevel model framework was applied to account for the clustered structure of the regional-level data in which individual-level data containing demographic characteristics and health information were nested. As a result of the analysis, Individuals living in the highest environmental noise area had a 1.55 times higher likelihood of experiencing depressive symptoms than those living in the lowest environmental noise area (95% CI, 1.04-2.31). After stratified analysis according to depressive symptom severity, individuals residing in areas with the highest environmental noise exposure had significantly higher odds of mild (aOR, 1.46; 95% CI, 1.02-2.07) and moderate symptoms (aOR, 1.70; 95% CI, 1.00-2.91). In conclusion, the higher the residential environmental noise, the higher the possibility of mild-to-moderate depressive symptoms. Our findings suggest the need for continued attention to and management of noise pollution, which has the potential to adversely affect individual's mental health.

Geospatial analysis for environmental noise mapping: A land use regression approach in a metropolitan city.

Environmental noise can lead to adverse health outcomes. Understanding the spatial variability of environmental noise is crucial for mitigating potential health risks and developing influential urban strategies for reducing noise levels. This study aimed to measure noise levels and develop a land use regression (LUR) model to determine the spatial variability of environmental noise in Shiraz, Iran. A grid-based technique was used to establish 191 noise measurement sites (summer) across the city to generate the LUR model based on two noise metrics: Lden and Lnight. Leave-one-out cross-validation (LOOCV) and 38 additional measurement sites (winter) were used for the LUR model assessment. The mean values of Lden and Lnight during summer were 68.20 (±8.05) and 58.95 (±9.55), respectively, while during winter, the corresponding values were 69.46 (±5.46) and 58.81 (±6.79). The LUR models explained 67% and 65% of the spatial variability in Lden and Lnight, respectively. LOOCV analysis demonstrated R2 values of 0.64 and 0.61. Moreover, findings indicated mean absolute error (MAE) values of 3.96 dB(A) for Lden and 4.74 dB(A) for Lnight. Validation based on an additional set of 38 measurement sites revealed R2 values of 0.62 for both Lden and Lnight, with MAE of 2.78 and 3.31, respectively. In addition, the adjusted R2 values were 0.54 and 0.53. The results indicated no significant temporal variations between summer and winter. The results revealed that road-related variables significantly influenced noise levels. Moreover, the results indicated that Lden and Lnight levels were higher than the World Health Organization recommendations for exposure to road traffic noise. The results of our study showed that the LUR modeling approach based on geographical predictors is an effective tool for assessing changes in ambient noise levels in other cities in Iran and around the globe.

The Stability of Competitive Metacommunities Is Insensitive to Dispersal Connectivity in a Fluctuating Environment.

AbstractMaintaining the stability of ecological communities is critical for conservation, yet we lack a clear understanding of what attributes of metacommunity structure control stability. Some theories suggest that greater dispersal promotes metacommunity stability by stabilizing local populations, while others suggest that dispersal synchronizes fluctuations across patches and leads to global instability. These effects of dispersal on stability may be mediated by metacommunity structure: the number of patches, the pattern of connections across patches, and levels of spatiotemporal correlation in the environment. Thus, we need theory to investigate metacommunity dynamics under different spatial structures and ecological scenarios. Here, we use simulations to investigate whether stability is primarily affected by connectivity, including dispersal rate and topology of connectivity network, or by mechanisms related to the number of patches. We find that in competitive metacommunities with environmental stochasticity, network topology has little effect on stability on the metacommunity scale even while it could change spatial diversity patterns. In contrast, the number of connected patches is the dominant factor promoting stability through averaging stochastic fluctuations across more patches, rather than due to more habitat heterogeneity per se. These results broaden our understanding of how metacommunity structure changes metacommunity stability, which is relevant for designing effective conservation strategies.

Population health implications of exposure to pervasive military aircraft noise pollution.

BACKGROUND: While the adverse health effects of civil aircraft noise are relatively well studied, impacts associated with more intense and intermittent noise from military aviation have been rarely assessed. In recent years, increased training at Naval Air Station Whidbey Island, USA has raised concerns regarding the public health and well-being implications of noise from military aviation. OBJECTIVE: This study assessed the public health risks of military aircraft noise by developing a systematic workflow that uses acoustic and aircraft operations data to map noise exposure and predict health outcomes at the population scale. METHODS: Acoustic data encompassing seven years of monitoring efforts were integrated with flight operations data for 2020-2021 and a Department of Defense noise simulation model to characterize the noise regime. The model produced contours for day-night, nighttime, and 24-h average levels, which were validated by field monitoring and mapped to yield the estimated noise burden. Established thresholds and exposure-response relationships were used to predict the population subject to potential noise-related health effects, including annoyance, sleep disturbance, hearing impairment, and delays in childhood learning. RESULTS: Over 74,000 people within the area of aircraft noise exposure were at risk of adverse health effects. Of those exposed, substantial numbers were estimated to be highly annoyed and highly sleep disturbed, and several schools were exposed to levels that place them at risk of delay in childhood learning. Noise in some areas exceeded thresholds established by federal regulations for public health, residential land use and noise mitigation action, as well as the ranges of established exposure-response relationships. IMPACT STATEMENT: This study quantified the extensive spatial scale and population health burden of noise from military aviation. We employed a novel GIS-based workflow for relating mapped distributions of aircraft noise exposure to a suite of public health outcomes by integrating acoustic monitoring and simulation data with a dasymetric population density map. This approach enables the evaluation of population health impacts due to past, current, and future proposed military operations. Moreover, it can be modified for application to other environmental noise sources and offers an improved open-source tool to assess the population health implications of environmental noise exposure, inform at-risk communities, and guide efforts in noise mitigation and policy governing noise legislation, urban planning, and land use.

Micro-Electro-Mechanical Systems Microphones: A Brief Review Emphasizing Recent Advances in Audible Spectrum Applications.

The MEMS microphone is a representative device among the MEMS family, which has attracted substantial research interest, and those tailored for human voice have earned distinct success in commercialization. Although sustained development persists, challenges such as residual stress, environmental noise, and structural innovation are posed. To collect and summarize the recent advances in this subject, this paper presents a concise review concerning the transduction mechanism, diverse mechanical structure topologies, and effective methods of noise reduction for high-performance MEMS microphones with a dynamic range akin to the audible spectrum, aiming to provide a comprehensive and adequate analysis of this scope.

Blind Calibration of Environmental Acoustics Measurements Using Smartphones.

Environmental noise control is a major health and social issue. Numerous environmental policies require local authorities to draw up noise maps to establish an inventory of the noise environment and then propose action plans to improve its quality. In general, these maps are produced using numerical simulations, which may not be sufficiently representative, for example, concerning the temporal dynamics of noise levels. Acoustic sensor measurements are also insufficient in terms of spatial coverage. More recently, an alternative approach has been proposed, consisting of using citizens as data producers by using smartphones as tools of geo-localized acoustic measurement. However, a lack of calibration of smartphones can generate a significant bias in the results obtained. Against the classical metrological principle that would aim to calibrate any sensor beforehand for physical measurement, some have proposed mass calibration procedures called "blind calibration". The method is based on the crossing of sensors in the same area at the same time, which are therefore supposed to observe the same phenomenon (i.e., measure the same value). The multiple crossings of a large number of sensors at the scale of a territory and the analysis of the relationships between sensors allow for the calibration of the set of sensors. In this article, we propose to adapt a blind calibration method to data from the NoiseCapture smartphone application. The method's behavior is then tested on NoiseCapture datasets for which information on the calibration values of some smartphones is already available.

Urban noise assessment in hospitals: measurements and mapping in the context of the city of Sorocaba, Brazil.

Noise pollution has become a public health problem in several countries worldwide. Noise maps are tools used in many cities, mainly on the European continent. In other regions, they are used in smaller areas, and few studies focus on hospital areas, considered noise-sensitive zones. In this context, this study aimed to perform sound measurements and noise maps for the day and night periods in the surroundings of three hospitals in Sorocaba, Brazil. Sound measurements occurred around the three hospitals based on NBR 10151 and ISO 1996 standards. The noise maps were drawn up using a calculation model based on ISO 9613-2. Results showed that the sound measurement points around the hospitals had levels above those recommended by the Brazilian standard for sensitive areas (LAeq 50 and 45 dB for day and night, respectively). The acoustic maps showed high sound levels on all faces of the hospital buildings, both during the day and at night. The worst scenario concerned the vicinity of the roads with the highest flow and speed of vehicles. We concluded that three different hospitals in the city have high sound levels in their surroundings above the recommended for sensitive areas.

The relationship between exposure to environmental noise and risk of atopic dermatitis, asthma, and allergic rhinitis.

BACKGROUND: Noise is defined as unwanted sound. It may induce negative emotions and mental health problems and may even lead to increased suicide risk. However, the impact of noise exposure on environmental diseases and disease severity is not well understood. This study aimed to elucidate the association between night-time noise exposure and the prevalence of environmental diseases in South Korea. METHODS: We conducted an analysis of the Environmental Disease Database provide by the National Health Insurance Service (NHIS) from 2013 to 2017. After spatially interpolating the noise data provided by the National Noise Information System (NNIS), night-time noise values in the district level were obtained by calculating the mean noise values at the administrative district level. The linear regression analyses were performed to test the association between the age-standardized prevalence ratio (SPR) and the night-time noise exposure in the district level. RESULTS: In areas with high night-time noise exposure (≥55 dB), the SPR for atopic dermatitis and allergic rhinitis were 1.0515 (95 % confidence interval [CI]:1.0508-1.0521) and 1.0202 (95 % CI:1.0201-1.0204), respectively, which were higher than those in the general population. The SPR for environmental diseases, including atopic dermatitis, asthma, and allergic rhinitis, was 1.0104 (95 % CI:1.0103-1.0105). Additionally, a significant linear association was observed between the level of nocturnal noise exposure and the total hospitalization period for atopic dermatitis (ß = 399.3, p < 0.01). CONCLUSION: We provide evidence of a significant association between night-time environmental noise and environmental diseases, particularly atopic dermatitis and allergic rhinitis. Furthermore, we observed a significant linear association between night-time noise exposure and the severity of atopic dermatitis.

Decision trees and labeling of low noise pavements as support for noise action plans.

Low noise pavements (LNPs) are a market driven trend to mitigate the high road traffic noise exposure levels. Their improvement towards acoustic efficiency and durability over time is a challenge since these factors can conflict with road primary functions, such as safety. LNPs are not always the most cost-effective solution in health effects prevention. Whilst Green Public Procurement (GPP) highlighted the importance of reducing rolling noise emissions by introducing new regulations for new-layed LNPs, the fixed minimum requirements are not exhaustive. Generally, limits are set following the Close ProXimity method, which is only source oriented. This method does not consider real traffic flows and it is not aimed at evaluating citizens' disturbance. This work presents strategy tools that could assist policymakers in choosing LNPs, when truly effective, over other mitigations. The approach includes a variety of indicators that would allow for comparing different facets of noise assessment. The proposed methodology does not require additional efforts from stakeholders because the measurements required for the estimation of the indicators must already be carried out for both verification of legal limits and GPP. The strategy tools are a decisional tree to support the evaluation of the applicability of a LNP before its approval, and an evaluation flowchart applicable after its laying to evaluate its efficiency. Finally, a first LNP labeling approach, based on the same set of indicators, is proposed. As a case study, these tools are applied to measurements performed before and after the laying of twelve LNPs part of the LIFE NEREiDE project.

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.

Associations between the urban environment and psychotic experiences in adolescents.

OBJECTIVE: In 2050 two-thirds of the world's population is predicted to live in cities, which asks for a better understanding of how the urban environment affects mental health. Urbanicity has repeatedly been found to be a risk factor, in particular for psychosis. Here, we explored what factors of the urban exposome underlie the association between urban characteristics and psychotic experiences (PE) in adolescents. METHODS: Participants were 815 adolescents (mean age 14.84 years, SD 0.78) from an at-risk cohort (greater Rotterdam area, the Netherlands) oversampled on their self-reported emotional and behavioral problems. We used linear regression analysis to examine the association with detailed geodata on urbanicity (surrounding address density), green space density (high and low vegetation), and mixed noise levels (road, rail, air, industry, and wind power) with PE in adolescents. Analyses were adjusted for multiple socio-economic and parental confounders. Furthermore, we explored sex-interaction effects. RESULTS: Higher surrounding address density and low greenspace density were each independently associated with more PE (B = 0.18, 95 % CI 0.02; 0.34 and B = 0.17, 95 % CI 0.01; 0.32, respectively). High mixed noise levels were only associated with more PE in boys (B = 0.23, 95 % CI 0.01; 0.46). A sex-interaction effect was found for high urbanicity (B = -0.46, 95 % CI -0.77; -0.14) and low greenspace density (B = -0.49, 95 % CI -0.73; -0.11), illustrating that these associations with PE were specific for boys. CONCLUSION: Multiple characteristics of living in an urban area are associated with more PE in adolescent boys. Our observations provide leads for prevention of mental health problems via urban designing.

Impact of environmental noise exposure as an inducing factor on the prognosis of sudden sensorineural hearing loss: a retrospective case-control study.

Objective: The study aimed to evaluate the clinical characteristics and prognostic factors associated with unilateral sudden sensorineural hearing loss (SSNHL) related to environmental noise exposure before its onset. Methods: A total of 50 unilateral SSNHL patients exposed to environmental noise before onset (case group) and 924 unilateral SSNHL patients without any exposure to obvious inducing factors before onset (control group) were enrolled between January 2018 and October 2022. We retrospectively analyzed differences between both groups using the chi-square test, Fisher's exact tests, independent t-tests, and Mann-Whitney U-tests as appropriate before and after propensity score matching (PSM) based on sex, age, and initial pure-tone average (PTA). Prognostic factors for the case group were analyzed using univariate and multivariate logistic analyses between the effective and ineffective groups. Results: Before PSM, significant differences were noted in age, sex, time to treatment, the proportion of combined diabetes mellitus, initial PTA, hearing gain, the incidence of vertigo or aural fulness, the rate of vestibular dysfunction or inner ear MRI abnormalities, the effective rate, the glucose and homocysteine levels, and the proportion of audiogram curve types (P < 0.05) between both groups. After PSM, compared to the control group, a longer time to treatment (Z= -3.02, P < 0.05), higher final PTA (Z= -2.39, P < 0.05), lower hearing gain (Z= -3.46, P < 0.05), lower rate of vestibular dysfunction (χ2 = 55.1, P < 0.001), and lower effective rate (χ2 = 4.87, P < 0.05) were observed in the case group. There was a significant difference between the audiogram curve types in both groups (χ2 = 14.9, P < 0.05). Time to treatment (95% confidence interval: 0.692-0.965, P < 0.05) and final PTA (95% confidence interval: 0.921-0.998, P < 0.05) were associated with the clinical outcomes for the case group. Conclusion: Unilateral SSNHL patients exposed to environmental noise triggers before onset showed a poorer effective rate and a lower rate of vestibular dysfunction than those who were not. The time to treatment and final PTA were associated with the prognosis of these patients.

Advanced Noise Indicator Mapping Relying on a City Microphone Network.

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

Occupational and Environmental Noise Exposure and Extra-Auditory Effects on Humans: A Systematic Literature Review.

Noise is a common harmful factor in our work and the environment. Most studies have investigated the auditory effects of noise exposure; however, few studies have focused on the extra-auditory effects of exposure to occupational or environmental noise. This study aimed to systematically review published studies on the extra-auditory effects of noise exposure. We reviewed literature from PubMed and Google Scholar databases up to July 2022, using the Patient, Intervention, Comparison, and Outcome criteria and Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines to identify studies that reported extra-auditory effects of occupational or environmental noise exposure. Studies were evaluated utilizing validated reporting tools (CONSORT, STROBE) appropriate to study design. A total of 263 articles were identified, of which 36 were finally selected and reviewed. Upon conducting a review of the articles, exposure to noise can elicit a variety of extra-auditory effects on humans. These effects include circulatory effects linked to higher risk of cardiovascular disease and decreased endothelial function, nervous system effects correlated with sleep disturbance, cognitive impairment, and mental health problems, immunological and endocrinal effects connected to increased physiological stress response and metabolic disorders, oncological and respiratory effects associated with an elevated risk of acoustic neuroma and respiratory disorders, gastrointestinal effects linked to an increased risk of gastric or duodenal ulcer, and obstetric effects connected to the risk of preterm birth. Our review suggests that there are numerous extra-auditory effects of noise exposure on human, and further investigations are needed to fully understand these effects.

The Impact of Aircraft Noise on the Cognitive Function of Elementary School Students in Korea.

Background: This study evaluated the effects of chronic exposure to aircraft noise on the cognitive functions of Korean elementary school students attending an elementary school around a military airfield and clarified the relationship between noise exposure and cognitive functions. Methods: Five schools with average weight equivalent continuous perceived noise levels (WECPNL) of ≥75 dB were selected from four regions in Korea. Each of these schools was matched with a non-exposed school. The Korean Intelligence Test Primary (KIT-P) was used to measure the scores of four subcategories and the intelligence quotient (IQ). The noise exposure groups were divided into high-exposure (WECPNL ≥ 80 dB) and medium-exposure (75 ≤ WECPNL < 80) groups. The period of exposure during the school year was collected. A linear mixed model, with matched pairs of schools, was used for statistical analysis. Results: In the multivariable linear mixed model adjusted by possible confounders, the reasoning score was significantly lower in the high-exposure group of students than in the no-exposure group. Other scores and IQ were lower in the noise exposure groups, although these were not statistically significant. The duration of exposure did not show a significant relationship with cognitive functions. Conclusion: Chronic exposure to noise from military airfields may influence the cognitive functions, thereby reducing the learning performance of Korean children.

Investigating sonic injustice: A review of published research.

Sound has been researched as either an environmental pollutant (noise) with detrimental health effects or an environmental resource with beneficial outcomes for well-being. We define sonic injustice as unjust inequalities in both noise exposure and access to high-quality, beneficial sound environments. We performed a comparative analysis of 34 peer-reviewed studies on sonic injustice. These studies were from Europe, North America, Accra and Hong Kong. We found suggestive evidence of a social inequality in noise exposure, particularly for low income and racial/ethnic groups. In contrast, children were often associated with an underexposure to noise. We did not find any studies on inequalities in access to beneficial sound environments, except for one study on quiet areas. As well, this review identifies trends in European and North American studies; discusses causal mechanisms for sonic inequalities; and presents avenues for future investigations into sonic injustice.

Use of noise prediction models for road noise mapping in locations that do not have a standardized model: a short systematic review.

Faced with the accelerated growth of cities and the consequent increase in the number of motor vehicles, urban noise levels caused by vehicular traffic have increased considerably. To assess noise levels in cities and implement noise control measures or identify the problem's location in different urban areas, it is necessary to obtain the noise levels to which people are exposed. Noise maps are tools that have applications as they are cartographic representations of the noise level distribution in an area and over a period of time. This article aims to identify, select, evaluate, and synthesize information, through a systematic literature review, on using different road noise prediction models, in sound mapping computer programs in countries that do not have a standard noise prediction model. The analysis period was from 2018 to 2022. From a previous analysis of articles, the choice of topic was based on identifying various models for predicting road noise in countries without a standardized sound mapping model. The papers compiled by a systematic literature review showed that studies concentrated in China, Brazil, and Ecuador, the most used traffic noise prediction models, were the RLS-90 and the NMPB, and the most used mapping programs were SoundPLAN and ArcGIS with a grid size of 10 × 10 m. Most measurements were carried out during a 15-min period at a height from the ground level of 1.5 m. In addition, it was observed that research on noise maps in countries that do not have a local model has been increasing over time.

Associations between environmental noise and myocardial infarction and stroke: Investigating the potential mediating effects of hypertension.

BACKGROUND: We investigated whether hypertension may be a mediator in the pathway linking environmental noise exposure to incident MI and stroke. METHODS: Separately for MI and stroke, we built two population-based cohorts from linked health administrative data. Participants were residents of Montreal (Canada) between 2000 and 2014, aged 45 years and older who were free of hypertension and MI or stroke at time of entry. MI, stroke and hypertension were ascertained from validated case definitions. Residential long-term environmental noise exposure, expressed as the annual mean level acoustic equivalent 24 h (LAeq24h), was estimated from a land use regression model. We performed mediation analysis based on the potential outcomes framework. We used a Cox proportional hazards model for the exposure-outcome model and a logistic regression for the exposure-mediator model. In sensitivity analysis we applied a marginal structural approach to estimate the natural direct and indirect effects. RESULTS: Each cohort included approximately 900 000 individuals, with 26 647 incident cases of MI and 16 656 incident cases of stroke. 36% of incident MI and 40% of incident stokes had previously developed hypertension. The estimated total effect per interquartile range increase (from 55.0 to 60.5 dB A) in the annual mean LAeq24h was 1.073 (95% confidence interval (CI): 1.070-1.077) for both MI for stroke. We found no evidence of exposure-mediator interaction for both outcomes. The relationships between environmental noise and MI and stroke was not mediated by hypertension. CONCLUSIONS: This population-based cohort study suggests that the main route by which environmental noise exposure may cause MI or stroke is not through hypertension.