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.

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

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

Exposure to ambient air pollutants and the onset of dementia in Québec, Canada.

BACKGROUND: Effects of air pollutants are related to oxidative stress which is also linked to the pathogenesis of dementia including Alzheimer's and related diseases. OBJECTIVE: We assessed associations between exposure to air pollutants and the onset of dementia; the association with the distance between residence and major roads was also assessed for the island of Montreal. METHODS: We created an open cohort of adults aged 65 years and older starting in 2000 and ending in 2012 in the province of Québec, Canada using linked medico-administrative databases. New cases of dementia were defined based on a validated algorithm. Annual residential levels of nitrogen dioxide (NO2) and fine particles (PM2.5) at residential levels were estimated for each year of follow up using estimates based on satellite images and ground air monitoring data. Hazard ratios (HRs) were assessed with Extended (time dependent exposure) Cox models with age as the time axis and stratified for sex, for the annual exposure level at each residential address. Models were adjusted for the calendar year, area-wide social and material deprivation indexes and for NO2 or PM2.5; they were also indirectly adjusted for smoking. RESULTS: 1,807,133 persons (13,242,270 person-years) were followed and 199,826 developed dementia. From models (adjusted for calendar year, social and material deprivation indexes), HRs for an interquartile range (IQR) increase in time-varying exposure to NO2 (IQR 13.26 ppb), PM2.5 (IQR 3.90 µg/m³), and distance to major roads (IQR 150 m, in Montreal only), were 1.005 (CI 95% 0.994-1.017), 1.016 (CI 95% 1.003-1.028) and 0.969 (CI 95% 0.958-0.980), respectively. CONCLUSIONS: Results suggest that the onset of dementia may be related to residential exposure to PM2.5, NO2, and distance to major roads.

Environmental and health impacts of transportation and land use scenarios in 2061.

We compared numbers of trips and distances by transport mode, air pollution and health impacts of a Business As Usual (BAU) and an Ideal scenario with urban densification and reductions in car share (76%-62% in suburbs; 55%-34% in urban areas) for the Greater Montreal (Canada) for 2061. We estimated the population in 87 municipalities using a demographic model and population projections. Year 2031 (Y2031) trips (from mode choice modeling) and distances were used to estimate those of Y2061. Emissions of nitrogen dioxide (NO2) and carbon dioxide (CO2) were estimated and NO2 used with dispersion modeling to estimate concentrations. Walking and Public Transit (PT) use and corresponding distances walked in Y2061 were >70% higher for the Ideal scenario vs the BAU, while car share and distances were <40% lower. NO2 levels were slightly lower in the Ideal scenario vs the BAU, but always higher in the urban core. Health impacts, summarized with disability adjusted life years (DALY), differed between urban and suburb areas but globally, the Ideal scenario reduced the impacts of the Y2061 BAU by 33% DALY. Percentages of car and PT trips were similar for the Y2031 and Y2061 BAU but kms travelled by car, CO2 and NO2 increased, due to increased populations. Drastic measures to decrease car share appear necessary to substantially reduce impacts of transportation.

Capturing the spatial variability of noise levels based on a short-term monitoring campaign and comparing noise surfaces against personal exposures collected through a panel study.

Environmental noise can cause important cardiovascular effects, stress and sleep disturbance. The development of appropriate methods to estimate noise exposure within a single urban area remains a challenging task, due to the presence of various transportation noise sources (road, rail, and aircraft). In this study, we developed a land-use regression (LUR) approach using a Generalized Additive Model (GAM) for LAeq (equivalent noise level) to capture the spatial variability of noise levels in Toronto, Canada. Four different model formulations were proposed based on continuous 20-min noise measurements at 92 sites and a leave one out cross-validation (LOOCV). Models where coefficients for variables considered as noise sources were forced to be positive, led to the development of more realistic exposure surfaces. Three different measures were used to assess the models; adjusted R2 (0.44-0.64), deviance (51-72%) and Akaike information criterion (AIC) (469.2-434.6). When comparing exposures derived from the four approaches to personal exposures from a panel study, we observed that all approaches performed very similarly, with values for the Fractional mean bias (FB), normalized mean square error (NMSE), and normalized absolute difference (NAD) very close to 0. Finally, we compared the noise surfaces with data collected from a previous campaign consisting of 1-week measurements at 200 fixed sites in Toronto and observed that the strongest correlations occurred between our predictions and measured noise levels along major roads and highway collectors. Our validation against long-term measurements and panel data demonstrates that manual modifications brought to the models were able to reduce bias in model predictions and achieve a wider range of exposures, comparable with measurement data.

Estimating the health benefits of planned public transit investments in Montreal.

BACKGROUND: Since public transit infrastructure affects road traffic volumes and influences transportation mode choice, which in turn impacts health, it is important to estimate the alteration of the health burden linked with transit policies. OBJECTIVE: We quantified the variation in health benefits and burden between a business as usual (BAU) and a public transit (PT) scenarios in 2031 (with 8 and 19 new subway and train stations) for the greater Montreal region. METHOD: Using mode choice and traffic assignment models, we predicted the transportation mode choice and traffic assignment on the road network. Subsequently, we estimated the distance travelled in each municipality by mode, the minutes spent in active transportation, as well as traffic emissions. Thereafter we estimated the health burden attributed to air pollution and road traumas and the gains associated with active transportation for both the BAU and PT scenarios. RESULTS: We predicted a slight decrease of overall trips and kilometers travelled by car as well as an increase of active transportation for the PT in 2031 vs the BAU. Our analysis shows that new infrastructure will reduce the overall burden of transportation by 2.5 DALYs per 100,000 persons. This decrease is caused by the reduction of road traumas occurring in the inner suburbs and central Montreal region as well as gains in active transportation in the inner suburbs. CONCLUSION: Based on the results of our study, transportation planned public transit projects for Montreal are unlikely to reduce drastically the burden of disease attributable to road vehicles and infrastructures in the Montreal region. The impact of the planned transportation infrastructures seems to be very low and localized mainly in the areas where new public transit stations are planned.

Socioeconomic status and environmental noise exposure in Montreal, Canada.

BACKGROUND: This study's objective was to determine whether socioeconomically deprived populations are exposed to greater levels of environmental noise. METHODS: Indicators of socioeconomic status were correlated with LAeq24h noise levels estimated with a land-use regression model at a small geographic scale. RESULTS: We found that noise exposure was associated with all socioeconomic indicators, with the strongest correlations found for median household income, proportion of people who spend over 30% of their income on housing, proportion of people below the low income boundary and with a social deprivation index combining several socio-economic variables. CONCLUSION: Our results were inconsistent with a number of studies performed elsewhere, indicating that locally conducted studies are imperative to assessing whether this double burden of noise exposure and low socioeconomic status exists in other contexts. The primary implication of our study is that noise exposure represents an environmental injustice in Montreal, which is an issue that merits both investigation and concern.

Outdoor falls in an urban context: winter weather impacts and geographical variations.

OBJECTIVES: Environmental factors associated with winter outdoor falls are poorly understood. This study describes the demographic, spatial and temporal distribution of outdoor falls that occurred in Laval and Montréal Island (Canada) in relation to meteorological conditions. METHOD: Data on falls, including geographic coordinates, were obtained from ambulance services (December 1, 2008 to january 31, 2009). Meteorological (temperature, precipitation levels) and land use data were used for descriptive analysis and mapping. RESULTS: During the study period, 3270 falls required ambulance interventions, of which 960 occurred outdoors. Most people injured outdoors were under 65 years of age (59%). Mapping showed a concentration of outdoor falls in central neighbourhoods and on commercial streets in Montreal. Three episodes of excess falls, representing 47% of all outdoor falls, were preceded by rain and followed by falling temperatures, or were concomitant with freezing rain. CONCLUSION: Our results demonstrate for the first time the distribution of outdoor falls in a densely populated urban setting with a northern climate. To promote active transportation, it is essential to take into account the safety of pedestrian travel. Snow removal and de-icing operations in municipalities should prioritize areas with high pedestrian activity.

Risk of childhood asthma prevalence attributable to residential proximity to major roads in Montreal, Canada.

OBJECTIVES: Exposure to traffic-related air pollutants plays a role in several health outcomes. A large body of evidence tends to link asthma in children with traffic exposure. Increasing asthma prevalence and incidence in children in Canadian cities has been of concern for public health authorities. The following study focuses on estimating the risk of asthma prevalence attributable to residing in proximity to major roads on the Island of Montreal, Canada. METHODS: Risk functions pertaining to asthma in children and residential proximity to major roads were selected from the literature and applied to Montreal. Asthma prevalence was taken from population-based studies. Population data were retrieved from Canadian census. Exposure was estimated using the proximity to major road and highway category of the Desktop Mapping Technologies Inc. database (DMTI Spatial Inc.). RESULTS: Based on different studies, the percentage of prevalent asthma cases attributable to residing within 50 metres of a major road or highway for children aged 2, 4 and 6 years varied between 2.4% (0-4.3), 5.6% (0.1-8.6) and 5.9% (0.1-9.0). For the 5-7 year age group residing within 75 m of a major road or highway, the percent of cases was 6.4% (2.6-9.3). For children aged 8 to 10 residing within 75 m of a highway only, the percent of cases was 0.7% (0.2-0.9). CONCLUSION: These numbers represent the best crude estimates and are an indication of a possible range of cases linked to residential proximity to major roads. As there are uncertainties linked to the application of exposure-response functions, these estimates will be reassessed as new evidence is gathered through further research.

Relationships between long-term residential exposure to total environmental noise and stroke incidence.

Background: Noise has been related to several cardiovascular diseases (CVDs) such as coronary heart disease and to their risk factors such as hypertension, but associations with stroke remain under-researched, even if CVD likely share similar pathophysiologic mechanisms. Aim: The objective of the study was to examine the association between long-term residential exposure to total environmental noise and stroke incidence in Montreal, Canada. Materials and Methods: We created an open cohort of adults aged ≥45years, free of stroke before entering the cohort for the years 2000 to 2014 with health administrative data. Residential total environmental noise levels were estimated with land use regression (LUR) models. Incident stroke was based on hospital admissions. Cox hazard models with age as the time axis and time-varying exposures were used to estimate associations, which were adjusted for material deprivation, year, nitrogen dioxide, stratified for sex, and indirectly adjusted for smoking. Results: There were 9,072,492 person-years of follow-up with 47% men; 26,741 developed stroke (21,402 ischemic; 4947 hemorrhagic; 392 had both). LUR total noise level acoustic equivalent for 24 hours (LAeq24h) ranged 44 to 79 dBA. The adjusted hazard ratio (HR) for stroke (all types), for a 10-dBA increase in LAeq24h, was 1.06 [95% confidence interval (CI): 1.03-1.09]. The LAeq24h was associated with ischemic (HR per 10 dBA: 1.08; 95% CI: 1.04-1.12) but not hemorrhagic stroke (HR per 10 dBA: 0.97; 95% CI: 0.90-1.04). Conclusion: The results suggest that total environmental noise is associated with incident stroke, which is consistent with studies on transportation noise and other CVD.

Modelling the variation of land surface temperature as determinant of risk of heat-related health events.

BACKGROUND: The evaluation of exposure to ambient temperatures in epidemiological studies has generally been based on records from meteorological stations which may not adequately represent local temperature variability. Here we propose a spatially explicit model to estimate local exposure to temperatures of large populations under various meteorological conditions based on satellite and meteorological data. METHODS: A general linear model was used to estimate surface temperatures using 15 LANDSAT 5 and LANDSAT 7 images for Quebec Province, Canada between 1987 and 2002 and spanning the months of June to August. The images encompassed both rural and urban landscapes and predictors included: meteorological records of temperature and wind speed, distance to major water bodies, Normalized Differential Vegetation Index (NDVI), land cover (built and bare land, water, or vegetation), latitude, longitude, and week of the year. RESULTS: The model explained 77% of the variance in surface temperature, accounting for both temporal and spatial variations. The standard error of estimates was 1.42°C. Land cover and NDVI were strong predictors of surface temperature. CONCLUSIONS: This study suggests that a statistical approach to estimating surface temperature incorporating both spatially explicit satellite data and time-varying meteorological data may be relevant to assessing exposure to heat during the warm season in the Quebec. By allowing the estimation of space- and time-specific surface temperatures, this model may also be used to assess the possible impacts of land use changes under various meteorological conditions. It can be applied to assess heat exposure within a large population and at relatively fine-grained scale. It may be used to evaluate the acute health effect of heat exposure over long time frames. The method proposed here could be replicated in other areas around the globe for which satellite data and meteorological data is available.

Manuscript title: Long─term residential exposure to environmental/transportation noise and the incidence of myocardial infarction.

BACKGROUND: Cardiovascular effects of environmental noise are a growing concern. However, the evidence remains largely limited to the association between road traffic noise and hypertension and coronary heart diseases. OBJECTIVES: To investigate the association between long-term residential exposure to environmental/transportation noise and the incidence of myocardial infarction (MI) in the adult population living in Montreal. METHODS: An open cohort of adults aged 45 years old and over, living on the island of Montreal and free of MI before entering the cohort was created for the years 2000-2014 with the Quebec Integrated Chronic Disease Surveillance System; a systematic surveillance system from the Canadian province of Quebec starting in 1996. Residential noise exposure was calculated in three ways: 1) total ambient noise levels estimated by Land use regression (LUR) models; 2) road traffic noise estimated by a noise propagation model CadnaA and 3) distances to transportation sources (roads, airport, railways). Incident MI was based on diagnostic codes in hospital admission records. Cox models with time-varying exposures (age as the time axis) were used to estimate the associations with various adjustments (material deprivation indicator, calendar year, nitrogen dioxide, stratification for sex). Indirect adjustment based on ancillary data for smoking was performed. RESULTS: 1,065,414 individuals were followed (total of 9,000,443 person-years) and 40,718 (3.8%) developed MI. We found positive associations between total environmental noise, estimated by LUR models and the incidence of MI. Total noise LUR levels ranged from ~44 to ~79 dBA and varied slightly with the metric used. The adjusted hazard ratios (HRs) (also adjusted for smoking) were 1.12 (95% Confidence Intervals [CI]: 1.08-1.15), 1.11 (95%CI: 1.07-1.14) and 1.10 (95%CI: 1.06-1.14) per 10 dBA noise levels increase respectively in Level Accoustic equivalent 24 h (LAeq24 h), Level day-evening-night (Lden) and night level (Lnight). We found a borderline negative association between road noise levels estimated with CadnaA and MI (HR: 0.99 per 10 dBA; 95%CI: 0.98-1.00). Distances to major roads and highways were not associated with MI while the proximity to railways was positively associated with MI (HR for ≤100 vs > 1000 m: 1.07; 95%CI: 1.01-1.14). A negative association was found with the proximity to the airport noise exposure forecast (NEF25); HR (<1 vs >1000 m) = 0.88 (95%CI: 0.81-0.96). CONCLUSIONS: These associations suggest that exposure to total environmental noise at current urban levels may be related to the incidence of MI. Additional studies with more accurate road noise estimates are needed to explain the counterintuitive associations with road noise and specific transportation sources.

Home environmental factors associated with poor asthma control in Montreal children: a population-based study.

BACKGROUND: Home environmental exposures may aggravate asthma. Few population-based studies have investigated the relationship between asthma control in children and home environmental exposures. OBJECTIVE: Identify home environmental exposures associated with poor control of asthma among asthmatic children less than 12 years of age in Montreal (Quebec, Canada). METHODS: This cross-sectional population-based study used data from a respiratory health survey of Montreal children aged 6 months to 12 years conducted in 2006 (n = 7980). Asthma control was assessed (n = 980) using an adaptation of the Canadian asthma consensus report clinical parameters. Using log-binomial regression models, prevalence ratios (PRs) with 95% confidence intervals (95% CIs) were estimated to explore the relationship between inadequate control of asthma and environmental home exposures, including allergens, irritants, mold, and dampness indicators. Subjects with acceptable asthma control were compared with those with inadequate disease control. RESULTS: Of 980 children with active asthma in the year prior to the survey, 36% met at least one of the five criteria as to poor control of their disease. The population's characteristics found to be related with a lack of asthma control were younger age, history of parental atopy, low maternal education level, foreign-born mothers, and tenant occupancy. After adjustments, children living along high-traffic density streets (PR, 1.35; 95% CI, 1.00-1.81) and those with their bedroom or residence at the basement level (PR, 1.30; 95% CI, 1.01-1.66) were found to be at increased risk of poor asthma control. CONCLUSIONS: Suboptimal asthma control appears to be mostly associated with traffic, along with mold and moisture conditions, the latter being a more frequent exposure and therefore having a greater public health impact.

The Potential Impacts of Urban and Transit Planning Scenarios for 2031 on Car Use and Active Transportation in a Metropolitan Area.

Land use and transportation scenarios can help evaluate the potential impacts of urban compact or transit-oriented development (TOD). Future scenarios have been based on hypothetical developments or strategic planning but both have rarely been compared. We developed scenarios for an entire metropolitan area (Montreal, Canada) based on current strategic planning documents and contrasted their potential impacts on car use and active transportation with those of hypothetical scenarios. We collected and analyzed available urban planning documents and obtained key stakeholders' appreciation of transportation projects on their likelihood of implementation. We allocated 2006-2031 population growth according to recent trends (Business As Usual, BAU) or alternative scenarios (current planning; all in TOD areas; all in central zone). A large-scale and representative Origin-Destination Household Travel Survey was used to measure travel behavior. To estimate distances travelled by mode, in 2031, we used a mode choice model and a simpler method based on the 2008 modal share across population strata. Compared to the BAU, the scenario that allocated all the new population in already dense areas and that also included numerous public transit projects (unlikely to be implemented in 2031), was associated with greatest impacts. Nonetheless such major changes had relatively minor impacts, inducing at most a 15% reduction in distances travel by car and a 28% increase in distances walked, compared to a BAU. Strategies that directly target the reduction of car use, not considered in the scenarios assessed, may be necessary to induce substantial changes in a metropolitan area.

Comparison of land use regression and random forests models on estimating noise levels in five Canadian cities.

Chronic exposure to environment noise is associated with sleep disturbance and cardiovascular diseases. Assessment of population exposed to environmental noise is limited by a lack of routine noise sampling and is critical for controlling exposure and mitigating adverse health effects. Land use regression (LUR) model is newly applied in estimating environmental exposures to noise. Machine-learning approaches offer opportunities to improve the noise estimations from LUR model. In this study, we employed random forests (RF) model to estimate environmental noise levels in five Canadian cities and compared noise estimations between RF and LUR models. A total of 729 measurements and 33 built environment-related variables were used to estimate spatial variation in environmental noise at the global (multi-city) and local (individual city) scales. Leave one out cross-validation suggested that noise estimates derived from the RF global model explained a greater proportion of variation (R2: RF = 0.58, LUR = 0.47) with lower root mean squared errors (RF = 4.44 dB(A), LUR = 4.99 dB(A)). The cross-validation also indicated the RF models had better general performance than the LUR models at the city scale. By applying the global models to estimate noise levels at the postal code level, we found noise levels were higher in Montreal and Longueuil than in other major Canadian cities.

Socio-economic inequalities in exposure to industrial air pollution emissions in Quebec public schools.

OBJECTIVES: We aimed to assess the relationships between deprivation at Quebec public schools, their proximity to polluting industries, and their exposure to industrial air emission sources including ambient fine particulate matter (PM2.5), sulphur dioxide (SO2) and nitrogen dioxide (NO2). METHODS: We obtained four indicators of school deprivation using data from the 2006 Canadian census called the low-income threshold indicator, the neighbourhood SES indicator, and the social and material deprivation indicators of Pampalon. Using proximity spatial tools, we constructed three buffers of 2.5, 5 and 7.5 km around each school and summed up total emissions of PM2.5, SO2 and NO2 for each school. Industrial air emissions were estimated using data from the 2006 Canadian National Pollutant Release Inventory. The Pearson correlations and LOESS regressions and natural log-transformed industrial air emissions were evaluated for Quebec public schools within the three buffers. RESULTS: Of the 2189 public schools in Quebec, 608 (27.8%), 1108 (50.6%) and 1384 (63.2%) schools were located near at least one industry emitting one or more pollutants of interest in buffers of 2.5 km, 5 km and 7.5 km of schools respectively. Weak positive Pearson correlations (r) were found between log-transformed tons of industrial emissions of PM2.5, SO2 and NO2 and both the social deprivation (r = {0.23; 0.33}) and low-income threshold (r = {0.17; 0.29}) indicators in a buffer of 2.5 km. However, we found negative associations between emissions and the neighbourhood SES (r = {0.06; 0.16}) and material deprivation (r = {-0.04; 0.08}) indicators. CONCLUSION: Our study suggests that schools in Quebec with higher rates of socio-economic deprivation among their students may be more likely to be exposed to higher emissions of industrial air pollutants.

Statistical modeling of the spatial variability of environmental noise levels in Montreal, Canada, using noise measurements and land use characteristics.

The availability of noise maps to assess exposure to noise is often limited, especially in North American cities. We developed land use regression (LUR) models for LAeq24h, Lnight, and Lden to assess the long-term spatial variability of environmental noise levels in Montreal, Canada, considering various transportation noise sources (road, rail, and air). To explore the effects of sampling duration, we compared our LAeq24h levels that were computed over at least five complete contiguous days of measurements to shorter sampling periods (20 min and 24 h). LUR models were built with General Additive Models using continuous 2-min noise measurements from 204 sites. Model performance (adjusted R2) was 0.68, 0.59, and 0.69 for LAeq24h, Lnight, and Lden, respectively. Main predictors of measured noise levels were road-traffic and vegetation variables. Twenty-minute non-rush hour measurements corresponded well with LAeq24h levels computed over 5 days at road-traffic sites (bias: -0.7 dB(A)), but not at rail (-2.1 dB(A)) nor at air (-2.2 dB(A)) sites. Our study provides important insights into the spatial variation of environmental noise levels in a Canadian city. To assess long-term noise levels, sampling strategies should be stratified by noise sources and preferably should include 1 week of measurements at locations exposed to rail and aircraft noise.

Sleep Disturbance from Road Traffic, Railways, Airplanes and from Total Environmental Noise Levels in Montreal.

The objective of our study was to measure the impact of transportation-related noise and total environmental noise on sleep disturbance for the residents of Montreal, Canada. A telephone-based survey on noise-related sleep disturbance among 4336 persons aged 18 years and over was conducted. LNight for each study participant was estimated using a land use regression (LUR) model. Distance of the respondent's residence to the nearest transportation noise source was also used as an indicator of noise exposure. The proportion of the population whose sleep was disturbed by outdoor environmental noise in the past 4 weeks was 12.4%. The proportion of those affected by road traffic, airplane and railway noise was 4.2%, 1.5% and 1.1%, respectively. We observed an increased prevalence in sleep disturbance for those exposed to both rail and road noise when compared for those exposed to road only. We did not observe an increased prevalence in sleep disturbance for those that were both exposed to road and planes when compared to those exposed to road or planes only. We developed regression models to assess the marginal proportion of sleep disturbance as a function of estimated LNight and distance to transportation noise sources. In our models, sleep disturbance increased with proximity to transportation noise sources (railway, airplane and road traffic) and with increasing LNight values. Our study provides a quantitative estimate of the association between total environmental noise levels estimated using an LUR model and sleep disturbance from transportation noise.

Annoyance from Road Traffic, Trains, Airplanes and from Total Environmental Noise Levels.

There is a lack of studies assessing the exposure-response relationship between transportation noise and annoyance in North America. Our aims were to investigate the prevalence of noise annoyance induced by road traffic, trains and airplanes in relation to distance to transportation noise sources, and to total environmental noise levels in Montreal, Canada; annoyance was assessed as noise-induced disturbance. A telephone-based survey among 4336 persons aged >18 years was conducted. Exposure to total environmental noise (A-weighted outdoor noise levels-LAeq24h and day-evening-night equivalent noise levels-Lden) for each study participant was determined using a statistical noise model (land use regression-LUR) that is based on actual outdoor noise measurements. The proportion of the population annoyed by road traffic, airplane and train noise was 20.1%, 13.0% and 6.1%, respectively. As the distance to major roads, railways and the Montreal International Airport increased, the percentage of people disturbed and highly disturbed due to the corresponding traffic noise significantly decreased. When applying the statistical noise model we found a relationship between noise levels and disturbance from road traffic and total environmental noise, with Prevalence Proportion Ratios (PPR) for highly disturbed people of 1.10 (95% CI: 1.07-1.13) and 1.04 (1.02-1.06) per 1 dB(A) Lden, respectively. Our study provides the first comprehensive information on the relationship between transportation noise levels and disturbance in a Canadian city. LUR models are still in development and further studies on transportation noise induced annoyance are consequently needed, especially for sources other than road traffic.

Grassroots projects aimed at the built environment: Association with neighbourhood deprivation, land-use mix and injury risk to road users.

OBJECTIVES: 1) To describe grassroots projects aimed at the built environment and associated with active transportation on the Island of Montreal; and 2) to examine associations between the number of projects and indicators of neighbourhood material and social deprivation and the built environment. METHOD: We identified funding agencies and community groups conducting projects on built environments throughout the Island of Montreal. Through website consultation and a snowballing procedure, we inventoried projects that aimed at transforming built environments and that were carried out by community organizations between January 1, 2006, and November 1, 2010. We coded and validated information about project activities and created an interactive map using Geoclip software. Correlational analyses quantified associations between number of projects, neighbourhood characteristics and deprivation. RESULTS: A total of 134 community organizations were identified, and 183 grassroots projects were inventoried. A large number of projects were aimed at increasing awareness of/improving active or public transportation (n=95), improving road safety (n=84) and enhancing neighbourhood beautification and greening (n=69). The correlation between the presence of projects and the extent of neighbourhood material deprivation was small (Kendall's t=0.26, p<0.001), but in areas with greater social deprivation there were more projects (Kendall's t=0.38, p<0.001). Larger numbers of projects were also associated with the presence of more extensive land-use mix (Kendall's t=0.23, p<0.001) and a greater proportion of road intersections with injured pedestrians, cyclists and motor vehicle users (Kendall's t=0.43, p<0.001). CONCLUSION: There is significant community mobilization around built environments and active transportation. Investigations of the implementation processes and impacts are warranted.