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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. [ABSTRACT FROM AUTHOR]

Residential wood burning can be a significant wintertime source of ambient fine particles in urban and suburban areas. We developed a statistical model to predict minute (min) levels of particles with median diameter of <1 μm (PM1) from mobile monitoring on evenings of winter weekends at different residential locations in Quebec, Canada, considering wood burning emissions. The 6 s PM1 levels were concurrently measured on 10 preselected routes travelled 3 to 24 times during the winters of 2008-2009 and 2009-2010 by vehicles equipped with a GRIMM or a dataRAM sampler and a Global Positioning System device. Route-specific and global land-use regression (LUR) models were developed using the following spatial and temporal covariates to predict 1-min-averaged PM1 levels: chimney density from property assessment data at sampling locations, PM2.5 'regional background' levels of particles with median diameter of <2.5 μm (PM2.5) and temperature and wind speed at hour of sampling, elevation at sampling locations and day of the week. In the various routes travelled, between 49% and 94% of the variability in PM1 levels was explained by the selected covariates. The effect of chimney density was not negligible in 'cottage areas.' The R2 for the global model including all routes was 0.40. This LUR is the first to predict PM1 levels in both space and time with consideration of the effects of wood burning emissions. We show that the influence of chimney density, a proxy for wood burning emissions, varies by regions and that a global model cannot be used to predict PM in regions that were not measured. Future work should consider using both survey data on wood burning intensity and information from numerical air quality forecast models, in LUR models, to improve the generalisation of the prediction of fine particulate levels. [ABSTRACT FROM AUTHOR]

Effects of air pollutants are related to oxidative stress which is also linked to the pathogenesis of dementia including Alzheimer's and related diseases. 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. 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 (NO 2) and fine particles (PM 2.5) 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 NO 2 or PM 2.5 ; they were also indirectly adjusted for smoking. 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 NO 2 (IQR 13.26 ppb), PM 2.5 (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. Results suggest that the onset of dementia may be related to residential exposure to PM 2.5 , NO 2 , and distance to major roads. • We studied dementia onset and residential exposure to air pollutants. • We used a cohort based on administrative health data in Quebec, Canada, 2000–2012. • Residential exposure to PM2.5, NO2 was based on satellite images and monitoring data. • PM2.5, NO2, distances to major roads (Montreal) were associated with dementia onset. [ABSTRACT FROM AUTHOR]