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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. [ABSTRACT FROM AUTHOR]

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. [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]