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There are acknowledged difficulties in epidemiological studies to accurately assign exposure to air pollution for large populations, and large, long-term cohort studies have typically relied upon data from central monitoring stations. This approach has generally been adequate when populations span large areas or diverse cities. However, when the effects of intra-urban differences in exposure are being studied, the use of these existing central sites are likely to be inadequate for representing spatial variability that exists within an urban area. As part of the Border Air Quality Strategy (BAQS), an international agreement between the governments of Canada and the United States, a number of air health effects studies are being undertaken by Health Canada and the US EPA. Health Canada''s research largely focuses on the chronic exposure of elementary school children to air pollution. The exposure characterization for this population to a variety of air pollutants has been assessed using land-use regression (LUR) models. This approach has been applied in several cities to nitrogen dioxide (NO2), as an assumed traffic exposure marker. However, the models have largely been developed from limited periods of saturation monitoring data and often only represent one or two seasons. Two key questions from these previous efforts, which are examined in this paper, are: If NO2 is a traffic marker, what other pollutants, potentially traffic related, might it actually represent? How well is the within city spatial variability of NO2, and other traffic-related pollutants, characterized by a single saturation monitoring campaign. Input data for the models developed in this paper were obtained across a network of 54 monitoring sites situated across Windsor, Ontario. The pollutants studied were NO2, sulfur dioxide (SO2) and volatile organic compounds, which were measured in all four seasons by deploying passive samplers for 2-week periods. Correlations among these pollutants were calculated to assess what other pollutants NO2 might represent, and correlations across seasons for a given pollutant were determined to assess how much the within-city spatial pattern varies with time. LUR models were then developed for NO2, SO2, benzene, and toluene. A multiple regression model including proximity to the Ambassador Bridge (the main Canada—US border crossing point), and proximity to highways and major roads, predicted NO2 concentrations with an R 2=0.77. The SO2 model predictors included distance to the Ambassador Bridge, dwelling density within 1500m, and Detroit-based SO2 emitters within 3000m resulting in a model with an R 2=0.69. Benzene and toluene LUR models included traffic predictors as well as point source emitters resulting in R 2=0.73 and 0.46, respectively. Between season pollutant correlations were all significant although actual concentrations for each site varied by season. This suggests that if one season were to be selected to represent the annual concentrations for a specific site this may lead to a potential under or overestimation in exposure, which could be significant for health research. All pollutants had strong inter-pollutant correlations suggesting that NO2 could represent SO2, benzene, and toluene. [Copyright &y& Elsevier]

Infant mortality is widely recognized as an indicator of poor living conditions. Scholars have identified economic, housing, environmental, and more recently, cultural determinants of infant mortality. Using individual-level data and record linkage this paper documents and explains the geography of infant mortality in Ottawa in 1901. Infant death in Ottawa mirrored the geography of poor living conditions in the city. The poorest and most densely settled community in Ottawa was Lowertown, a mostly French-Canadian part of the city with a disproportionate share of the city's infant deaths. In addition to environmental factors, infant mortality was linked to economic standing. Poorer families in Lowertown were more likely to have one of their infants die than better off families. After controlling for economic standing, however, cultural factors were stronger predictors of infant deaths. French-Canadian families in Lowertown had a greater risk of infant deaths than did families of other backgrounds irrespective of material circumstances. Supporting conclusions drawn elsewhere, this paper suggests that the interaction of particular cultural practices, such as shorter periods of breast-feeding among French-Canadians and a poor sanitary environment, resulted in high infant mortality rates in Ottawa. [ABSTRACT FROM AUTHOR]

Abstract: The latest meeting in the series of International Conferences of Historical Geographers was held in Kyoto in 2009. The series originated in a meeting of Canadian and British historical geographers held in Kingston, Ontario, in 1975. Four subsequent meetings held in Britain, Canada and the USA saw an increasingly international participation and the sixth meeting, held in 1986, was accorded the title of the Sixth International Conference of Historical Geographers. Eight further such conferences have been held since then, some in locations well beyond Britain and North America. This paper records the basic historical and geographical characteristics of all of the meetings between 1975 and 2009. [Copyright &y& Elsevier]

This paper sought to examine chronic disease risk behaviour latent classes and their association with Body Mass Index (BMI), assessing for gender differences. Participants were youth (n = 116,086; grades 9-12) enrolled in the COMPASS study (Ontario, Canada) during 2013, 2014, 2015. Multilevel latent class analysis was used to identify underlying, homogenous classes of youths' engagement in physical activity, smoking, binge drinking and marijuana use. Adjusted multilevel models regressed BMI on the latent classes controlling for ethnicity and grade. Three latent classes were identified: active experimenters (ACE), inactive clean youth (INC) and inactive substance users (INSU). This study found that gender differences are apparent in chronic disease risk behaviour latent classes and their association with BMI. INC males (OR = 0.85, 95% CI = 0.78, 0.93) were associated with a lower odds of overweight/obesity relative to active males who experimented with substance use. As for females, the class with the highest proportion of youth using substances were associated with higher odds (Females: OR = 1.2, 95% CI = 1.1, 1.4) of overweight/obesity relative to their active experimenting peers. As such, youth in latent classes with substance use are associated with higher BMI and weight status. Successful interventions may include school policies/programs that limit screen time use, as they were seen to have a positive effect on PA engagement and including social-influences approaches for substance use. Future research and interventions should be gender-specific as our results show that different latent classes are associated with obesity across genders. [ABSTRACT FROM AUTHOR]