A Cohort Study of Traffic-Related Air Pollution and Mortality in Toronto, Ontario, Canada

BackgroundChronic exposure to traffic-related air pollution (TRAP) may contribute to premature mortality, but few studies to date have addressed this topic.ObjectivesIn this study we assessed the association between TRAP and mortality in Toronto, Ontario, Canada.MethodsWe collected nitrogen dioxide samples over two seasons using duplicate two-sided Ogawa passive diffusion samplers at 143 locations across Toronto. We calibrated land use regressions to predict NO2 exposure on a fine scale within Toronto. We used interpolations to predict levels of particulate matter with aerodynamic diameter < or = 2.5 microm (PM(2.5)) and ozone levels. We assigned predicted pollution exposures to 2,360 subjects from a respiratory clinic, and abstracted health data on these subjects from medical billings, lung function tests, and diagnoses by pulmonologists. We tracked mortality between 1992 and 2002. We used standard and multilevel Cox proportional hazard models to test associations between air pollution and mortality.ResultsAfter controlling for age, sex, lung function, obesity, smoking, and neighborhood deprivation, we observed a 17% increase in all-cause mortality and a 40% increase in circulatory mortality from an exposure contrast across the interquartile range of 4 ppb NO2. We observed no significant associations with other pollutants.ConclusionsExposure to TRAP was significantly associated with increased all-cause and circulatory mortality in this cohort. A high prevalence of cardiopulmonary disease in the cohort probably limits inference of the findings to populations with a substantial proportion of susceptible individuals

Spatial analysis of air pollution and childhood asthma in Hamilton, Canada: comparing exposure methods in sensitive subgroups

<p>Abstract</p> <p>Background</p> <p>Variations in air pollution exposure within a community may be associated with asthma prevalence. However, studies conducted to date have produced inconsistent results, possibly due to errors in measurement of the exposures.</p> <p>Methods</p> <p>A standardized asthma survey was administered to children in grades one and eight in Hamilton, Canada, in 1994–95 (N ~1467). Exposure to air pollution was estimated in four ways: (1) distance from roadways; (2) interpolated surfaces for ozone, sulfur dioxide, particulate matter and nitrous oxides from seven to nine governmental monitoring stations; (3) a kriged nitrogen dioxide (NO₂) surface based on a network of 100 passive NO₂monitors; and (4) a land use regression (LUR) model derived from the same monitoring network. Logistic regressions were used to test associations between asthma and air pollution, controlling for variables including neighbourhood income, dwelling value, state of housing, a deprivation index and smoking.</p> <p>Results</p> <p>There were no significant associations between any of the exposure estimates and asthma in the whole population, but large effects were detected the subgroup of children without hayfever (predominately in girls). The most robust effects were observed for the association of asthma without hayfever and NO₂LUR OR = 1.86 (95%CI, 1.59–2.16) in all girls and OR = 2.98 (95%CI, 0.98–9.06) for older girls, over an interquartile range increase and controlling for confounders.</p> <p>Conclusion</p> <p>Our findings indicate that traffic-related pollutants, such as NO₂, are associated with asthma without overt evidence of other atopic disorders among female children living in a medium-sized Canadian city. The effects were sensitive to the method of exposure estimation. More refined exposure models produced the most robust associations.</p

Can antibiotic prescriptions in respiratory tract infections be improved? A cluster-randomized educational intervention in general practice – The Prescription Peer Academic Detailing (Rx-PAD) Study [NCT00272155]

BACKGROUND: More than half of all antibiotic prescriptions in general practice are issued for respiratory tract infections (RTIs), despite convincing evidence that many of these infections are caused by viruses. Frequent misuse of antimicrobial agents is of great global health concern, as we face an emerging worldwide threat of bacterial antibiotic resistance. There is an increasing need to identify determinants and patterns of antibiotic prescribing, in order to identify where clinical practice can be improved. METHODS/DESIGN: Approximately 80 peer continuing medical education (CME) groups in southern Norway will be recruited to a cluster randomized trial. Participating groups will be randomized either to an intervention- or a control group. A multifaceted intervention has been tailored, where key components are educational outreach visits to the CME-groups, work-shops, audit and feedback. Prescription Peer Academic Detailers (Rx-PADs), who are trained GPs, will conduct the educational outreach visits. During these visits, evidence-based recommendations of antibiotic prescriptions for RTIs will be presented and software will be handed out for installation in participants PCs, enabling collection of prescription data. These data will subsequently be linked to corresponding data from the Norwegian Prescription Database (NorPD). Individual feedback reports will be sent all participating GPs during and one year after the intervention. Main outcomes are baseline proportion of inappropriate antibiotic prescriptions for RTIs and change in prescription patterns compared to baseline one year after the initiation of the tailored pedagogic intervention. DISCUSSION: Improvement of prescription patterns in medical practice is a challenging task. A thorough evaluation of guidelines for antibiotic treatment in RTIs may impose important benefits, whereas inappropriate prescribing entails substantial costs, as well as undesirable consequences like development of antibiotic resistance. Our hypothesis is that an educational intervention program will be effective in improving prescription patterns by reducing the total number of antibiotic prescriptions, as well as reducing the amount of broad-spectrum antibiotics, with special emphasis on macrolides

Object Properties in the Raven System

Raven consists of an object-oriented programming language and a runtime system that supports distributed and multiprocessor computing. This paper describes the motivation behind the design of the object property scheme used in the Raven system, the behavioral semantics for each of the properties supported, and schemes by which inter-object dependencies can be described. Raven provides a set of system-defined properties, such as concurrency control and persistence, as well as support for user-defined properties. Raven is distinguishable from similar systems in several fundamental ways: the behavioral semantics of each system supported property is truly orthogonal to those of the others, allowing properties to be combined without side effects; the system allows the seamless integration of user-defined properties into the property scheme; and all properties (even user properties) can be assigned dynamically, in any combination, to objects, even after object creation. Property support is p..

A GIS - environmental justice analysis of particulate air pollution in Hamilton, Canada

The authors address two research questions: (1) Are populations with lower socioeconomic status, compared with people of higher socioeconomic status, more likely to be exposed to higher levels of particulate air pollution in Hamilton, Ontario, Canada? (2) How sensitive is the association between levels of particulate air pollution and socioeconomic status to specification of exposure estimates or statistical models? Total suspended particulate (TSP) data from the twenty-three monitoring stations in Hamilton (1985 - 94) were interpolated with a universal kriging procedure to develop an estimate of likely pollution values across the city based on annual geometric means and extreme events. Comparing the highest with the lowest exposure zones, the interpolated surfaces showed more than a twofold increase in TSP concentrations and more than a twentyfold difference in the probability of exposure to extreme events. Exposure estimates were related to socioeconomic and demographic data from census tract areas by using ordinary least squares and simultaneous autoregressive (SAR) models. Control for spatial autocorrelation in the SAR models allowed for tests of how robust specific socioeconomic variables were for predicting pollution exposure. Dwelling values were significantly and negatively associated with pollution exposure, a result robust to the method of statistical analysis. Low income and unemployment were also significant predictors of exposure, although results varied depending on the method of analysis. Relatively minor changes in the statistical models altered the significant variables. This result emphasizes the value of geographical information systems (GIS) and spatial statistical techniques in modelling exposure. The result also shows the importance of taking spatial autocorrelation into account in future justice - health studies.

A cohort study of traffic-related air pollution and mortality in Toronto, Ontario, Canada.

BackgroundChronic exposure to traffic-related air pollution (TRAP) may contribute to premature mortality, but few studies to date have addressed this topic.ObjectivesIn this study we assessed the association between TRAP and mortality in Toronto, Ontario, Canada.MethodsWe collected nitrogen dioxide samples over two seasons using duplicate two-sided Ogawa passive diffusion samplers at 143 locations across Toronto. We calibrated land use regressions to predict NO2 exposure on a fine scale within Toronto. We used interpolations to predict levels of particulate matter with aerodynamic diameter &lt; or = 2.5 microm (PM(2.5)) and ozone levels. We assigned predicted pollution exposures to 2,360 subjects from a respiratory clinic, and abstracted health data on these subjects from medical billings, lung function tests, and diagnoses by pulmonologists. We tracked mortality between 1992 and 2002. We used standard and multilevel Cox proportional hazard models to test associations between air pollution and mortality.ResultsAfter controlling for age, sex, lung function, obesity, smoking, and neighborhood deprivation, we observed a 17% increase in all-cause mortality and a 40% increase in circulatory mortality from an exposure contrast across the interquartile range of 4 ppb NO2. We observed no significant associations with other pollutants.ConclusionsExposure to TRAP was significantly associated with increased all-cause and circulatory mortality in this cohort. A high prevalence of cardiopulmonary disease in the cohort probably limits inference of the findings to populations with a substantial proportion of susceptible individuals