Publications

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2019
Cakmak, S, Hebbern C, Vanos J, Crouse DL, Tjepkema M.  2019.  Exposure to traffic and mortality risk in the 1991-2011 Canadian Census Health and Environment Cohort (CanCHEC). Environment International. 124:16-24.   10.1016/j.envint.2018.12.045   AbstractWebsite

There is evidence that local traffic density and living near major roads can adversely affect health outcomes. We aimed to assess the relationship between local road length, proximity to primary highways, and cause-specific mortality in the 1991 Canadian Census Health and Environment Cohort (CanCHEC). In this long-term study of 2.6 million people, based on completion of the long-form census in 1991 and followed until 2011, we used annual residential addresses to determine the total length of local roads within 200m of postal code representative points and the postal code's distance to primary highways. The association between exposure to traffic and cause-specific non-accidental mortality was estimated using Cox proportional hazards models, adjusting for individual covariates and contextual factors, including census division-level proportion in high school, the percentage of recent immigrants, and neighborhood income. We performed sensitivity analyses, including adjustment for exposure to PM2.5, NO2, or O-3, restricting to subjects in core urban areas, and spatial variation by climatic zone. The hazard ratio (HR) for all non-accidental mortality associated with an interquartile increase in length of local roads was 1.05 (95% CI 1.04, 1.05), while for an interquartile range increase in proximity to primary highways, the HR was 1.03 (95% CI 1.02, 1.04). HRs by traffic quartile increased with increasing lengths of local roads, as well as with closer proximity to primary highways, for all mortality causes. The associations were stronger within subjects' resident in urban core areas, attenuated by adjustment for PM2.5, and HRs showed limited spatial variation by climatic zone. In the CanCHEC cohort, exposure to higher road density and proximity to major traffic roads was associated with increased mortality risk from cerebrovascular and cardiovascular disease, ischemic heart disease, COPD, respiratory disease, and lung cancer, with unclear results for diabetes.

2017
Graham, DA, Vanos JK, Kenny NA, Brown RD.  2017.  Modeling the Effects of Urban Design on Emergency Medical Response Calls during Extreme Heat Events in Toronto, Canada. International Journal of Environmental Research and Public Health. 14   10.3390/ijerph14070778   AbstractWebsite

Urban residents are at risk of health-related illness during extreme heat events but the dangers are not equal in all parts of a city. Previous studies have found a relationship between physical characteristics of neighborhoods and the number of emergency medical response (EMR) calls. We used a human energy budget model to test the effects of landscape modifications that are designed to cool the environment on the expected number of EMR calls in two neighborhoods in Toronto, Canada during extreme heat events. The cooling design strategies reduced the energy overload on people by approximately 20-30 W m(-2), resulting in an estimated 40-50% reduction in heat-related ambulance calls. These findings advance current understanding of the relationship between the urban landscape and human health and suggest straightforward design strategies to positively influence urban heat-health.

2015
Vanos, JK, Cakmak S, Kalkstein LS, Yagouti A.  2015.  Association of weather and air pollution interactions on daily mortality in 12 Canadian cities. Air Qual Atmos Health. 8:307-320.   10.1007/s11869-014-0266-7   Abstract

It has been well established that both meteorological attributes and air pollution concentrations affect human health outcomes. We examined all cause nonaccident mortality relationships for 28 years (1981-2008) in relation to air pollution and synoptic weather type (encompassing air mass) data in 12 Canadian cities. This study first determines the likelihood of summertime extreme air pollution events within weather types using spatial synoptic classification. Second, it examines the modifying effect of weather types on the relative risk of mortality (RR) due to daily concentrations of air pollution (nitrogen dioxide, ozone, sulfur dioxide, and particulate matter <2.5 mum). We assess both single- and two-pollutant interactions to determine dependent and independent pollutant effects using the relatively new time series technique of distributed lag nonlinear modeling (DLNM). Results display dry tropical (DT) and moist tropical plus (MT+) weathers to result in a fourfold and twofold increased likelihood, respectively, of an extreme pollution event (top 5 % of pollution concentrations throughout the 28 years) occurring. We also demonstrate statistically significant effects of single-pollutant exposure on mortality (p < 0.05) to be dependent on summer weather type, where stronger results occur in dry moderate (fair weather) and DT or MT+ weather types. The overall average single-effect RR increases due to pollutant exposure within DT and MT+ weather types are 14.9 and 11.9 %, respectively. Adjusted exposures (two-way pollutant effect estimates) generally results in decreased RR estimates, indicating that the pollutants are not independent. Adjusting for ozone significantly lowers 67 % of the single-pollutant RR estimates and reduces model variability, which demonstrates that ozone significantly controls a portion of the mortality signal from the model. Our findings demonstrate the mortality risks of air pollution exposure to differ by weather type, with increased accuracy obtained when accounting for interactive effects through adjustment for dependent pollutants using a DLNM.