BackgroundAdvancements in geographic information systems over the past two decades have increased the specificity by which an individual’s neighborhood environment may be spatially defined for physical activity and health research. This study investigated how different types of street network buffering methods compared in measuring a set of commonly used built environment measures (BEMs) and tested their performance on associations with physical activity outcomes.MethodsAn internationally-developed set of objective BEMs using three different spatial buffering techniques were used to evaluate the relative differences in resulting explanatory power on self-reported physical activity outcomes. BEMs were developed in five countries using ‘sausage,’ ‘detailed-trimmed,’ and ‘detailed,’ network buffers at a distance of 1 km around participant household addresses (n = 5883).ResultsBEM values were significantly different (p < 0.05) for 96% of sausage versus detailed-trimmed buffer comparisons and 89% of sausage versus detailed network buffer comparisons. Results showed that BEM coefficients in physical activity models did not differ significantly across buffering methods, and in most cases BEM associations with physical activity outcomes had the same level of statistical significance across buffer types. However, BEM coefficients differed in significance for 9% of the sausage versus detailed models, which may warrant further investigation.ConclusionsResults of this study inform the selection of spatial buffering methods to estimate physical activity outcomes using an internationally consistent set of BEMs. Using three different network-based buffering methods, the findings indicate significant variation among BEM values, however associations with physical activity outcomes were similar across each buffering technique. The study advances knowledge by presenting consistently assessed relationships between three different network buffer types and utilitarian travel, sedentary behavior, and leisure-oriented physical activity outcomes.

The public health consequences of extreme heat events are felt most intensely in metropolitan areas where population density is high and the presence of the urban heat island phenomenon exacerbates the potential for prolonged exposure. This research develops an approach to map potential heat stress on humans by combining temperature and relative humidity into an index of apparent temperature. We use ordinary kriging to generate hourly prediction maps describing apparent temperature across the Greater Toronto Area, Canada. Meteorological data were obtained from 65 locations for 6 days in 2008 when extreme heat alerts were issued for the City of Toronto. Apparent temperature and exposure duration were integrated in a single metric, humidex degree hours (HDH), and mapped. The results show a significant difference in apparent temperature between built and natural locations from 3 PM to 7 AM; this discrepancy was greatest at 12 AM where built locations had a mean of 2.8 index values larger, t(71) = 5.379, p < 0.001. Spatial trends in exposure to heat stress (apparent temperature, ≥ 30°C) show the downtown core of the City of Toronto and much of Mississauga (west of Toronto) as likely to experience hazardous levels of prolonged heat and humidity (HDH ≥ 72) during a heat alert. We recommend that public health officials use apparent temperature and exposure duration to develop spatially explicit heat vulnerability assessment tools; HDH is one approach that unites these risk factors into a single metric.

Objectives The use of online imagery by non-local observers to conduct remote, centralized collection of streetscape audit data in international studies has the potential to enhance efficiency of collection and comparability of such data for research on built environments and health. The objectives of the study were to measure (1) the consistency in responses between local in-field observers and non-local remote online observers and (2) the reliability between in-country online observers and non-local remote online observers using the Microscale Audit of Pedestrian Streetscapes Global tool to characterize pedestrian-related features along streets in five countries. Methods Consistency and inter-rater reliability were analyzed between local and non-local observers on a pooled database of 200 routes in five study regions (Melbourne, Australia; Ghent, Belgium; Curitiba, Brazil; Hong Kong, China; and Valencia, Spain) for microscale environmental feature subscales and item-level variables using the intraclass correlation coefficient (ICC). Results A local in-field versus remote online comparison had an ICC of 0.75 (95 % CI: 0.68–0.80) for the grand total score. An ICC of 0.91 (95 % CI: 0.88–0.93) was found for the local online versus remote online comparison. Positive subscales yielded stronger results in comparison to negative subscales, except for the similarly poor-performing positive aesthetics/social characteristics. Conclusions This study demonstrated remote audits of microscale built environments using online imagery had good reliability with local in-field audits and excellent reliability with local online audits. Results generally supported remote online environmental audits as comparable to local online audits. This identification of low-cost and efficient data acquisition methods is important for expanding research on microscale built environments and physical activity globally.

Abstract.Numerous environmental justice studies have confirmed a relationship between population characteristics such as low-income or minority status and the location of environmental health hazards. However, studies of the health risks from exposure to harmful substances often do not consider their toxicological characteristics. We used two different methods, the unit-hazard and the distance-based approach, to evaluate demographic and socio-economic characteristics of the population residing near industrial facilities in the City of Toronto, Canada. In addition to the mass of air emissions obtained from the national pollutant release inventory (NPRI), we also considered their toxicity using toxic equivalency potential (TEP) scores. Results from the unit-hazard approach indicate no significant difference in the proportion of low-income individuals living in host versus non-host census tracts (t(107) = 0.3, P = 0.735). However, using the distance-based approach, the proportion of low-income individuals was significantly higher (+5.1%, t(522) = 6.0, P <0.001) in host tracts, while the indicator for "racialized" communities ("visible minority") was 16.1% greater (t(521) = 7.2, P <0.001) within 2 km of a NPRI facility. When the most toxic facilities by non-carcinogenic TEP score were selected, the rate of visible minorities living near the most toxic NPRI facilities was significantly higher (+12.9%, t(352) = 3.5, P = 0.001) than near all other NPRI facilities. TEP scores were also used to identify areas in Toronto that face a double burden of poverty and air toxics exposure in order to prioritise pollution prevention.

Understanding neighborhood preferences remains a key focus for planners. While many studies document the effects of either neighborhood design or neighborhood preference on health and travel behavior, few have explored their combined effect in smaller regions. Using a sample of 2,597 adults in the Region of Waterloo, Ontario, we found an unmet demand for walkable neighborhoods. Results suggest that walkable neighborhoods are independently associated with less vehicle travel after adjusting for sociodemographic and residential preferences. Our study highlights the importance of combining the effects of walkable neighborhoods and preferences for them when addressing health and sustainability goals in suburban communities.