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A geography of child and elderly pedestrian injury in the City of Toronto, Canada
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A geography of child and elderly pedestrian injury in the City of Toronto, Canada Emily Griséa,⁎,1, Ron Buliunga, Linda Rothmanb, Andrew Howardc,d a
Department of Geography and Programs in Environment, University of Toronto Mississauga, 3359 Mississauga Road, Mississauga, ON L5L 1C6, Canada Faculty of Health-School of Kinesiology & Health Science, York University, Norman Bethune College, Canada c Child Health Evaluative Sciences, Departments of Surgery & Health Policy, Management & Evaluation, University of Toronto, Canada d Orthopedic Surgery, The Hospital for Sick Children, Canada b
A R T I C L E I N F O
A B S T R A C T
Keywords: Pedestrian motor vehicle collisions Age Spatial analysis Built environment
Walking is one of the most accessible forms of physical activity for people of all ages. Promoting increased walking for transport may contribute to reduced air pollution, noise and traffic congestion. Understanding the geography of pedestrian motor vehicle collisions (PMVCs) can provide evidence to inform policy and planning that targets increased walking while reducing pedestrian injury risk, however age-related differences in the geography of injury are expected given differences in activity patterns and physical and cognitive abilities. The purpose of this paper is to explore spatial patterns of pedestrian motor vehicle collisions (PMVCs) by age, injury severity, and location in Canada's largest city, the City of Toronto. Geographical variation in PMVCs and injuries by age (namely seniors and children) and severity were explored using indirect standardized rates. Moran's I statistics were estimated to study the spatial clustering of PMVCs across urban and inner suburban neighbourhoods. Distinct spatial patterns of PMVCs and injuries were evident among children and seniors. While evidence of spatial clustering was indicated for both age groups, children's injuries revealed the strongest clustering, while PMVCs involving seniors were more dispersed. Furthermore, fatal and major injury events appeared to be concentrated toward and within Toronto's inner suburbs for both age groups. Findings from this study demonstrate the importance of planning pedestrian safety interventions that acknowledge spatial differences in geographic patterns of PMVCs by age.
1. Introduction Walking for transport has the potential to contribute to reduced air pollution, noise and traffic congestion, while also providing a form of physical activity that is widely accessible for individuals of all ages. While such benefits may accumulate, to the individual and broader society, without question the act of walking in many cities presents some risk of injury and even fatality, particularly in the presence of a modernist legacy of planning for and accommodating automobility. These risks, and injury outcomes are unevenly distributed over space and across the population. Walking also requires a variety of cognitive skills, including reaction time and understanding or anticipating the behaviour of other road users. The design of road networks can further complicate and potentially endanger the safety of pedestrians, particularly in urban regions with road designs that favour automobile traffic flow (Dumbaugh and Rae, 2009). Furthermore, the complexity of the road environment, particularly in areas with high vehicle volumes
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and speeds, creates potentially dangerous situations for older pedestrians (O'Hern et al., 2015) and children (Zeedyk et al., 2001). Road traffic injury is the single largest cause of years of life lost (YLL) (17%) in children and youth in Canada (Institute for Health Metrics and Evaluation, 2013). Among all types of road traffic injury, child and youth pedestrian injury accounts for 25% of total injuries. In regard to seniors, their overrepresentation among pedestrian motor vehicle collisions (PMVCs) is alarming. According to a 2012 report produced by the International Transport Forum, individuals aged 65 years represented up to 50% of injured pedestrians in OECD countries (International Transport Forum (ITF), 2012). Specifically in Canada, individuals over the age of 65 represented 35% of the pedestrian fatalities between the years 2004–2008, despite this age group only representing 13% of the population (Transport Canada, 2011). However in the City of Toronto, Canada's largest city, between the years 2011–2015, older pedestrians (55 + years of age) comprised 63% of fatalities despite their relatively low representation in the population
Corresponding author at: Department of Geography and Programs in Environment, University of Toronto Mississauga, 3359 Mississauga Road, Mississauga, ON L5L 1C6, Canada. E-mail addresses: [email protected] (E. Grisé), [email protected] (R. Buliung), [email protected] (L. Rothman), [email protected] (A. Howard). Present address: School of Urban Planning, McGill University, Suite 400, 815 Sherbrooke St. W., Montréal, Québec, H3A 0C2, Canada
http://dx.doi.org/10.1016/j.jtrangeo.2017.10.003 Received 14 July 2016; Received in revised form 2 October 2017; Accepted 11 October 2017 0966-6923/ © 2017 Elsevier Ltd. All rights reserved.
Please cite this article as: Grisé, E., Journal of Transport Geography (2017), http://dx.doi.org/10.1016/j.jtrangeo.2017.10.003
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is safer, and they feel it is dangerous to cross the road where these facilities are missing (Bernhoft and Carstensen, 2008). Despite the perception of safety at intersections, a high proportion of pedestrian injuries involving seniors occur at signalized intersections. Specifically, in a review of pedestrian fatalities that occurred across Canada between 2004 and 2008, 63% of individuals who were involved in a fatal collision at intersections were aged 65 years and older (Transport Canada, 2011). Reduced walking speeds of older adults increase exposure levels to vehicle traffic. The reduced physical mobility and perceptual and cognitive functions of some of the elderly also affects their judgment and their ability to safely crossing streets (Oxley et al., 2004; Oxley et al., 1997). With regard to environmental risk factors, two primary determinants of pedestrian injury include vehicle and pedestrian volume (Lee and Abdel-Aty, 2005; Miranda-Moreno et al., 2011; Wier et al., 2009). Urban development patterns and urban design impact safety primarily through the traffic volumes they produce and attract, and secondarily through the allowable speed limits or the traffic speeds they inadvertently encourage (Ewing and Dumbaugh, 2009). Traffic speed is a critical predictor of pedestrian injury severity and the likelihood of suffering a fatal injury, and it is generally accepted that the chance of survival decreases non-linearly with increasing vehicle speed (Rosen et al., 2011). Accordingly, fatality risk is severely diminished at speeds less than or equal to 40 km/h. However, achieving slower speeds, even on residential streets, is known to be as much a political challenge more than anything else (Keenan, 2017). While speed remains a critical risk factor for PMVCs and fatality (Peden, 2004), children and seniors are particularly vulnerable to a severe injury outcome in the event of a collision with a vehicle. Children may be impacted differently due to their physical size. As a result of the short stature of a child, a vehicle may directly strike a child's head or vital organs resulting in a more severe injury outcome regardless of speed. In adults, a vehicle's windshield and its frame are the main source of head injuries in PMVCs, which can cause severe brain injuries and lead to lifelong disability or death (Yao et al., 2008). While vehicle speed is a critical predictor of the severity of injury sustained after a collision, pedestrians over the age of 65 experience higher injury rates than younger people at all speeds (Henary et al., 2006). Therefore, while speed remains a critical factor of the severity of injury following an accident for these two populations, emphasis must simultaneously be placed on reducing potential conflicts with vehicles, particularly in areas where there is a high presence of children and seniors. A limitation of the literature discussed above and within the broader field of pedestrian planning, is that there is insufficient evidence of the geography of pedestrian injury. While it is imperative for research to continue to expand our knowledge on the determinants of injury to develop evidence to support effective interventions, planners, policy makers, and injury epidemiologists should probe more deeply into the geographies of injury risk and outcomes, because the processes that produce injury are likely to be geographically and temporally uneven. Understanding the geography of injury production and reduction, is helpful knowledge, particularly for those working in the urban professions who wrestle with the fiscal, political and design challenges that are often folded into discussions about the prioritization and targeting of spending in both the fixed capital and operational domains. Accordingly, this paper presents an exploratory spatial analysis of pedestrian injury by age and severity, with a view to contributing to a global conversation about urban traffic injury among vulnerable road users. With the majority of the world's population concentrated in urbanized areas, and with the global burden of traffic injury on the rise (Organisation for Economic Co-operation and Development, 1998; World Health Organization, 2015), it is particularly salient to contribute to a conversation about where traffic injury occurs within major global cities.
(26%) (City of Toronto, 2016). The focus on vulnerable road users such as children and the elderly is particularly salient given the unique physical and cognitive aspects of these populations that shape their injury risks. The literature on child pedestrian injury risk factors indicates that children experience unique risk factors and exhibit distinct locational patterns of injury (Ha and Thill, 2011; Koopmans et al., 2015; Lightstone et al., 2001; Rothman et al., 2012), which appear to differ from locational patterns of injury involving seniors (Dunbar et al., 2004; Oxley et al., 2004; Zegeer, 2002). Accordingly, locational patterns of collisions involving children and seniors' should be examined separately, as it is hypothesized that the geographic distribution of pedestrian injury risks among children and seniors will also differ. Accordingly, this research explores spatial patterns of PMVCs involving children and seniors using the City of Toronto as a case study. Results of this study are intended to provide planners, engineers and policy makers with a better understanding of the geographical locations of high risk for child and elderly pedestrian injury, to enable the development of effective age-based interventions in the built environment. This sort of spatial analysis can be followed by site visits by practitioners to assess the situation on the ground in terms of the presence of infrastructures and behaviours (of all road users) that may be putting pedestrians at risk of injury or death. The remainder of the paper is organized as follows. The next section of this article discusses the background literature on determinants of pedestrian injury specific to children and seniors. This is followed by a detailed overview of the study area and a description of the data used in this study. The next section describes the study's research methods, which is followed by the empirical results. Finally, the findings of this paper are discussed and the research findings and the policy and planning implications are drawn into focus in the final section. 2. Literature review Walking requires a variety of cognitive skills, including visual examination, gap judgment, reaction time and understanding or at least anticipating the behaviour of other road users. At different ages, variation in these abilities may be critical to understanding and explaining injury risk. The cognitive and perceived risks associated with being a pedestrian and the unique characteristics and locational patterns associated with pedestrian injury within an urban environment, specifically in relation to children and seniors are outlined and discussed below. Research into the relationship between the built environment and child pedestrian injury suggests that features that either slow down traffic (e.g. traffic calming), separate children in space from traffic (e.g. playgrounds) or separate children in time (e.g. exclusive traffic-light phasing) decrease pedestrian injury risk (Rothman et al., 2013). The majority of child pedestrian injury occurs close to home (Ha and Thill, 2011; Lightstone et al., 2001), particularly on non-arterial, neighbourhood roads or local streets. Furthermore, child PMVCs are more common during mid-block crossings, producing more severe injuries (Rothman et al., 2012). As children age, the prevalence of severe injury on neighbourhood roads appears to decline (Rothman et al., 2010), and children are more likely to be involved in PMVCs at intersections (Koopmans et al., 2015). For elderly pedestrians, supportive walking environments are particularly important, as walking is a preferred form of physical activity for this age group (Eyler et al., 2003). There are several explanations to account for the heightened crash risk for older pedestrians. Older pedestrians are more exposed to potential collisions than younger people, as they tend to reduce or stop driving and are thus limited to walking (aided or unaided) or combine walking with public transportation (Oxley et al., 2004). Seniors are more likely to use signalized intersections than young pedestrians when they cross streets (Lightstone et al., 2001; Zegeer, 2002). This observation can be explained in part by the preference of older pedestrians (70 years and older), to cross at signalized intersections because they perceive that this type of crossing 2
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Fig. 1. Map of Toronto with the former municipality borders, and the classification of downtown and inner suburbs.
3. Study area and data
recognizes the need for targeted efforts for the increased safety of children and seniors, and provides detailed countermeasures specific to each population. While a geographical analysis was employed to identify areas with high numbers of collision and fatality events involving children and seniors, a major flaw in that analysis was that there was no attempt to model pedestrian exposure at locations with high pedestrian collision or fatality rates. Accordingly, there is little evidence to suggest that the geography of child and elderly pedestrian injury is adequately understood. Data on weekday motor vehicle collisions involving pedestrians that occurred in Toronto, between January 1, 2000 and December 31, 2011 were obtained from Motor Vehicle Collision Reports filed by the Toronto Police Services. Injury severity is recorded by the Toronto Police Service (TPS) using five categories (MTO, 2007): no injury; minimal injury: i.e., scrapes and bruises but no hospital visit; minor injury: hospital visit, treated in the emergency room but not admitted; major injury: requiring hospital admission; and fatal: person killed immediately or within 30 days of the collision. Injury severity is examined by comparing the spatial pattern of all PMVCs to ‘severe’ injury events (defined as major or fatal injury). Aggregation of major and fatal injuries was informed by previous research indicating that examining major injuries combined with fatal injuries results in the identification of locations distinguishable from places where minor injuries typically occur (San Francisco Department of Public Health, 2005; Sciortino et al., 2005). Furthermore the factors and circumstances that differentiate a fatal collision from a collision resulting in serious injury are minimal (City of Toronto, 2016). Weekday pedestrian injury events are the focus of this analysis because of expected differences between weekday and weekend activity patterns (Buliung et al., 2008). Age is categorized according to Statistics Canada's Life Cycle Groupings: children (0–14 years) and seniors (65 years and over). Rates were estimated for the two age groups. Injury patterns between Toronto's downtown and inner suburbs are particularly of interest, due in part to differences in urban design and transport mode share for commuting and other activities.
The City of Toronto is an interesting place to study traffic injury due in part to the presence of diversity in neighbourhood design from its core to its inner suburban neighbourhoods (Fig. 1). These stark differences in the built environment across Toronto are manifested in the commuting mode shares across the city. As of 2011, 11% of morning commute trips in the City of Toronto were by cycling and walking, however, this number increases to 31% in the original City of Toronto (classified as downtown in Fig. 1) (City of Toronto, 2016). Downtown refers to the original City of Toronto (prior to political amalgamation of the six original municipalities in 1998), and the inner suburbs include the suburban regions adjacent to or surrounding the downtown. The city hosts neighbourhood streets that can in some cases be dated to the colonial period, but also includes car-oriented modern neighbourhoods within its inner-suburbs, older neighbourhoods between the suburbs and the city centre, and several emerging post-industrial condominium neighbourhoods. Toronto is also Canada's largest city, and among the most ethno-culturally diverse cities globally. The City of Toronto has the highest pedestrian-motor vehicle collision (PMVC) rate among all Canadian cities (Toronto Public Health, 2012). Toronto pedestrians represent 52% of all fatalities from motor vehicle collisions, despite the presently low commute mode share of walking at 7% (Toronto Public Health, 2012). The city has experienced 15% more fatalities in the last five years, than during the previous five year time period (Moore, 2016). Due to the increasing number of pedestrian fatalities, the city is presently engaged in a heated debate about how to treat its pedestrian injury and death problem. In 2016, Toronto City Council adopted Toronto's newest Road Safety Plan: Vision Zero (City of Toronto, 2016). There was initially considerable confusion reported by the media, concerning the city's and the mayor's target for reduced injury and fatality (Moore, 2016). Through increased funding for pedestrian safety-related improvements, such as lower speed limits, roadway and intersection modifications, additional police enforcement and school safety zones, the plan initially targeted a 20% reduction in fatalities and serious injuries within a decade. The Road Safety Plan 3
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Therefore; spatial (or local) Empirical Bayes (EB) smoothing was used to stabilize local standardized ratios by “borrowing” information from surrounding zones (Waller and Gotway, 2004). In other words, because CT construction can often follow the road network, cases (events) may end up sitting on the boundary between multiple CTs. To accommodate for this issue, rates were smoothed. The spatial EB smoother corrects for variance instability, which is associated with rates that have a smallexpected number of events or a small population. Local EB smoothing maintains variability across the study area, as mean estimates are determined from neighbouring reference means rather than from a global mean (Waller and Gotway, 2004). Using the smoothed rates, global and local indicators of spatial association were estimated using Global and then the Local Moran's statistic (Anselin, 1995). Here, the goal is not to explore the efficacy of the myriad ways in which spatial autocorrelation can be studied, analysed, estimated, for that is a field of inquiry unto itself (Bailey and Gatrell, 1995; Bivand et al., 2008; Torabi, 2012; Waller and Gotway, 2004). Rather, the intention is to apply a local indicator of spatial association to gain insight into the varied geographies of traffic injury in the child and senior populations. Moran's I is a measure of the level of spatial autocorrelation between values observed in adjacent areas. Global cluster analysis provides a measure of the overall ‘global’ spatial clustering of standardized collision/morbidity ratios across the study area. The global Moran's I statistic ranges from − 1 (negative autocorrelation) to + 1 (positive spatial autocorrelation) and 0 implies absence of spatial autocorrelation (random distribution). Local cluster analysis provides a resulting cluster index for each CT, indicating if the standardized collision/morbidity ratio for a CT is closer to the value of its neighbours or to the average of the study area. The local Moran's I results were mapped to explore spatial patterns of injury and differences in the patterns and severity of injury across the child and elderly populations.
Fig. 2. Outline of main research methods.
4. Methods There were three main steps in the data analysis (Fig. 2). Indirect standardization was first used to account for heterogeneity in the population at risk, and to identify Census Tracts (CTs) where there were either greater or fewer collisions or injuries observed in the study population than expected. Census Tracts (CTs) are part of Canada's national census geography, and are described in greater detail later in this section. Spatial Empirical Bayes smoothing was conducted to stabilize local standardized ratios and consider spatial dependence, by accounting for collisions or injuries occurring in surrounding CTs. Finally, global followed by local spatial autocorrelation tests were conducted, with the resulting local clusters are mapped to explore the spatial pattern of PMVCs and injury events for children and seniors in Toronto (Fig. 2). Using residential population data from the 2006 Canadian Census, indirect age-standardized rates were estimated to account for heterogeneity in the population at risk. Standardized rates were used to allow for comparisons of PMVCs and injury rates involving children and senior populations across Toronto's CTs. Census tracts were chosen as the spatial unit of analysis. CTs in Toronto (n = 528) are small areas, with generally homogenous environmental and urban design features, with a population between 2500 and 8000 persons. CT boundaries are delineated along permanent and easily recognizable physical features, such as the road network. Using residential population as a measure of exposure was appropriate for the particular populations in this study, because weekday collisions are likely to occur close to home for children (Ha and Thill, 2011; Joly et al., 1991; Lightstone et al., 2001). Similarly PMVCs involving seniors tend to occur on regular trips, generally also occurring close to home (Oxley et al., 2004), and older adults tend to take shorter trips, closer to home (Rosenbloom, 2004). Indirectly standardized age-specific rates were estimated for the standard population (the City of Toronto) and applied to the study population (each census tract) to determine the expected number of events. Using the age-specific rates, the observed number of events in the study population was divided by the expected number of events to determine the standardized collision/morbidity ratio. Standardized collision ratios (all PMVC events) and standardized morbidity ratios (SMR) (all severe events) indicate a relative excess (values > 1) or deficit (values between 0 and 1) in the actual number of collisions or injuries observed in the study population on the basis of the rates observed for the standard population. An excess number of collisions, indicates that given the population structure of that CT, the number of PMVCs or injuries observed was greater than expected. Collision events may occur at the intersection of multiple CTs.
5. Results The standardized collision ratios and SMRs indicated levels of clustering in the spatial variation of injury intensity across Toronto. Results of the global Moran's I analysis were as follows: children's standardized collision ratio was 0.489, children's SMR was 0.603, seniors' standardized collision ratio was 0.335 and seniors' SMR was 0.274 indicating significant (p < 0.001) positive spatial autocorrelation. These results indicate that PMVCs and injuries involving children are more spatially clustered across the City of Toronto, whereas the global Moran's I values for seniors indicate a more dispersed pattern. To determine where the clusters were located, the local Moran's I cluster maps are shown below for children and seniors (Figs. 3–4), showing evidence of statistically significant clustering (p < 0.05). These figures display distinct patterns of collisions/injuries between the child and elderly populations. The classification scheme of the local Moran's I results is as follows, high-high indicates clustering of high values of standardized collision/morbidity ratios (positive spatial autocorrelation); low-high indicates that low values were adjacent to high values of standardized ratios; low-low indicates clustering of low values of standardized ratios; high-low indicates that high values were adjacent to areas of low values; and not significant indicates that there was no spatial autocorrelation. High-standardized collision ratios for children appear to be concentrated toward central Toronto and toward the north-western neighbourhoods of the city (Fig. 3). There is a predominant clustering pattern along the east side of the West Toronto Rail Corridor, which is the rail corridor displayed in Fig. 3. Shifting the focus to children's SMR results reveals a greater number of areas with high values of injury, primarily distributed within the periphery of the inner suburbs as well as bordering around the West Toronto Rail Corridor. Additionally, there is a significant clustering pattern of high SMR values in the south-east end of Toronto. 4
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FIG. 3. Local Moran's I cluster map results of children's standardized collision ratios and morbidity ratios.
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FIG. 4. Local Moran's I cluster map results of seniors' standardized collision ratios and morbidity ratios.
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number of pedestrian collisions and injuries involving seniors in the CBD was similarly reported by (O'Hern et al., 2015), and the authors speculated that this is related to high levels of pedestrian and vehicle activity, which highlights the need for greater separation of modes and greater prioritization of pedestrian movements. Further investigation into the circumstances immediately prior to the occurrence of PMVCs involving seniors, particularly in the CBD, is warranted for effective prevention strategies. Future research would likely be most successful if conducted using a mixed methods approach where seniors share their walking experiences and identify how mobility for the elderly population can be enhanced in ways that are both safe and practical. This approach would ideally develop a deeper understanding of issues associated with constructing safe walking environments and policy recommendations to improve walkability for the senior population, which is expected to improve walking conditions for all residents. Differences in PMVCs and injury risk by age were also noted across Toronto's urban to inner suburban divide. Fatal and major injury events involving children and seniors appear to be more concentrated toward and within Toronto's inner suburbs, particularly for children. This result is consistent with a study of various counties across the United States that found that urban sprawl is a significant risk factor for traffic fatalities, especially for pedestrians (Ewing et al., 2003). Vehicle speed may be an important contributor to the increased risk of fatalities between the inner suburbs and the downtown core. Sprawling areas tend to have wide, long streets that encourage excessive speed, which directly increases the chance of being killed when struck by a vehicle (Ewing et al., 2003). The high prevalence of severe injuries found in Toronto's inner suburbs may be indicative of injury risks associated with the neighbourhood design somewhat typical of urban sprawl, as described by Ewing et al. (2003). Countermeasures, such as a reduction in the width of traffic lanes, a reduction in the number of lanes and replacing the space with bicycle lanes or wider sidewalks, or traffic calming measures are recommended to mitigate the number of severe injuries in suburban neighbourhoods. Additionally, such interventions should be prioritized during reconstruction projects of existing roads in the inner suburbs, by ensuring that careful consideration of pedestrians, particularly children and seniors, are made. The geographical analysis approach of this study can be used to enhance the effectiveness of injury prevention programs by identifying places of potentially high risk, even when contextual and a broader range of compositional factors that could explain underlying patterns of injury are unknown (Yiannakoulias et al., 2003). This research indicates that children and seniors have different spatial patterns of injury, which supports previous studies that have emphasized the potential for age-based guidance for pedestrian safety interventions into the built environment, for example near schools or playgrounds (Koopmans et al., 2015). Furthermore, the clustering patterns found in this analysis indicate that there is an inequitable spatial distribution of pedestrian collision and injury risk, particularly for children, providing evidence of spatial inequality in child pedestrian injuries across the City of Toronto. The level of dispersion of PMVCs and injuries involving seniors suggests the importance of adopting planning and policy decisions that are more considerate of the physical and cognitive difficulties seniors face as a pedestrian in an urban environment. The methodology adopted in this study is an important first step in understanding the complex geography of pedestrian collisions and severe injuries, and this work must be followed by in depth analyses to better understand what is happening in the high-risk CTs, using methods such as monitoring traffic conflicts and interactions (Hydén, 2016), in order to plan safety interventions accordingly. One limitation of this study is the use of residential population data to measure pedestrian exposure. This measure of pedestrian exposure is arguably best suited to the analysis of children and seniors, as previous research has found that these populations are more likely to be involved in PMVCs close to home (Ha and Thill, 2011; Joly et al., 1991; Lightstone et al., 2001; Oxley et al., 2004). This is unlikely the case for
High standardized collision ratios for seniors are highly concentrated in the downtown core, specifically within Toronto's central business district (CBD). Many of the census tracts with evidence of clustering of pedestrian collisions involving seniors are characterized as Toronto's most densely populated neighbourhoods. However, the cluster analysis of high SMR values reveals the addition of clusters outside the CBD, in the periphery of the inner suburbs and similar to children, along the West Toronto Rail Corridor. These clusters identify areas in Toronto where there appears to be a greater number of pedestrian severe injuries and fatalities than would be expected given the population of seniors. Accordingly, the locations of high-high clustering identified in this analysis should be carefully examined to develop appropriate strategies for safety intervention. 6. Discussion and conclusions This article reports on an exploratory spatial analysis of pedestrian motor vehicle collisions involving children and seniors. Study findings indicate unique spatial patterns of both collisions and severe and fatal injuries between the child and senior populations. Clearly omnibus interventions that fail to acknowledge diversity within the pedestrian population may fall flat. Geography and social and demographic differences should be considered to adequately develop safety interventions. Children and seniors appear to be injured in different parts of the city, the determinants of such outcomes may also vary geographically and across the child and senior populations. Planning or traffic safety goals for injury and fatality reduction should translate to thoughtful interventions that acknowledge local variation in injury outcomes within the population of vulnerable road users. High standardized collision ratios for children appear to be concentrated toward central downtown Toronto and toward the northwestern neighbourhoods of the city. This clustering pattern is predominantly located along the east side of the West Toronto Rail Corridor. However, there is a greater level of dispersion of high SMR clusters, primarily distributed within the periphery of the inner suburbs. The apparent clustering of high SMRs in the periphery of the downtown core and toward the inner suburbs are likely indicative of concentrations of high child populations, where children are walking in greater proportions than in the downtown. Furthermore, children in these areas may be walking or playing independent of adults in greater numbers. The concentration of severe injury events involving children in the inner suburbs is consistent with studies that have found that children from lower income families cross more roads, encounter higher vehicle volume and have a greater risk of injury (Morency et al., 2012). Residential communities neighbouring the West Toronto Rail Corridor, where a predominant clustering pattern of PMVCs and injuries were detected, have a high proportion of children living below the low-income cut-off (City of Toronto, 2015). Further attention is warranted to explore the presence/absence of protective infrastructures in that corridor (such as a lack of green space or recreational space to play) (Collins and Kearns, 2005), and to examine institutional and political roles, processes and responsibilities associated with the infrastructure piece. Moreover, attention should be given to understanding social processes or practices contributing to greater PMVC risk related to supervision, independence, and play (Haynes et al., 2003). The cluster analysis of PMVCs involving seniors reveals that high standardized collision ratios are highly concentrated in the downtown core, specifically the central business district (CBD). However, the cluster analysis of high SMR values reveals the addition of clusters outside the CBD, in the periphery of the inner suburbs and similar to children, along the West Toronto Rail Corridor. The cluster of high SMRs in the CBD is potentially a result of amenities or health and social services located downtown that attracts walking trips for seniors where the walking environment is not supportive of elderly pedestrians. It is important to note, that high SIR and SMR rates in the CBD is in part related to low populations of seniors living in the CBD, however a high 7
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Roberts, S.E., Vingilis, E., Wilk, P., Seeley, J., 2008. A comparison of self-reported motor vehicle collision injuries compared with official collision data: an analysis of age and sex trends using the Canadian National Population Health Survey and transport Canada data. Accid. Anal. Prev. 40 (2), 559–566. Rosen, E., Stigson, H., Sander, U., 2011. Literature review of pedestrian fatality risk as a function of car impact speed. Accid. Anal. Prev. 43 (1), 25–33. Rosenbloom, S., 2004. Mobility of the elderly. Transp. Aging Soc. 3–21. Rothman, L., Slater, M., Meaney, C., Howard, A., 2010. Motor vehicle and pedestrian collisions: burden of severe injury on major versus neighborhood roads. Traffic Inj. Prev. 11 (1), 43–47. Rothman, L., Howard, A., Camden, A., Macarthur, C., 2012. Pedestrian crossing location influences injury severity in urban areas. Inj. Prev. http://dx.doi.org/10.1136/ injuryprev-2011-040246. Rothman, L., Buliung, R., Macarthur, C., To, T., Howard, A., 2013. Walking and child pedestrian injury: a systematic review of built environment correlates of safe walking. Inj. Prev 10.1136/injuryprev-2012-040701. San Francisco Department of Public Health, 2005. Profile of Injury in San Francisco. (Retrieved from San Francisco Injury Center, CA). Sciortino, S., Vassar, M., Radetsky, M., Knudson, M.M., 2005. San Francisco pedestrian injury surveillance: mapping, under-reporting, and injury severity in police and hospital records. Accid. Anal. Prev. 37 (6), 1102–1113. Torabi, M., 2012. Spatial disease cluster detection: an application to childhood asthma in Manitoba, Canada. J. Biom. Biostat.(7). Toronto Public Health, 2012. Road to Health: Improving Walking and Cycling in Toronto. (Retrieved from). Transport Canada, 2011. Road Safety in Canada. Retrieved from. https://www.tc.gc.ca/ media/documents/roadsafety/tp15145e.pdf. Waller, L.A., Gotway, C.A., 2004. Applied Spatial Statistics for Public Health Data. vol. 368 John Wiley & Sons. Wier, M., Weintraub, J., Humphreys, E., Seto, E., Bhatia, R., 2009. An area-level model of vehicle-pedestrian injury collisions with implications for land use and transportation
youth and adults who generally have larger activity spaces and are thus are less likely to be injured in the CT in which they reside. Furthermore, to determine whether low risk of injury is an indication of a highly walkable and safe environment or a result of very low walking rates requires highly disaggregate pedestrian volume data. Data of this sort, and particularly for non-work travel, are not available with sufficient geographical or temporal coverage for the study area. The Canada Census population data used here are readily accessible and reliable (Greene-Roesel et al., 2010). In the absence of pedestrian volume data, for example at intersections, Census population counts effectively adjust for differences in the underlying residential population, while also providing a crude adjustment of residential vehicle volume, as a function of population density (Greene-Roesel et al., 2010). The police-reported collision data employed in this analysis has two commonly identified limitations associated with its use that are important to note. The first of which is underreporting of incidence, which has the potential to produce biased estimates as the data available only involves individuals in either collisions reported to the police or who received treatment in a hospital (Roberts et al., 2008). Agran et al. (1990) conducted a study in San Diego County, California, that compared police reports to a hospital monitoring system to identify limitations of police databases. It was found that police under-reported the number of injured pedestrians by at least 20%. Similarly, in San Francisco police collision reports underestimated the number of injured pedestrians by 21% (Sciortino et al., 2005). The second limitation associated with the use of police report data is that the operational definition of injuries can be inaccurate (Roberts et al., 2008). A reporting officer uses best judgment to record injury severity following a PMVC, rather than by a medical professional following an examination. Furthermore, the frequency of delayed injuries, injuries that develop or become more severe after the initial collision, is unknown. Police collision reports remain a comprehensive resource for geographic information, and are an indispensable source of data (Agran et al., 1990), however some suggest that surveillance efforts should include greater linkages with hospital data to increase case ascertainment and to produce better assessment of health outcomes (Sciortino et al., 2005). Acknowledgements The authors would like to thank Michael Brady (City of Toronto) for providing the data. References Agran, P.F., Castillo, D.N., Winn, D.G., 1990. Limitations of data compiled from police reports on pediatric pedestrian and bicycle motor vehicle events. Accid. Anal. Prev. 22 (4), 361–370. Anselin, L., 1995. Local indicators of spatial association—LISA. Geogr. Anal. 27 (2), 93–115. Bailey, T., Gatrell, A., 1995. Interactive spatial data analysis. vol. 413 Longman Scientific & Technical Essex. Bernhoft, I., Carstensen, G., 2008. Preferences and behaviour of pedestrians and cyclists by age and gender. Transport. Res. F: Traffic Psychol. Behav. 11 (2), 83–95. Bivand, R., Pebesma, E., Gomez-Rubio, V., Pebesma, E., 2008. Applied Spatial Data Analysis With R. vol. 747248717 Springer. Buliung, R., Roorda, M., Remmel, T., 2008. Exploring spatial variety in patterns of activity-travel behaviour: initial results from the Toronto travel-activity panel survey (TTAPS). Transportation 35 (6), 697. City of Toronto, 2015. Children Living in Poverty, Proportion of Children Living Below LICO. Retrieved from. http://www.toronto.ca/reportcardonchildren/gmap_lico.htm. City of Toronto, 2016. Road Safety Plan (RSP) 2017–2021. Retrieved from. https:// www1.toronto.ca/City%20Of%20Toronto/Transportation%20Services/VisionZero/ Links/2017%20Vision%20Zero%20Road%20Safety%20Plan.pdf. Collins, D.C., Kearns, R.A., 2005. Geographies of inequality: child pedestrian injury and walking school buses in Auckland, New Zealand. Soc. Sci. Med. 60 (1), 61–69. Dumbaugh, E., Rae, R., 2009. Safe urban form: revisiting the relationship between community design and traffic safety. J. Am. Plan. Assoc. 75 (3), 309–329. Dunbar, G., Holland, C.A., Maylor, E.A., 2004. Older Pedestrians: A Critical Review of the Literature. Ewing, R., Dumbaugh, E., 2009. The built environment and traffic safety a review of empirical evidence. J. Plan. Lit. 23 (4), 347–367. Ewing, R., Schieber, R.A., Zegeer, C.V., 2003. Urban sprawl as a risk factor in motor
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D.C., 2003. Zones of prevention: the geography of fall injuries in the elderly. Soc. Sci. Med. 57 (11), 2065–2073. Zeedyk, M., Wallace, L., Carcary, B., Jones, K., Larter, K., 2001. Children and road safety: increasing knowledge does not improve behaviour. Br. J. Educ. Psychol. 71 (4), 573–594. Zegeer, C., 2002. Pedestrian Facilities Users Guide: Providing Safety and Mobility. Federal Highway Administration, Washington, DC.
planning. Accid. Anal. Prev. 41 (1), 137–145. World Health Organization, 2015. Global Status Report on Road Safety. pp. 2015. Retrieved from. http://www.who.int/violence_injury_prevention/road_safety_ status/2015/en/. Yao, J., Yang, J., Otte, D., 2008. Investigation of head injuries by reconstructions of realworld vehicle-versus-adult-pedestrian accidents. Saf. Sci. 46 (7), 1103–1114. Yiannakoulias, N., Rowe, B.H., Svenson, L.W., Schopflocher, D.P., Kelly, K., Voaklander,
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Contents lists available at ScienceDirect
Journal of Transport Geography journal homepage: www.elsevier.com/locate/jtrangeo
A geography of child and elderly pedestrian injury in the City of Toronto, Canada Emily Griséa,⁎,1, Ron Buliunga, Linda Rothmanb, Andrew Howardc,d a
Department of Geography and Programs in Environment, University of Toronto Mississauga, 3359 Mississauga Road, Mississauga, ON L5L 1C6, Canada Faculty of Health-School of Kinesiology & Health Science, York University, Norman Bethune College, Canada c Child Health Evaluative Sciences, Departments of Surgery & Health Policy, Management & Evaluation, University of Toronto, Canada d Orthopedic Surgery, The Hospital for Sick Children, Canada b
A R T I C L E I N F O
A B S T R A C T
Keywords: Pedestrian motor vehicle collisions Age Spatial analysis Built environment
Walking is one of the most accessible forms of physical activity for people of all ages. Promoting increased walking for transport may contribute to reduced air pollution, noise and traffic congestion. Understanding the geography of pedestrian motor vehicle collisions (PMVCs) can provide evidence to inform policy and planning that targets increased walking while reducing pedestrian injury risk, however age-related differences in the geography of injury are expected given differences in activity patterns and physical and cognitive abilities. The purpose of this paper is to explore spatial patterns of pedestrian motor vehicle collisions (PMVCs) by age, injury severity, and location in Canada's largest city, the City of Toronto. Geographical variation in PMVCs and injuries by age (namely seniors and children) and severity were explored using indirect standardized rates. Moran's I statistics were estimated to study the spatial clustering of PMVCs across urban and inner suburban neighbourhoods. Distinct spatial patterns of PMVCs and injuries were evident among children and seniors. While evidence of spatial clustering was indicated for both age groups, children's injuries revealed the strongest clustering, while PMVCs involving seniors were more dispersed. Furthermore, fatal and major injury events appeared to be concentrated toward and within Toronto's inner suburbs for both age groups. Findings from this study demonstrate the importance of planning pedestrian safety interventions that acknowledge spatial differences in geographic patterns of PMVCs by age.
1. Introduction Walking for transport has the potential to contribute to reduced air pollution, noise and traffic congestion, while also providing a form of physical activity that is widely accessible for individuals of all ages. While such benefits may accumulate, to the individual and broader society, without question the act of walking in many cities presents some risk of injury and even fatality, particularly in the presence of a modernist legacy of planning for and accommodating automobility. These risks, and injury outcomes are unevenly distributed over space and across the population. Walking also requires a variety of cognitive skills, including reaction time and understanding or anticipating the behaviour of other road users. The design of road networks can further complicate and potentially endanger the safety of pedestrians, particularly in urban regions with road designs that favour automobile traffic flow (Dumbaugh and Rae, 2009). Furthermore, the complexity of the road environment, particularly in areas with high vehicle volumes
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and speeds, creates potentially dangerous situations for older pedestrians (O'Hern et al., 2015) and children (Zeedyk et al., 2001). Road traffic injury is the single largest cause of years of life lost (YLL) (17%) in children and youth in Canada (Institute for Health Metrics and Evaluation, 2013). Among all types of road traffic injury, child and youth pedestrian injury accounts for 25% of total injuries. In regard to seniors, their overrepresentation among pedestrian motor vehicle collisions (PMVCs) is alarming. According to a 2012 report produced by the International Transport Forum, individuals aged 65 years represented up to 50% of injured pedestrians in OECD countries (International Transport Forum (ITF), 2012). Specifically in Canada, individuals over the age of 65 represented 35% of the pedestrian fatalities between the years 2004–2008, despite this age group only representing 13% of the population (Transport Canada, 2011). However in the City of Toronto, Canada's largest city, between the years 2011–2015, older pedestrians (55 + years of age) comprised 63% of fatalities despite their relatively low representation in the population
Corresponding author at: Department of Geography and Programs in Environment, University of Toronto Mississauga, 3359 Mississauga Road, Mississauga, ON L5L 1C6, Canada. E-mail addresses: [email protected] (E. Grisé), [email protected] (R. Buliung), [email protected] (L. Rothman), [email protected] (A. Howard). Present address: School of Urban Planning, McGill University, Suite 400, 815 Sherbrooke St. W., Montréal, Québec, H3A 0C2, Canada
http://dx.doi.org/10.1016/j.jtrangeo.2017.10.003 Received 14 July 2016; Received in revised form 2 October 2017; Accepted 11 October 2017 0966-6923/ © 2017 Elsevier Ltd. All rights reserved.
Please cite this article as: Grisé, E., Journal of Transport Geography (2017), http://dx.doi.org/10.1016/j.jtrangeo.2017.10.003
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is safer, and they feel it is dangerous to cross the road where these facilities are missing (Bernhoft and Carstensen, 2008). Despite the perception of safety at intersections, a high proportion of pedestrian injuries involving seniors occur at signalized intersections. Specifically, in a review of pedestrian fatalities that occurred across Canada between 2004 and 2008, 63% of individuals who were involved in a fatal collision at intersections were aged 65 years and older (Transport Canada, 2011). Reduced walking speeds of older adults increase exposure levels to vehicle traffic. The reduced physical mobility and perceptual and cognitive functions of some of the elderly also affects their judgment and their ability to safely crossing streets (Oxley et al., 2004; Oxley et al., 1997). With regard to environmental risk factors, two primary determinants of pedestrian injury include vehicle and pedestrian volume (Lee and Abdel-Aty, 2005; Miranda-Moreno et al., 2011; Wier et al., 2009). Urban development patterns and urban design impact safety primarily through the traffic volumes they produce and attract, and secondarily through the allowable speed limits or the traffic speeds they inadvertently encourage (Ewing and Dumbaugh, 2009). Traffic speed is a critical predictor of pedestrian injury severity and the likelihood of suffering a fatal injury, and it is generally accepted that the chance of survival decreases non-linearly with increasing vehicle speed (Rosen et al., 2011). Accordingly, fatality risk is severely diminished at speeds less than or equal to 40 km/h. However, achieving slower speeds, even on residential streets, is known to be as much a political challenge more than anything else (Keenan, 2017). While speed remains a critical risk factor for PMVCs and fatality (Peden, 2004), children and seniors are particularly vulnerable to a severe injury outcome in the event of a collision with a vehicle. Children may be impacted differently due to their physical size. As a result of the short stature of a child, a vehicle may directly strike a child's head or vital organs resulting in a more severe injury outcome regardless of speed. In adults, a vehicle's windshield and its frame are the main source of head injuries in PMVCs, which can cause severe brain injuries and lead to lifelong disability or death (Yao et al., 2008). While vehicle speed is a critical predictor of the severity of injury sustained after a collision, pedestrians over the age of 65 experience higher injury rates than younger people at all speeds (Henary et al., 2006). Therefore, while speed remains a critical factor of the severity of injury following an accident for these two populations, emphasis must simultaneously be placed on reducing potential conflicts with vehicles, particularly in areas where there is a high presence of children and seniors. A limitation of the literature discussed above and within the broader field of pedestrian planning, is that there is insufficient evidence of the geography of pedestrian injury. While it is imperative for research to continue to expand our knowledge on the determinants of injury to develop evidence to support effective interventions, planners, policy makers, and injury epidemiologists should probe more deeply into the geographies of injury risk and outcomes, because the processes that produce injury are likely to be geographically and temporally uneven. Understanding the geography of injury production and reduction, is helpful knowledge, particularly for those working in the urban professions who wrestle with the fiscal, political and design challenges that are often folded into discussions about the prioritization and targeting of spending in both the fixed capital and operational domains. Accordingly, this paper presents an exploratory spatial analysis of pedestrian injury by age and severity, with a view to contributing to a global conversation about urban traffic injury among vulnerable road users. With the majority of the world's population concentrated in urbanized areas, and with the global burden of traffic injury on the rise (Organisation for Economic Co-operation and Development, 1998; World Health Organization, 2015), it is particularly salient to contribute to a conversation about where traffic injury occurs within major global cities.
(26%) (City of Toronto, 2016). The focus on vulnerable road users such as children and the elderly is particularly salient given the unique physical and cognitive aspects of these populations that shape their injury risks. The literature on child pedestrian injury risk factors indicates that children experience unique risk factors and exhibit distinct locational patterns of injury (Ha and Thill, 2011; Koopmans et al., 2015; Lightstone et al., 2001; Rothman et al., 2012), which appear to differ from locational patterns of injury involving seniors (Dunbar et al., 2004; Oxley et al., 2004; Zegeer, 2002). Accordingly, locational patterns of collisions involving children and seniors' should be examined separately, as it is hypothesized that the geographic distribution of pedestrian injury risks among children and seniors will also differ. Accordingly, this research explores spatial patterns of PMVCs involving children and seniors using the City of Toronto as a case study. Results of this study are intended to provide planners, engineers and policy makers with a better understanding of the geographical locations of high risk for child and elderly pedestrian injury, to enable the development of effective age-based interventions in the built environment. This sort of spatial analysis can be followed by site visits by practitioners to assess the situation on the ground in terms of the presence of infrastructures and behaviours (of all road users) that may be putting pedestrians at risk of injury or death. The remainder of the paper is organized as follows. The next section of this article discusses the background literature on determinants of pedestrian injury specific to children and seniors. This is followed by a detailed overview of the study area and a description of the data used in this study. The next section describes the study's research methods, which is followed by the empirical results. Finally, the findings of this paper are discussed and the research findings and the policy and planning implications are drawn into focus in the final section. 2. Literature review Walking requires a variety of cognitive skills, including visual examination, gap judgment, reaction time and understanding or at least anticipating the behaviour of other road users. At different ages, variation in these abilities may be critical to understanding and explaining injury risk. The cognitive and perceived risks associated with being a pedestrian and the unique characteristics and locational patterns associated with pedestrian injury within an urban environment, specifically in relation to children and seniors are outlined and discussed below. Research into the relationship between the built environment and child pedestrian injury suggests that features that either slow down traffic (e.g. traffic calming), separate children in space from traffic (e.g. playgrounds) or separate children in time (e.g. exclusive traffic-light phasing) decrease pedestrian injury risk (Rothman et al., 2013). The majority of child pedestrian injury occurs close to home (Ha and Thill, 2011; Lightstone et al., 2001), particularly on non-arterial, neighbourhood roads or local streets. Furthermore, child PMVCs are more common during mid-block crossings, producing more severe injuries (Rothman et al., 2012). As children age, the prevalence of severe injury on neighbourhood roads appears to decline (Rothman et al., 2010), and children are more likely to be involved in PMVCs at intersections (Koopmans et al., 2015). For elderly pedestrians, supportive walking environments are particularly important, as walking is a preferred form of physical activity for this age group (Eyler et al., 2003). There are several explanations to account for the heightened crash risk for older pedestrians. Older pedestrians are more exposed to potential collisions than younger people, as they tend to reduce or stop driving and are thus limited to walking (aided or unaided) or combine walking with public transportation (Oxley et al., 2004). Seniors are more likely to use signalized intersections than young pedestrians when they cross streets (Lightstone et al., 2001; Zegeer, 2002). This observation can be explained in part by the preference of older pedestrians (70 years and older), to cross at signalized intersections because they perceive that this type of crossing 2
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Fig. 1. Map of Toronto with the former municipality borders, and the classification of downtown and inner suburbs.
3. Study area and data
recognizes the need for targeted efforts for the increased safety of children and seniors, and provides detailed countermeasures specific to each population. While a geographical analysis was employed to identify areas with high numbers of collision and fatality events involving children and seniors, a major flaw in that analysis was that there was no attempt to model pedestrian exposure at locations with high pedestrian collision or fatality rates. Accordingly, there is little evidence to suggest that the geography of child and elderly pedestrian injury is adequately understood. Data on weekday motor vehicle collisions involving pedestrians that occurred in Toronto, between January 1, 2000 and December 31, 2011 were obtained from Motor Vehicle Collision Reports filed by the Toronto Police Services. Injury severity is recorded by the Toronto Police Service (TPS) using five categories (MTO, 2007): no injury; minimal injury: i.e., scrapes and bruises but no hospital visit; minor injury: hospital visit, treated in the emergency room but not admitted; major injury: requiring hospital admission; and fatal: person killed immediately or within 30 days of the collision. Injury severity is examined by comparing the spatial pattern of all PMVCs to ‘severe’ injury events (defined as major or fatal injury). Aggregation of major and fatal injuries was informed by previous research indicating that examining major injuries combined with fatal injuries results in the identification of locations distinguishable from places where minor injuries typically occur (San Francisco Department of Public Health, 2005; Sciortino et al., 2005). Furthermore the factors and circumstances that differentiate a fatal collision from a collision resulting in serious injury are minimal (City of Toronto, 2016). Weekday pedestrian injury events are the focus of this analysis because of expected differences between weekday and weekend activity patterns (Buliung et al., 2008). Age is categorized according to Statistics Canada's Life Cycle Groupings: children (0–14 years) and seniors (65 years and over). Rates were estimated for the two age groups. Injury patterns between Toronto's downtown and inner suburbs are particularly of interest, due in part to differences in urban design and transport mode share for commuting and other activities.
The City of Toronto is an interesting place to study traffic injury due in part to the presence of diversity in neighbourhood design from its core to its inner suburban neighbourhoods (Fig. 1). These stark differences in the built environment across Toronto are manifested in the commuting mode shares across the city. As of 2011, 11% of morning commute trips in the City of Toronto were by cycling and walking, however, this number increases to 31% in the original City of Toronto (classified as downtown in Fig. 1) (City of Toronto, 2016). Downtown refers to the original City of Toronto (prior to political amalgamation of the six original municipalities in 1998), and the inner suburbs include the suburban regions adjacent to or surrounding the downtown. The city hosts neighbourhood streets that can in some cases be dated to the colonial period, but also includes car-oriented modern neighbourhoods within its inner-suburbs, older neighbourhoods between the suburbs and the city centre, and several emerging post-industrial condominium neighbourhoods. Toronto is also Canada's largest city, and among the most ethno-culturally diverse cities globally. The City of Toronto has the highest pedestrian-motor vehicle collision (PMVC) rate among all Canadian cities (Toronto Public Health, 2012). Toronto pedestrians represent 52% of all fatalities from motor vehicle collisions, despite the presently low commute mode share of walking at 7% (Toronto Public Health, 2012). The city has experienced 15% more fatalities in the last five years, than during the previous five year time period (Moore, 2016). Due to the increasing number of pedestrian fatalities, the city is presently engaged in a heated debate about how to treat its pedestrian injury and death problem. In 2016, Toronto City Council adopted Toronto's newest Road Safety Plan: Vision Zero (City of Toronto, 2016). There was initially considerable confusion reported by the media, concerning the city's and the mayor's target for reduced injury and fatality (Moore, 2016). Through increased funding for pedestrian safety-related improvements, such as lower speed limits, roadway and intersection modifications, additional police enforcement and school safety zones, the plan initially targeted a 20% reduction in fatalities and serious injuries within a decade. The Road Safety Plan 3
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Therefore; spatial (or local) Empirical Bayes (EB) smoothing was used to stabilize local standardized ratios by “borrowing” information from surrounding zones (Waller and Gotway, 2004). In other words, because CT construction can often follow the road network, cases (events) may end up sitting on the boundary between multiple CTs. To accommodate for this issue, rates were smoothed. The spatial EB smoother corrects for variance instability, which is associated with rates that have a smallexpected number of events or a small population. Local EB smoothing maintains variability across the study area, as mean estimates are determined from neighbouring reference means rather than from a global mean (Waller and Gotway, 2004). Using the smoothed rates, global and local indicators of spatial association were estimated using Global and then the Local Moran's statistic (Anselin, 1995). Here, the goal is not to explore the efficacy of the myriad ways in which spatial autocorrelation can be studied, analysed, estimated, for that is a field of inquiry unto itself (Bailey and Gatrell, 1995; Bivand et al., 2008; Torabi, 2012; Waller and Gotway, 2004). Rather, the intention is to apply a local indicator of spatial association to gain insight into the varied geographies of traffic injury in the child and senior populations. Moran's I is a measure of the level of spatial autocorrelation between values observed in adjacent areas. Global cluster analysis provides a measure of the overall ‘global’ spatial clustering of standardized collision/morbidity ratios across the study area. The global Moran's I statistic ranges from − 1 (negative autocorrelation) to + 1 (positive spatial autocorrelation) and 0 implies absence of spatial autocorrelation (random distribution). Local cluster analysis provides a resulting cluster index for each CT, indicating if the standardized collision/morbidity ratio for a CT is closer to the value of its neighbours or to the average of the study area. The local Moran's I results were mapped to explore spatial patterns of injury and differences in the patterns and severity of injury across the child and elderly populations.
Fig. 2. Outline of main research methods.
4. Methods There were three main steps in the data analysis (Fig. 2). Indirect standardization was first used to account for heterogeneity in the population at risk, and to identify Census Tracts (CTs) where there were either greater or fewer collisions or injuries observed in the study population than expected. Census Tracts (CTs) are part of Canada's national census geography, and are described in greater detail later in this section. Spatial Empirical Bayes smoothing was conducted to stabilize local standardized ratios and consider spatial dependence, by accounting for collisions or injuries occurring in surrounding CTs. Finally, global followed by local spatial autocorrelation tests were conducted, with the resulting local clusters are mapped to explore the spatial pattern of PMVCs and injury events for children and seniors in Toronto (Fig. 2). Using residential population data from the 2006 Canadian Census, indirect age-standardized rates were estimated to account for heterogeneity in the population at risk. Standardized rates were used to allow for comparisons of PMVCs and injury rates involving children and senior populations across Toronto's CTs. Census tracts were chosen as the spatial unit of analysis. CTs in Toronto (n = 528) are small areas, with generally homogenous environmental and urban design features, with a population between 2500 and 8000 persons. CT boundaries are delineated along permanent and easily recognizable physical features, such as the road network. Using residential population as a measure of exposure was appropriate for the particular populations in this study, because weekday collisions are likely to occur close to home for children (Ha and Thill, 2011; Joly et al., 1991; Lightstone et al., 2001). Similarly PMVCs involving seniors tend to occur on regular trips, generally also occurring close to home (Oxley et al., 2004), and older adults tend to take shorter trips, closer to home (Rosenbloom, 2004). Indirectly standardized age-specific rates were estimated for the standard population (the City of Toronto) and applied to the study population (each census tract) to determine the expected number of events. Using the age-specific rates, the observed number of events in the study population was divided by the expected number of events to determine the standardized collision/morbidity ratio. Standardized collision ratios (all PMVC events) and standardized morbidity ratios (SMR) (all severe events) indicate a relative excess (values > 1) or deficit (values between 0 and 1) in the actual number of collisions or injuries observed in the study population on the basis of the rates observed for the standard population. An excess number of collisions, indicates that given the population structure of that CT, the number of PMVCs or injuries observed was greater than expected. Collision events may occur at the intersection of multiple CTs.
5. Results The standardized collision ratios and SMRs indicated levels of clustering in the spatial variation of injury intensity across Toronto. Results of the global Moran's I analysis were as follows: children's standardized collision ratio was 0.489, children's SMR was 0.603, seniors' standardized collision ratio was 0.335 and seniors' SMR was 0.274 indicating significant (p < 0.001) positive spatial autocorrelation. These results indicate that PMVCs and injuries involving children are more spatially clustered across the City of Toronto, whereas the global Moran's I values for seniors indicate a more dispersed pattern. To determine where the clusters were located, the local Moran's I cluster maps are shown below for children and seniors (Figs. 3–4), showing evidence of statistically significant clustering (p < 0.05). These figures display distinct patterns of collisions/injuries between the child and elderly populations. The classification scheme of the local Moran's I results is as follows, high-high indicates clustering of high values of standardized collision/morbidity ratios (positive spatial autocorrelation); low-high indicates that low values were adjacent to high values of standardized ratios; low-low indicates clustering of low values of standardized ratios; high-low indicates that high values were adjacent to areas of low values; and not significant indicates that there was no spatial autocorrelation. High-standardized collision ratios for children appear to be concentrated toward central Toronto and toward the north-western neighbourhoods of the city (Fig. 3). There is a predominant clustering pattern along the east side of the West Toronto Rail Corridor, which is the rail corridor displayed in Fig. 3. Shifting the focus to children's SMR results reveals a greater number of areas with high values of injury, primarily distributed within the periphery of the inner suburbs as well as bordering around the West Toronto Rail Corridor. Additionally, there is a significant clustering pattern of high SMR values in the south-east end of Toronto. 4
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FIG. 3. Local Moran's I cluster map results of children's standardized collision ratios and morbidity ratios.
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FIG. 4. Local Moran's I cluster map results of seniors' standardized collision ratios and morbidity ratios.
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number of pedestrian collisions and injuries involving seniors in the CBD was similarly reported by (O'Hern et al., 2015), and the authors speculated that this is related to high levels of pedestrian and vehicle activity, which highlights the need for greater separation of modes and greater prioritization of pedestrian movements. Further investigation into the circumstances immediately prior to the occurrence of PMVCs involving seniors, particularly in the CBD, is warranted for effective prevention strategies. Future research would likely be most successful if conducted using a mixed methods approach where seniors share their walking experiences and identify how mobility for the elderly population can be enhanced in ways that are both safe and practical. This approach would ideally develop a deeper understanding of issues associated with constructing safe walking environments and policy recommendations to improve walkability for the senior population, which is expected to improve walking conditions for all residents. Differences in PMVCs and injury risk by age were also noted across Toronto's urban to inner suburban divide. Fatal and major injury events involving children and seniors appear to be more concentrated toward and within Toronto's inner suburbs, particularly for children. This result is consistent with a study of various counties across the United States that found that urban sprawl is a significant risk factor for traffic fatalities, especially for pedestrians (Ewing et al., 2003). Vehicle speed may be an important contributor to the increased risk of fatalities between the inner suburbs and the downtown core. Sprawling areas tend to have wide, long streets that encourage excessive speed, which directly increases the chance of being killed when struck by a vehicle (Ewing et al., 2003). The high prevalence of severe injuries found in Toronto's inner suburbs may be indicative of injury risks associated with the neighbourhood design somewhat typical of urban sprawl, as described by Ewing et al. (2003). Countermeasures, such as a reduction in the width of traffic lanes, a reduction in the number of lanes and replacing the space with bicycle lanes or wider sidewalks, or traffic calming measures are recommended to mitigate the number of severe injuries in suburban neighbourhoods. Additionally, such interventions should be prioritized during reconstruction projects of existing roads in the inner suburbs, by ensuring that careful consideration of pedestrians, particularly children and seniors, are made. The geographical analysis approach of this study can be used to enhance the effectiveness of injury prevention programs by identifying places of potentially high risk, even when contextual and a broader range of compositional factors that could explain underlying patterns of injury are unknown (Yiannakoulias et al., 2003). This research indicates that children and seniors have different spatial patterns of injury, which supports previous studies that have emphasized the potential for age-based guidance for pedestrian safety interventions into the built environment, for example near schools or playgrounds (Koopmans et al., 2015). Furthermore, the clustering patterns found in this analysis indicate that there is an inequitable spatial distribution of pedestrian collision and injury risk, particularly for children, providing evidence of spatial inequality in child pedestrian injuries across the City of Toronto. The level of dispersion of PMVCs and injuries involving seniors suggests the importance of adopting planning and policy decisions that are more considerate of the physical and cognitive difficulties seniors face as a pedestrian in an urban environment. The methodology adopted in this study is an important first step in understanding the complex geography of pedestrian collisions and severe injuries, and this work must be followed by in depth analyses to better understand what is happening in the high-risk CTs, using methods such as monitoring traffic conflicts and interactions (Hydén, 2016), in order to plan safety interventions accordingly. One limitation of this study is the use of residential population data to measure pedestrian exposure. This measure of pedestrian exposure is arguably best suited to the analysis of children and seniors, as previous research has found that these populations are more likely to be involved in PMVCs close to home (Ha and Thill, 2011; Joly et al., 1991; Lightstone et al., 2001; Oxley et al., 2004). This is unlikely the case for
High standardized collision ratios for seniors are highly concentrated in the downtown core, specifically within Toronto's central business district (CBD). Many of the census tracts with evidence of clustering of pedestrian collisions involving seniors are characterized as Toronto's most densely populated neighbourhoods. However, the cluster analysis of high SMR values reveals the addition of clusters outside the CBD, in the periphery of the inner suburbs and similar to children, along the West Toronto Rail Corridor. These clusters identify areas in Toronto where there appears to be a greater number of pedestrian severe injuries and fatalities than would be expected given the population of seniors. Accordingly, the locations of high-high clustering identified in this analysis should be carefully examined to develop appropriate strategies for safety intervention. 6. Discussion and conclusions This article reports on an exploratory spatial analysis of pedestrian motor vehicle collisions involving children and seniors. Study findings indicate unique spatial patterns of both collisions and severe and fatal injuries between the child and senior populations. Clearly omnibus interventions that fail to acknowledge diversity within the pedestrian population may fall flat. Geography and social and demographic differences should be considered to adequately develop safety interventions. Children and seniors appear to be injured in different parts of the city, the determinants of such outcomes may also vary geographically and across the child and senior populations. Planning or traffic safety goals for injury and fatality reduction should translate to thoughtful interventions that acknowledge local variation in injury outcomes within the population of vulnerable road users. High standardized collision ratios for children appear to be concentrated toward central downtown Toronto and toward the northwestern neighbourhoods of the city. This clustering pattern is predominantly located along the east side of the West Toronto Rail Corridor. However, there is a greater level of dispersion of high SMR clusters, primarily distributed within the periphery of the inner suburbs. The apparent clustering of high SMRs in the periphery of the downtown core and toward the inner suburbs are likely indicative of concentrations of high child populations, where children are walking in greater proportions than in the downtown. Furthermore, children in these areas may be walking or playing independent of adults in greater numbers. The concentration of severe injury events involving children in the inner suburbs is consistent with studies that have found that children from lower income families cross more roads, encounter higher vehicle volume and have a greater risk of injury (Morency et al., 2012). Residential communities neighbouring the West Toronto Rail Corridor, where a predominant clustering pattern of PMVCs and injuries were detected, have a high proportion of children living below the low-income cut-off (City of Toronto, 2015). Further attention is warranted to explore the presence/absence of protective infrastructures in that corridor (such as a lack of green space or recreational space to play) (Collins and Kearns, 2005), and to examine institutional and political roles, processes and responsibilities associated with the infrastructure piece. Moreover, attention should be given to understanding social processes or practices contributing to greater PMVC risk related to supervision, independence, and play (Haynes et al., 2003). The cluster analysis of PMVCs involving seniors reveals that high standardized collision ratios are highly concentrated in the downtown core, specifically the central business district (CBD). However, the cluster analysis of high SMR values reveals the addition of clusters outside the CBD, in the periphery of the inner suburbs and similar to children, along the West Toronto Rail Corridor. The cluster of high SMRs in the CBD is potentially a result of amenities or health and social services located downtown that attracts walking trips for seniors where the walking environment is not supportive of elderly pedestrians. It is important to note, that high SIR and SMR rates in the CBD is in part related to low populations of seniors living in the CBD, however a high 7
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vehicle occupant and pedestrian fatalities. Am. J. Public Health 93 (9), 1541–1545. Eyler, A.A., Brownson, R.C., Bacak, S.J., Housemann, R.A., 2003. The epidemiology of walking for physical activity in the United States. Med. Sci. Sports Exerc. 35 (9), 1529–1536. Greene-Roesel, R., Diogenes, M.C., Ragland, D.R., 2010. Estimating Pedestrian Accident Exposure (1055–1425). Retrieved from. University of California, Berkeley. Ha, H., Thill, J., 2011. Analysis of traffic hazard intensity: a spatial epidemiology case study of urban pedestrians. Comput. Environ. Urban. Syst. 35 (3), 230–240. Haynes, R., Reading, R., Gale, S., 2003. Household and neighbourhood risks for injury to 5–14 year old children. Soc. Sci. Med. 57 (4), 625–636. Henary, B., Ivarsson, J., Crandall, J., 2006. The influence of age on the morbidity and mortality of pedestrian victims. Traffic Inj. Prev. 7 (2), 182–190. Hydén, C., 2016. Traffic conflict techniques: some data to supplement accident analysis. Transp. Plann. 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Retrieved from. Ministry of Transportation Ontario, Safety Policy & Education Branch. O'Hern, S., Oxley, J., Logan, D., 2015. Older adults at increased risk as pedestrians in Victoria, Australia: an examination of crash characteristics and injury outcomes. Traffic Inj. Prev. 16 (Suppl. 2), S161–S167. Organisation for Economic Co-operation and Development, 1998. Retrieved from. http:// www.oecd.org/sti/transport/roadtransportresearch/2103492.pdf. Oxley, J., Fildes, B., Ihsen, E., Charlton, J., Day, R., 1997. Differences in traffic judgements between young and old adult pedestrians. Accid. Anal. Prev. 29 (6), 839–847. Oxley, J., Corben, B., Fildes, B., O'Hare, M., Rothengatter, T., 2004. Older vulnerable road users- measures to reduce crash and injury risk. In: Monash University Accident Research Centre Reports. vol. 218. pp. 162. Peden, M., 2004. World Report on Road Traffic Injury Prevention. Retrieved from. World Health Organization, Geneva, Switzerland. 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youth and adults who generally have larger activity spaces and are thus are less likely to be injured in the CT in which they reside. Furthermore, to determine whether low risk of injury is an indication of a highly walkable and safe environment or a result of very low walking rates requires highly disaggregate pedestrian volume data. Data of this sort, and particularly for non-work travel, are not available with sufficient geographical or temporal coverage for the study area. The Canada Census population data used here are readily accessible and reliable (Greene-Roesel et al., 2010). In the absence of pedestrian volume data, for example at intersections, Census population counts effectively adjust for differences in the underlying residential population, while also providing a crude adjustment of residential vehicle volume, as a function of population density (Greene-Roesel et al., 2010). The police-reported collision data employed in this analysis has two commonly identified limitations associated with its use that are important to note. The first of which is underreporting of incidence, which has the potential to produce biased estimates as the data available only involves individuals in either collisions reported to the police or who received treatment in a hospital (Roberts et al., 2008). Agran et al. (1990) conducted a study in San Diego County, California, that compared police reports to a hospital monitoring system to identify limitations of police databases. It was found that police under-reported the number of injured pedestrians by at least 20%. Similarly, in San Francisco police collision reports underestimated the number of injured pedestrians by 21% (Sciortino et al., 2005). The second limitation associated with the use of police report data is that the operational definition of injuries can be inaccurate (Roberts et al., 2008). A reporting officer uses best judgment to record injury severity following a PMVC, rather than by a medical professional following an examination. Furthermore, the frequency of delayed injuries, injuries that develop or become more severe after the initial collision, is unknown. Police collision reports remain a comprehensive resource for geographic information, and are an indispensable source of data (Agran et al., 1990), however some suggest that surveillance efforts should include greater linkages with hospital data to increase case ascertainment and to produce better assessment of health outcomes (Sciortino et al., 2005). Acknowledgements The authors would like to thank Michael Brady (City of Toronto) for providing the data. References Agran, P.F., Castillo, D.N., Winn, D.G., 1990. Limitations of data compiled from police reports on pediatric pedestrian and bicycle motor vehicle events. Accid. Anal. Prev. 22 (4), 361–370. Anselin, L., 1995. Local indicators of spatial association—LISA. Geogr. Anal. 27 (2), 93–115. Bailey, T., Gatrell, A., 1995. Interactive spatial data analysis. vol. 413 Longman Scientific & Technical Essex. Bernhoft, I., Carstensen, G., 2008. Preferences and behaviour of pedestrians and cyclists by age and gender. Transport. Res. F: Traffic Psychol. Behav. 11 (2), 83–95. Bivand, R., Pebesma, E., Gomez-Rubio, V., Pebesma, E., 2008. Applied Spatial Data Analysis With R. vol. 747248717 Springer. Buliung, R., Roorda, M., Remmel, T., 2008. Exploring spatial variety in patterns of activity-travel behaviour: initial results from the Toronto travel-activity panel survey (TTAPS). Transportation 35 (6), 697. City of Toronto, 2015. Children Living in Poverty, Proportion of Children Living Below LICO. Retrieved from. http://www.toronto.ca/reportcardonchildren/gmap_lico.htm. City of Toronto, 2016. Road Safety Plan (RSP) 2017–2021. Retrieved from. https:// www1.toronto.ca/City%20Of%20Toronto/Transportation%20Services/VisionZero/ Links/2017%20Vision%20Zero%20Road%20Safety%20Plan.pdf. Collins, D.C., Kearns, R.A., 2005. Geographies of inequality: child pedestrian injury and walking school buses in Auckland, New Zealand. Soc. Sci. Med. 60 (1), 61–69. Dumbaugh, E., Rae, R., 2009. Safe urban form: revisiting the relationship between community design and traffic safety. J. Am. Plan. Assoc. 75 (3), 309–329. Dunbar, G., Holland, C.A., Maylor, E.A., 2004. Older Pedestrians: A Critical Review of the Literature. Ewing, R., Dumbaugh, E., 2009. The built environment and traffic safety a review of empirical evidence. J. Plan. Lit. 23 (4), 347–367. Ewing, R., Schieber, R.A., Zegeer, C.V., 2003. Urban sprawl as a risk factor in motor
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D.C., 2003. Zones of prevention: the geography of fall injuries in the elderly. Soc. Sci. Med. 57 (11), 2065–2073. Zeedyk, M., Wallace, L., Carcary, B., Jones, K., Larter, K., 2001. Children and road safety: increasing knowledge does not improve behaviour. Br. J. Educ. Psychol. 71 (4), 573–594. Zegeer, C., 2002. Pedestrian Facilities Users Guide: Providing Safety and Mobility. Federal Highway Administration, Washington, DC.
planning. Accid. Anal. Prev. 41 (1), 137–145. World Health Organization, 2015. Global Status Report on Road Safety. pp. 2015. Retrieved from. http://www.who.int/violence_injury_prevention/road_safety_ status/2015/en/. Yao, J., Yang, J., Otte, D., 2008. Investigation of head injuries by reconstructions of realworld vehicle-versus-adult-pedestrian accidents. Saf. Sci. 46 (7), 1103–1114. Yiannakoulias, N., Rowe, B.H., Svenson, L.W., Schopflocher, D.P., Kelly, K., Voaklander,
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