Child Pedestrian-Motor Vehicle Collisions and Walking to School in the City of Toronto: The Role of the Built Environment

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1 Child Pedestrian-Motor Vehicle Collisions and Walking to School in the City of Toronto: The Role of the Built Environment By Linda May Rothman A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy The Institute of Medical Science University of Toronto Copyright by Linda Rothman, 2014

2 Child Pedestrian-Motor Vehicle Collisions and Walking to School in the City of Toronto: The Role of the Built Environment Linda May Rothman Doctor of Philosophy The Institute of Medical Science University of Toronto 2014 Abstract Introduction: Child pedestrian-motor vehicle collisions are a major population health issue worldwide. Although there are numerous benefits of active transportation, walking to school could potentially increase collision risk. The built environment has been associated with selfreported walking to school and with child pedestrian motor-vehicle collisions. It is important to determine if there are built environment features related to more walking but which also create safe walking environments. The thesis objective was to examine the relationships between observed walking to school, child pedestrian-motor vehicle collisions and the role of the built environment in Toronto, Canada. Methods: Literature related to children walking for transportation, pedestrian-motor vehicle collisions and the built environment was systematically reviewed. Observational counts of school travel mode were conducted at 118 elementary schools in 2011 and mapped onto school attendance boundaries together with police-reported child pedestrian-motor vehicle collisions ( ) and built and social environment data. The relationship between walking proportions and collision rates was examined controlling for the environment. Results: There was a mean collision rate of 7.1/10,000/year within school boundaries. The mean proportion of observed walking was 67%. Several built environment features were ii

3 related to more walking; however, school crossing guards reduced the influence of other features on walking. Walking to school was unrelated to collision rates once built environment features were controlled for. Higher multi-family dwelling density was related to lower collision rates; whereas higher one way street and traffic calming densities, lower traffic light density, school crossing guards and lower school socioeconomic status were related to higher collision rates. Significant features were generally related to road crossing. Conclusions: This is the first large observational study examining walking to school, collision risk and the environment. Results suggest that safety is concerned with built environment features primarily related to road crossing, and not the numbers walking. The associations between school crossing guards and traffic calming with higher collision rates were unexpected. Mechanisms for mitigating road crossings for children are not well understood and controlled research designs are needed. Future policy to increase children s active transportation should be developed from strong evidence that addresses child pedestrian safety. iii

4 Acknowledgments I owe my sincerest gratitude to the following people without whom this research would not have been possible: Dr. Andrew Howard, for his continued guidance, support, and mentorship over the years. He has been a true mentor; encouraging me to pursue this doctoral research, and providing me with both the professional and personal support to find my own path as a researcher. Dr. Teresa To, for her mentorship and valued methodological guidance. Her calm and caring support was invaluable throughout the process. Dr. Colin Macarthur, for his keen interest, and attention to detail which was instrumental in ensuring the scientific quality of this work. His clarity of vision and communication was instrumental in helping me to clarify my directions and my goals. Dr. Ron Buliung, for his invaluable and unique contributions. Most notably, he broadened my perspective by introducing me to a whole new way of thinking as related to geography and urban planning, and helped me integrate this knowledge into the area of child injury prevention. My peers and friends at the Hospital for Sick Children and at IMS, particularly Morgan Slater, Maricar Aruta, Sarah Richmond and Joanne Goldman, for their encouragement and support throughout the process. My parents, in-laws and my sister for their encouragement throughout. And my brother, Lorne, for his patient delivery of statistical support whenever needed. I owe my deepest gratitude to my husband, Gary, and my children, Zev, Kobi and Gil. After many years of deliberation regarding the pursuit of a doctoral degree, their encouragement, patience, love and never-ending energy are responsible for making the completion of this thesis possible. This thesis is dedicated to my family. iv

5 I would also like to acknowledge the following scholarship/fellowship programs: Canadian Institutes of Health Research (CIHR) Doctoral Research Award Program and Frederick Banting and Charles Best Canada Graduate Scholarship, The Hospital for Sick Children, Research Training Program (Restracomp) and the Ontario Neurotrauma Foundation, Summer Internship Program in Injury Prevention. v

6 Contributions Linda Rothman (author) solely prepared this thesis. She conducted the systematic literature review with the assistance of the research librarian and a second reviewer. She developed the field survey, hired the student observers and organized and supervised the data collection and data entry of the primary data. She procured the secondary datasets and processed and conducted spatial and traditional statistical analyses. She was responsible for the writing of the thesis and all resulting publications.. The following contributions by other individuals are acknowledged: Dr. Andrew Howard (Primary Supervisor) mentorship; guidance and assistance in planning, execution, and statistical analysis as well as manuscript/thesis preparation. Dr. Teresa To (Co-supervisor) mentorship; guidance and assistance in planning, execution, and statistical analysis as well as manuscript/thesis preparation. Dr. Colin Macarthur (Thesis Committee Member) guidance and assistance in planning, execution, and statistical analysis as well as manuscript/thesis preparation. Dr. Ron Buliung guidance and assistance in planning, execution, and spatial analysis as well as manuscript/thesis preparation. Elizabeth Uleryk (Research Librarian, Hospital for Sick Children) -assistance in developing the literature search strategy (Chapter 3). Andi Camden -assistance in reviewing the articles (Chapter 3). vi

7 Table of Contents Acknowledgments... iv Contributions... vi List of Tables... xii List of Figures... xiv List of Appendices... xv List of Abbreviations... xvi 1 Introduction Rationale Overall Objective Specific Objectives Thesis Organization Background Burden of Motor Vehicle Collisions Pedestrian-Motor Vehicle Collisions Children Injury and Disability Health Outcomes of Walking for Transportation Child Pedestrian-Motor Vehicle Collisions Prevention of Chronic Conditions Measurement Child Pedestrian-Motor Vehicle Collisions Walking to School Conceptual Frameworks Child Pedestrian-Motor Vehicle Collisions Walking to School Correlates and Interventions Child Pedestrian-Motor Vehicle Collisions Correlates Interventions to Decrease Child Pedestrian-Motor Vehicle Collisions Walking to School Correlates Interventions to Increase Walking to School Geographic Information Systems (GIS) GIS and Child Pedestrian-Motor Vehicle Collisions GIS and Walking to School The Setting - The City of Toronto Policy Child Injury Prevention National Provincial Walking to School National vii

8 Provincial Municipal Gaps in Knowledge Regarding Child Pedestrian-Motor Vehicle Collisions, Walking to School and the Built Environment Walkable but Unsafe? A Systematic Review of Built Environment Correlates of Walking and Child Pedestrian Injury Preface Abstract Objectives Methods Results Conclusions Introduction Methods Eligibility Data Extraction Quality Assessment Analysis Results Walking Child Pedestrian Injury Quality Assessment Walking Child Pedestrian Injury Safety and Walking Less Injury (Safer) and Walking Correlates More Injury (Less Safe) and Walking Correlates Inconsistent/Untested Correlates of Injury and Walking Discussion Conclusions Supplementary/Supporting Analysis Walking to School Supplementary Tables Influence of Social and Built Environment Features on Children s Walking to School: An Observational Study Preface Abstract Objectives Methods Results Conclusions Introduction Methods Study Design, Setting and Population Outcome Variable Independent Variables Built Environment viii

9 Density Diversity Design Social Environment Statistical Analysis Results Discussion Limitations Strengths Conclusion Supplementary/Supporting Analyses Principal Component Analysis Proportion Observed Walking Network Analysis Predicted Values Sensitivity Analysis Trimming of Variables Residual Diagnostics Alternative Modeling Strategies Supplementary Tables Supplementary Figures Motor Vehicle-Pedestrian Collisions and Walking to School: The Role of the Built Environment Preface Abstract Objectives Methods Results Conclusions Introduction Methods Study Design, Setting and Population Outcome Exposure Potential Covariates Data Sources Canadian Census Municipal Property Assessment Corporation (MPAC) Site Audits City of Toronto Toronto District School Board Statistical Analysis Results Discussion Comparisons of Findings to Previous Studies Confounders Effect Modifiers ix

10 5.6.4 Unexpected Results Strengths and Limitations Future Research Conclusions and Policy Implications Supplementary/Supporting Analyses Collision Rates Pedestrian Action During Collision Predicted Values Sensitivity Analysis Residual Diagnostics School Travel Time Collisions Alternative Collision Data Years Alternative Outcome Supplementary Tables Supplementary Figures Detailed Methods Data Sources Observational Study Site Survey Canadian Census City of Toronto Toronto Police Services Toronto District School Board (TDSB)/Toronto Catholic District School Board (TCDSB) Municipal Property Assessment Corporation (MPAC) Teranet (via licensing from the University of Toronto) Mapping Spatial Analysis Area Interpolation- Polygon in Polygon Areal Weighting Buffer Analysis Network Analysis Statistical Analysis Negative Binomial Regression Forward Stepwise Manual Regression Confounding Effect Modification (Interactions) General Discussion Summary Unifying Discussion Density: Diversity Design Distance to School Design Features with No Significant Associations with Child Pedestrian-Motor Vehicle Collisions Design Features with Significant Positive Associations with Child Pedestrian-Motor Vehicle Collisions x

11 6.3 Strengths and Limitations Strengths Limitations Policy Implications Integration of Walking to School and Child Pedestrian-Motor Vehicle Policies Identification of Evidence-Based Targets Walking to School Child Pedestrian-Motor Vehicle Collision Targets Appropriate Outcome Measurement Evidence-Based Built Environment Strategies Distance and School Boundaries Short-term Versus Long-term Built Environment Strategies Knowledge Translation Activities Future Research Further Analysis from the Present Study Specific Built Environment Design Features and Collisions Parent- Perceived Traffic Danger and the Built Environment Observed versus Self-Reported Walking Methodological Approaches for Future Studies Randomized Controlled Trials (RCT) Longitudinal Cohort Case Control Quasi Experimental, Pre-Post Design Cross Sectional Studies in Other Settings Conclusions References Appendices xi

12 List of Tables Table 2-1: Haddon's Matrix. Pedestrian-motor vehicle collision example Table 2-2: Built environment variables most associated with travel demand Table 3-1: Quality assessment using EAI: Number of studies (%) Table 3S-1: Correlates of walking to school and child pedestrian injury Table 4-1: Descriptive statistics of candidate variables for multivariate modeling Table 4-2: Unadjusted Incident Rate Ratios (95% CI) for candidate variables (p<.2) for multivariate modeling Table 4-3: Correlates of walking to school in adjusted analysis (IRR = incident rate ratios (IRR, 95% CI = confidence interval) Table 4-4: Correlates of walking to school in adjusted analysis stratified by presence of school crossing guard (IRR = incident rate ratios, 95% CI = confidence interval) Table 4S-1: Data sources and variable type Table 4S-2: Built environment factor loadings from principal component analysis Table 4S-3: Results of negative binomial regression excluding 3 outlier schools Table 5-1: Variables according to conceptual component, level of measurement and data source Table 5-2: Descriptive statistics and significant unadjusted incident rate ratios (p <.20, IRR = incident rate ratio, 95% CI= 95% confidence interval) Table 5-3: Correlates of child pedestrian collisions in adjusted analyses (IRR = incident rate ratio, 95% CI= 95% confidence interval) Table 5-4: Incidence rate ratios of collisions stratified by traffic light density tertiles Table 5S-1: Correlates of child pedestrian collisions in adjusted analysis for all schools and excluding 7 outlier schools Table 5S-2: Correlates of child pedestrian collisions in unadjusted and adjusted models for all collisions and those restricted to school travel times Table 5S-3: Correlates of child pedestrian collisions in unadjusted and adjusted models for 10 years, 7 years and 5 years of collision data Table 5S-4: Correlates of child pedestrian collisions and walking to school in adjusted analysis using school populations as alternative denominator xii

13 Table 6-1: Summary table of built environment variables associated with walking to school and child pedestrian-motor vehicle collision from the literature and from the study analyses Table 6-2: Individualized school report knowledge users Table 6-3: Actions taken attributed to individualized school reports by school principals xiii

14 List of Figures Figure 2-1: The causal model for injuries Figure 2-2: Conceptual framework of an elementary-aged child's travel behavior Figure 2-3: A conceptual framework for the environmental determinants of active travel in children Figure 2-4: A behavioral model of school transportation Figure 2-5: Distance to school Figure 2-6: Child pedestrian-motor vehicle collisions and roadway design features Figure 2-7: Child pedestrian-vehicular collisions in school zones Figure 2-8: Six former municipality boundaries prior to Figure 2-9: Pre-World War II grid street patterns in downtown Toronto Figure 2-10: Post-World War II street patterns in inner suburbs (Scarborough) Figure 3-1: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram Figure 3-2: Correlates of walking and child pedestrian injury Figure 4-1: Flowchart of school participation Figure 4S-1: Distribution of walking proportion across 118 study schools Figure 4S-2: Distribution of the proportion of roads in 118 study school boundaries within 1.6 km of schools Figure 4S-3: Predicted walking rates by intersection density Figure 5-1: Multivariate relationships between walking to school, child pedestrian injury and the built environment Figure 5S-1: Distribution of collision rates/10,000/year within 118 study school boundaries Figure 5S-2: Top 5 pedestrian actions at time of collisions Figure 5S-3: Predicted collision rate/10,000/year by multi-family dwelling density xiv

15 List of Appendices Appendix A: Search Strategies Appendix B: Summary of walking publications Appendix C: Summary of child pedestrian-motor vehicle collision publications Appendix D: Elementary school boundaries (TDSB) and pre-amalgamated City of Toronto Appendix E: Observational counts data collection form Appendix F: Site survey Appendix G: Vehicle speed data collection form xv

16 List of Abbreviations AIC AST ATLICO CI DA DALY GIS GTA EAI HMC IRR IKT JK LOI LMC MPAC PRISMA SD SES SRTS STP TDSB VIF YLD Akaike information criteria Active school transportation After tax, low income cut-offs Confidence interval Dissemination areas Disability adjusted life years Geographic information systems Greater Toronto Area Epidemiological Appraisal Instrument High motorized countries Incidence rate ratio Integrated knowledge translation Junior kindergarten Learning opportunities index Low motorized countries Municipal Property Assessment Corporation Preferred Reporting Items for Systematic Reviews and Meta-Analyses Standard deviation Socioeconomic status Safe routes to school School travel planning Toronto District School Board Variance inflation factors Years Lived with Disability xvi

17 1 Introduction In this chapter, the rationale for conducting the research is presented along with the overall and specific thesis objectives. The thesis organization is then described by chapter and terminology used throughout the thesis is clarified. 1.1 Rationale Walking as a form of active transportation has numerous benefits at the individual and population level. The benefits for the individual include prevention of obesity, hypertension, osteoporosis and other chronic conditions; and for the population include reduced traffic congestion, better air quality, and improved quality of life. There is evidence that children s physical activity is related to physical activity in adulthood and therefore, the promotion of walking in children could potentially help prevent adult onset of chronic conditions. There are risks however, associated with walking near roadways. Road traffic injuries are the leading cause of death for school age children in Canada. Much of children s exposure to walking and to traffic is during their travel to school. It is important that the relationship between the rates of children walking to school and pedestrian-motor vehicle collisions be established given the recent popularity of programs to increase walking to school. There is evidence that increased walking in a community may be associated with less pedestrian-motor vehicle collisions because of a safety in numbers effect. There is also evidence; however, that increased traffic exposure when walking to school is associated with more pedestrian-motor vehicle collisions. These conflicting findings may be due to differences in the built environment, in that some environments may provide safer walking conditions than others. Specific features of the built environment have been associated with self-reported walking to school as well as with child pedestrian-motor vehicle collisions. However, no studies to date have used objective observational exposure data. Studies of the built environment and child 1

18 pedestrian-motor vehicle collisions have also generally not taken into account road traffic exposure in the context of proportion of children walking to school. It is important to determine if there are features of the built environment which are positively associated with increased walking and create a safer environment (i.e., less injury) to provide optimal environments for walking to school. It is equally important to determine if there are features of the built environment that are associated with increased walking but with an increased risk of injury. 1.2 Overall Objective To examine the relationships between observed walking to school, child pedestrian-motor vehicle collisions in the City of Toronto, and the role of the built environment. 1.3 Specific Objectives 1. To systematically review the literature on the relationships between the built environment, walking to school and child pedestrian-motor vehicle collision rates. 2. To estimate the proportion of observed children walking to school in the City of Toronto (kindergarten to grade 6). 3. To determine the association between the built environment and proportions of children walking to school. 4. To estimate child pedestrian-motor vehicle collision rates in the areas surrounding elementary schools in the City of Toronto. 5. To determine how features of the built environment influence the relationship between proportion of children walking to school and child pedestrian-motor vehicle collisions. 2

19 1.4 Thesis Organization Chapter 1 provides a brief rationale along with the overall objective of the research and specific research objectives. Chapter 2 presents the context of the research through a detailed review of literature pertaining to child pedestrian-motor vehicle collisions and walking to school (with a focus on Canada). Excepts of this literature review have been included in a book chapter that has been accepted for publication (Buliung R, Larsen K, Falkner G, Rothman L, Fusco C. Driven to School: Social Fears and Traffic Environment. In: Walks A. ed. Driving Cities, Driving Inequality, Driving Politics: The Political Economy and Ecology of Automobility. Winnipeg, MB: Routledge). The literature review describes the burden of pedestrian-motor vehicle collisions focusing on children, and examines potential health outcomes of walking to school. The measurement of pedestrian-motor vehicle collisions and walking to school is discussed, and conceptual frameworks related to both outcomes are presented. Correlates and interventions related to both child pedestrian-motor vehicle collisions and walking to school are reviewed with a focus on the built environment. The use of Geographic Information Systems (GIS) to study both child pedestrian-motor vehicle collisions and walking to school is presented, and the City of Toronto, as the setting of the study, is described. The current status of Canadian policy related to pedestrian injury prevention and walking to school is summarized. Finally, the gaps in knowledge regarding walking to school, child pedestrian-motor vehicle collisions and the built environment are identified. Chapters 3-5 are reformatted versions of manuscripts that have been published or are currently under review. Supplementary/supportive analyses that were not included in the published versions are appended at the end of the chapters. Chapter 3 presents a systematic literature review addressing Objective #1 identified above. The material in this chapter has been published in Injury Prevention (Rothman, L., Macarthur, C., Buliung, R., To, T., & Howard, A. Walkable but unsafe? a systematic review of built environment correlates of walking and child pedestrian injury. Injury Prevention, 18 (Suppl 1) 2012: A223-A223.) Chapter 4 addresses Objectives 2 and 3, and has been published in Preventive Medicine. (Rothman L, To T, Buliung R, Macarthur C, To T, Howard A. Influence of social and built environment features on children s walking to school: an observational study. Prev Med. 60; 2013:10-15). 3

20 Chapter 5 addresses Objectives 4 and 5 and has been published online in Pediatrics (Rothman L, To T, Buliung R, Macarthur C, To T, Howard A Pedestrian-motor vehicle collisions and walking to school: the role of the built environment. Pediatrics published online: 2014(doi: /peds ). Chapter 5 includes a detailed methods section further describing the data collection and analyses pertinent to both Chapters 4 and 5, which was not included in the published papers. In Chapter 6, the major findings of the thesis are summarized and the strengths and limitations are discussed, followed by a description of policy implications, knowledge translation activities and an outline of proposed future studies. Several terms are used interchangeably in the literature and in this thesis and require clarification. The terms child pedestrian injuries and child pedestrian-motor vehicle collisions were used interchangeably. Although child pedestrian injury implies a measure of severity, many studies use this terminology to reflect the collision occurrence. The terms active school transportation (AST) and walking to school were also used interchangeably. AST consists of not only walking to school, but also cycling and other active means (e.g. scooters). Since the numbers of children using active means other than walking in Toronto are extremely small, AST generally reflects walking to school in this location. Finally, built environment is also referred to as the physical environment or urban form in many of the referenced papers. The built environment refers to the man-made physical environment that provides the setting for human activities. It includes urban form, physical road infrastructure, land use patterns and transportation systems. 1 2 Background The purpose of this chapter is to provide background information and context for this thesis. This section discusses the global burden of motor vehicle collisions with a focus on pedestrian collisions and children. This section also describes the injury and disability burden of motor vehicle collisions and collisions involving pedestrians. 4

21 2.1 Burden of Motor Vehicle Collisions Road safety is an international health policy imperative, given the devastating burden of road traffic injuries. Road safety is also a priority for global sustainable development policy, directed at increasing the safety and accessibility of non-motorized transportation to reduce air pollution and traffic congestion. 2,3 In March 2010, The United Nations General Assembly declared the Decade of Action for Road Safety with the aim of reducing road traffic injuries and fatalities. 2 In 2010, road traffic crashes resulted in approximately 1.24 million people killed and another million non-fatal injuries worldwide. 2 According to the Global Burden of Disease Study, in 2010, road injury ranked eighth for global death rates with a 47% increase since Road injury also ranked seventeenth for Years Lived with Disability (YLDs) with a 30% increase since It is predicted that road injury will rise in ranking to the fifth leading cause of death globally and the seventh leading cause of Disability Adjusted Life Years (DALYs) lost by The burden of road traffic collision is higher in low and middle income countries which have higher annual road traffic fatality rates (18.3 and 20.1 per population, respectively) compared to high-income countries (8.7 per ). 2 Middle income countries have seen rapid motorization over the last 20 years, with similar trends in lower income countries. 8,9 Unfortunately, this rapid motorization has not been accompanied by investment in road design planning and safety strategies, such as law enforcement and education Pedestrian-Motor Vehicle Collisions The UN General Assembly dedicated the Second UN Global Road Safety Week in May 2013 to pedestrian safety, in the context of the Decade of Action for Road Safety Pedestrian fatalities represent approximately 22% of road traffic deaths worldwide. 2 In low income countries, the proportion is as high as 35% as more people use walking as their main mode of transportation. 2 Some countries report more than 75% of their road traffic fatalities occur in pedestrian/cyclists. 2 Higher fatalities among vulnerable road users in middle and low income 5

22 countries is the result of increased motorization and the traffic mix, where there is less developed traffic safety infrastructure. Pedestrian-motor vehicle collision rates in high income countries have been declining over the past 20 years. Declining trends have been noted in the United States, Canada, Europe and New Zealand In Toronto, Canada, there was a 24% decline in collision rates from Despite declining pedestrian-motor vehicle collision rates from , pedestrians accounted for approximately 50% of all road traffic fatalities in Toronto. 16 Although pedestrians accounted for only 7% of the transportation mode share, they represented 52% of all fatalities and 11% of all collisions involving motor vehicles. 16 The high proportion of pedestrian fatalities is markedly different than that of the rest of Canada, where pedestrians account for 13% of road traffic fatalities. 17 This indicates that pedestrian-motor vehicle fatalities are a serious problem in urban environments. In Toronto, 39% of pedestrian-motor vehicle collisions led to hospital visits, 8.8% resulted in hospitalization and 1.4% resulted in fatality in The estimated annual cost of pedestrian -motor vehicle collisions in Toronto, which include discounted future earnings, direct medical costs and other direct costs, totals $53,606, Children Children are especially vulnerable to road traffic injuries because of their small stature and developing physical and cognitive skills. In 2010, road injuries were the 5th leading cause of death for children ages 5-9 years, the 4th leading cause for ages years and the leading cause for young people years of age world-wide. 4,18 Road traffic crashes result in more than 260,000 child fatalities each year and approximately 10 million non-fatal injuries; leaving one million children with long-term disabilities. 19 Child pedestrians represent 5-10% of children of those with road traffic injuries in high-income countries, whereas they represent between 30-40% in low and middle-income countries. 20 In Cape Town Safe Africa, 75% of children admitted to a hospital trauma unit in 2011 as a result of road traffic collisions, were pedestrians. 21 In these countries, child pedestrians share the roads with many types of motorized transport. 20 Although there has been a downward trend in road traffic injuries in high income countries, they continue to be a leading cause of child death. 5,10,22 In high-income European countries, 1 in 5 6

23 childhood injury deaths are the result of road traffic injuries. 5 In the United States, motor vehicle crashes were the leading cause of death for children under the age of 14 years in 2011, with 3 child fatalities and 469 injuries on average, every day. 23 In Canada, unintentional injuries are the leading cause of death in children, with motor vehicle fatalities occurring almost six times more often than any other unintentional injury group. 24 Hospitalization due to motor vehicle injuries ranks 2 nd (after falls) for all injury admissions in young people in Canada. 24 In 2010, there were 295 fatalities, approximately 2000 serious injuries and almost 30,000 reported injuries due to traffic crashes in Canadian children ages 0-19, caused by vehicle occupant trauma, pedestrian injury, and cycling collisions. 17 Beyond the injuries and the burden it places on emergency and rehabilitation systems, road traffic injuries in children 0-19 years of age cost the Canadian health care system $1 billion annually. 25 There was a 50% decline in hospitalizations and deaths due to child pedestrian-motor vehicle collisions in Canada from ,26 Despite these declines, the burden remains high. In children under age 14 in 2001, the proportion of all road user fatalities that were pedestrian related is 25% as opposed to 13% in adults. 27 Approximately 56 child pedestrians die and 780 are hospitalized with serious injuries in Canada every year. 10 In children ages 5-9 years, pedestrian-motor vehicle collisions are tied with motor vehicle collisions at 18% as the primary cause of unintentional injury death in this age group in Canada Injury and Disability Head injuries are the leading cause of traffic-related injuries and fatalities, especially in children. 28 Injuries to limbs such as fractures, abrasions and contusions are also common in road traffic collisions, particularly for those injured as pedestrians. 20 Child pedestrian-motor vehicle collisions are more severe than collisions involving motor vehicle occupants because of the lack of physical protection separating them from the colliding force. Because of a child s short stature, a child s head is frequently the first point of contact with the bumper of a colliding vehicle. From , pedestrian injuries accounted for two thirds of all severe/fatal traffic injuries in children under 17 years of age in the Northern Manhattan Injury Surveillance System, with 45% sustaining head trauma. 29 In children presenting to the emergency department after a 7

24 road traffic collision in Great Britain, approximately 2/3 of pedestrians had injuries above the neck, with 33% sustaining severe head injuries. 30 Brison et al. found that head and neck injuries were the primary cause of pedestrian-related death in children under five years in Washington. 31 Head injuries accounted for over 20% of pedestrian hospital admissions in Canada in those < 20 years in 2002, 32 and 19% presenting to emergency departments in 2008/ Long-term disability is common among those who survive motor vehicle collisions, with road traffic injuries ranking 9 th in 2002 for DALYS, representing an estimated 38 million DALYs. 8 Toronto, Canada, 72% of child pedestrians and 59% of motor vehicle occupants who were seriously injured and admitted to hospital, required assistance with daily activities when they returned home after six months. 33 Younger age and a primary diagnosis of a central nervous system injury were associated with requiring assistance. In 2.2 Health Outcomes of Walking for Transportation Child pedestrian-motor vehicle collisions and the prevention of chronic conditions are potential health outcomes of walking for transportation. This section reviews the trends in walking to school and child pedestrian-motor vehicle collisions over the last 20 years and discusses the potential relationship between pedestrian volume and collisions. The benefits of walking as a means of physical activity are discussed and the relationships to health outcomes such as obesity are described Child Pedestrian-Motor Vehicle Collisions Many believe the downward trend in child pedestrian-motor vehicle collisions over the last 20 years in higher income countries, is because of children walking less, thereby reducing their exposure to the risk of collisions with a motor vehicle. 12,14,34 In the United States, 41% of schoolchildren walked or biked to school in 1969, and this had dropped to 13% in In the 2004 Canadian National Transportation Survey, 50% of children reported never walking to 8

25 school. 36 In an analysis of the Transportation Tomorrow Survey (TTS), Buliung et al. found that walking mode share for trips to school in year olds in the Greater Toronto Area (GTA) decreased from 53% to 42.5% from The 2013 Active Healthy Kids Canada Report Card on Physical Activity for Children and Youth indicated that parents report that 24% of Canadian 5-17 year olds use only active transportation to and from school and 14% use a combination of active and inactive modes of transportation. 38 There has been an increase in those who only report inactive modes of transportation to/from school from 51% to 62% from Despite the decreasing numbers of children walking to school, almost 50% of pedestrian-motor vehicle collisions involving children <17 years in Toronto, occurred during school travel times and months. Warsh et al. used Geographic Information Systems (GIS) to assess the distance of police-reported collisions in school age children related to school location. 39 More than 1/3 of collisions were within 300 m of a school, with the highest density of collisions among children occurring within 150m of a school. Yiannakoulias et al. analyzed emergency department surveillance data from all hospitals in Edmonton. Peak times of child pedestrian-motor vehicle collisions were in the morning (7:00-9:00) and afternoon (15:00-18:00) which corresponded with school start and finish times and peak times of traffic volume. 40 Unfortunately, road traffic exposure is poorly understood and there exists conflicting evidence related to pedestrian volume and collisions. Jacobsen found a safety in numbers effect in 3 large population datasets conducted in Europe and the U.S. Pedestrian volume, as measured by journey to work share, distance or trip/day/capita was associated with decreased collisions. Jacobsen calculated that an individual pedestrian s collision risk decreased to 66% in communities where there is twice as much walking. 41 Studies which address pedestrian-motor vehicle collisions and specifically walking to school, have found the reverse, namely that positive associations exist between walking exposure and child pedestrian-motor vehicle collisions Macpherson et al. conducted a survey in 2,501 grades 1 and 4 students in 43 elementary schools in Montreal, Quebec. A strong positive correlation was found between numbers of parent-reported road crossings on a school day and child pedestrian-motor vehicle injuries according to police records (correlation coefficient = 0.78). 42 Rao et al. conducted surveys in 804 grades 1 and 4 students in 26 schools in Baltimore, Maryland. They found a significant inverse correlation between the proportion of children driven home from school as 9

26 reported by parents and students, and the rate of police-reported pedestrian-motor vehicle collisions (r = -0.79, p<.01). 43 In the Canadian Health Behavior in School-Aged Children Survey, a weighted sample of 20,076, year old students completed self-report surveys in 419 schools regarding their use of active transportation and active transportation injuries. 45 Gropp et al. reported a 1.5 increase in the odds of active transportation injury in the year previous to the survey for those who engaged in active transportation over longer distances (>15 minutes), after adjusting for age and urban/rural status. 44 There was evidence of a dose response relationship between longer travel distances and injury. Therefore, depending on the mix of walking and driving and the environmental conditions present, walking promotion could either increase or decrease the risk of injury per trip. Additionally, environmental conditions that ensure safe walking may be different for children compared to adults. Optimal conditions for safe walking to school must be defined, because if planned poorly, increased walking has the potential to increase injury risk in children Prevention of Chronic Conditions The promotion of physical activity in children is important to encourage healthy lifelong lifestyles and to reduce the prevalence of obesity and associated impact on health. Obesity is on the rise in Canada. Almost 9 % of children ages 6-17 in Canada are obese and this has increased 2.5 times from 1978/1979 to A systematic review of the literature by Singh et al. found that children who are overweight or obese are at an increased risk of becoming an overweight adult. 47 Another review of the literature by Ball et al. found that childhood obesity contributes to the early development of cardiovascular diseases and type 2 diabetes. 48 The proportion of deaths attributed to being overweight or obese in adults has been estimated to have increased from 5.1% in 1985 to 9.3% in 2000 in Canada. 49 The Canadian physical activity guidelines for children 5-17 years recommend a minimum of 60 minutes of moderate-to vigorous-intensity activity per day. 50 It was estimated in the Canadian Physical Activity Levels Among Youth study, that 88% of children and youth do not meet the recommended physical activity guidelines. 51 Focus is turning more towards lifestyle activities to increase physical activity such as walking, biking and taking stairs which can be done on a daily 10

27 basis and over the lifespan. Walking is an especially accessible means of physical activity for most people, as there is no special equipment or facilities required and it can be incorporated into the daily trips to work or to school. In addition to the numerous health benefits of active transportation, there are other transportation benefits including less traffic congestion, less fuel costs, shorter and more reliable travel times, and fewer road traffic collisions, and societal benefits including less air and noise pollution, less crime, community cohesion and higher real estate value. 16 In adults, active transportation has been shown to be associated with less obesity. 16 Gordon- Larsen et al. found that men who walked or cycled to work were half as likely to be obese. 52 Frank et al. found a 6% increase in the likelihood of obesity with every additional hour spent in a car every day. 53 A systematic literature review by Faulkner et al. found that children who actively commute to school reported significantly higher levels of physical activity. 54 Although the cross-sectional design of the majority of papers prevent inferences of causality between AST and physical activity, it is possible to conclude that children who engage in AST are more physically active. There was little evidence of a relationship between active transportation to school and healthier BMI, probably due to the short walking distances to school. The physical benefits of physical activity in children have not been well established, perhaps because of the low frequency of morbidity due to sedentary behaviours in children. 55 The benefits of active commuting in childhood may not be apparent until years later, assuming the active commuting habits are maintained. 54 There is evidence that children s physical activity is related to physical activity in adulthood. In a review of the literature, Malina found a correlation between participation in physical activity during childhood and youth into adulthood. 56 In a study of children and adolescence, pre or early-pubescent boys classified as sedentary based on measurements of TV viewing and video game playing were 2.2 times more likely than their peers to be classified as sedentary adolescents, five years later. 57 In a 21-year tracking study using data from the Cardiovascular Risk in Young Finns Study, Telama et al. found that high levels of physical activity at ages 9 to 18 years increased the odds that the individuals would be highly active adults, with the probability being even higher if the physical activity had lasted for several years in youth. 58 The evidence supports the promotion of walking and active transportation in children as a form of physical activity, which may continue into adulthood to prevent obesity and the development of chronic conditions. 11

28 2.3 Measurement Accurate measure of outcomes is essential to the validity of the research process. In this section, the strengths and limitations of different methods used to measure child pedestrian-motor vehicle collisions are reviewed. The issues around the inconsistency in measurement of walking to school and the effect on prevalence estimates are discussed Child Pedestrian-Motor Vehicle Collisions To effectively study the relationship between walking to school and collisions, the validity of data sources and outcome measurement must be established. The main sources for pedestrianmotor vehicle collision data are hospital/trauma surveillance databases, death registries, coroner s reports and police-reported data. Standardized Emergency Medical Services (EMS) clinical databases in Canada and in the United States may also be potential sources for collision data. Although death registries, coroner s reports, EMS service reports and health/trauma databases can potentially be rich sources of information regarding the specifics of the injury and health outcome, the patient population represents the most severe end of the pedestrian-motor vehicle collision spectrum and results are not generalizable to all collisions. Police-reported collision data also have limitations, as they have been found to underreport child pedestrianmotor vehicle collisions In a study of pedestrian-motor vehicle collisions in those under 15 years old, comparing emergency department records and the coroner s logbook to a policereported database in Orange County, California, Agran et al. found that 20% of hospital admissions in children under 15 years of age were not reported to police. 61 Generally, unreported collisions were in very young children (0-4 years) and were non-traffic, such as backing up collisions and those occurring off-road (e.g. on sidewalk). Unreported pedestrianmotor vehicle collisions may also be due to the perception of these types of collisions as injury events rather than a reportable motor vehicle collision. 61 In the U.S., some jurisdictions are also not required to report collisions occurring on private property, where most non-traffic incidents 12

29 occur. 61 Police data are also less likely to capture less severe collisions. In Ontario, the Highway Traffic Act indicates that collisions must be reported if it results in personal injury or in property damage exceeding $1, Therefore, police-reported collision databases in Ontario would likely not include collisions where there was no or very minimal injury. Collision reporting is very different in lower income countries as reporting of collisions to police is not always mandatory. In Uganda, by Lee et al. found police-reported child pedestrian injury rates were approximately the same as in a hospital-based trauma registry, but were 14 times lower than those found in a community-based survey, and 35 times lower than those reported by teachers. 63 Underestimation by the police may be because of failure of the police to record the incident or failure to report to the police. 64 The limitations of using police-reported data in lower income countries must be recognized as collision rates may be severely underestimated. Police-reported collision data are routinely collected in high income countries. These data are population-based and therefore have greater generalizability compared to data restricted to a particular hospital or trauma registry system. These data also include detailed on-scene information regarding location and circumstances, and geographic coordinates of collision locations. Although it is recognized that collisions involving no/little injury may be underrepresented in police-reported collision databases, these databases provide the most useful data compared to other sources when investigate environmental conditions associated with pedestrian-motor vehicle collisions Walking to School The methods of measurement of walking to school are inconsistent between studies. There are a differences in how the outcome is measured (e.g. usual trip, numbers of trips per week), recall time frames (last week, today), and age ranges from study to study. 65,66 Self-reported methods are generally used to measure walking to school, including parent or student written questionnaire, online or telephone surveys or travel diaries. 65,66 Self-report or proxy-report measures of walking to school have not been well-validated, which could lead to error due to selection and social desirability bias, recall error and low response 13

30 rates. 65,67 Rossen et al. reported only moderate agreement between parent versus child-reported walking to school during face-to-face interviews (kappa= 48.7%). 68 An older study reported by Routledge et al. in 1974, used a moving observer technique to validate child-reported exposure. One hundred and forty two children were followed home from school, and were then interviewed regarding road crossings the next day. 69 A statistically significant difference was found in number of road crossings with children slightly underreporting crossings. Stevenson et al. also examined the validity of children s reported estimates of usual walking activities during the course of a typical week (i.e., habitual exposure ) using several different techniques including the moving observer technique and pedestrian diaries. 70 An interview was conducted with the child daily for a week and asked questions regarding the regular walking journey each day (habitual exposure). The moving observer also recorded the characteristics of the journey described above. A total of 52 observations were made for 13 children. A high concordance was found between reported and observed habitual exposure. However, higher mean values were reported in diaries than at the interview for 3/5 habitual exposure questions. More consistent and objective measures of walking would improve accuracy of prevalence estimates of walking to school. 65,71 To date, only one study by Sirard et al. used direct observational counts of children s mode of transport to school to examine prevalence and correlates of active transportation. 72 In their study, two to three observers visited 8 schools to identify travel behavior in the morning and afternoon on 5 consecutive school days in the fall. The study sample was small, and correlates examined only included school SES level, school urbanization level, weather conditions and temperature. The study results were limited by minimal geographic diversity. 2.4 Conceptual Frameworks Conceptual frameworks help frame the multitude of factors affecting child pedestrian-motor vehicle collisions and walking to school. This section presents conceptual frameworks related to both these outcomes, with a focus on those which incorporate the built environment. The influence of the built environment has been well recognized in both the injury prevention and the 14

31 active transportation fields. Conceptual frameworks related to pedestrian-motor vehicle collisions have evolved over the last 40 years, whereas, the development of frameworks related to school travel have been more recent; generally occurring over the last 15 years as interest has grown regarding the promotion of active transportation. In all models related to AST, the outcome of interest has been school travel mode; no models have been extended to illustrate the impact of school travel mode on pedestrian-motor vehicle collisions as an outcome.. Similarly, none of the models focused on pedestrian-motor vehicle collisions have incorporated walking exposure. Therefore, the intention of this research was to build on the models presented below, to explore how the built environment influences the relationship between walking to school and child pedestrian-motor vehicle collision outcomes Child Pedestrian-Motor Vehicle Collisions The most prominent conceptual model originally developed to describe motor vehicle collisions and later extended to all types of injury, is known as Haddon s matrix. 73 Pre-event (before the child is hit) Event (during collision) Road crossing behaviour Adult supervision Child s age Child s gender Risk taking Head striking vehicle Speed Driver behaviour Driver knowledge Driver experience Vehicle design Vehicle impacting pedestrian Physical Road design Presence/ condition of sidewalks Pedestrian proximity to traffic Signage Crosswalks Type of housing Weather Daylight Availability of phone for emergency call Table 2-1: Haddon's Matrix. Pedestrian-motor vehicle collision example (adapted from SafeKids Canada, 2004, Copyright Parachute 2013, permission granted to reproduce). 74 Host Agent/Vehicle Environment Social Value placed on pedestrian safety Policy/promotion of pedestrian safety measures Law enforcement Neighbourhood socioeconomic conditions Person available to notify emergency personnel Post-event (after child is injured) Post injury care Severity of injuries Distance to trauma center Family and social support Trauma center training 15

32 This model by William Haddon Jr. was instrumental in increasing the understanding of the different factors contributing to both the occurrence and the severity of road traffic crashes. In the first dimension of the 9-cell model matrix, there are 3 phases of hazardous events during which countermeasures can be taken: the pre-event stage, the event, and the post event stage. The 2nd dimension of the model includes 3 factors: Host, agent, and environment. Table 2-1 presents an example of the Haddon matrix completed for child pedestrian-motor vehicle collisions. In this example, the host is the child at risk of injury and the agent is the energy transferred to the host by a vehicle. The environment refers to the physical environment, including the characteristics of the setting in which the injury event takes place (the roadways), and the social environment, which refers to the social and legal norms and practices (e.g. child supervision, speed limits). 75 By examining the 3 factors during the different crash phases, it is possible to identify risk/protective factors and develop preventive strategies. 76 In another causal model for injury by Peek-Asa, the environment influences the transfer of kinetic energy (i.e., agent) through a vehicle (motor vehicle) to the human host (Figure 2-1). 77 She describes the environment, as physical (either natural or man-made), social, economic cultural and demographic. Peek-Asa emphasizes that modification to the physical environment is the most effective approach to preventing injuries, as it is passive (i.e., does not require anything from the host to be effective), and it affects populations rather than just individuals. Figure 2-1: The causal model for injuries (permission granted to reproduce) Walking to School The first conceptual framework relating to an elementary children s travel behaviour was developed by McMillan (Figure 2-2). 78 In this model, school travel mode is a result of parental decision processes. Urban form has an indirect relationship with a parent s decision regarding the child s mode of transport to school. Elements of the urban form have to be processed 16

33 through factors such as social/cultural norms, sociodemographic characteristics, household transportation options and real/perceived neighborhood and traffic safety, which are then linked directly to the parent s decision of transportation model. Mediating factors -Neighborhood safety (real/perceived) -Traffic safety (real/perceived) -Household transportation options Moderating Factors -Social-cultural norms -Parental attitudes -Sociodemographic Urban Form Parental decision-making Children s travel behavior (trip to school) Figure 2-2: Conceptual framework of an elementary-aged child's travel behavior (permission granted to reproduce). More detail regarding the concept of the built environment is provided in models by Panter et al. 79 and Mitra. 80 Panter et al. took an ecological approach to understanding travel behavior in their conceptual framework of the environmental determinants of active travel in children (Figure 2-3). 79 The framework describes four domains of influence on choice of active travel modes; individual/household (i.e., attitudes, characteristics, and perceptions), external factors (e.g. weather), the main moderators (age, sex and distance), and finally, physical environmental factors, including characteristics of the neighbourhood, destination and route environment. 79 This framework does not, however, account for the underlying behavioural processes involved in choosing modes of transportation. More recently, Mitra developed a behavioural model of school transportation using a socialecological framework, which draws on ecological theories of human behaviour such as described by Bronfenbrenner and Sallis et al. (Figure 2-4) These theories emphasize the influence of the environment on behaviour. Mitra s model hypothesizes multiple levels of influence of mode choice for school transportation and independent mobility: the urban environment, household, characteristics of a child/youth, and other external factors. 80 The urban environment is an important component of this model and influences travel by its spatial structure (i.e., distribution of residences, employment and other facilities), its built environment (i.e., land use mix, transportation network and urban design features) and its social environment

34 Figure 2-3: A conceptual framework for the environmental determinants of active travel in children (permission granted to reproduce).. Figure2-4: A behavioral model of school transportation (permission granted to reproduce). 18

35 A broad range of many intercorrelated built environment factors have been studied in relation to walking to school, necessitating a model to organize these factors. A landmark study from the urban design literature by Cervero and Kockelman described a model that proposed that built environment variables related to travel demand can be organized and described along 3 principal dimensions, referred to as the 3Ds: density, diversity and design (Table 2-2). 83 Table 2-2: Built environment variables most associated with travel demand (permission granted to reproduce). 3 D s Built Environment Variables Density Population per developed acre Employment per developed acre Accessibility to all jobs Diversity Dissimilarity index (proportion dissimilar land use) Mean entropy (land use mix index) Per developed acre rates of: -retail stores -activity centers -parks and recreational sites Proportion of commercial-retail parcels that are vertically mixed (more than one land-use on site) Proportion of residential acres within ¼ mile of convenience or retail store Design Proportion of intersections that are four-way Proportion of blocks with: -sidewalks -planting strips -overhead lights -flat terrain (< 5% slope) -quadrilateral shape Block face length Sidewalk width Distance between overhead lights Proportion of commercial parcels with: -paid parking -side or front lot, on-street parking According to this model, those living in higher-density neighbourhoods that have more land use diversity and more pedestrian-oriented designs (e.g. street trees, sidewalks ) are more likely to walk or bike for transportation. 83 This 3D model has continued to be used and adapted to include other D s in the literature (e.g. destination accessibility and distance to transit) to organize built environment factors. 84 This model was originally developed to study adult walking behaviour, 19

36 but recently has also been used in the children s school transport literature. Wong et al. used the model to organize literature in a systematic review of the literature related to GIS measurement of built environment correlates of active school transport. 85 Lin et al. in their analysis of built environment effects on children s school travel in Taipei also organized the explanatory variables according to the 3Ds. 86 The usefulness of using the 3 Ds paradigm to classify built environment has been well demonstrated, and it will be subsequently used in this thesis. 2.5 Correlates and Interventions This section reviews the correlates of child pedestrian-motor vehicle collisions and interventions designed to reduce collisions with the focus on the built environment. The correlates of walking to school and interventions to increase walking are also discussed along with the issues related to inconsistencies in the association between walking and the built environment Child Pedestrian-Motor Vehicle Collisions Correlates Behavioural, social, cultural and built environmental factors all play a role in child pedestrianmotor vehicle collisions. However, increased emphasis is being placed on factors related to the built environment which are felt to be the most modifiable. Risk factors of child pedestrianmotor vehicle collisions were examined in a systematic review of Medline literature by Wazana et al. in Eighteen analytic studies were reviewed and risk factors were classified into the following groups 1) child 2) social/cultural 3) physical environment and 4) driver. The child risk factors were identified in descending order of impact: younger age, behaviour (e.g. impulsivity), non-white and male. Social risk and cultural risk factors were: lower income, more children living in home, less parent preventive behaviours, mother working, lower maternal education, history of mother being hospitalized and illness in family. The physical environment risk factors for child pedestrian-motor vehicle collisions or greater severity of injury were: higher traffic 20

37 volume, higher speed limit and vehicle speed, absence of play area, being on road (versus offroad), streets with predominantly rental units and multi-family dwellings, higher proportion of curb side parking, shared driveway, major roadways, after 3 pm, rainy weather, and darkness. The driver risk factors for increased injury severity were lack of avoidance behaviour and higher speed driving. Wazana defined directly modifiable factors as risk factors which can be directly affected by an intervention. He indicated that the most directly modifiable risk factors were those related to the physical environment and that other than age and SES, the physical environment risk factors had the greatest magnitude of risk associated with them. Wazana described how the focus on the modification of environmental risk factors in Sweden and Denmark may explain their success in decreasing child pedestrian mortality rates. A recent paper by Dimaggio and Li, systematically reviewed the literature focused on pediatric pedestrian injury risk and the built roadway environment. 88 A meta-analysis using Bayesian techniques was conducted to synthesize the evidence on the association of roadway characteristics with pediatric pedestrian injury risk. Ten databases were searched and 26 quantitative articles were selected for inclusion. The synthesized effect estimate for the association of roadway characteristics with injury risk was OR = 2.5 (95% CI: 1.8, 3.2) for pediatric populations. Although this analysis did not specifically identify which roadway characteristics are most amenable to intervention, the analysis suggested that built environment interventions directed at the roadway may result in meaningful reductions in pediatric pedestrian injury risk Interventions to Decrease Child Pedestrian-Motor Vehicle Collisions Interventions to reduce child pedestrian-motor vehicle collisions have traditionally been directed at traffic safety education. Educational interventions when used in isolation, however; have not led to a reduction in deaths and serious injuries from road traffic collisions. 89 Although these interventions can change behaviour, effectiveness has not been shown in terms of reducing rates of road traffic crashes. 8 A systematic review of randomized trials of road safety educational interventions to reduce pedestrian-motor vehicle collisions found some programs did improve 21

38 safety knowledge and road crossing behavior but methodological quality was poor and none of the studies reviewed linked changes in these behaviours to injury. 90 Pedestrian-motor vehicle collision prevention programs are felt to have limited value, as they have not been shown to have substantial effects on injury rates. 12,91,92 Roberts has suggested that scarce resources be redirected instead to environmental approaches which have substantial evidence supporting their efficacy. 91 Modification of the built environment removes the responsibility for traffic safety solely from the individual, and benefits the community as a whole which is a more promising and efficient approach. A cost effectiveness analysis demonstrated that 18 child pedestrian deaths could be prevented each year in New Zealand if funds were redirected from pedestrian education to traffic calming. 91 In many countries, roads have been built focused on motor vehicle users, with less consideration for pedestrian safety. High speeds road have been built in residential areas and there have not been adequate safe play and walking areas integrated into the planning of communities. 20 Many environmental modification strategies have focused on speed reduction. Speed is the major risk factor for crashes, and directly influences injury severity. 8,93 The World Health Organization reports that pedestrians have a 90% chance of surviving collisions at < 30 km/h or below, but less than a 50% chance of surviving at collisions at >45 km/hr. 8,94 Since 2002, speeding has been a factor in approximately 1/3 of motor vehicle crash deaths in the United States. 95 In Sweden, a power model estimating the relationship between speed and safety found a 5% increase in mean speed led to approximately a 10% increase in all injury and a 20% increase in fatal collisions. 96 Changes in speed limit laws and reducing speed limits from 30 mph to 20 mph was associated with an estimated reduction in child pedestrian-motor vehicle collisions by 67% in the United Kingdom. 97 In Zurich, reduction of speed from 60 to 50 km/hr was associated with a decrease in collisions by 16%, injured pedestrians by 20%, and fatalities by 25%. 98 Other interventions aimed at environmental modification have shown effectiveness in reducing collisions and injury. Retting et al. in a review of traffic engineering literature and pedestrianmotor vehicle collisions divided countermeasures into 3 categories: speed control, separation of pedestrians from vehicles and measures that increase the visibility of pedestrians. 99 Speed control measures included traffic calming devices such as speed humps and lane narrowing and multiway stop-sign controls. Separation of pedestrians from vehicles included devices to 22

39 separated pedestrians by time (i.e., exclusive pedestrian signal phases) or by place (i.e., barriers and sidewalks). Visibility interventions included lighting, crosswalk markings and adaptations to parking. Measures that were found to be highly effective were single-lane roundabouts, pedestrian islands and pedestrian signal phasing and increased roadway lighting. There were other promising measures which had only limited evaluation. The review concluded that pedestrian-motor vehicle collisions could be reduced by 50% to 75% in specific locations and 25% area-wide. Sixteen controlled before-after studies in high income countries addressing area-wide traffic calming strategies such as those to slow down traffic (e.g. speed humps), visual changes (lighting), redistribution of traffic (e.g. one-way streets) and changes to road environments (e.g. trees) were reviewed by Bunn et al. 100 This review found evidence for a 37% reduction in fatal outcomes and 11% reduction in severe outcomes using area wide traffic calming. Other systematic reviews focus specifically on the effectiveness of red light cameras, 101 speed enforcement detection devices, 102 and street lighting in reducing crashes. 103 All reviews reported that these types of interventions are effective in reducing the number of crashes causing injury/fatality. A study was recently published by Dimaggio and Li, which examined the effectiveness of environment safety improvements in reducing pedestrian injuries in school-age children in New York City as part of the Safe Routes to School Program (SRTS). 104 Improvements at 124 schools included speed reduction devices (e.g. speed bumps, speed boards), high visibility crosswalks, and exclusive pedestrian signals. The annual rate of pedestrian injury decreased 33% in school-age children (44% during school-travel hours), and 14% in other age groups in census tracts with SRTS interventions. The rates remained unchanged in areas without SRTS interventions. This study highlighted the need for evaluation of programs designed to increase walking to school to focus on pedestrian injury outcomes, as well as on walking rates. 23

40 2.5.2 Walking to School Correlates Several literature reviews have investigated the correlates of active travel by children. The strongest and most consistent correlate with walking to school is distance to school. Wong et al. conducted a systematic review examining GIS measured built environment correlates of AST, and found that measured distance to school was negatively associated with AST. 85, In an Australian study, the odds of walking to school was 5 times greater for school trips < 800 m compared to trips > 800, for 5-6 year olds, and 10.2 times greater for year olds. 108 Mitra et al. in a study of year olds in Toronto found that a 1 km decrease in GIS measured travel distance increased the odds of walking by 0.71 to 0.72 times. 105 Reported distance to school is also strongly associated with school travel mode. 78, In a study by Mcmillan, the probability of AST increased if reported distance from home to school was less than a mile (i.e., < 1.6 km). 117 In an analysis of the US Department of Transportation s 2001 National Household Travel Survey for ages 5-13 years, Mcdonald found that travel time (i.e., distance to school) had the strongest effect on the decision to walk to school with a 10% increase in walk travel time leading to a 7.5% decrease in walk mode share. 111 She created scenarios based on findings from her study (Figure 2-5): for example, if all children lived 0.8 km from their school the model estimates that 34% would walk. If students lived 1.6 km (1 mile) from their school, 19% would walk. In a model by Salmon, 47% of those living within a 15-minute walk to school (estimated to be approximately 1.6 km) usually walked compared with 4% of those living further away. 112 Other correlates of active travel in children are more difficult to define. Many studies have examined the correlates of walking in adults, with some consensus that walking in adults % Figure 2-5: Distance to school.

41 is related to density, mixed land use, pedestrian facilities (including sidewalks, trails, crosswalks), high connectivity grid network, short block lengths, many intersections with few cul-de-sacs/dead ends and accessibility (proximity to multiple destinations). 67,118,119 Studies of walking in elementary school-age children are less common and results are inconsistent with what has been found in adults. In children, walking to school has been examined as their primary walking destination. In a systematic review of the literature which analyzed walking to school correlates using multivariate analysis, Sirard et al, distinguished between factors at the policy, neighbourhood and parent/family level that influenced AST. 65 Correlates identified to have a positive association with AST included: 1) Policy level: physical education classes 2) Neighborhood level (objectively measured): shorter distance to school, urban area, street/intersection density, windows facing the street, complete sidewalk system, mixed land use, area-level SES (higher SES), residential and/or workplace density, and population density 3) Parent/family level (reported): urban area, stores/facilities close by, walking and bike facilities, land-use mix, aesthetics, socialization, family approval of walking, sidewalks on most streets (child report), male gender, single-parent family, number of children and stay-at-home parent. Associations with built environment variables tend to be inconsistent. In the Sirard review, many built environment correlates had positive associations with walking in some studies, and null associations in other. 65 The related concepts of route directness and street connectivity have been reported to be both positively associated, 112,120 and negatively associated with walking. 108,121 Residential/population density, mixed land use, sidewalks, crosswalks, trails, traffic lights, parks/recreational facilities, lower road class, lower traffic volume and less street connectivity (including dead- ends and cul-des sacs), have all been found to be associated with walking to school in some studies, 35,105,107,108, ,116,117, with other studies reporting null associations. 105,107,117,120,121,124,127,130,136,137 Traffic calming and less speed were consistently associated with more walking. 117,121,125,130 There are several possible explanations for the inconsistent results. Built environment correlates vary by walking purpose in children. 130 Age ranges of targeted populations of children vary from study to study. There are differences in how walking outcome is measured (parent versus child-reported) and how walking is conceptualized, with the reporting of usual trip, trip 25

42 per/week, or with different recall time frames. Differences in how the correlates are measured can also affect results, as some studies measured the built environment using perceived measures and others using objective measures such as field surveys and databases using GIS. There have also been methodological challenges identified when using GIS measurement of correlates. In a systematic review of 14 studies examining GIS measured environmental correlates of AST by Wong et al., inconsistencies were identified between studies regarding how data were geocoded, the different buffer size and shapes used, the quality of environmental data and difficulties with the estimation of the school routes. 85 As a result, conclusions were limited; with distance to school being the only consistent significant negative correlate with AST identified. Measurement standards are required to establish a definitive list of factors that influence walking in children Interventions to Increase Walking to School Few studies examine the effectiveness of interventions directed at increasing AST. A systematic review conducted in 2011 by Chillon et al. found 14 studies focused on interventions to increase walking to school in children and adolescents. 138 The intervention design for each study was examined using the Active Living by Design Community Action Model. 139 This model is a framework with multi-level strategies to increase physical activity and has been used in other AST studies. There are five strategies outlined in this model: 1) Preparation: deliberate process of getting ready for and reinforcing action 2) Promotion: education and encouraging opinion leaders and the public 3) Programs: organized activities directed at increasing physical activities 4) Policies: rules or standards that affect physical activities and 5) Physical projects: removing barriers to physical activity and create opportunities by directly changing the built environment. Chillon reviewed 13 studies, of which 2 studies included all 5 strategies. Only 3 studies integrated physical projects. Only the studies by Boarnet et al. focused on physical projects directed at the built environment in terms of infrastructure projects in the community. 128,140 Boarnet et al. found that children who passed infrastructure projects completed as part of Safe Routes to School programs, including sidewalk, crossing and traffic control projects in California at 10 schools were more likely to show increases in active school travel than those who did not (15% vs. 4%). 128 Projects with evidence of success in increasing AST were related to 26

43 replacement of 4-way stop signs with traffic signals, and sidewalk gap closures. 140 Generally, there was evidence of promising yet small effectiveness of interventions. All interventions evaluated were heterogeneous in nature and it was therefore difficult to determine which aspects of the interventions were most effective. All studies were also rated weak in the global rating in the quality assessment. The review emphasized the need for higher quality studies examining interventions directed at increasing AST, including experimental study designs, appropriate statistical analysis (taking into account confounders) and reliable and valid data collection methods. 2.6 Geographic Information Systems (GIS) This section discusses the use of Geographic Information Systems (GIS) in public health and in collision research. Studies that have used GIS to examine the spatial distribution of child pedestrian-motor vehicle collisions and walking to school are reviewed. The benefits of the use of GIS for this type of research are described. When studying the influence of the built environment on transportation and health outcomes at a population level, data are most effectively organized using GIS. GIS are tools that can be used to organize data from existing sources that incorporate a spatial framework. GIS are commonly described as computer information platforms designed to collect, manage, store, and analyze spatial and non-spatial data. 141,142 Although the use of GIS in geographic research is well established, the use of GIS for public health issues is relatively new. 143,144 The development of desktop GIS software in the last 20 years has enabled health researchers to examine data spatially and to create maps. 143,144 Since then, the use of GIS has proliferated into many areas of public health worldwide and in Canada. GIS databases are comprised of geometric data (street addresses, postal codes, cities, coordinates) and attribute data (socioeconomic data, census data.). 143 With these data, GIS can be used to create large datasets based on geography to identify relationships among variables that influence collisions according to a range of aggregations, such as census geographic areas or other types of administrative boundaries. 145 For 27

44 example, child pedestrian-motor vehicle collisions can be mapped onto school attendance boundaries along with roadway features (Figure 2-6). Figure 2-6: Child pedestrian-motor vehicle collisions and roadway design features GIS and Child Pedestrian-Motor Vehicle Collisions Child pedestrian-motor vehicle collision studies incorporating GIS methodology have emerged in the past several years primarily from the geography, engineering and environmental and life sciences disciplines, with only a few studies from the public health sector. GIS methodology is particularly useful to study child pedestrian-motor vehicle collisions as these collisions have a strong geographical component. GIS can be used to describe geographically based high risk areas and populations, and to identify potential correlates of collisions in these locations. Many GIS studies have focused on identifying locations and cluster/hot spots of child pedestrian-motor vehicle collisions, 137, with several also investigating temporal aspects. 137,147,149,150 For example, one of the earliest studies using GIS to examine child pedestrian-motor vehicle collisions was conducted by Braddock et al. who mapped police-reported child pedestrian-motor vehicle collisions and the child s residence to identify high-occurrence areas in Connecticut. 146 They found two high occurrence areas and compared characteristics between the two areas. Weiner et al. used emergency department and trauma registry to locate and examine child pedestrian-motor vehicle collisions in Jacksonville, Florida and found a high density of collision in the urban core of northwest Jacksonville

45 Several studies have investigated child pedestrian-motor vehicle collisions related specifically to school locations, which are unique in that these locations are characterized by fluctuating periods of high intensity car and pedestrian traffic. 39,147,148,151,152 Warsh et al. used GIS to investigate child pedestrian-motor vehicle collisions within and outside school zones in Toronto based on time of day and school months. 39 They found that the highest density of collisions occurred within 150m of schools (Figure 2-7). Figure 2-7: Child pedestrian-vehicular collisions in school zones (permission granted to reproduce). In Montreal Canada, Cloutier et al. investigated the association between social and built environment variables and child pedestrian-motor vehicle collisions near schools, as identified by the Quebec Automobile Insurance Corporation (SAAQ). 151 Positive associations were found between child pedestrian injury risk and school crossing guards, land use diversity, residential density, deprivation and child population density. Yiannakoulias et al. used emergency department surveillance systems in Edmonton Alberta, to identify peak collisions times and location of high collision incidence, specifically related to school travel. 40 GIS methodologies have also been used to examine both environmental and individual correlates of child pedestrian-motor vehicle collisions. 148, Lightstone et al. used GIS to map child 29