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Children’s travel to school : the influence of built form and perceptions of safety Niece, Jennifer Lynn 2006

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CHILDREN'S T R A V E L TO S C H O O L : T H E INFLUENCE OF BUILT FORM AND PERCEPTIONS OF S A F E T Y  by  JENNIFER LYNN NIECE  B.ES, University of Waterloo, 2000  A T H E S I S S U B M I T T E D IN PARTIAL F U L F I L M E N T O F T H E REQUIREMENTS FOR THE D E G R E E OF  M A S T E R S O F A R T S in P L A N N I N G in  T H E FACULTY OF G R A D U A T E STUDIES  T H E U N I V E R S I T Y O F BRITISH C O L U M B I A August 2006  © Jennifer Lynn Niece, 2006  ABSTRACT Background: C h i l d r e n in d e v e l o p e d n a t i o n s a r e s p e n d i n g m o r e time in c a r s a r e w a l k i n g to s c h o o l t h a n 4 0 y e a r s a g o . T h i s t r e n d h a s i m p l i c a t i o n s for c h i l d r e n ' s p h y s i c a l activity a n d h e a l t h , pollution c o n g e s t i o n in the vicinity of s c h o o l s , a n d c h i l d r e n ' s o p p o r t u n i t i e s independent decision-making.  and fewer important a n d traffic to p r a c t i c e  Objective: To e x a m i n e the r e l a t i o n s h i p b e t w e e n c h i l d r e n ' s m o d e of travel to s c h o o l a n d f a c t o r s of d e m o g r a p h i c s , m i c r o - s c a l e built f o r m , a n d p e r c e p t i o n s of safety. To c o m p a r e m i c r o - s c a l e built e n v i r o n m e n t c o n d i t i o n s with p a r e n t a l p e r c e p t i o n s of safety. Methods: G e n d e r , a g e , i n c o m e , d i s t a n c e , h o u s e h o l d v e h i c l e o w n e r s h i p , m o d e of travel to s c h o o l , a n d p e r c e p t i o n s of s a f e t y w h i l e w a l k i n g to s c h o o l w e r e o b t a i n e d f r o m travel s u r v e y s distributed to g r a d e 4 a n d 5 c h i l d r e n a n d their p a r e n t s at 7 e l e m e n t a r y s c h o o l s in the L o w e r M a i n l a n d of B . C . Built e n v i r o n m e n t f e a t u r e s w e r e e v a l u a t e d at the s t r e e t - s e g m e n t a n d i n t e r s e c t i o n s c a l e u s i n g a s t a n d a r d i z e d s u r v e y . E a c h child w a s a s s i g n e d a u n i q u e " p e d e s t r i a n f r i e n d l i n e s s " s c o r e b a s e d o n a n e s t i m a t e d route b e t w e e n their h o m e a n d s c h o o l . A binary logistic r e g r e s s i o n m o d e l w a s d e v e l o p e d to statistically e x a m i n e r e l a t i o n s h i p s . Results: D i s t a n c e b e t w e e n h o m e a n d s c h o o l h a d the s t r o n g e s t i n f l u e n c e o n travel m o d e c h o i c e with v e h i c l e o w n e r s h i p a n d p a r e n t a l p e r c e p t i o n s of s a f e t y f r o m traffic a n d f r o m s t r a n g e r s or bullies b e i n g significant but l e s s influential. C o n t r a r y to a c c e p t e d n o r m s in the literature, h o u s e h o l d i n c o m e w a s not significant e v e n after r e m o v i n g d i s t a n c e a n d v e h i c l e o w n e r s h i p f r o m the m o d e l . I n d e x e d s c o r e s of m i c r o - s c a l e p e d e s t r i a n e n v i r o n m e n t v a r i a b l e s w e r e f o u n d to b e highly influential for c h i l d r e n living within a 5 0 0 m e t r e r a d i u s of s c h o o l , but not for the o v e r a l l s a m p l e . P a r e n t a l p e r c e p t i o n s of s a f e t y f r o m traffic w e r e significantly a s s o c i a t e d with the "worst c a s e " street s e g m e n t a n d intersection s c o r e s o n a c h i l d ' s route to s c h o o l , but o t h e r m e a s u r e s of p e r c e p t i o n of s a f e t y w e r e not. T h e i n f l u e n c e of d i s t a n c e is c o n f o u n d e d by its c l o s e r e l a t i o n s h i p s with p e r c e p t i o n of s a f e t y f r o m traffic a n d p e d e s t r i a n f r i e n d l i n e s s s c o r e s . T h e l a c k of s i g n i f i c a n c e of the built e n v i r o n m e n t m e a s u r e s is likely affected by the relatively low l e v e l of variation in m e a s u r e d c h a r a c t e r i s t i c s in the n e i g h b o u r h o o d s s e l e c t e d for study. Conclusion: o m e to s c h o o l d i s t a n c e h a d the s t r o n g e s t i n f l u e n c e o n w h e t h e r c h i l d r e n w o u l d b e a c t i v e or not o n the w a y to s c h o o l . T h e i n d e x of m i c r o - s c a l e m e a s u r e s of the p e d e s t r i a n e n v i r o n m e n t e x a m i n e d in this s t u d y w e r e highly influential for c h i l d r e n living l e s s t h a n half a kilometre f r o m s c h o o l e v e n after controlling for v e h i c l e o w n e r s h i p a n d p a r e n t a l p e r c e p t i o n s of safety. T h e p e d e s t r i a n e n v i r o n m e n t w a s not significant for the entire s a m p l e , a l t h o u g h the i n f l u e n c e of d i s t a n c e m a y m a s k this r e l a t i o n s h i p . H o u s e h o l d v e h i c l e o w n e r s h i p a n d parental p e r c e p t i o n s of s a f e t y f r o m traffic a n d s t r a n g e r s w e r e significant a c r o s s the entire s a m p l e . F u r t h e r r e s e a r c h s h o u l d i n c l u d e a b r o a d e r diversity of street c h a r a c t e r i s t i c s to m o r e c o m p l e t e l y u n d e r s t a n d the i n f l u e n c e of the m i c r o - s c a l e built e n v i r o n m e n t . T h e f a c t o r s influencing p a r e n t a l p e r c e p t i o n of safety, a n d the role of c o n v e n i e n c e in d e c i s i o n - m a k i n g s h o u l d a l s o b e s t u d i e d in m o r e detail. ii  TABLE OF CONTENTS Abstract  ii  T a b l e of C o n t e n t s  iii  List o f T a b l e s  v  List o f Figures  vi  List o f P h o t o s . . .  vii  Acknowledgements  viii  C H A P T E R 1 - Introduction;  1  1.1 C u r r e n t T r e n d s  1  1.2 W h y Walk? 1.3 R e s e a r c h Objectives a n d H y p o t h e s i s 1.4 Project Outline  2 5 8  C H A P T E R 2 - Review o f C u r r e n t Literature 2.1 2.2 2.3 2.4 2.5  Theoretical Context E x p l o r i n g Existing Evidence Intra- a n d Interpersonal Factors E n v i r o n m e n t a l Factors Conclusion  CHAPTER 3 - Methods 3.1 3.2 3.3 3.4  Introduction.... Behavioural a n d Perceptual Data M i c r o - S c a l e Survey o f the Built E n v i r o n m e n t D e t e r m i n i n g a U n i q u e Built E n v i r o n m e n t Score for Each C h i l d 3.5 Data A n a l y s i s 3.6 M e t h o d o l o g i c a l Limitations  C H A P T E R 4 - D e s c r i p t i v e Statistics 4.1 4.2 4.3 4.4 4.5 4.6 4.7 4.8  Overall S a m p l e B r o o k s b a n k Elementary B o u n d a r y Elementary B r e n t w o o d Park Elementary Hatzic Elementary M a r l b o r o u g h Elementary M i s s i o n Central Elementary Walter M o b e r l y Elementary  C H A P T E R 5 - A n a l y t i c a l Statistics 5.1 Factors Influencing Travel M o d e 5.2 Factors Influencing Parental Perceptions o f Safety 5.3 C o n c l u s i o n  10 10 15 18 21 31 32 32 34 44 57 65 65 69 70 85 ....90 ..94 98 103 106 11 0 114 11 8 141 1 42  iii  CHAPTER 6 - Discussion and Conclusion 6.1 6.2 6.3 6.4 6.5 6.6 6.7 6.8  Overall T r e n d s Distance H o u s e h o l d and V e h i c l e O w n e r s h i p T h e Influence o f the Built E n v i r o n m e n t Perceptions of Safety Observations on Methods S u m m a r y a n d R e c o m m e n d a t i o n s for Future Research Policy R e c o m m e n d a t i o n s  144 144 145 147 1 47 149 1 51 1 56 1 58  Endnotes  1 62  Bibliography  165  Appendices:  A p p e n d i x A : Parent a n d C h i l d Travel Surveys  1 72  A p p e n d i x B: M i c r o - S c a l e Built E n v i r o n m e n t Survey  183  A p p e n d i x C : U B C Behavioural Research Ethics Board  197  Certificate of A p p r o v a l A p p e n d i x D: C o v e r Letters A c c o m p a n y i n g Travel Surveys  198  A p p e n d i x E: S u m m a r y of Inter-Rater Reliability (Kappa) T e s t s  200  A p p e n d i x F: S u m m a r y of Descriptive Statistics  204  iv  List of Tables: Chapter 3 Table 3.1  Travel Survey Data Entry Error Checking Record  38  Table 3.2  List of Variables Selected from Parent and Child Travel Surveys  39  Table 3.3  R e s p o n s e Rate Per School  40  Table 3.4  Imputation Methods for Parent and Child Survey Data  42  Table 3.5  School Selection Criteria  47  Table 3.6  Categories of Variables Included in the Micro-Scale Survey  50  Table 3.7  Number of Intersections and Street Segments Evaluated  53  Per School Table 3.8  Variables selected from the N Q L S Micro-Scale Survey  54  Table 3.9  Impact of Catchment Area Exclusion on Total Sample Size  58  Table 3.10  Converting Categorical Data into Calculable Scores  61  Table 3.11  Ordinal Ranking of Variables for the Equal Weight Index  64  Table 4.1.  Summary of Selected Demographic Variables  72  Table 4.2  Summary of Selected Travel Behaviour Variables  76  Table 4.3  Summary of Selected Perception of Safety Variables  78  Table 4.4  Summary of Selected Pedestrian Environment Scores  84  Chapter 4  Chapter 5 Table 5.1  Glossary of Variables  115  Table 5.2  Correlation of Demographic Variables  119  Table 5.3  Correlations Between perceptions of safety variables..  120  Table 5.4  Correlations Between Demographics and Perceptions of Safety  120  Table 5.5  Correlation Between Micro-Scale Variables  121  Table 5.6  Chi Square relationships with Active / Not Active Travel Mode  122  Table 5.7  Results of Various Binary Logistic Regression Models  126  Table 5.8  Binary Regression By Distance  134  Table 5.9  Distance Correlated with Pedestrian Friendliness Scores  140  Table 5.10  Chi Square Comparing Perceived Safety to Built Environment Measures..  141  Binary Regression Measuring the Effects of Lowest Pedestrian Friendliness Score on the High and Low Perception of Safety from Traffic  142  Table 5.11  List of Figures: Chapter 2 Figure 2.1  Ecological Model of Travel Mode Choice  14  Figure 2.2  Street Network Versus Straight Line Distances  22  Chapter 3  Figure 3.1.  Ideal Categories of Neighbourhood for Participant Recruitment  45  Figure 3.2.  Sample Catchment Area Map with Evaluated Street Segments Marked  52  Sample map of route to school [Brentwood Elementary]  60  Figure 4.1  Locating Participating Schools in the Lower Mainland  70  Figure 4.2  Income Distribution of Total Sample  71  Figure 4.3  Reported and C e n s u s Average Incomes by School Neighbourhood  71  Figure 3.3  Chapter 4  Figure 4.4. Average Vehicle Ownership by Household Income  72  Figure 4.5.  Distribution of Home to School Distances....  73  Figure 4.6.  Morning and Afternoon Travel Modes  74  Figure 4.7 Figure 4.8. Figure 4.9  Morning Travel Mode Versus Favourite Travel Mode Proportion of Active Travel by Distance Census-Reported Mode of Travel to Work  ,.  74 75 75  Figure 4.10  Parental Perceptions of Safety  76  Figure 4.11  Children's Perceptions of Safety  77  Figure 4.12.  Proportional Distribution of Intersection Characteristics  79  Figure 4.13a  Variation of Traffic Control Features by School  79  Figure 14.13b Variation of Crosswalk Signage by School  80  Figure 4.14  80  Proportional Distribution of Street Segment Characteristics  Figure 4.15a  Variation of Sidewalk Coverage by School.  81  Figure 4.15b  Variation in the Presence of Traffic Calming Elements  81  Figure 4.16a  Distribution of Pedestrian Friendliness Scores  82  Figure 4.16b  Distribution of Lowest Pedestrian Friendliness Scores  82  Figure 4.17a  Pedestrian Friendliness Score Quartiled by School  83  Figure 4.17b  Lowest Pedestrian Friendliness Score Quartiled by School  83  Figure 4.18  Brooksbank Elementary Catchment Area  86  Figure 4.19  Boundary Community Catchment Area  91  Figure 4.20  Brentwood Park Elementary Catchment Area  95  Figure 4.21  Hatzic Elementary Catchment Area  99  Figure 4.22  Marlborough Elementary Catchment Area  103  Figure 4.23  Mission Central Elementary Catchment Area  107  Figure 4.24  Walter Moberly Elementary Catchment Area  111  List of Photos: Chapter 3 Photo 3.1a  and b - Short Cuts in the Hatzic and Boundary Elementary Catchments  59  Chapter 4 Photo 4.1: Brooksbank Elementary School  85  Photo 4.2  Boundary Community Elementary  90  Photo 4.3  Brentwood Park Elementary School  94  Photo 4.4  Hatzic Elementary School  98  Photo 4.5  Marlborough Elementary School  103  Photo 4.6  Mission Central Elementary School  106 vii  Photo 4.7 Walter Moberly Elementary School.....  110  Chapter 6 Photo 6.1a,b,c: Streets with the s a m e segment scores  152  Photo 6.2a,b: Intersections with the same traffic control scores  154  viii  ACKNOWLEDGEMENTS There are many people who deserve thanks and recognition for their contributions to this research project. Without their guidance and hard work, this thesis would not have been possible.  Dr. Lawrence Frank, Associate  Professor and J. Armand Bombardier Chair in Sustainable Transportation, UBC School of Community and Regional Planning was the academic supervisor of this project. Thank you for your guidance throughout the process and for pushing me to stretch my limits.  Dr. Stephanie Chang, Associate Professor and Canada Research Chair in Disaster Management and Urban Sustainability, UBC School of Community and Regional Planning was the second academic advisor on this thesis and provided valuable statistical advice. Dr. Heather McKay, Associate  Professor of Family Practice, Department of Orthopaedics, UBC Faculty of Medicine and Dr. P.J. Naylor are the co-investigators on the Action Schools! B C research program who provided the research opportunity. Dr. M c K a y also acted as the external examiner for this thesis.  The Canadian Institutes of Health Research for funding the Action Schools! B C research program, including distribution of the children's travel surveys.  Dr. J i m Sallis, Professor of Psychology, San Diego State University\ot providing feedback on the travel survey and a c c e s s to the computerized Micro-Scale Survey through the Neighbourhood Quality of Life Study ( N Q L S ) . Ms. Sharon Storoschuck, Research Coordinator and Ms. Deetria Egeli, Research Assistant at the U B C Bone Health Research Group for their extensive work coordinating administration of the travel surveys. Ms. Kelli Cain, Project Manager, Neighbourhood Quality of Life Study for assistance in installing and using the Micro-Scale Survey and G P S equipment. Ms. Karen Zeller, Administrator, U B C Centre for Human Settlements for her assistance with numerous administrative tasks. Dr. Kathleen Kern, Community Planner, City of Vancouver for training the evaluators on the use of the Micro-Scale Survey. T h e S C A R P students in P L A N 581 the many days spent evaluating the built environment at each of the elementary schools; Eric Doherty, Peter Giles, Eric Grant, Ugo  Lachappelle, Haley Mousseau, Ren Thomas, and Lee Chan  All of the elementary school students, their parents, teachers, and administrators for agreeing to participate in the research program.  school  Ms. J u x i n Liu, P h D . Candidate, U B C Department of Statistics for providing advice on the data analysis.  •  -  Financial support was provided by the Government of C a n a d a through the Social Sciences and Humanities Research Council ( S S H R C ) and by the University of British Columbia. Special thanks to my parents for a lifetime of love and support, for encouraging me to follow my dreams, and for letting me walk to school. And to Vic - thank you for listening, and for the photos of Mississauga!  ix  CHAPTER  1:  INTRODUCTION  "If we can build a successful city for children we will have a successful city for all people." Enrique Penalosa, former mayor of Bogota, Colombia Gilbert  1.1  and O'Brien,  2005,  p.5  Current T r e n d s  How children travel to school is an issue of increasing interest to researchers, educators, parents, health professionals, and policy-makers. This interest parallels concern over the negative impacts of traffic congestion, air pollution, and declining levels of physical activity among people of all ages. But there are many reasons why children's travel, and travel to places where children congregate (such as schools and community centres) deserves specific attention.  This study focuses on how children travel to school, and explores  various factors that influence their mode choice decisions.  Evidence suggests that children across the developed world are spending more time in cars and fewer are walking to school than 30 to 40 years ago.  1  Although national travel  data are scarce in C a n a d a , figures from some regional surveys corroborate this trend. In the Greater Toronto Area (GTA) between 1986 and 2001, the number of week-day car trips taken per child increased by 83%, while their parents' trips only increased by 11%.  2  T h e 2004 Trip Diary Survey in Greater Vancouver confirms that children between the ages of 5 and 12 travel as automobile passengers nearly 70% of the time, with walking and cycling accounting for 30% of their trips.  3  (Note that both these studies account for all  children's trips, not just the journey to school). A national study conducted by G o for Green in 1998 indicated that nearly one in three children walks to school, although the survey of 1501 adults included only 429 with school-aged children. The same study found that 4  4 3 % of children use a school bus; since school boards generally set a minimum threshold distance for providing bus service this suggests that large school catchment a r e a s  3  are  a A school catchment area is a geographic boundary drawn around a school and from within which most students attending the school are drawn. INTRODUCTION  1  contributing to decreased walking to school.  Specific data on walking to school are more readily available outside of C a n a d a . In the United States the proportion of children walking to school decreased from 48% in 1969 to only 15% in 2000.  6  5  In Great Britain, the proportion of children being driven to school  increased from 16% to 29% between 1989 and 1999. In Melbourne and Perth, Australia, 7  60% of children travel to school by private car.  8  Part of this trend is influenced by the  increasing size of school catchment areas, which mean longer average distances to school and thus greater difficulty for children to walk.  9  However American children living close to  school are also walking less. In 1969, 90% of children living less than 1 mile from school walked to school - by 2000 this number had dropped to only 3 0 % .  10  Statistics grouped  by distance to school in C a n a d a are somewhat more promising; the G o for Green study estimated that 86% of Canadian children living within 1 kilometre, and 50% of those within 1-3 kilometres of their school will walk "most of the time".  1.2  Why Walk?  P h y s i c a l Activity a n d Health: Sedentary lifestyles cars  11  13  12  - and in particular time spent in  - are closely linked to increased risks of becoming overweight or obese. E x c e s s  body weight and physical inactivity (regardless of body weight) are both associated with health risks such as chronic heart disease, hypertension, diabetes, osteoporosis, and some forms of c a n c e r .  14  O b e s e children are more likely than their average-weight peers  to develop hypertension, glucose intolerance, and orthopedic complications; they face greater challenges of social acceptance, and are likely to remain obese as adults. Physical 16  activity is decreasing among Canadians of all a g e s  16  and observed rates of overweight  and obesity doubled among Canadian children between 1981 a n d 1 9 9 6 .  17  In response,  encouraging children to exercise more has become a major public health concern and walking to school is an important source and regular source of this exercise.  Research has demonstrated that children who walk to school accumulate higher levels of physical activity than their counterparts who are driven.  18  It is unclear whether walking  INTRODUCTION  2  to school by itself is enough to attenuate body weight,  19  but after excluding the journey to  school as a source of exercise, children who walk to school are found to remain more active throughout the day than their peers who are driven.  20  Measured with accelerometers,  b  children expend nearly as much energy while walking as while playing team sports; moreover, walking to school accumulates significantly more minutes of exercise per week than typically scheduled physical education periods. The early establishment of an 21  active lifestyle helps children to maintain healthy body weights, and avoid chronic health problems associated with obesity and sedentary lifestyles later in life.  22  Traffic a n d P o l l u t i o n : A s more parents choose to drive their children to school, school zones are becoming high-traffic areas with increased probability of accidents. T h e Insurance Corporation of British Columbia (ICBC) estimates that 20-25% of traffic in morning peakperiods are related to travel to and from schools.  23  Parked cars reduce visibility for and  of children, making it hazardous for them to cross at intersections and increasing the chance they will not be seen running between parked c a r s .  24  School administrators have  cited reducing the number of vehicles around schools as the most important reason to encourage students to walk or cycle to school.  25  Pollution is also problematic and idling vehicles increase concentrations of priority pollutants such as particulate matter and ground level ozone within the immediate vicinity of the school yards. Concentrations of benzene and carbon monoxide inside cars can be many times higher than those on the sidewalk.  25  The Canadian Institute of Health highlights  children's special vulnerability because they inhale more air per unit of body weight than adults, have narrower airways, and because environmental toxicants can interfere with the chemical messengers involved in growth.  27  Elevated levels of air pollution are significant  contributors to both acute and chronic respiratory problems such as asthma that result in lost days of school for children and significant costs to C a n a d a ' s public health care system. Trips to school are generally "short trips", which are considered to produce more 28  pollution per travel distance than longer ones;  29  short trips are prime candidates for non-  b An accelerometer is a small device worn on a belt that monitors the intensity of an individual's physical activity (except for swimming) on a minute by minute basis. INTRODUCTION  3  motorized transportation modes and thus are an important target for reducing overall traffic demand.  C h i l d D e v e l o p m e n t : Finally, walking is an important partofthe intellectual and psychological development of children.  30  Walking in their neighbourhood, including to school, is a key  opportunity for children to explore and learn confidence, to practice learned safety skills, to develop cognitive mapping skills, and to experience independence.  31  In one example,  children who traveled primarily by car demonstrated a poorer perception of distances and the placement of key destinations relative to one another than their peers who walked to school.  32  Walking to school may contribute to a stronger s e n s e of community which  has been associated with lower rates of drug use and petty crime. Moreover, walking to 33  school is a good start to developing life-long habits of physical activity and transportation choice.  34  If our society wishes to reduce traffic congestion, foster a healthy population,  and address issues of air pollution and climate change, it is essential that our children be exposed to transportation alternatives at an early a g e . life-long walking.habits, even a  35  If walking to school develops into  10-20% shift in modal split for home to school trips could  have significant benefit for society in both the short and long-term.  Recognizing the importance of children being able to walk to school, school districts in both C a n a d a and the United States have adopted programs such as "Active and Safe Routes to School" (Ontario), "Way to Go!" (British Columbia), and "Safe Routes to School" (US). In C a n a d a the programs receive little to no funding from government and are facilitated primarily by non-profit organizations in partnership with school boards and community associations.  Programs focus on social-marketing strategies - providing curriculum-  related materials to teach traffic safety and appropriate route selection. Programs also include intra- and inter-school competitions to see which group can accumulate the most distance walked, "walking school buses" led by parent chaperones, neighbourhood mapping exercises, and restrictions on parking within a certain radius surrounding the school.  36  Programs in the United States receive state and federal funding for a combination  of social-marketing strategies (such as those used in Canada) and improvements to the  INTRODUCTION  4  physical pedestrian infrastructure in the vicinity of schools.  In 2005 the U.S. Congress  passed legislation called S A F E T - L U that includes $612 million over 4 years.  Seventy  to ninety percent of these funds are allocated to infrastructure with the remaining going to student education, public awareness campaigns, traffic law enforcement, and related programs to encourage cycling and walking.  37  There appearto be two potentially complimentary policy approaches to consider; investment in infrastructure improvements, and/or in social-marketing strategies.  Unfortunately,  although there is an extensive and growing body of knowledge on adult travel choices, less is understood about the factors that influence children's travel c h o i c e s  39  38  which could  positively inform such policy decisions. Research has demonstrated that adults tend to walk more in neighbourhoods with high population densities, interconnected street networks, a diverse mix of land uses, and more commerical destinations overall. T h e small existing 40  body of research on children's travel suggests that these factors are not influential on the journey to school, but results are somewhat contradictory and explorations of alternative influencing factors are limited.  41  In addition, the studies on children are concentrated in  the southern United States and no empirical research has been conducted on the topic in C a n a d a . It is hoped that an improved understanding of these influences will contribute to more informed policy decisions and better program design to achieve desired walk to school objectives.  1.3  Research Objectives and Hypotheses  T h e primary objective of this study is to better understand the factors influencing a child's mode of travel to school. Existing research on urban form associations with children's travel, and travel to school in particular, is inconclusive. S o m e studies show that macro-scale built environment features of density, street connectivity, and land use mix are important predictors of the total amount that children will walk. Others focusing specifically on the trip to school find these predictors not to be significant. The current study focuses on the child's trip to school by examining the influence of micro-scale pedestrian environment. Micro-scale characteristics are those measured at the street-scale such as number of  INTRODUCTION  5  l a n e s , p r e s e n c e of s i d e w a l k s , i n t e r s e c t i o n a n d c r o s s w a l k c o n t r o l s , a n d traffic c a l m i n g measures.  R e c o g n i z i n g the i m p o r t a n c e of n o n - i n f r a s t r u c t u r a l  i s s u e s , this s t u d y a l s o  e x p l o r e s p e r s o n a l p e r c e p t i o n s of s a f e t y w h i l e w a l k i n g to s c h o o l , d i s t a n c e b e t w e e n h o m e and s c h o o l , and d e m o g r a p h i c factors s u c h a s i n c o m e and vehicle ownership.  S p e c i f i c a l l y , this s t u d y a s k s the f o l l o w i n g four q u e s t i o n s :  1) To w h a t d e g r e e d o e s a n i n d e x of s e l e c t e d m i c r o - s c a l e f e a t u r e s of t h e p e d e s t r i a n e n v i r o n m e n t i n f l u e n c e w h e t h e r o r not a c h i l d r e g u l a r l y u s e s a n o n - m o t o r i z e d f o r m of travel to g e t to s c h o o l ?  2) T o w h a t d e g r e e d o e s p a r e n t a l p e r c e p t i o n of n e i g h b o u r h o o d s a f e t y (from traffic a n d c r i m e ) i n f l u e n c e w h e t h e r or not a c h i l d r e g u l a r l y u s e s a n o n - m o t o r i z e d f o r m of travel to get to s c h o o l ?  3) To w h a t d e g r e e a r e m e a s u r e s of the p e d e s t r i a n e n v i r o n m e n t a s s o c i a t e d with the d i s t a n c e b e t w e e n a c h i l d ' s h o m e a n d their s c h o o l ? 4) To w h a t d e g r e e d o m i c r o - s c a l e f e a t u r e s of the p e d e s t r i a n e n v i r o n m e n t a n d d i s t a n c e b e t w e e n h o m e a n d s c h o o l i n f l u e n c e p a r e n t a l p e r c e p t i o n s of s a f e t y for their c h i l d w a l k i n g to s c h o o l ?  B a s e d o n p r e v i o u s s t u d i e s , it is h y p o t h e s i z e d that c h i l d r e n w i t h h i g h - q u a l i t y p e d e s t r i a n e n v i r o n m e n t s o n their r o u t e to s c h o o l will b e s i g n i f i c a n t l y m o r e likely to w a l k t h a n t h o s e w i t h l o w - q u a l i t y p e d e s t r i a n e n v i r o n m e n t s a l o n g their route to s c h o o l .  H o w e v e r , it is  s u s p e c t e d that this p o s i t i v e r e l a t i o n s h i p b e t w e e n w a l k i n g a n d p e d e s t r i a n e n v i r o n m e n t s will b e m o d e r a t e d b y t h e i n f l u e n c e s of:  a ) t r a v e l d i s t a n c e (with t h e l i k e l i h o o d of w a l k i n g d e c r e a s i n g a s d i s t a n c e i n c r e a s e s ) ;  b)  h o u s e h o l d i n c o m e (with t h e l i k e l i h o o d of w a l k i n g d e c r e a s i n g a s h o u s e h o l d i n c o m e  increases);  INTRODUCTION  6  c) household vehicle ownership (with the likelihood of walking decreasing as the number of household vehicles increases), and  d)  parental perception of safety (with increased perception of risk associated with  decreased likelihood of walking).  T h e perceived relative convenience of different travel modes is likely also an influence, although this was not measured directly in this study. It was also suspected that pedestrian environment scores would be associated with distance between home and school, with children living closer to school having higher (better) pedestrian environment scores than those living farther away.  Finally, it was hypothesized that there would be an inverse relationship between parental perceptions of safety and the  pedestrian  environment  scores, with higher (better)  pedestrian environment scores associated with lower levels of concern over safety risks.  Methodological  Approach  This study applies a cross-sectional reasearch design to evaluate the influence of the pedestrian environment and perceptions of safety on children's walking to school while controlling for socio-economic factors and distance between home and school. The microscale pedestrian environment was measured using a standardized tool designed for the Neighbourhood Quality of Life Study (NQLS), a collaborative research project based at S a n Diego University.  42  It has been used only once for surveys in Washington State  and the results of the N Q L S micro-scale evaluation have not yet been published. This research is unique in the tactic of assigning a specific assumed route between  home  and school for each child participating the study, and then quantitatively evaluating the pedestrian-friendliness of each unique route. Previous research has focused on the attributes across the area in which the trip takes place but none have isolated specific trip routes for analysis. Thus two methodological questions became integral to the purpose of the research:  INTRODUCTION  7  1)  Is this micro-scale pedestrian environment survey an effective tool for measurement in the Greater Vancouver area?  2)  C a n the data collected using this measurement tool provide sufficient detail to integrate with the route-specific methodology applied in this study?  It is hypothesized that the measurement tool would provide a quality of data sufficient to answer the primary research questions but that the study would produce recommendations for improvements and refinements in subsequent applications of the methodology.  1.4 Project Outline  This thesis contains 6 chapters. Chapter 1, which you have just read, provided background on international trends in children's travel to school patterns, highlighted the benefits of increasing the number of children walking to school, and presented the research objectives and hypotheses. Subsequent chapters are each described briefly below:  Chapter 2 outlines current theoretical models of travel choice among adults, and highlights specific factors known to influence modal choice decisions. Validation is provided for the selection of each of the pedestrian environment, demographic, and perceptual factors selected for detailed analysis in this study.  Chapter 3 details the methods used in the data collection and statistical analysis of data. Methods are described within the theoretical and practical context of current best practices for data collection.  Chapter 4 describes each of the schools selected for participation in the study, based on data obtained through surveys of children and their parents, and surveys of pedestrian environment characteristics surrounding the schools.  INTRODUCTION  8  Chapter 5 describes the inferential statistical analysis undertaken to answer the four primary quantitative questions posed in section 1.3.  Chapter 6 discusses this author's interpretation of the study results including possible explanations for unexpected outcomes, a review of how the outcomes may have been affected by the study methodology, and recommendations are made for further research. This chapter concludes with a discussion of the policy implications arising from this study.  INTRODUCTION  9  C H A P T E R 2: REVIEW O F C U R R E N T LITERATURE "...the large number of variables (almost 200)  used in the instruments to capture envi-  ronmental factors...indicates a lack of knowledge about the effect of single variables on walking and bicycling." Moudon  and Lee,  2003  2.1 Theoretical Context  It is widely recognized that transportation is a derived demand; people travel to accomplish tasks and participate in activities, rarely for the sake of travel itself.  1  Models explaining  personal transportation choices are traditionally based in micro-economic theory that assumes individuals seek to maximize their own personal utility for any particular trip.  2  Personal utility is defined through a cost-benefit equation where pecuniary (monetary) costs and non-monetary costs such as time and effort are balanced against the anticipated benefits of the activity at the intended destination. S u c h costs are perceived by the 3  individual decision-maker in different ways.  For example, the decision to make a trip  may be heavily influenced by that specific trip's (relatively low) marginal monetary costs (e.g. the cost of gas and parking), even though the true cost of the trip is actually much higher after considering the fixed or sunken costs of vehicle purchase and maintenance.  4  In this way travel decision-making is also hierarchical; the decision to accept the sunken costs of car ownership is made only once compared to numerous daily decisions over marginal costs. O n c e the vehicle purchase cost is accepted, an individual is predisposed 5  to accept the comparatively small marginal costs associated with each trip. Transportation decisions also inherently include both sunken and marginal social costs such as the waste associated with vehicle production, traffic congestion and air pollution but these are generally externalized in both theoretical and practical applications.  Non-monetary costs of transportation include travel time, comfort, and convenience (relative to not taking the trip).  Difference in trip time is thought to be one of the most  important factors in mode choice, with longer trip times representing lost opportunities C U R R E N T L I T E R A T U R E 10  to engage in other activities.  6  Benefits include the pleasure or utility derived from the  destination activity, particularly in contrast to the (assumed lesser) benefit of alternatives to the journey, or not taking a trip at all.  Utility theory a s s u m e s that individuals make  rational decisions based on an awareness of and a c c e s s to the full range of alternatives,  7  although this may not actually be the case.  In the context of utility theory, a child's trip to school is particularly complex because of its interrelationship with travel demands of their parent.  T h e perceived relative costs  of different travel modes must consider the schedules and destinations of at least two individuals. Travel to school frequently becomes part of a complex trip-chain of sequential origins and destinations.  Higher order hierarchical decisions such as how (or if) the  parents travel to work will in turn influence the available mode choice options for the child's trip. For example, the incremental cost of driving a child to school en route to work is negligible after accepting the sunken costs of vehicle ownership and the incremental costs of the parent's trip to work.  In contrast a multi-modal trip chain of walking with a  child to school, then returning home (by foot) before driving to work incurs significant decreases in utility due to the additional time costs (which will vary depending on the home to school distance).  T h e nature of the transportation system acts as a mediator between  destinations  by increasing or decreasing the net utility of various trips and their associated mode c h o i c e s . For example, transit systems providing frequent and rapid service may increase 8  the perceived utility of public transit, whereas infrequent, poorly connected services will increase the attractiveness of the personal automobile.  Similarly, elements of the built  environment such as population density or the presence of sidewalks may alter the utility of non-motorized forms of travel (as discussed further in this chapter).  In contrast to utility theory, ecological models of behaviour or behavioural models of 9  the environment alternatives.  10  do not explain behaviour as rational cost-benefit comparison among  Instead, they recognize choices in terms of individuals' internal influencing  C U R R E N T L I T E R A T U R E 11  factors, social environments, and external  influences such as the built and  environments and institutional/ organizational structures.  11  natural  Ecological models recognize a  complex set of interacting influences beyond explicit costs and benefits. They recognize that behavioural influences are multi-layered, composed of physical settings (weather and built form), organizations, socio-demographic and socio-cultural environments, and the availability of social supports  12  and that effecting change requires multi-disciplinary  strategies customized to each layer.  13  A s e g u e between transportation theorists and ecological models of behaviour has come via the discipline of public health (where ecological models are commonly used), and shared desires to increase walking and cycling for physical activity and community transportation benefits.  14  T h e link with transportation planning has increased the emphasis on built-  environment aspects of physical activity, while the behavioural models have expanded how transportation  researchers view travel choice.  Moudon and L e e  categories of determinants in choosing non-motorized forms of travel.  1 5  define three  Described in the  context of children's travel to school, these are:  1.  Intra- a n d inter-personal f a c t o r s . It is widely recognized that socio-demographic factors of income and vehicle ownership have the strongest influence on travel mode c h o i c e .  15  Other factors are wide-ranging and include the child's level of  cognitive development and their ability to deal with risks, accepted norms among the peer groups of the child and parent, the physical fitness level of the child, preferred travel modes, perceived convenience of alternative travel modes, the degree to which the school administration encourages walking and cycling, local and provincial restrictions on vehicular activity in school zones, and school board policies on providing bussing.  2.  E n v i r o n m e n t a l f a c t o r s are sub-divided into three components of a trip. •  Origin and Destination:  availability of bike racks, changing areas, parking and/or  drop-off facilities, school-yard supervision before and after school, •  Route:  distance and directness of route, street type and design, proximity  between pedestrian/cyclist space and vehicular space, traffic controls within  C U R R E N T L I T E R A T U R E 12  school zones, presence of other children walking, presence of other road users (all modes) •  Overall Area:  density, land-use and street connectivity (which combine to  heavily influence distance), climate and weather, the number of other road users of different modes  3.  Trip c h a r a c t e r i s t i c s including single-purpose trip versus a trip chain, purpose and timing of other trips within the same trip-chain, the distance between home and school, activities taking place at the school influencing equipment to be taken (special sports days, large school projects, field trips), requirements for transportation and/or equipment at other parts of the trip chain.  It should be noted that the environmental factors in this model are extremely disaggregate; in a review of 31 pedestrian environment audit instruments, Moudon and L e e  1 6  found  over 200 discrete measures considered to influence the use of non-motorized travel. More evidence is clearly needed to understand the built environment component of the ecological model.  T h e three components of a journey (described under "environmental factors" above) are not only useful in considering environmental variables, but are also a valid way to categorize the inter-/intra-personal factors and trip characteristics. Any trip's origin and destination are fundamentally affected by personal preferences which determine  the  purpose of the trip, the best location for that purpose (e.g. the grocery store with the lowest prices), and whether the trip will be taken at all.  T h e trip destination and trip  purpose interact to influence the type of clothing to be worn, belongings or other people who must be transported, and the length of stay at the destination.  Moreover, recent  evidence in the literature makes it clear that personal preferences influence residential location choice which underpins travel behaviour.  17  All elements of a trip's route or the  area in which it takes place are viewed through the individual's personal perceptions and threshold tolerances for safety, enjoyment, weather, and convenience.  Figure 2.1  illustrates this author's conception of an ecological model of travel choice with specific  C U R R E N T L I T E R A T U R E 13  reference to the variables considered in the current study.  F i g u r e 2.1  E c o l o g i c a l M o d e l of Travel C h o i c e  traffic (  piroximttv .) '—*  Croat e'directness) •  ,  dissance  oo<*>-  ,  y  j | r — *s. < '  dress eofle ,)  " — - — '  /  Monfltofls j i " 1  1  • fanes and  v  .  f personal \  \  0  / /  /  C  \_ factors  /  preference)'  , • < - — — -  <Zt T Zo^T —••, i>————  N  4  {.socio-economicMC  7 , .  )  J \\  \  1  V »wdwidlh ^  •  ^.^^""-Cpeer suppou  E  HOICS; \ \  <•  Policy  X  /  inter/inlr a-  \  >  ' — A  —  " ' 7 ~  \  ^ ^ , ' - ^ _ _ "^ - ' /^ T^R ,A V E ' L\Y ' V . f - -passeneersP,  _  ^  /  Jch'aracteiistlcs\ / \% /y  N  —  jC£on»/en:l^^J«'''"public/irvs{i1uiwnal'"\  J  ]  r  m  ^>  VC.  s  11 *  V  —  kj)etsonai safety  Ctfen-stly.  I  NL^  J L_ people  " "'" " XL  ' """""N  . , — - 7 — " - ' — ' —  vjjehicje j c c g s § j  \  /eiwironme-nl\ \_fani%' structurgE  -  C sidewalks  : ^-r  J>  ^ H J K . SireS' !•<!><'••. tr. . JB eel d&sfam  v  Jatad usstypesj  .-•  A-Oiluene and 'lype\\ r r 'J IUI « i c a i i u iyv~ :  .  I  ""-T" -  s-  „  Cyehficie speed J? C weal her  >,  J  of other road users  \  \_  j I  : y  It is important to remember that these theories.of travel behaviour are based on adultcentric research. However, parents do play a strong role in travel choices of their children, particularly younger children still in elementary s c h o o l , thus the categories of factors in 18  the ecological model are likely also applicable to children's travel.  Children's particular  vulnerabilities of age, physical size, and cognitive skills, their differing range of desirable destinations, and comparatively low levels of independence give reason to believe there will be differing degrees of influence from the multiple variables within the model.  Ecological models of behaviour are beneficial in recognizing the multiplicity of interacting influences that contribute to travel behaviour and transportation mode choice. Although it is important to recognize this diversity of factors it is next to impossible to measure and analyze them all within one research project.  T h e remainder of this chapter identifies  specific factors selected for consideration in the current study and reviews the existing literature on relationships between them, travel choice in general, and the travel choices of children in particular.  C U R R E N T L I T E R A T U R E 14  2.2 Exploring Existing Evidence  A n extensive literature review revealed 12 studies that specifically examined mode of travel to school, although several others examined other aspects of the journey to school such as physical activity benefits and school age and catchment area s i z e . 19  20  The growing  interest in this topic is evidenced by the fact that more than half of these were published within the past 2 years.  Of the identified studies, 7 were conducted in the United States (South and North Carolina, Florida, and California); 3 are from Australia and 1 from the U.K. T h e majority of these utilized cross-sectional travel mode data provided at one point in time through parent and child surveys administered through s c h o o l s . local and federal trip diary d a t a ,  22  21  In one case researchers drew data from  another visually observed the mode by which children  arrived at participating s c h o o l s , and a third relied on hand-count data provided by 23  teachers.  24  Most studies used the school as the unit of analysis and used local averages  for demographic data.  At least three studies were able to link travel mode choice and  independent variables on a case by c a s e basis.  Independent variable data were obtained from a variety of sources including:  • U.S. C e n s u s (density and intersections per street mile ); 25  • State department of education or local school board data (school size, percent of students on public welfare, and ethnic background ; school urbanization levels and 26  percent students with lunch s u b s i d i e s ; school enrollment data ); 27  •  28  Local and state transportation modeling systems (density of residents and jobs, population-employment balance, job mix ); 29  • Local property assessment databases (commercial floor-area ratio ); 30  • County bicycle and pedestrian level of service database (proportion of street miles with street trees, bike lanes/paved shoulders, and/or sidewalks, average sidewalk width ); 31  • R e s p o n s e s from direct surveys or state/local travel survey data (reasons for travel mode  C U R R E N T L I T E R A T U R E 15  and reasons not to walk ; socioeconomic data ), and 32  33  • Direct observation (pedestrian counts, vehicle flows, and micro-scale urban form ). 34  Two of these studies are of sufficient importance to describe their research methods in further detail at this time. The first, conducted in Gainsville, Florida by Ewing, Schroeer and G r e e n ,  35  examined the most comprehensive set of independent variables of any  children's travel study published to date. It is also the only study that utilized behavioural data from regional travel surveys instead of relying on school-based study populations, thus obtaining data from a more random and representative sample of neighbourhoods. S e v e n hundred and nine journeys to school by children Kindergarten to grade 12 were identified from a combined database of the Florida Department of Transportation ( F D O T ) and Gainsville Metropolitan Transportation Planning Organization ( M T P O ) trip diary surveys.  Survey responses indicated the transportation analysis zone (TAZ)  a  of their  origin and destination locations, from which trip time and trip distance were estimated. Respondents also indicated the size of their household, number of household motor vehicles, annual household income, and whether the student had a driver's license. Macroscale built environment data included density of people and jobs, jobs-housing balance, and the mix of available jobs (industrial, commercial, or service).  Property assessment  data provided intensity of pedestrian-oriented commercial development, and county roads data indicated the presence of street trees, bikes lanes/paved shoulders, and sidewalks - all averaged by T A Z . Analysis was conducted using multi-nomial and nested logit mode choice models. A n important limitation of this study was that only a very small proportion of trips to school were by active mode (4.5% walked and 3.4% bicycled).  T h e second significant study evaluated infrastructure improvements made under the Safe Routes to School program in California and has been analyzed from two different perspectives.  36  Student participants were recruited from 10 schools across the state  where changes had been made to pedestrian infrastructure over the past year. In the first a TAZ's are regionally designated polygons roughly equivalent to census tracts and are commonly used in transportation demand modeling in the United States. TAZ' in urban centres are often quite small such as city block due to the concentration of trip-ends in these locations. Trips are characterized by the TAZ's in which they begin and end; the system implicitly excludes trips that originate and end within the same TAZ. C U R R E N T L I T E R A T U R E 16  analysis , researchers conducted direct observations of site-specific traffic conditions 37  before and after installation of infrastructure improvements. T h e analysis found that children walking to school were likely to use the improved infrastructure, and that pedestrian risk was decreased due to separation from traffic and increased driver courtesy at crosswalks. T h e second analysis  38  used cross-sectional survey data on children's mode of travel to  school, comparing children whose routes to school were or were not affected by the new infrastructure.  Retrospective questions asked parents whether their children walked or  biked to school more often after the improvements than before.  This study could not  conduct a regression analysis to determine the relative impact of specific factors because the type of improvements varied from school to school; projects included replacing stop signs with lights, closing gaps in sidewalk networks, and installing pedestrian/bicycle crossing lights. The outcomes of this study actually showed a net decrease in the number of children walking. Eighteen percent of parents stated their child walked or bicycled less after the project while only 10% indicated their child walked more; 71.5% stated their child's walking or cycling remained the same.  However, 15.4% of children whose route  to school had been affected by the new infrastructure reported an increase in walking while only 4.3% of those not affected by the improvements increased how much they walked.  T h e proportion of children who reported walking or bicycling less was equally  divided between the two groups, suggesting that decreases in walking were unrelated to the infrastructure improvements.  T h e remainder of this chapter describes current knowledge of the factors influencing mode choice. Results from all 12 children's travel studies are described as relevant to the individual variables discussed.  Following the ecological model of behaviour, intra- and  inter-personal variables are presented first, followed by environmental factors and trip characteristics.  C U R R E N T L I T E R A T U R E 17  2.3 Intra- and Inter-Personal Factors 2.3.1 Socioeconomic Status and A c c e s s to Vehicles Numerous studies have demonstrated a significant link between household income and travel choices to the extent that income is the most common variable to be controlled for in travel behaviour studies. Adults living in lower income households tend to walk and use public transit more than those with higher i n c o m e s , follow the same trend.  40  39  and children in such households  Household income is not always available but higher rates of  walking have also been found at schools with a higher proportion of students on welfare, and at public schools compared to private s c h o o l s .  42  41  (The relationship to private schools  may be confounded by larger average travel distances.)  This income-travel choice relationship is largely due to the high cost of owning and operating a private vehicle. Lower income households own fewer vehicles (on average) than those of higher income and thus their transportation  choices are more  often  restricted to alternatives other than single-occupant vehicles.. Vehicle ownership rates can be influenced by factors other than than income, for example the number of licensed drivers or personal preferences for other travel modes.  Regardless of the reason, less  vehicle a c c e s s is likely to increase rates of walking. In the literature, children's travel modes are more strongly connected to household vehicle ownership than to income, and many studies have found this to be the strongest influence on mode of travel to school.  43  In Melbourne, Australia 5-6 year old girls in households with 2 or more cars  were 70% less likely to walk or cycle regularly (3 or more times per week) than their counterparts in families with one or no c a r s .  44  In Gainsville, Florida, Ewing et al. found  that the probability of walking decreased by a factor of -1.16 with additional vehicles per member of household, while the change with respect to household income was only 0.84 regardless of vehicle ownership.  45  That study's authors suggest that the variables of  household income and per person vehicle ownership "individually and together may have a strong enough influence on mode choice to overwhelm other factors favouring walking trips, such as short distance to and from school".  46  C U R R E N T L I T E R A T U R E 18  Although children of low-income parents may be more likely to walk overall, a British study found that mothers without the pressure of paid work are more likely to walk to school with their child rather than drive.  47  This suggests that the presence of non-working  adults in the household may be a more important predictor of walking to school, at least among higher-income groups.  2.3.2 Perceptions of Safety from Traffic and Safety from Strangers  Parents' concerns about the physical safety of their children are not without reason. It is thought that children younger than 10 or 11 lack the cognitive abilities to anticipate risk and make complex decisions - particularly those involving vehicle speed and distance, but also potentially regarding other risks.  48  Children have shorter attention spans than  adults, are easily distracted, and are less able to follow instructions consistently. Finally, children travel to school during peak traffic periods and the growing number of children being driven has increased traffic volumes and congestion in the immediate vicinity of elementary schools.  This combination of factors contributes to making pedestrian and  cycling accidents a leading cause of death and hospitalization among school-age children in North America, the U.K., and Australia.  49  It is not a coincidence that a high proportion of  these deaths occur on the way to and from school. Safety from traffic is associated with the nature of the pedestrian environment (as discussed in section 2.4), but pedestrian injuries have also been linked to neighbourhoods with higher unemployment, fewer highincome households (perhaps because there are fewer cars per person), and higher traffic volumes.  50  Whether a real or perceived threat, it is generally believed that children are less likely to walk if their parents perceive the nature and volume of traffic to be dangerous on the child's route to s c h o o l .  51  Although most of a route may be reasonably safe, the presence  of one or more major street crossings can be enough to discourage walking or cycling.  52  In one cognitive mapping exercise, children's understanding and perceptions of their surroundings were negatively affected by the presence of high-volume, high-speed traffic  C U R R E N T L I T E R A T U R E 19  which may increase the barriers to walking safely.  53  Although the likelihood of child abduction is much lower than traffic injury, safety from strangers is an important and growing concern, with parents perceiving the outcome of abduction or assault as being "vastly more hideous" than the consequences of a car accident.  54  In some surveys, fear of abduction ranked as the most or second-most (after  traffic) frequently cited reason for parents driving their children to s c h o o l .  T h e U.S.  55  Centre for Disease Control ( C D C ) found that fear of traffic or abduction was much higher among parents of elementary school children than of high school children, although other barriers ranked about the same between the two g r o u p s . A few studies have referenced 56  safety from bullies as a parental concern regarding walking to school, but no relationship has been quantified.  57  A multi-disciplinary literature review found a diverse body of research linking fears of personal safety to decreased physical activity levels and prevalence of obesity.  58  However,  the s a m e review revealed research with contradictory conclusions, and a diversity of metrics to measure response variables and define safety that make it difficult to draw definitive conclusions.  Finally, most (but not all) of the studies reviewed focused on  adults.  T h e most comprehensive study found examining perceptions of safety and children's travel choices was conducted by Timperio et al. in Melbourne, Australia.  59  "Stranger  danger" was found to be a significant influence on both boys and girls walking to destinations in their neighbourhoods, with slightly more concern indicated from parents of girls (compared to boys) and parents of 5-6 year olds (compared to 10-12 year olds). A lack of signalized crossings was a significant influence for boys while having to cross "several roads" to a c c e s s play areas was significant for girls. A more general statement regarding road safety in the area was not significant for either. Fewer than half as many children indicated concern about strangers and traffic than adults, although perceptions of personal safety, and opinions about their parents' perceptions were both found to be  C U R R E N T L I T E R A T U R E 20  significant influences.  2.4 Environmental Factors  T h e built environment or urban form component of travel behaviour models is the subject of a significant and growing body of research. T h e subjects of these studies are individual people who have pre-selected a place to live for a variety of reasons, making it more difficult to demonstrate causality between urban form and travel behaviour.  60  It is nonetheless possible to quantify the strength and direction of relationships and to identify trends across neighbourhoods of similar design. The majority of studies have examined macro-scale elements of the built environment (measured on an area-wide basis), while others have focused on micro-scale elements that influence the safety and ambiance of specific routes. Clusters of characteristics have emerged as contributing to increased levels of walking and cycling; neighbourhoods that exhibit these characteristics are labeled "walkable" and the measured degree to which the characteristics are present is called "walkability".  61  While rates for walking for exercise are similar in walkable and  unwalkable communities, overall physical activity has been found to be higher due to walking for transportation p u r p o s e s .  62  T h e following paragraphs describe which attributes  at the macro- and micro-scales of measurement contribute to enhancing walkability and increasing walking activity.  2.4.1 Macro-Scale Elements A significant body of evidence links adult travel and physical activity to macro-scale elements of the built environment. It has been found that even after controlling for income, individuals living in higher-density communities with well-connected street networks and a diverse mix of land uses are more likely to choose non-motorized forms of transportation for their daily trips.  63  Although levels of physical activity for exercise are often similar  between walkable and unwalkable communities, walking for transportation significantly increases the total amount of exercise of people living in walkable neighbourhoods.  64  T h e primary reason for this relationship is thought to be the effect on distance. Distance  C U R R E N T L I T E R A T U R E 21  (discussed further in section 2.4.2), is perhaps the most important limiting factor in the choice to use non-motorized forms of travel. A diversity of land uses in close proximity increases the potential number of destinations within a reasonable walking radius. The viability of retail services for day to day needs is linked to the population in close proximity, thus higher population densities are required to support land use diversity.  T h e third macro-scale aspect of walkability is street connectivity. Highly interconnected street networks with short blocks and grid-pattern design enable more direct routes between origins and destinations. This minimizes the difference between straight-line distance and the street network (walking path) distance.  65  Grid street networks also  increase route choice, giving pedestrians and cyclists the opportunity to travel on lowertraffic streets without appreciably increasing the distance of their trip.  Figure 2.2 illustrates the difference between street network and straight line distances in two of the school catchment areas used in this study.  Figure 2.2 Street Network Versus Straight Line Distances  ———r—  1  L  1  —  1—— 1  7-rri  1 — ' — J —  Image A: Grid Pattern (Walter Moberly) Straight Line (red): 500 metres Street Network (blue): 700 metres Distance Ratio: 1.4  Image B: Curvilinear Street Pattern (Boundary) Straight Line (red): 500 metres Street Network (blue): 1200 metres Distance Ratio. 2.4  T h e body of literature on children's travel patterns is much less conclusive regarding the influence of the macro-scale built environment. Three studies have examined population density; two of these in relation to children's travel to s c h o o l  66  and one in relation to walking  C U R R E N T L I T E R A T U R E 22  for all travel p u r p o s e s . A California study using data aggregated by schools found density 67  was found to be significant.  68  However the Gainsville, Florida study that used unique  data for each child found density was not significant at a l l .  69  T h e California study also  examined intersection density but found it was only significant in pairwise correlations but not in the multiple regression analysis.  70  A third study found that short blocks and mixed  land uses had a negative influence on children walking to school, although there was little variance between school sites which reduced the significance of these findings.  71  Evidence on mixed-use is contradictory as other authors (with non-empirical studies) suggest diversity of uses provides important "eyes on the street" and points of refuge for children.  72  T h e Gainsville study analyzed macro-scale variables of land use mix, population density, and school size and found none to be influential after controlling for distance.  73  This  suggests that population density has an indirect influence on walking rates because of its affect on catchment size as discussed in Section 2.4.2. However, a study in the Atlanta region did find these macro-scale variables to be significant. T h e study analyzed travel for all purposes among children and youth based on trip-diaries collected through the S M A R T R A Q program.  74  Participants fell into one of 4 age-based groups ranging between  5 and 20 years; children living in neighbourhoods with the highest tertiles of intersection density and population density were respectively 1.3 to 2.0 and 1.8 to 3.7 times more likely to report walking at least once during the 2-day survey than those in the lowest tertiles (likelihood varied by age group). T h e presence of mixed land uses (versus single-use), at least one commercial land use (versus none), and at least one public recreation/open space nearby (versus none) also increased the likelihood that the child would walk.  T h e Gainsville study's authors speculate that children's journeys to school do not fit typical (i.e. adult) travel choice models because they are mandatory and thus may be less sensitive to variation in the walking environment than discretionary travel.  Trips to  school, especially for young children, are also less likely to be linked to other errands compared to their parents' trips, reducing the impact of mixed-use development. Although  C U R R E N T L I T E R A T U R E 23  the Atlanta study did find macro-scale variables to be significant, the trip diaries included both discretionary and mandatory trips. Thus the outcome does not refute the hypothesis that school-trips are not significantly affected by macro-scale urban form variables.  A third hypothesis is that the mandatory trips to school are more influenced by microscale characteristics measured at the street-scale rather than the neighbourhood scale. It may also be that non-infrastructure factors such as perceived safety (as discussed in section 2.3) are more influential, and/or that urban form's influence on perception of safety indirectly affects travel choice. It is these hypotheses that the current study is designed to test.  2.4.2  Distance  In the ecological model of behaviour, absolute travel distance is considered a "trip characteristic" rather than a component of the built environment. relationship  between  distance and  However, the clear  macro-scale variables just described makes  it  appropriate to discuss distance at this point. Distance is frequently cited among the most important barriers to walking for transportation for all trips and all a g e s .  75  In a Canadian  survey, 47% of respondents cited distance as a barrier to walking, with time (directly related to distance) being the second-most frequently cited at 1 9 % . Canada  7 7  and the U S  7 8  76  National studies in  found distance to be the most frequently cited barrier to children  walking to school (mentioned by 55% and 53% of parents respectively).  S e c o n d most  common were weather (11% among Canadian parents) and traffic danger (40% among American parents). T h e Canadian study found that 86% of children living within 1 km from school walked "most of the time", compared to only 36% among all children. Only 5% of those living greater than 3 km walk to s c h o o l .  79  Results of empirical studies also indicate  that distance is a significant predictor of whether or not children will walk to s c h o o l .  80  Density and connectivity interact with the policy decisions of local school boards that determine the size of schools (i.e. number of students) and the school catchment area  C U R R E N T L I T E R A T U R E 24  - the geographic boundary from within which most students are drawn.  Holding school  populations equal, catchment areas are smaller in high-density than in low-density neighbourhoods. Special programs such as French immersion draw students from outside the standard catchment area and increase the average travel distance for children at that school. There is an emerging trend, at least in the United States, of systematic increases in school s i z e s , and increasing school size has been correlated with fewer children 81  walking.  However, school enrollment does not s e e m to be significant after controlling  82  for distance.  83  Opinion is varied on a clear threshold distance above which walking to school drops dramatically. Gilbert and O ' B r i e n suggest that children's common destinations (schools, 84  parks, etc.) should be located within 2 km of their homes. G o for Green found 86% of Canadian children living less than 1 km from school walked, a statistic that dropped to only 50%o for those within 1-3km, and only 5% of those living greater than 3km away.  85  Finally, a  study of compact urban areas in Britain found that the probability of being driven to school by automobile was 20% for children living less than half a mile (800 metres) from school, increasing to 50% for those living 1.25 miles (2km), and 80% at 2 miles (3.2km).  86  However, it s e e m s that if a threshold distance does exist, it has decreased significantly in recent d e c a d e s . It is estimated that in 2001, 31% of American children aged 5 to 15 years living within 1 mile of school walked or biked , while the equivalent figure in 1969 87  was 9 0 % .  88  A South Carolina study indicates an increase in the use of hazard busing  - i.e. school bus transportation provided to students living close to the school but who encounter barriers such as highways en route.  89  It is probable that other factors such as  two income households (fewer parents available to walk with children to school), heavier traffic volumes, a less pedestrian-friendly environment, and increased perceptions of risk from strangers are mitigating the maximum acceptable distance.  C U R R E N T L I T E R A T U R E 25  2.4.3  Micro-Scale Elements  Micro-scale elements of the pedestrian environment include features for safety and comfort (e.g. sidewalks, cross-walks, traffic calming), and contributors to ambiance (street trees and landscaping, street furniture). There is a small base of evidence that such elements influence rates of non-motorized travel,  90  although they have not been incorporated into  empirical travel models to the s a m e degree. Demonstrating links independent from macroscale elements is difficult because built environment features tend to co-vary in space; for example sidewalks and street trees are often found in high-density neighbourhoods with street-oriented retail.  91  Nonetheless, urban micro-scale features are frequently cited  in reference to children's travel and pedestrian safety . 92  In the absence of any clear  relationships between children's travel and macro-scale measures, it is useful to explore the micro-scale in greater detail.  This study has chosen to focus on a specific sub-set of micro-scale elements, detailed below. T h e s e elements were selected based on the frequency with which they are referenced in the literature on children's travel and this author's perception of their association with the safety and attractiveness of walking to school. T h e primary focus on safety elements follows Ewing, Schroeer and Greene's observation that school trips are non-discretionary and that the presence of street trees is not a significant influence.  93  Sidewalks Sidewalks provide a clearly designated space for pedestrians within the road right-of-way. They are frequently (although not always) grade-separated from the road, providing slight added protection from wayward vehicles, and may even be buffered from the road with a planting strip or other landscaped area. It is recommended that a sidewalk or pathway network be continuous between homes and schools, and that the sidewalk be 3-4 metres wide to accommodate young cyclists, and parents with strollers.  94  The presence of  sidewalks near homes and schools was the most significant built-environment (macro- or micro-) factor for children walking to school in Gainsville, Florida. Sidewalk construction  C U R R E N T L I T E R A T U R E 26  and closing of gaps were undertaken for 4 of the schools in the California Safe Routes to School evaluation. Observations at 3 of the 4 indicated increased levels of safety (children no longer walking on the road) and slight increases in the numbers of children walking to s c h o o l .  95  After project construction, the children whose route included improvements  were significantly more likely to have increased walking than those children whose route did not.  96  Intersections Pedestrian risks from motorized vehicles increase at intersections when they must leave sidewalks and cross vehicular paths. This is particularly true for children whose abilities to judge the speed and intentions of motorized vehicles are not as well developed as adults, whose attention is more easily distracted, and for whom seeing and being seen are more difficult.  97  Ideal cross-walk conditions are described as having minimal width, being  well marked on road and with high-visibility signage, preferably with specific pedestrian crossing signals; cross-walks should accommodate all physical abilities by raising the crosswalk to sidewalk level (with a speed table), or providing ramps for strollers and wheeled mobility a i d s .  98  Barring timed signals, 4-way stops are preferable to 2-way stops  or yield signs, marked crosswalk lines or textured pavement preferable to no pavement markings.  99  Cross walk improvements were installed in the Safe Routes to School project  described under sidewalks (above), but otherwise little empirical data has recorded the efficacy of cross walks in encouraging walking.  Traffic Calming Vehicle speed is a significant factor in the severity of traffic accidents and influences the probability of accidents through reduced time to see and respond to people or vehicles unexpectedly entering the r o a d .  100  Incremental increases in vehicle speed at the time  of crash dramatically increase the severity of pedestrian injuries.  Most pedestrians will  survive a crash at 15 miles (24 km) per hour with only minor injuries. Severe injuries and a 50% chance of fatality are associated with collisions at 25 miles (40km) per hour; at 40 miles (64km) per hour 90% of crashes are fatal.  101  In British Columbia, the legal speed  C U R R E N T L I T E R A T U R E 27  limit in a school zone is 30km per hour. O n residential streets immediately adjacent to such zones (where many children must walk), the statutory speed limit is 50 km per hour.  102  Measures to reduce speed or "calm" traffic can reduce the chance and severity of accidents  103  , while producing the qualitative  benefits of reduced traffic volumes and  associated traffic noise. A study in New Jersey conducted a comparison of driver behaviour before and after the installation of a raised median, curbs, and sidewalks on a 4-lane suburban arterial.  It was found that the 8 5  th  percentile s p e e d decreased by 2 miles (3.6  km) per hour, and pedestrian risk was lowered by 2 8 % .  104  Bradshaw  105  refers to a British  longitudinal study involving 185 traffic calming projects implemented near schools in the early 1980's; accidents dropped by 85% in slow speed zones and severity of accidents also decreased. There is no empirical evidence that increased safety from traffic calming induces more walking, but it is nonetheless an important consideration for protecting those who already choose to walk or cycle.  Buffer Buffers are the strips of land that separate the sidewalk from the road. They increase pedestrian comfort and safety by creating a separation from moving cars, providing an overflow space when the sidewalk is too narrow, preventing utility poles from blocking the sidewalk, and can include landscaping such as street trees and benches. Buffers affect the proximity between pedestrians and motorized traffic which is a critical factor in determining utility and perceived safety. Additional elements in the buffer such as shade trees or street furniture can affect the perception of enjoyment along the route. A buffer is recommended for streets where traffic is moving faster than 30 kilometres per hour and it is suggested that a 3 metre (9 foot) width may reduce children's exposure to pollution from idling v e h i c l e s .  106  There is no evidence on the relationship between rates of walking  and the presence of buffers.  C U R R E N T L I T E R A T U R E 28  Road Width Increased road width increases the volume and speed of vehicular traffic and reduces visibility of pedestrians waiting to cross at intersections. Wide roads increase pedestrian crossing distances and times, increasing their length of exposure in the intersection, and decreasing their chances of crossing during one light or one break in traffic. Vanderslice advocates a "4S" approach to creating safe pedestrian environments, all of which are affected by road width: i)Slow the traffic, ii) Shorten the crossing distance, iii) Put pedestrians where they can S e e and be S e e n , and iv) Slash the number of lanes to cross at o n c e .  1 0 7  Gilbert and O'Brien corroborate this, recommending that wide roads should  have a median island for refuge so the road can be crossed in two s t a g e s .  108  However,  there is no empirical evidence demonstrating a clear relationship between road width and rates of walking.  2.4.4 Residential self-selection  Research relating the built environment to travel mode choice and physical activity makes a significant assumption that has been subject to vocal critique; that is the assumption that residential location decisions are exogenous to employment status, vehicle ownership, personal travel preferences, and other related factors. In many c a s e s this simplification is accepted because available data is insufficient to test relationships one way or another and would make predictive models significantly more c o m p l e x .  109  Critics argue that personal  values such as a desire to be physically active or to use less polluting travel modes lead individuals to select neighbourhoods that support those values - a theory called residential self-selection.  110  Thus evidence appears to support a relationship between  urban form and travel behavoiur when the real relationship is between travel behaviour and personal values. This assumption can lead to overestimating the significance of the built environment influence in this equation.  Self-selection theory presents a valid argument, and is complimentary to the ecological model of behaviour with respect to intra-personal influences.  It is known that travel  C U R R E N T L I T E R A T U R E 29  choice is affected by personal values to some d e g r e e  111  , but researchers disagree about  whether these values outweigh the influence of built form.  A study using longitudinal  data of families before and after moving neighbourhoods found no change in total vehicle kilometres traveled despite changes in built f o r m .  112  This study did not examine changes  in physical activity patterns.  It is reasonable to believe that school proximity and opportunity to walk contribute to housing decisions. However self-selection theory makes it own assumptions - primarily that individuals and families are always able to live in the neighbourhood of their choice. This reality was demonstrated by a study in the Atlanta region that evaluated walking for transportation and recreation, while controlling for the participants' stated preferences of neighbourhood t y p e .  113  Twenty-five percent of participants indicated they were not  living in their preferred neighbourhood type; of these, 8 1 % preferred a high walkability area but were residing in a car-oriented one, indicating a significant unfilled demand for high-density, mixed-use neighbourhoods.  This study did confirm that rates of walking  were strongly associated with personal preferences.  It also demonstrated that among  individuals preferring car-oriented areas, those living in walkable neighbourhoods walked more than those in the neighbourhood type of their choice. Likewise, individuals preferring walkable neighbourhoods but living in car-oriented areas walked much less than those who were living in their preferred neighbourhood type.  High relative housing costs in downtown Vancouver and Toronto suggest there is high unfilled demand for mixed-use, walkable neighbourhoods in those Canadian regions (thereby increasing market prices). A latent demand for walking was also expressed in two Canadian studies. Eighty percent of adults in the first survey indicated they would prefer to walk more, and 60% would like to cycle more than they currently d o .  114  In southern-  Ontario, 75% of elementary school students indicated a preference for walking to school while only 62% actually d i d .  115  However these studies did not indicate specifically if the  built environment was a significant deterrent to walking more.  C U R R E N T L I T E R A T U R E 30  2.5 C o n c l u s i o n  Understanding travel choice is obviously complicated. A s mentioned previously, over 200 distinct variables of the pedestrian environment have been evaluated for their influence on walking for transportation and recreation.  116  T h e s e include vehicle speed, street  lighting, building setbacks, on-street parking, and the presence of street trees and street furniture to name a few. Inter- and intra-personal influences on children's travel to school include convenience, parent's workplace location, availability of an adult to walk with the child, extra-curricular activities before and after school, and whether siblings attend the same school. A limited number of variables have been selected for analysis in this study, the known influence of which was described in this chapter. Chapter 3 details how each of these variables was measured forthe current analysis and the route-specific methodology used to collate them into the final analysis.  C U R R E N T L I T E R A T U R E 31  CHAPTER 3 - METHODS "Few studies have simultaneously a s s e s s e d perceptions and objectively measured environmental factors and their relative association with transport or recreational physical activity." Hoehner et al., 2005 3.1  Introduction  This study utilizes cross-sectional primary data from two sources collected as part of a larger school-based intervention study funded by the Canadian Institutes of Health Research.  T h e primary objective was to statistically compare responses on children's  modes of travel to school against demographics, perceptions of safety, and a specific subset of characteristics of the pedestrian environment. T h e s e two data sources are:  1) Self-reported cross-sectional data obtained from paired parent and child surveys distributed to grade 4 and 5 students in selected schools in British Columbia's lower mainland. (In this text, these are hereafter referred to as "travel surveys".) T h e s e surveys provided both travel mode data for the child's trip to school and data on how parents and children perceive the child's safety while walking in the neighbourhood of the school. Full text of the two surveys can be found in Appendix A.  2) A database of field observations that enumerated micro-scale features of the pedestrian environment such as those described in Chapter 2. T h e field data collection was conducted by trained student evaluators from the University of British Columbia's (UBC's) School of Community and Regional Planning ( S C A R P ) using a standardized survey first developed for the Neighbourhood Quality of Life Study. Full text of the pedestrian environment survey can be found in Appendix B. 1  In this text, this is referred to as the Micro-Scale Survey.  METHODS  32  T h e study focuses on the child's trip to school - a very specific journey that is nondiscretionary and is common to all participants.  Knowledge of the home addresses and  location of the schools was used to estimate a unique route for each child's trip from home to school. Micro-scale data were combined to create a simple index that rated the pedestrian friendliness of each child's route against others in the sample. A combination of inferential statistical methods was used to test the influence of the pedestrian environment and perceptions of safety on children's choices in travel mode to school. T h e efficacy of the micro-scale survey tool was evaluated based on qualitative observations during data collection and insights gained through subjecting the data to rigorous statistical analysis.  Action Schools!  B.C.  Action  BC (AS! B C ) is a public school-based program designed to increase  Schools!  physical activity levels and healthy eating among children. In 2005 a research program was launched to a s s e s s the efficacy of the A S I B C model in promoting healthy school environments, and the program's effects on children's health. The primary investigator in the study is Dr. P.J. Naylor, Professor at the University of Victoria's Department of Physical Education. Funding was provided by the Canadian Institutes of Health Research. T h e study involves grade 4 and 5 students at elementary schools across the province, providing a valuable opportunity to collect information from children and their parents on several other health-related issues.  Dr. Lawrence Frank, Associate Professor in U B C ' s  School of Community and Regional Planning was invited to conduct a sub-survey on children's travel patterns, and thus the travel survey became one of several adjunct surveys distributed to students at a subset of participating schools.  T h e ethics review,  participant recruitment (schools and individuals), and administration of the travel survey were conducted by the main ASIBC  research team and are discussed in more detail later  in this chapter.  A s required by U B C ' s Office of Research Services, the study's objectives, recruitment strategies, research methods, and surveys were reviewed and approved by U B C ' s Behavioural Research Ethics Board. T h e ethics review process was managed by Dr.  METHODS  33  McKay and the core ASIBC  research team. A copy of the Behavioural Research Ethics  Board Certificate of Approval can be found in Appendix C .  T h e remainder of this chapter details the key stages of data collection, data cleaning and compilation - first for the behavioural and perceptual data and second for the microscale survey data. The data analysis is described including development of a pedestrian friendliness index from the micro-scale data, and the inferential statistical analysis.  3.2  3.2.1 Two  Behavioural and Perceptual Data  Survey Design multiple-choice  surveys were based in part on previous survey  instruments  developed and tested as part of the Neighbourhood Quality of Life Study funded by the National Institutes of Health (U.S.). Survey development was also based on the review of children's travel literature (see Chapter 2), and adapting specific questions posed in the Neighbourhood Quality of Life Study , and the Ontario Walkability Survey. 2  Surveys were  3  amended based on feedback provided by thesis supervisor Dr. Lawrence Frank and Dr. J a m e s Sallis of S a n Diego University . (The full text of both student and parent surveys 4  are found in Appendix A.)  T h e first survey was designed to be completed by the participating students. It questioned the children's current mode of travel to and from school, how often (if ever) they use a non-motorized travel mode to get to school, whether they ever travel by a non-motorized mode for non-school trips, if they have been encouraged to walk to school by their teachers, and asked them to rank on a Likert scale how safe they feel when walking in their neighbourhood.  T h e second survey was designed for parents of the participating children. demographic information  It requested  such as gender and age of the child, household vehicle  ownership, and household income. It questioned how the child travels to and from school,  METHODS  34  how the parent travels to work, and how often (if ever) the family uses non-motorized travel modes for non-school trips. Parents responded on a Likert scale to a diversity of statements relating to their perceptions of neighbourhood safety and barriers that may prevent their child from walking to school. E a c h also indicated which two of a broad list of factors are the most influential in their decision of how their child travels to school. T h e parental survey included an open-ended question to give parents the opportunity to explain more complex decision-making factors that may not have been captured in the multiple-choice survey questions.  3.2.2  Participant R e c r u i t m e n t  T h e ASIBC research team recruited school principals to become involved in the study by introducing the ASIBC program and the intended research at seminars and conferences across the province, followed by a formal letter of invitation. Confirmation of participation was made after discussion with principals and teachers with a goal of participation by approximately 128 grade 4 and 5 teachers from 50 schools throughout the province, representing a total student sample of approximately 2000 students.  Schools were  selected through a stratified random sample to ensure geographic representation across all 5 B C Health Regions. In addition, efforts were made to include both large and small schools, and those located in both large and small urban areas. Half the schools in each region were randomly assigned to implement the ASIBC  program (the intervention), so  by agreeing to participate, teachers and school administrators at these schools had to commit to implementing the program for a year.  T h e challenge of establishing working relationships with individual schools and gaining consent of school administrators, classroom teachers, and parent placed some limits on the choice of schools.  This challenge was exacerbated due to a strike by the B . C .  Teacher's Federation in October 2005 which compressed the time frame for the overall study, and reduced the willingness of some teachers to take on extracurricular projects. Ultimately 13 schools in the lower mainland were selected to receive the travel survey.  METHODS  35  Following the ASIBC study design, all grade 4 and 5 students at the 13 schools were invited to participate, except those children who were unable to participate in physical education classes.  This excluded any students who have to be driven to school as a result of a  physical disability. T h e survey was distributed to all children that returned a consent form signed by a parent or guardian. While this sample eliminated the opportunity to a s s e s s travel patterns at different ages, it did provide a large sample of children in the same age range that can be compared to one another. A s discussed in section 2.3, this is the age near or at which most children are developmentally capable of the decision-making skills required for walking trips in their neighbourhood.  3.2.3 Survey Administration Travel survey packages contained a cover letter, one survey each for child and parent on differently coloured paper, and a stamped self-addressed envelope for the return of the completed surveys. Survey packages were initially distributed to 839 children at their school by an ASIBC  research assistant between December 2005 and February 2006.  When returned, the paired parent and child surveys were coded with a four-digit identifier by the ASIBC  research team, and then hand-delivered to Dr. Frank's research lab for data  entry and analysis. A copy of the initial cover letter is included in Appendix D. In February 2006, participants who had not returned their surveys received a duplicate package by mail with a cover letter encouraging them to submit a completed survey.  A response rate per school of 60% was considered feasible because participating students had previously consented to participate, would have the surveys hand-delivered, and would be receiving multiple prompts related to their participation in the larger study. To achieve a desired  sample of 200 c a s e s it was hoped that each school would return  at least 30 surveys; this anticipated level of response was a primary factor in school selection (discussed in Section 3.3).  By the end of March 2006, a total of 498 children's surveys and 500 parental surveys (representing  504 individual participants) were returned from the 13 schools.  This  METHODS  36  represents an overall response rate of just over 59%. Eight more completed survey pairs were subsequently submitted but these were not received in time to include in the current analysis.  3.2.4  Data Compilation  A s with any large data set the travel survey data had to be cleaned to remove unusable data.  T h e dataset was then culled to confine the analysis to a manageable number  of variables.  C a s e s with missing data among this subset of variables were identified  and where possible, variables were imputed to create the complete dataset required for regression analysis.  Entering Data and Establishing the Study Sample A scan of the returned surveys revealed that the multiple choice options to questions relating to the child's mode of travel to and from school were not interpreted as intended. 3  T h e options "driven to school by myself or with brothers/sisters" (child survey) and "driven to school by him/herself or with brothers/sisters" (parents survey) were intended for any child driven to school by an adult when the only passengers in that car are the child and his/her siblings. This differentiated them from children in a carpool when the parents of two families share the driving.  However, responses suggested these options were  interpreted as the child driving him/herself - which is obviously impossible for 9 and 10 year olds. Respondents who misinterpreted this question checked "other" and indicated the child was driven by their parents. "Other" responses of this nature were categorized as "driven to school by myself or with my brothers/sisters" since to treat them otherwise would have significantly skewed the results of the travel mode data toward "other" and made valid analysis impossible.  In addition, some questions requested a single response but multiple responses were entered.  In order to retain as much information as possible all checked responses were  entered. In the case of travel mode to or from school, multiple answers were later treated  a  Questions 2 and 3 on the child's survey; questions 8 and 9 on the parent's survey. METHODS  37  as such and a s s u m e d to mean that no one mode of travel was predominant for that child. A sub-sample of the data was then drawn to include only respondents from the 7 schools selected for the additional Micro-Scale Survey described in section 3.1. (See section 3.3.1 for the school selection process.)  Sub-sampling the dataset at this time reduced  work required at later stages of data cleaning and imputation (see section 3.2.5).  Verifying  Accuracy  Data entry accuracy was checked by selecting a stratified random sample that represented 10% of the surveys from each of the 7 schools, always rounding up to the nearest complete survey.  Entered responses in the database were checked against the original surveys  for all questions in the survey. A n error was considered to be any question, or part of a question, where the response entered differed from the response on the original survey. T h e number of data entry errors was tallied for each school and for the total sample, as well as how many surveys were involved; results are displayed in Table 3.1.  T h e error  rate was determined by dividing the number of errors by the total number of question responses entered for that survey. (See example in Table 3.1 below for Walter Moberly Elementary School.) The overall error rate of only 0.38% was considered low enough to a s s u m e the accuracy of all surveys in the series.  Table 3.1: Travel Survey Data Entry Error Checking Record School Nilne  Number survey pairs  Nil nil) er checked  Number of Errors  Error Rate  Boundary Brentwood Park Brooksbank Hatzic Marlborough Elementary Mission Central Walter Moberly  42 45  5 5  1 0  0.3%  39.  4  27 101  3  11  0% 0% 0.4%  38  4  0 0 3 (on 2 surveys) 0  52  6  6 (on 2 surveys)  6 errors / [6 survey pairs x 70 questions per pair] = 1.4% error  Total  344  38  10  1  0%  0%  0.38%  METHODS  38  Selecting Study Variables T h e travel survey pairs provided data on 70 separate variables related to children walking to school.  It was clearly necessary to select a subset of key variables for the purposes  of the current analysis. This step was conducted before the data cleaning and imputation in order to minimize the work required at that stage.  Variables were selected from  three separate categories: demographics and geographic location (control variables), travel behaviour (dependent variable), and perception of neighbourhood safety (target independent variable). Table 3.2 summarizes each of the variables selected from both the parent and child surveys. To simplify the analysis, demographic and travel behaviour data were all selected from the parent surveys even though some questions were answered by both parent and child. For exact wording of questions, please see Appendix A .  Table 3.2: List of Variables Selected from Parent and Child Travel Surveys Demographics Parent Survey: Postal Code (QI) Gender (Q2) and Age (Q3) of child Household Income (Q17) Number of Household Vehicles (Q5) Distance between home and school (Q4) Travel Behaviour Parent Survey: Mode of travel TO school (Q8) Mode of travel FROM school (Q9) Two reasons for travel choice (Q10) Non-motorized travel for non-school trips (Q13) Perception of Safety Parent Survey: Likert scale of agreement with statements about child (Q15) • Safe walking in the neighbourhood • Safe from traffic while walking to school • Safe from strangers/bullies while walking to school • Driving child to school is an important parental responsibility • Distance is too far to walk or bicycle  Child Survey: N/A  Child Survey: Favourite way to get to school? (Q8) Teachers encouraging active transport? (Q1D)  Child Survey: Likert scale of agreement with statements about walking or biking in neighbourhood: • Feel safe from cars • Feel safe from strangers/bullies • Easy and fun to walk • Feel safe walking alone  METHODS  39  3.2.5 Cleaning and Imputing Data A m o n g the 7 schools, 354 families had returned some part of the travel survey; 6 families submitted only parental response and 3 only the child's response. T h e s e responses were removed so that only matched pairs of surveys remained, leaving a total of 345 matched surveys. This produced a practical response rate of 61.2%. Table 3.3 indicates the actual response rate per school.  Table 3.3. Response Rate Per S c h o o l  School  Boundary Community Brentwood P a r k Brooksbank Hatzic Marlborough M ission Central Walter Moberly  TOTAL  Consent Forms  Complete Survey Pairs Returned  57 53 65 47 153 63 119 562  42 45 39 27 101 38 52 344  Response Rate  73.68% 84.91% 60.00% 57.45% 63.92% 60.32% 43.70% 6121%  In addition to missing complete surveys, many of the respondents omitted responses to selected questions. Gender was the only variable for which there were no gaps in the data. Of the 19 remaining variables, 10 were missing data for fewer than 5 c a s e s .  Eight  ranged from 10 to 30 c a s e s with missing data, and household income was missing from 52 out of 345 c a s e s . Removing all these surveys would have reduced the sample to below a size practical for significant analysis. Instead, a process of imputation was used to create the most "likely" value for the missing c a s e . Recommended imputation methods vary depending on the nature of the variable in question, the original source of the data set, and other information known to the researcher.  5  T h e process requires a systematic  method to infer data based on known values and relationships between values.  T h e most reliable method of imputing is deduction - determining the most likely true value based on responses to other questions in the same survey.  6  In this c a s e , the process  of deduction was facilitated by the paired surveys since some questions were asked on METHODS  40  both the parent and child surveys. In the c a s e s where the parent had not responded (for example travel mode choice), the child's answer was used. For the variable of distance from school, children's addresses were known so the route distance from home to school could be measured using G - m a p pedometer (an on-line service using the Google Maps feature that measures point-to-point distances).  7  Ultimately this technique was used  to determine the actual travel distance to school for all children because the survey response choices were not equally s p a c e d which would have decreased the rigor of the final analysis. Routes to school were based on those described in section 3.4.2.  W h e n it was not possible to deduce a variable based on information already in the survey, a random numbers table was used to select a response from another respondent in a relevant sub-sample of the data. For example, perceptions of neighbourhood safety were randomly selected from the sub-sample of all respondents from the same school (i.e. living in the s a m e or immediately adjacent neighbourhood). Table 3.4 contains a list of each variable, the number of missing c a s e s , and the method used to impute data. Kalton and Kasprzyk refer to random imputation as a "hot-deck" method; while this is not the 8  most ideal approach it was the only one feasible for the variables with which it was used. Where possible, a sub-set of the data was selected based on a correlation analysis as described in Table 3.4 on the following pages. It should be noted that data points imputed through random selection represent a very small portion of the data set, with no one variable having greater than 7.5% of data points randomly imputed.  METHODS  41  Table 3.4.  Imputation M e t h o d s for Parent a n d C h i l d Travel S u r v e y Data  Suivey Question  Number of Missing Values  Method of Imputation  Gender Age  0  Not r e q u i r e d  Distance from school  30  U s e d address a n d postal code i n f o r m a t i o n p r o v i d e d to l o c a t e r e s i d e n c e and measured distance from school using the G o o g l e M a p s b a s e d G - m a p p e d o m e t e r tool.  Household income  52  H o u s e h o l d i n c o m e w a s i m p u t e d by d e t e r m i n i n g the m e d i a n h o u s e h o l d i n c o m e for t h e c e n s u s d i s s e m i n a t i o n a r e a (CDA.) in w h i c h e a c h c h i l d lived ( b a s e d on p o s t a l a d d r e s s ) . T h e C D A is t h e s m a l l e s t c e n s u s a r e a for w h i c h i n c o m e d a t a is a v a i l a b l e without o b t a i n i n g s p e c i a l a c c e s s t o information t h r o u g h S t a t i s t i c s C a n a d a .  N u m b e r of h o u s e h o l d vehicles  2  M o d e of T r a v el t o S c ho o 1 ( a s r e p o r t e d by the parent)  2  R a n d o m s e l e c t i o n of o n e v e h i c l e o w n e r s h i p v a l u e f r o m a s u b - s a m p l e of r e s p o n d e n t s in t h e s a m e i n c o m e group. ( P e a r s o n ' s C o r r e l a t i o n p= 0 . 0 0 0 b e t w e e n income and vehicle ownership) T h e child's r e s p o n s e to the s a m e q u e s t i o n w a s u s e d to i m p u t e .  M o d e of T r a v e l f r o m S c h o o l ( a s r e p o r t e d by t h e parent)  1  T h e child's r e s p o n s e to the s a m e q u e s t i o n w a s u s e d to i m p u t e .  R e a s o n s cited for travel choice.  13  Not a p p l i c a b l e - this d a t a w a s u s e d only in t h e d e s c r i p t i v e s e c t i o n of the a n a l y s i s w h i c h did not require a c o m p l e t e d a t a set.  A c t i v e T r a v e l for n o n school trips (as reported  10  T h e c h i l d ' s r e s p o n s e t o the s a m e q u e s t i o n w a s u s e d to i m p u t e . In o n e c a s e , the child h a d not a n s w e r e d this q u e s t i o n either a n d s o a r a n d o m r e s p o n s e w a s d r a w n f r o m the entire sample.  by t h e parent)  A v e r a g e of the s c h o o l , r o u n d e d to n e a r e s t full y e a r .  METHODS  42  Table 3.4. (continued) Imputation Methods for Parent and Child Travel Survey Data Parent's Perception of trie  Neighbourhood:  M y ' n e i g h b o u r h o o d is a s a f e p l a c e for my c h i l d to walk.  4  I m p u t e d by d r a w i n g a r a n d o m r e s p o n s e f r o m a s u b - s a m p l e of r e s p o n d e n t s , b a s e d on the child's s c h o o l .  M y c h i l d is s a f e f r o m traffic w h i l e w a l k i n g to s c h o o l or w a i t i n g for the s c h o o l b u s / p u b l i c transit.  10  I m p u t e d by d r a w i n g a r a n d o m r e s p o n s e f r o m a s u b - s a m p l e of r e s p o n d e n t s , b a s e d on the child's s c h o o l .  My child is safe f r o m s t r a n g e r s or b u l l i e s while w a l k i n g to s c h o o l or w a i t i n g for the s c h o o l b u s / p u b l i c transit.  12  I m p u t e d by d r a w i n g a r a n d o m r e s p o n s e f r o m a s u b - s a m p l e of r e s p o n d e n t s , b a s e d on the child's s c h o o l .  D r i v i n g my child to s c h o o l is a n important part of my r e s p o n s i b i l i t y a s a parent.  18  I m p u t e d by d r a w i n g a r a n d o m r e s p o n s e f r o m t h e entire s a m p l e of r e s p o n d e n t s .  O u r h o u s e is too f a r a w a y f m m s c h o o 1 f or my c h i l d to w a l k or ride their b i c y c l e .  13  I m p u t e d by d r a w i n g a r a n d o m r e s p o n s e f r o m a s u b - s a m p l e of r e s p o n d e n t s , b a s e d on the reported distance between h o m e and school.  W h a t is y o u r favourite w a y to get to s c h o o l ?  10  H a v e the t e a c h e r s at y o u r school ever encouraged y o u r to w a l k , bike, j o g , roller b l a d e , s k a t e b o a r d , or u s e a s c o o t e r to get to school?  3  I m p u t e d by d r a w i n g a r a n d o m r e s p o n s e f r o m a s u b - s a m p l e of r e s p o n d e n t s , b a s e d o n h a v i n g t h e s a m e t r a v e l to s c h o o l mode. ( P e a r s o n ' s C o r r e l a t i o n p= 0 . 0 2 2 b e t w e e n a ctu a I a n d fav ou rite trav e I rn od e) I m p u t e d by d r a w i n g a r a n d o m r e s p o n s e f r o m a s u b - s a m p l e of r e s p o n d e n t s , b a s e d o n t h e c h i l d ' s s c h o o l . ( A s s u m i n g that t h e y have t h e s a m e teachers, the s c h o o l subs a m p l e is m o r e likely to p r o d u c e a correct response).  Child's  Responses  METHODS  43  Table 3.4. (continued) Imputation Methods for Parent and Child Travel Survey Data Child's  perception  of tie neighbourhood:  1 feel safe f r o m cars.  2  1 feel safe f r o m strangers a n d bullies. It i s e a s y a n d f u n to w a l k .  4  1 f e e l s a f e w a l k i n g by  4  myself.  wiien 1 walk in my  neighbourhood...  I m p u t e d by d r a w i n g a r a n d o m r e s p o n s e f r o m a s u b - s a m p l e of r e s p o n d e n t s , b a s e d on the child's school. I m p u t e d by d r a w i n g a r a n d o m r e s p o n s e f r o m a s u b - s a m p l e of r e s p o n d e n t s , b a s e d on the child's school. I m p u t e d by d r a w i n g a r a n d o m r e s p o n s e f r o m a s u b - s a m p l e of r e s p o n d e n t s , b a s e d on the child's school. I m p u t e d by d r a w i n g a r a n d o m r e s p o n s e f r o m a s u b - s a m p l e of r e s p o n d e n t s , b a s e d on the child's school.  3.3 Micro-Scale Survey of the Pedestrian Environment 3.3.1 School Selection T h e limited number of students recruited from any single school steered the collection of micro scale data towards the selection of a subset of 7 schools for inclusion in the microscale survey component of this study. Ideally travel survey participants would have been recruited from neighbourhoods that represent extremes in the range of neighbourhood types (walkable, not walkable) desired for the study. Given the strong correlation between income and travel choice (as discussed in Chapter 2), it is likewise essential to ensure that participants represent extremes of socioeconomic backgrounds. If applying this strategy, schools would be selected from neighbourhoods representing the four quadrants of income and walkability illustrated in Figure 3.1 (developed for the Neighbourhood Quality of Life Study noted above), with one or more schools being selected from each quadrant. Participants would then be recruited from schools in each quadrant until a sufficient number were obtained to achieve some statistical significance.  METHODS  44  Figure 3.1. Ideal C a t e g o r i e s o f N e i g h b o u r h o o d f o r Participant  Recruitment  High Walkability, High Income  Low Walkability, High Income  High Walkability, Low Income  Low Walkability, Low Income  However, objectives of the ASIBC  research program took precedence in school selection  so the available neighbourhoods were limited to those associated with only 13 schools in B.C.'s lower mainland which had not been selected based on these neighbourhood types. It was decided that a maximum of 7 schools could be evaluated given available data collection resources. T h e following considerations were used to better understand the choices available:  1. Income Household income levels were a s s e s s e d by finding the 2001 C a n a d a C e n s u s Tract in which each school is located, and using the average household income as a proxy for the average income of the participating families. This analysis determined that average incomes ranged from a low of $33,223 to a high of $86,866.  2. Diversity of Neighbourhood  Types  Before selecting the schools for the final analysis, it was necessary to compare the pedestrian environment in the neighbourhoods under consideration to ensure a s diverse a sample of the pedestrian environment as possible. Since data on the micro-scale pedestrian environment are only available through direct observation,  street network  connectivity was chosen as a proxy measure. Street connectivity was selected because it is:  a) known to be a significant influence on adult travel patterns (as discussed in Section 2.4.1); b) an important influence on travel distance which is the most frequently  cited  M E T H O D S 45  deterrent to walking (as discussed in Section 2.4.1); and c) the only walkability variable that can be compared with reasonable accuracy from a simple visual analysis of a street map.  Admittedly there is no evidence of a relationship between street connectivity and microscale features of the pedestrian environment.  Given that selection of neighbourhoods  was already limited (and would be further by income and sample size considerations), connectivity was considered a reasonable proxy.  To estimate connectivity, street maps of the school catchment areas were obtained at 1:33333 scale (1.5cm=500m) using the on-line M a p Q u e s t ® tool.  9  This allowed a simple  visual comparison of the interconnectedness of the street network. More grid-like street patterns became the proxy for a more walkable community, and more curvilinear street patterns being a proxy for a less walkable one  3. Potential Sample Size At the time of school selection many participants had already returned consent forms, providing an estimate of the maximum possible responses per school.  T h e potential  number of responses utimately became the primary decision factor in school selection, under the assumption that a response rate of 60% would be achieveable.  Final Selection Of the 13 schools, one (Yarrow Elementary) was located in Chilliwack, a distance too far away to obtain reasonable pedestrian environment data under the circumstances. T h e 12 remaining schools were compared using Table 3.5.  It was determined that  Hatzic Elementary School has a street network pattern that is distinct among the 12 schools; it has longer blocks with more cul-de-sacs and curvilinear streets than the other neighbourhoods, and in addition it is geographically isolated from the core area of the Town of Mission. It was thus an important school to include in the sample, despite having only 47 signed consent forms (requiring a 64% response rate to meet the target of 30).  METHODS  46  There were no other schools with small sample sizes with a street pattern unique enough to warrant inclusion.  T h e final s e v e n schools selected were 6 of the 7 with more than  50 participants, plus Hatzic Elementary with 47 students.  Windebank Elementary was  excluded s o there would not be three schools all in Mission School District.  Table 3.5. S c h o o l Selection Criteria School Name  Walkability  (City)  Average Number of Selected Household Inc ome Students for Participating Study? (from Census 2001)  Boundary Elementary (North Vancouver)  High/connected  $76,770.00  57  Yes  Brentwood Park Elementary (Burnaby)  Low/disconnected  $56,299.00  53  Yes  Britannia Elementary (Vancouver)  High/connected  $43,063.00  15  No  Moderately connected  $33,223.00  65  Yes  High/connected  $71,797.00  42  No  Hatzic Elementary (Mission)  Very low/disconnected  $71,623.00  47  Yes  Lakeview Elementary (Burnaby)  Moderatelyconnected  $83,866.00  37  No  Marlborough Elementary (Burnaby)  Low/connected  $37,305.00  158  Yes  Mission Central Elementary (Mission)  Mix of connected and disconnected  $42,716.00  63  Yes  Walter Moberly Elementary (Vancouve r)  High/connected  $57,184.00  119  Yes  W e s t Heights Elementary (Mission)  Moderately connected  $47,116.00  35  No  Windebank Elementary (Mission)  High/connected  $67,280.00  74  No  Brooksbank Elementary (North Vancouver) Florence Nightengale Elementary (Vancouve r)  3.3.2 Selection of a Survey Tool Numerous audit instruments have been developed to inventory or otherwise  quantify  macro- and micro-scale elements of the built environment as related to non-motorized METHODS  47  travel and physical activity.  10  It is recommended that any instrument address each of the  origin/ destination, route, and area aspects of a journey as discussed in Chapter 2, but this is rarely done due to the expense of primary data collection. Unfortunately there is little 11  consistency between measuring tools. O n e review identified over 200 different variables across a sample of 31 tools, which makes it unlikely that any two tools look at the same combination of variables.  In addition, those recording the same variables may quantify  them in different ways. This makes it difficult to compare results between jurisdictions, even though each study contributes something to a broader understanding of the topic.  T h e route from home to school was chosen as the location from which micro-scale features would be evaluated and correlated with each student's travel choice to school. This does not completely discount the origin/destination and area elements. The focus on a specific trip common to all participants makes the destination component almost a constant. Although the micro-scale pedestrian environment in the immediate vicinity of each school may vary, there are several similarities. All elementary schools are all subject to provincially legislated vehicle s p e e d restrictions (30 km per hour in school z o n e s ) . 12  In addition, trip characteristics are similar with respect to time of day, belongings that a child must bring with them, the mandatory nature of the destination, and the presence of supervisory adults at each end of the trip (if not also along the route). Trip origins are more diverse, but are at least consistent in being the child's place of residence. O n c e they leave their driveway, variation in the pedestrian environment is accounted for through the route evaluation. T h e area component of the journey is not included because this study is predicated on previous research that discounted the influence of area-wide/macroscale characteristics. Limitations on resources for data collection and analysis were also a factor.  T h e micro-scale survey selected for use in this study was developed for the Neighbourhood Quality of Life Study ( N Q L S ) which is funded by the U.S. National Institutes for Health and operates out of S a n Diego State University.  13  T h e N Q L S survey has been used  once previously in the Seattle area but results from the data have not been published  METHODS  48  to date.  This tool was selected due to Dr. Frank's association with the N Q L S project.  This association allowed Palm Pilot computes already programmed with the previously developed and tested survey instrument to be provided on-loan for use at U B C .  The  Palm Pilots were also programmed with a G P S device enabling the location of specific street segment start and end points as described below. T h e current study provided an opportunity to test the transferability of the N Q L S survey to a different jurisdiction and test the application of the resulting data to a different research framework.  From this  perspective testing the utility of the survey tool in the Greater Vancouver context became a secondary research objective of this study.  Micro-Scale  Survey  Content  T h e micro-scale survey includes over 60 micro-scale measures that are thought to influence the safety and enjoyment of walking along the route of a trip. T h e s e measures fit into the broad categories outlined in Table 3.6, which together provide, a comprehensive inventory of pedestrian environment features. A complete version of the micro-scale survey can be found in Appendix B. The survey is divided into two distinct components so that street segments and intersections can be evaluated as the units of analysis.  Street Segment = T h e block of street between two Intersection  intersections  = T h e place where two or more officially designated streets meet or cross  T h e junctions of laneways or driveways are not considered intersections, although they can present similar risks for the purposes of pedestrian and some vehicular travel.  Enumeration of micro-scale variables on each street segment and intersection is conducted by responding to a series of multiple choice questions. A survey software was designed by GeoStats, L L P in Atlanta, Georgia, that enables the data to be entered directly onto a hand-held Palm Pilot computer and administered on-location.  A global positioning  system ( G P S ) device attaches to the Palm Pilot to provide geo-refererices to each of the  METHODS  49  street segments and intersections evaluated with the survey that enables data to later be entered into a geographic information system (GIS)  database.  However the G P S data  were not used for the current analysis.  Table 3.6. C a t e g o r i e s of V a r i a b l e s Included in the M i c r o - S c a l e S u r v e y  BROAD  CATEGORY  SPECIFIC ELEMENTS  Intersection  Traffic control s i g n s and signals, c r o s s w a l k d e s i g n , curb design  Roadway  N u m b e r of l a n e s , type of curb, on-street parking, roadway grade  Traffic C a l m i n g  P r e s e n c e of s p e e d h u m p s , signs, traffic circles, or other infrastructure modifications to slow traffic  Buffer-  P r e s e n c e and width of a buffer-zone b e t w e e n the s i d e w a l k and v e h i c u l a r traffic  Street Furniture  P r e s e n c e of v a r i o u s street furniture or public amenities, s p a c i n g of street lights  T r e e s and S h a d i n g  N u m b e r of trees, percent cover of w a l k w a y by tree c a n o p i e s , awnings, etc.  Sidewalks  P rese nee, c o nt in u ity, width, mat eri a 1, a nd st at e cf re pa i r  Private D e v e l o p m e n t  Building s e t b a c k s a n d heights, land use, p e r c e n t a g e of w i n d o w fro nt ag e, b u il d in g state of rep a ir  Community Open S p a c e  T y p e of o p e n s p a c e adjacent to street, other pedestrian routes connected to the street,  Negatively P e r c e i v e d Characteristics  P r e s e n c e of graffiti, litter, posters/stickers, g e n e r a l m a i n t e n a n c e and c l e a n l i n e s s  METHODS  50  3.3.3  Defining the Study Area and Selecting Street Segments  T h e goal of the micro-scale data collection was to obtain sufficient information so that pedestrian conditions could be described for each child's route from home to school. To this end, the addresses of each child were used to pin-point their home location. T h e s e locations then informed selection of street segments for evaluation with the intent of maximizing the number of streets enumerated on each child's route. This approach is highly unique and maximizes the linkage between the pedestrian environment stimulus (the route to school) and the response (travel choice). It is furthermore highly consistent with theoretical models presented in Chapter 2.  Maps of the school catchment areas were obtained from the 4 relevant school districts. Most respondents live within the catchment area, however 30% were found to live between several blocks and several kilometres outside this boundary. T h o s e external to the catchment were primarily from Marlborough and Mission Central Elementary Schools where French Immersion programs (which draw from a larger catchment) are offered. T h e catchment areas for each school are illustrated in Chapter 4.  It was decided to restrict street and intersection evaluations to the area inside each school's catchment boundary, which had several benefits.  Since most students live  inside the catchment this guaranteed only a small number would be excluded from the micro-scale analysis. It also ensured that for students within the catchment, real data would be available for a greater proportion of their route. Finally, the relatively compact nature of the catchment areas (average 2.36km ) allowed evaluators to minimize the 2  time they spent traveling between segments, thus enabling data collection on more street segments for the overall time spent. A sample of 25 to 30 street segments and their adjoining intersections were selected within each catchment area with a specific emphasis on including segments along which the children would be required to travel on their trips to school. E a c h street segment and adjoining intersection were assigned a unique identifier that attributed it to the specific school. (For example Hatzic Elementary is school #6; Hatzic street segments were coded 601 to 630.)  Figure 3.2 provides an  METHODS  51  e x a m p l e of the B r e n t w o o d P a r k E l e m e n t a r y S c h o o l c a t c h m e n t a r e a a n d the distribution of s t r e e t s e g m e n t s s e l e c t e d for e v a l u a t i o n .  Figure 3.2 Sample Catchment Area Map with Evaluated Street Segments Marked  MAP LEGEND Streets: Street Names:  Grand Av  School Location: Catchment Area Boundary* Evaluated • Street Segments: Observed Short Cuts;  I III n i l i n 1 1 I I I I  3.3.4 Evaluator Training and Data Collection D a t a c o l l e c t i o n w a s c o n d u c t e d a s a S C A R P c l a s s project in " N o n - M o t o r i z e d T r a n s p o r t a t i o n a n d U r b a n D e s i g n " ( P L A N 5 8 1 ) t a u g h t at U B C b y Dr. F r a n k .  Eight student evaluators  f r o m P L A N 581 w e r e t r a i n e d b y Dr. K a t h l e e n K e r n w h o h a d p r e v i o u s l y w o r k e d c o l l e c t i n g d a t a o n the N Q L S s t u d y in S e a t t l e . T w o t h r e e - h o u r training s e s s i o n s w e r e h e l d a s part of the c l a s s c u r r i c u l u m . T h e first r e v i e w e d the s u r v e y i n s t r u m e n t a n d c o m p a r e d the p o s s i b l e a n s w e r s for s p e c i f i c t y p e s of v a r i a b l e s in a s l i d e s h o w (for e x a m p l e , the d i f f e r e n c e b e t w e e n a s q u a r e a n d a rolled c u r b , h o w to d e f i n e a buffer, etc.). T h e s e c o n d training s e s s i o n w a s in the f i e l d , u s i n g the s u r v e y i n s t r u m e n t a s a g r o u p , a n d t h e n p r a c t i c i n g i n d i v i d u a l l y o n both r e s i d e n t i a l a n d c o m m e r c i a l s t r e e t s .  T h e i n t e g r a t i o n of this project w i t h i n a c l a s s  setting o f f e r e d a n o p p o r t u n i t y for first y e a r m a s t e r ' s s t u d e n t to g a i n d i r e c t e x p o s u r e to real w o r l d f a c t o r s i n f l u e n c i n g the p e d e s t r i a n e n v i r o n m e n t a n d to t h e s i s r e s e a r c h d e s i g n a n d  METHODS  52  development while collecting the data used for this study.  Street and intersection evaluations were conducted over a 4 week period in February and March 2006. T h e trained evaluators were each assigned to a pair of schools, with one as the "primary" and one as the "secondary" evaluatorfor each neighbourhood; an "a" or "b" was added to segment codes to differentiate between evaluators at each school. T h e primary evaluator was responsible for completing the survey for each segment selected within the neighbourhood.  T h e secondary evaluator completed half of the assigned  segments, selected at random. This allowed for an evaluation of inter-rater reliability to estimate the level of precision in the data collection. T h e computerized survey system automatically transformed data into a comma delimited (.csv) database.  3.3.5  Data C o m p i l a t i o n  Compilation of the micro-scale data collected revealed that data were not available for all'street segments and intersections originally selected for evaluation.  Despite pre-  testing of the hand-held computers and training of evaluators there was a loss of data due to a probable combination of equipment malfunction and evaluator error/oversight. Unfortunately, time constraints prevented return site visits to replace the missing data. Nonetheless, a sufficient amount of data remained to undertake the desired analysis. Table 3.7 indicates the number of complete segment and intersection evaluations for which data are available.  Table 3.7. N u m b e r of E v a l u a t e d Per S c h o o l  School  Intersections  and  Street  Segments  Number of lutei sections  Number of Street Segments  Boundary Community  26  28  Brentwood Park Brooksbank  27 31  28 30  Hatzic Marlborough  23 29  23 27  Mission Central  28  30  Walter Moberly  23  29  METHODS  53  T h e data set produced by the N Q L S Micro-Scale Survey contained far too many variables to manage within the context of this analysis. B a s e d on the literature available and this author's personal perception, a limited number of variables were selected that were suspected to have a particular influence on children's travel patterns. For example sidewalk quality, intersection controls, and road width were all given a high priority because of their relation to pedestrian safety from traffic. Land use types were excluded on the assumption that the travel choices of children in grades 4 and 5 are unlikely to be influenced by their ability to run errands on the way to/from school (although it is acknowledged that land use mix can contribute or detract from street safety/ambiance).  Street lighting was thought  not to be important for the exclusively day-time trips such as travel to school. Table 3.8 lists the specific variables selected.  Table 3.8. Variables s e l e c t e d f r o m the N Q L S M i c r o - S c a l e S u r v e y Street Segments Number of lanes Extent of Sidewalks (left and right h a n d side) Presence of Buffer (left and right hand side) S t e e p n e s s of Grade Presence of Traffic Calming M e a s u r e s Other Pedestrian Routes Connected to the Sidewalk (left and right hand side) :  Inter-Rater  Intersections Intersection design (T-type or 4-way) Type of Traffic Control CrosswaIk Marking Crosswalk Signage Pedestrian Button  Reliability  T h e second step in compiling the micro-scale survey data set was to a s s e s s the reliability of the data for the variables selected using a Kappa test to measure inter-rater reliability (IRR). T h e Kappa score calculation is stronger than evaluating simple percent agreement because it accounts for the level of agreement that would occur simply by chance. Kappa scores can range between -1 and +1; a score of 1 indicates perfect agreement while a score of-1 indicates perfect disagreement; a zero score means there is no more agreement than what would be expected by c h a n c e .  14  Variables with few potential values are known  to generate lower Kappa scores because there is a greater likelihood that agreement will occur by chance; this is an important observation because most of the data from the micro-scale survey are recorded as dichotomous values. Thus Kappa scores were generally expected to be low.  Bakeman and Gottman  15  state that Kappa scores of 0.7  METHODS  54  or greater are considered satisfactory. In this case, Kappa values larger than 0.7 would validate a decision to use the primary evaluator's data for each school.  IRR was tested by limiting the sample to only those segments and intersections scored by both evaluators at each school. The recorded values were then compared segment by segment and variable by variable using S P S S to determine the level of agreement between responses from the two evaluators at each school.  Results of the Kappa test  are reported here because validation of this data was essential prior to developing the pedestrian friendliness index (see section 3.4.3).  T h e IRR for the overall sample was extremely high. Seventy-nine percent of the measures were considered constants, indicating 100% agreement.  This condition resulted when  both evaluators indicated the s a m e score and the variable has the same value for all segments at the school."  School-by-school IRR of 100% varied from 65% at Mission  Central to 92.5% at Brentwood Elementary. A n additional 10% of the IRR scores could not be calculated because the responses from one rater were a constant (i.e. one rater scored that variable consistently the same for the entire school while the other did not). In these c a s e s a simple percent agreement was used, with 95% of the c a s e s scoring between 70-95% and the remaining 5% scoring 60% simple percent agreement.  T h e second summary value of interest is the number of variables with a Kappa score below 70%.  Only 7% of all the variables compared scored in this range.  Complete  results of the Kappa test are contained in Appendix E.  Street grade was one variable with consistently low Kappa scores (ranging between schools from a low of 0.364 to a high of 0.772). However, it is known that this variable is one of the most subjective in the data set. Closer examination of the data reveals most of the non-agreements are a difference between "steep" and "moderate" or "moderate" and "slight" slopes, rather than more worrisome differences such as between "flat" and "steep"  b Unfortunately this is also an indication of low variation among some variables such as number of lanes which may be contributing to inconclusive results in the inferential analysis. METHODS  55  slopes. It was decided to accept this data despite the low Kappa scores.  T h e variable of "other pedestrian routes" was initially selected for the analysis phase of this research.  However, the Kappa scores for pathways showed the least amount of  agreement of all the variables across all pairs of evaluators with an average of only 0.6 and scores ranging from -0.22 to 0.886. A s a result adjacent pathway data were excluded from further analysis. This is not considered detrimental to the study as the presence of pathways or significant short-cuts were accounted for when determining routes to school (see section 3.4.2).  Considering the outcomes of the Kappa scores, it was decided to accept data collected by the primary evaluator for each school for all the variables listed in Table 3.8, except for the "other pedestrian routes" which was excluded entirely from the analysis.  Imputing Micro-Scale  Data  Due to the data collection methods there were no missing values in any of the street segments or intersections. However every catchment area contained numerous street segments that were not evaluated. In order to reasonably estimate pedestrian conditions for each child's entire route to school it was necessary to impute values for the unevaluated street segments.  This was undertaken by drawing from known street segments and  intersections within the same catchment area. Street segments and intersections were compared only on the basis of the variables selected for the detailed analysis (see Table 3.8 above), excluding "other pathways" which were eliminated due to poor Kappa scores.  T h e single most important tool used to determine similarity of streets was direct on-site observation and the expert opinion of this author. This method allowed direct measurement through a single trained observer, increasing the degree of standarization. This was particularly important for the two schools in Mission where the presence of sidewalks and buffers was extremely inconsistent. Rules were established to standardize decision making.  Known segments directly adjacent on the s a m e street were considered first,  METHODS  56  followed by a different segment on the s a m e street.  If neither of these were available or  suitable, a segment on a parallel street of similar nature would be used.  Intersections  were required to be of the s a m e type (t or 4-way) and between streets of a similar nature to the intersection missing data. Imputing intersections was simplified by the fact that the original survey collects a low level of detail on intersection traffic controls. For example, it does not distinguish between 2-way and 4-way stops. This made it easier to impute values that would score the same survey values despite some differences in actual conditions. (This is discussed further in Chapter 6.)  For future reference, a record was maintained of which street segments and intersections (as defined by street names) were equivalent to which evaluated street segments (as defined by an evaluation code).  It should be noted that the limited number of variables  analyzed in this study greatly facilitated the imputation process. The greater the number of variables being analyzed, the more difficult it will be to find street segments that approximate one another.  3.4 Determining a Unique Pedestrian Environment Score for Each Child 3.4.1 Students in the Catchment Area In order to analyze the influence of micro-scale environment on travel choice it was essential to asign a unique score to each child's route to school that might help explain variation in travel choice between children living in the s a m e neighbourhood. A s indicated in Section 3.3.3, 30% of students were found to live outside the catchment area; these students were excluded from further analysis because pedestrian environment data were only available within the catchment boundaries. A small number of children living on streets outside but directly adjacent to the catchment were retained when it was felt sufficient data existed to accurately asign a unique score.  Table 3.9 indicates the number of students from each school found to live inside the catchment area.  T h e impact of this exclusion was most profound at Marlborough and  Mission Central Elementary Schools, both of which offer French Immersion programs that METHODS  57  draw students from a very broad geographic area. However, the remaining sample of 239 is still large enough for a rigorous statistical analysis.  Table 3.9. Size  Impact of Catchment Area E x c l u s i o n on Total Sample School  Complete Survey Pairs Returned  # Responding Students Inside C atch mient  Area Boundary Brentwood Park Brooksbank Hatzic . Marlborough Mission Central Walter Moberly  ^2  34 33 35 20 43 20 5i_  TOTAL  344  239  « 45 39 27 101  3.4.2 Estimating Routes It is generally accepted that pedestrians choose the shortest route possible when walking for utilitarian trips.  16  With this in mind, site visits to each school identified the location of  important short-cuts between homes and schools.  For example, Boundary Community  and Mission Central Elementary schools each have public staircases providing short-cuts between streets (particularly those separated by steep hills). O n e street near Brentwood Park has bollards blocking cars mid-way, but provides a continuous pedestrian route that dramatically shortens the walking distance for several students in the study. Walter Moberly is surrounded by public playing fields that provide an easy shortcut to avoid streets and a c c e s s the school from the rear. The location of these shortcuts was taken into consideration in determining each child's route to school.  It was also a s s u m e d that  smaller (narrower) streets are preferable due to safety (lower volumes, slower traffic) and are more pleasant (less noise and pollution) than their larger counterparts.  Photos 3.1a  and 3.1b illustrate some of the short cuts.  METHODS  58  Photo 3.1a Short cut at Mission Central connecting the s c h o o l yard to 2 n d at Welton.  Photo 3.1b Short cut at Boundary connecting Tempe Cres to TemDe Knoll  After identifying the home location, each child's walking route to school was estimated based on the assumptions that the preferred route would:  1)  Be the shortest and most direct possible route between home and school;  2)  Include all identified shortcuts between home and school that serve to shorten the route, and  3)  Favour a minor/residential street over a larger street if that choice did not lengthen the overall trip.  Figure 3.3 illustrates the route to school selected for one participant at Brentwood Park Elementary School. Using this method, two unique "route equations" were created for each child consisting of the segment numbers along which they would have to travel to reach the school; one for street segments and one for intersections. For children living on the s a m e block as the school, the closest intersection was used to create a complete data set, even though these children may not have to cross the street.  Obviously this method has limitations because route choice can be affected by many factors. A child may detour to walk with a friend, choose a different route b e c a u s e there are multiple options that are all the same distance, or may begin/end their trip at the location of a  METHODS  59  b a b y s i t t e r o r d a y c a r e r a t h e r t h a n their h o m e a d d r e s s . U n d e r t h e c i r c u m s t a n c e s o b t a i n i n g this l e v e l of d e t a i l f r o m e a c h p a r e n t w o u l d h a v e r e q u i r e d e q u i p p i n g e a c h s t u d e n t with a G P S d e v i c e d u r i n g t h e s u r v e y r e s u l t i n g in a s m a l l e r s a m p l e s i z e a n d a different s t u d y d e s i g n . T h e m e t h o d u s e d r e s u l t e d in i n c r e a s e d p o w e r i n s a m p l e s i z e a n d g e n e r a l i z a b i l i t y a n d is b a s e d o n r e a s o n a b l e s h o r t e s t p a t h a s s u m p t i o n s o f t r a v e l r o u t e c h o i c e .  Figure 3.3 Sample Map of Route to School (Brentwood Catchment)  MAP LEGEND Streets: Street N a m e s :  Grand Av  School Location: Catchment A r e a Boundary. Evaluated Street S e g m e n t s : Observed Short Cuts:  I f t l t i t ! ! i i 11 til >  3.4.3 Creating an Index of Pedestrian Friendliness A s d e s c r i b e d in C h a p t e r 2 , f e a t u r e s of t h e built e n v i r o n m e n t t e n d to c o - v a r y in s p a c e , m e a n i n g that c e r t a i n a m e n i t i e s a r e f r e q u e n t l y f o u n d t o g e t h e r . B u f f e r s d o not e x i s t without a s i d e w a l k ( a l t h o u g h s i d e w a l k s e x i s t without b u f f e r s ) ; l i g h t - c o n t r o l l e d i n t e r s e c t i o n s t e n d to c o m e with p e d e s t r i a n c r o s s i n g s i g n a l s . T h i s m e a n s it is often difficult to i s o l a t e t h e influence of o n e variable from another.  S i m i l a r l y , t h e i n f l u e n c e of c e r t a i n f e a t u r e s m a y  v a r y d e p e n d i n g o n w h a t c o m p l i m e n t a r y f e a t u r e s a r e a v a i l a b l e . A p e d e s t r i a n n e t w o r k with s i d e w a l k s a n d s i g n a l i z e d c r o s s i n g s is likely to b e m o r e e f f e c t i v e t h a n a n e t w o r k w i t h o n l y o n e o r t h e other. T o h e l p c o m p e n s a t e f o r this it i s c o m m o n t o c r e a t e a n i n d e x - o n e n u m b e r M E T H O D S 60  that represents a combined score of all pedestrian environment m e a s u r e s .  17  Four basic  methods were tested in an effort to create a "pedestrian friendliness" index appropriate for this c a s e study: the z-score index, the equal weighting index, and two "lowest score" indices based on values from both the z-score and equal weighting indices.  Index Method 1: Z-Score Index T h e first index tested used a z-score (the number of standard deviations from the mean) to standardize values for each of the variables considered. This method followed that applied to macro-scale variables in the N Q L S study.  To create z-scores, categorical  18  variables were first converted into a form that could be manipulated numerically as described in Table 3.10.  For example, crosswalk markings and signage were recorded  on a yes/no basis for each leg of an intersection; these values were converted into a proportion of intersection legs that exhibited that feature.  Table 3.10. Converting Categorical Data into Calculable Scores Variable  Original Measure  Tra n sfo rme d M e asu re-  Number of Lanes  Number of travel lanes on left and right side of segment. 0 rdinal score for proportion of sidewalk on left and right side of segment.  Total number of lanes  Street Segtnet its  Extent of Sidewalks (left and right hand side) Presence of Buffer (left and right hand side) Steepness of Grade Presence of Traffic Calming Measures  Presence/absence of buffer on left and right side of segment. Ordinal score for steepness of grade (higher score is more steep). Presence/absence of each of 7 different traffic calming elements.  Intersections Intersection design (T-type or 4-way)  Nominal selection of which intersection lype.  Type of Traffic Control  Nominal selection of which traffic control type for the intersection.  Crosswalk Marking  Presence/absence of crosswalk marking for each leg of the intersection. Presence/absence of crosswalk signage for each leg of the intersection. Presence/absence of pedestrian button.  Crosswalk Signage Pedestrian Button  Ordinal score for amount of sidewalk on the street side with the longest continuous sidewalk. Ordinal score for total amount of buffer (none, 1 side, or both sides) No transformation required. Total number of traffic calming elements present on the street segment. No transformation possible; variable was initially removed from the analysis. Created ordinal score with none=0, yield or traffic circle=1, stop sign=2, traffic light s=3 Proportion of intersection legswith a crosswalk marking. Proportion of intersection legs with a crosswalk signage. Ordinal ranking (none = 0, present=1)  METHODS  61  T h e z-scores for the number of lanes and steepness of grade were multiplied by -1 to reverse the direction of influence because steeper slopes and more lanes were thought to decrease the attractiveness of walking.  A set of unique scores for each child was created by averaging the z-scores of each variable from each of the segments or intersections in that child's route equation. This process is illustrated below; recall that the s a m e segment/intersection identifier may appear multiple times due to the imputation process.  School: #1 Walter Moberly Participant Code: 1037 Street Segment Identifiers: 22 + 3 1 + 3 1 + 1 Street Segment Score for Sidewalks = average of sidewalk z-scores for each segment = (0.69056 + -1.51477 + -1.51477 + 0.69056)/4 = -0.41211  Intersection Identifiers: 22 + 22 + 2 + 1 Intersection Score for Crosswalk Signage = average of crosswalk signage z-scores for each segment = (-0.37 + -0.37 + 2.44 + -0.37V4 = 0.33352  Three simple indices were created by summing the following scores for each child:  1) Street Segment Index (sum of street segment variable scores) 2) Intersection Index (sum of intersection variable scores) 3)  Pedestrian  Friendliness Index (sum of Street  Segment and  Intersection  Indices)  Finally each of the indices was quartiled to accentuate the differences between groups.  Analysis of these index scores revealed that the z-score based standardization caused significant problems because the variable scores were not normally distributed.  This  meant that relatively rare street characteristics received disproportionately high or low z-scores simply because they were rare. For example, the minimum z-score for the type METHODS  62  of traffic control was -2.99 because most streets had stop signs but only a few had no controls. In contrast the minimum possible score for traffic calming was only -0.52. W h e n these were combined into the pedestrian friendliness score, streets that scored poorly on traffic controls fared much worse than those scoring poorly on traffic calming.  There is  no evidence from this study or in the literature to suggest that the disproportionate scores actually reflect the relative influence of these street characteristics on probability of walking. In fact exploring that relative influence is an objective of this study. This observation highlighted the need to create an index where each variable would be weighted equally, which led to the Equal Weighting Index.  Index Method 2: Equal Weighting Index T h e second approach to index development was to assign a value between 0 and 1 to each variable characteristic so that the maximum potential score would be the same for each variable. This was done using ordinal scoring as described in Table 3.11. Note that for this index, stop signs and traffic lights are assigned the s a m e score. This was done because tests of the first index suggested that intersections with lights scored much higher than those without because they tend to also have crosswalk signage and pedestrian buttons. However, intersections with lights also tend to be the widest and have the most traffic - making it counterintuitive that they would score really high. For this reason, the variable of pedestrian buttons was also removed completely. Segment, intersection, and pedestrian friendliness index scores were created for each child using the s a m e method described above, but substituting the equally weighted variable scores for the z-score based values.  Index Methods 3 and 4: Lowest Score Indices A n alternative hypothesis was that the safety or perceived safety of a child's trip to school could be strongly influenced by dangerous conditions along only one street segment or at one particular intersection along the route. To test this hypothesis each street segment and each intersection were given two indexed scores calculated by adding the scores for each variable on that segment. E a c h child was then assigned a "lowest segment" score  METHODS  63  and "lowest intersection" score based on the lowest scoring segment and intersection along their identified route to school. T h e s e two scores were then added for each child to determine the "lowest pedestrian friendliness" score.  Table 3.11. Ordinal Ranking of Variables for the Equal Weighting Index Variable Nam e Number of Lanes  Street Grade  Traffic Calming  Buffet-  Sidewalk (amount on side with longest)  Traffic Control  Crosswalk Marking  Crosswalk Signage  Rank in Original Data 2 lanes 3 lanes 4 lanes 6 lanes 0 - flat 1 - slight slope 2 - moderate slope 3 - steep slope 0 elements 1 element 2 elements 3 elements None 1 side both sides None 1-25% 25-50% 50-75% 75-99% 100% None Yeild Traffic circle Stop sign • Traffic Light None 1 of 4 legs 1 of 3 legs 2 of 4 legs 2 of 3 legs 3 of 4 legs All legs None 1 of 4 legs 1 of 3 legs 2 of 4 legs 2 of 3 legs 3 of 4 legs All legs  Standardized Score (0-1) 1 0.67 0.33 • 0 1 0.67 0.33 0 0 0.33 0.67 1 0 0.5 1 0 0.2 0.4 0.6. 0.8 1 0 0.5 0.5 1 1 0 0.25 0.33 0.5 0.67 0.75 1 0 0.25 0.33 0.5 0.67 0.75 1  METHODS  64  T h e Lowest Score Indices were calculated and tested for their level of significance using both the Z - S c o r e Index and the Equal Weighting Index. (It was calculation of the lowest score that revealed the problems of the z-score index discussed previously.)  3.5 Data Analysis 3.5.1  Descriptive Analysis  Travel survey and micro-scale survey data were described in terms of frequencies for each response on a school-by-school basis and for the combined sample population of 239 respondents. Measures of central tendency were calculated, alternatively using the mean and mode as appropriate.  Results of this descriptive analysis are presented in  Chapter 4.  2.2.2  Inferential Analysis  Methods of inferential analysis are described in Chapter 5 in tandem with presentation of results.  Due to the issues identified with the Z - S c o r e Index, only the Equal Weighting  Index and it's variations (Lowest Score and Modified Equal Weighting) were used in the inferential analysis stage.  3.5.3  Qualitative Analysis  Qualitative objectives of the study were to a s s e s s the efficacy of the selected microscale survey tool within the context of the Greater Vancouver Area and the route-specific research methods. Analysis of this efficacy was based on on-going observations of the author and micro-scale evaluators made during both the data collection and analysis stages of the study. Results and recommendations arising from this qualitative evaluation are contained in Chapter 6.  3.6 Methodological Limitations S o m e limitations in the methodology were identified at the point of study design while others only became apparent as the data were collected and analyzed. This was expected as evaluation of the methodology was a significant research question. Limitations initially identified are discussed here; some of these were referenced previously in this chapter. METHODS  65  Limitations arising during the research process are presented in Chapter 6 as results of the qualitative evaluation of the process. S o m e of the limitations have implications for the quality of data collected and the subsequent analysis and results. S u c h implications are referenced here and discussed further with the presentation of results in Chapter 5.  School Selection and Variability of Neighbourhood A s discussed in section 3.3.1 Schools!  BC  Form  (School Selection), the research priorities of the  Action  project placed significant restrictions on the types of neighbourhoods  available for inclusion in the study. This means that inter-school variation among the 7 selected schools is not likely to represent the true extremes of possible variation in microscale attributes.  O n top of this, intra-school variation is limited due to the nature of the  catchment areas selected. Most of the catchment boundaries in this study are defined by major roads, meaning that few (if any) students have to cross major roads on their trip to school. The compactness increases the chance that streets will have been developed at similar times and thus have similar characteristics. T h e s e factors in combination are likely to remove a substantial amount of variation when considering the micro-scale pedestrian environment on a route-specific basis.  Travel Survey Design and  Administration  Time constraints prevented the survey from being pre-tested with a sub-sample population to identify potential misinterpretations of questions, add relevant questions that had not been asked, or to otherwise refine the survey. Analysis of the survey responses confirms some issues that may have been addressed through a pre-test.  Although a pre-test  could have improved the range of questions asked on the survey, it not believed that this omission substantially impacts the quality of data for the variables used in this analysis. Many of the questions used in the survey were drawn from other survey instruments which offered a de-facto pre-test for these questions.  A n additional limitation was that the strike of the B . C . Teachers Federation moved  METHODS  66  distribution of the survey closer to Christmas holidays for most of the participating schools. This may have reduced the overall response rate.  Imputing Data Missing data points in the travel survey were dealt with as systematically as possible. Household income was by far the most common missing value and is also the most difficult to impute accurately.  T h e results of analysis on income may have been affected  by this situation.  Data imputation is likewise a significant uncertainty in the micro-scale survey data and may have influenced the outcome of the pedestrian friendliness index.  However it is  suspected that greater uncertainty was introduced by the nature of the micro-scale survey itself - an issue discussed further in Chapter 6.  The Pedestrian Friendliness Index Assuming the micro-scale data collected are an accurate representation of the pedestrian environment, the method of averaging street segment scores to create a unique route score decreased the precision of the tool. Not all street segments are the s a m e length; a score more proportional to the actual street lengths could be calculated if this study were to be replicated using GIS technology but was not possible in this analysis.  In addition to this, several assumptions were made regarding the child's route to school (as discussed in Section 3.4.2). T h e s e assumptions may have produced an estimated route different from the child's normal route, for example if they take a slightly longer route in order to avoid busy intersections.  In addition, there was no micro-scale evaluation  conducted on the short cuts (except for one with bollards diving a street) because they were only pedestrian pathways. Several of the public staircases provided were extremely steep (at Mission Central in particular), and some could be perceived as too secluded for safety (too many surrounding trees, etc.). T h e conditions of these shortcuts may influence parental perceptions of safety but their attributes are not reflected in the micro-scale  METHODS  67  pedestrian environment data.  Despite these limitations, it is believed that the methods  of producing theses scores remain a reasonable basis on which to explore route-specific pedestrian environment conditions.  A larger problem lies with the accuracy with which the micro-scale survey reflects actual road conditions. This accuracy was unknown before data collection began; observations and recommendations for survey improvement are discussed in Chapter 6.  METHODS  68  C H A P T E R 4 - DESCRIPTIVE STATISTICS  T h i s C h a p t e r p r e s e n t s r e s u l t s of a d e s c r i p t i v e a n a l y s i s of the t r a v e l s u r v e y a n d m i c r o s c a l e s u r v e y d a t a . T h i s is c o n t r a s t e d with d a t a f r o m the C a n a d i a n C e n s u s to p r o v i d e a picture of the total s t u d y s a m p l e , the s p e c i f i c n e i g h b o u r h o o d s i n v o l v e d , a n d the v a r i a t i o n in d e m o g r a p h i c s , t r a v e l b e h a v i o u r , a n d u r b a n f o r m i n c l u d e d in the study.  Summary  f r e q u e n c y t a b l e s of the d a t a u s e d in this d e s c r i p t i v e a n a l y s i s a r e c o n t a i n e d in A p p e n d i x F.  C e n s u s d a t a p r o v i d e d h e r e w e r e c o m p i l e d f r o m the c o m b i n a t i o n of C e n s u s D i s s e m i n a t i o n A r e a s ( C D A s ) that m o s t c l o s e l y r e p r e s e n t the c a t c h m e n t a r e a of e a c h s c h o o l . C D A s a r e the s m a l l e s t g e o g r a p h i c a r e a for w h i c h 2 0 0 1 C e n s u s d a t a a r e a v a i l a b l e t h r o u g h U n i v e r s i t y of B r i t i s h C o l u m b i a a g r e e m e n t s (i.e. w i t h o u t m a k i n g a s p e c i f i c o r d e r to Statistics^ C a n a d a ) .  O u t of the s e v e n s c h o o l s i n c l u d e d in this a n a l y s i s , 5 6 2 s t u d e n t s a g r e e d to  participate  in the s u r v e y b y returning s i g n e d c o n s e n t f o r m s . O f t h e s e , 3 4 5 r e t u r n e d a c o m p l e t e p a i r of travel s u r v e y s , g i v i n g a n o v e r a l l r e s p o n s e rate of a l m o s t 6 1 % . H o w e v e r , 1 0 6 of t h e s e s t u d e n t s l i v e d o u t s i d e their s c h o o l ' s c a t c h m e n t b o u n d a r y , l e a v i n g o n l y 2 3 9 ( 4 2 % of t h o s e w h o r e t u r n e d c o n s e n t f o r m s ) for w h o m c o m p l e t e d a t a - i n c l u d i n g the p e d e s t r i a n environment m e a s u r e s - w e r e available. T h e following descriptive results are drawn only f r o m this s a m p l e of r e s p o n d e n t s living within the s c h o o l c a t c h m e n t a r e a .  R e s u l t s a r e first p r e s e n t e d for the entire s a m p l e , f o l l o w e d b y d e s c r i p t i o n s o n a s c h o o l - b y school basis.  DESCRIPTIVE STATISTICS  69  4.1 Overall Sample T h e 7 s c h o o l s i n c l u d e d in this a n a l y s i s r e p r e s e n t a r a n g e of n e i g h b o u r h o o d s a c r o s s 4 different s c h o o l districts in B . C . ' s L o w e r M a i n l a n d . T w o a r e l o c a t e d in e a c h of the B u r n a b y , N o r t h V a n c o u v e r , a n d M i s s i o n S c h o o l D i s t r i c t s ; o n e s c h o o l is l o c a t e d in t h e V a n c o u v e r S c h o o l District.  F i g u r e 4.1 illustrates the a p p r o x i m a t e l o c a t i o n of e a c h s c h o o l .  Figure 4.1. Locating Participating Schools in the Lower Mainland Base maps courtesty of the Greater Vancouver and Fraser Valley Regional Districts respectively. Not to Scale.  North  1- W a l t e r M o b e r l y  Vancouver  2 - Marlborough  District  3 - B r e n t w o o d Park 4-  Boundary  Coqui 5 . B r o o k s b a n k 6 - Mission Central 7 - Hatzic  4.1.1  Demographics - Household Income and Vehicle Ownership  S l i g h t l y m o r e girls ( 5 1 % ) r e s p o n d e d to the s u r v e y t h a n b o y s . T h e i r a g e s r a n g e f r o m 8 to 11, w i t h t h e v a s t majority b e i n g 9 y e a r o l d s ( 4 7 % ) a n d 1 0 y e a r o l d s ( 4 8 % ) .  This means  that the p a r t i c i p a n t s a r e all at c o m p a r a b l e d e v e l o p m e n t a l s t a g e s with r e s p e c t to their l e v e l s of i n d e p e n d e n c e a n d d e c i s i o n - m a k i n g skills for w a l k i n g a l o n e .  H o u s e h o l d i n c o m e s , a s illustrated in F i g u r e 4 . 2 r a n g e f r o m l e s s t h a n $ 2 0 , 0 0 0 to o v e r $ 1 0 0 , 0 0 0 , a l t h o u g h t h e r e is s i g n i f i c a n t u n c e r t a i n t y b e c a u s e 1 7 % of t h e s e w e r e  imputed  from c e n s u s d a t a . T h e least frequently reported i n c o m e brackets are b e t w e e n $ 7 0 , 0 0 0  DESCRIPTIVE STATISTICS  70  a n d $ 1 0 0 , 0 0 0 p e r y e a r , totaling o n l y 1 6 % o f the entire s a m p l e . T h i s is s u b s t a n t i a l l y l o w e r t h a n the 22% e a r n i n g b e t w e e n $ 0 a n d $ 3 0 , 0 0 0 e v e n t h o u g h the r a n g e o f i n c o m e s i s t h e s a m e in t h o s e t w o g r o u p s . T h e a p p r o x i m a t e a v e r a g e i n c o m e l i e s b e t w e e n $ 4 0 , 0 0 0 a n d $49,000.  Figure 4.2 Income Distribution of Total Sample Household 16.0  are  incomes  not  evenly  14.0  d i s t r i b u t e d b e t w e e n the 12.0  7 neighbourhoods - a s  s 10.0 c  illustrated in F i g u r e 4 . 3 .  }  8 0 +  •  ;  Three  6.0  schools  have  4 0  approximate  average  20  incomes  between  $60,000  and$70,000;  00  <$ 19,999  $30,000$39,999  $50,000$59,999  $70,000$79,999  $90,000$99,999  three  Htamhotd he eat  are  between  $40,000 and $49,000,  Figure 4.3 Reported and Census Average Incomes by a n d o n e is b e t w e e n School Neighbourhood $30,000 and $39,000. $90,000  Figure4.3illustratesthat  $80,000 $70,000  the  £ $60,000 o  at  c $50,000 Dl $40,000 -H  average each  incomes  school  are  consistently lower than  § $30,000  the  $20,000 T l $10,000  average  Census-  reported  incomes  for  the area.  T h i s is likely  $0  1 2  5  iS  £ 2  a>  d u e in  part  to w a y  incomes  are reported.  C e n s u s d a t a r e q u e s t s a c t u a l i n c o m e , w h e r e a s t h e h i g h e s t p o s s i b l e i n c o m e b r a c k e t in the s u r v e y w a s $ 1 0 0 , 0 0 0 o r g r e a t e r .  Incomes of $ 1 5 0 , 0 0 0 w o u l d i n c r e a s e the a v e r a g e  c e n s u s i n c o m e but w o u l d h a v e l e s s i n f l u e n c e o n the s a m p l e d a t a . D E S C R I P T I V E S T A T I S T I C S 71  Vehicle ownership is correspondingly distributed with 7 households (3%) indicating no vehicles, 4 3 % indicating one, 4 2 % indicating two, and 12% indicating three or more vehicles.  Figure 4.4 illustrates the relationship between household income and vehicle  ownership, with higher-income households reporting on-average more vehicles than those with lower incomes.  Figure 4.4. Average Vehicle Ownership by Household Income  <$29.999  $30-$49,000  $50-$69,000  $70-$89,000  >$90,000  Table 4.1. Summary of Selected Demographic Variables. (See complete details in Appendix F)  Sample Size Demographics A v e H H Income  Full Sample 239  B'bank 33  Boundary 34  B'wood 33  Hatzic 20  M'brough 47  Mission 20  Moberly 52  $40-$49,000  $60-$69,000  $60469,000  $40-$49,000  $60469,000  Ave H H Vehicles  1.49  1.94  2.09  1.52  2.3  1.26  1.4  1.5  Distance (Mode)  500m-1km  550m-1km  0-500m  500m-1km  0-500m  0-500m  500-1 k m  0-500m  $40449,000 $40449,000  $30439,000  4.1.2 Distance Limiting the sample to children within the catchment boundary inherently reduces variability in the home to school distances. Figure 4.5 reflects this as 4 0 % of all students report living less than half a kilometre away from their school. A n additional 46% live between 500m to 1km away, and 13% live between 1-2 kilometres from school. A s with the limited  D E S C R I P T I V E S T A T I S T I C S 72  age range, the catchment areas concentrate the sample within a reasonable (less than half an hour) walking distance from school that allows the analysis focus more on microscale conditions as influences on travel choice.  Figure 4.5. Distribution of Home to S c h o o l Distances  4.1.3 Travel Behaviour Overall, 64% of children in the sample "usually" use an active mode of travel for at least one of their trips to/from school.  Forty-nine percent walk in the morning and 56% walk  home after school; 42% are driven in the morning but only 35% get a drive home in the afternoon.  School buses are of little importance in the sample (less than 2%), while no  students take public transit.  This is not surprising given that the sample is limited to  within the school catchment areas which are all fairly small in size.  Somewhat more  surprising is that active modes other than walking are also very rare.  Less than 2% of  respondents report using an active mode other than walking - although fully 15% indicate a preference for bicycling or using another active mode.  Figures 4.6 and 4.7 illustrate  these relationships.  D E S C R I P T I V E S T A T I S T I C S 73  Figure 4.6. Morning and Afternoon Travel Modes  60.0  T  50.0 s  40.0  i | 30.0 * 20.0 10.0 0.0  1 n  1 1  <F  /^  XT  Figure 4.7 Mode  D M o m i n g Trip • Afternoon Trip  n ^^ <f^  ^  ^  ^  Morning Travel Mode Versus Favourite Travel  70 60 50 | 40  ....  • Morning Trip  5 30  • Favourite Mode  20 10 0  —1—*—  1, 4?  , J ,  ,  ri-  <P  Despite limiting the sample to children living within school catchment areas, Figure 4.8 illustrates that distance is still an important factor. This relationship is tested more rigorously through the inferential analysis in Chapter 5.  Fewer than half of respondents indicated their teachers had ever encouraged them to walk or bicycle to school; none of the schools are participating in a formal "safe routes to school" type program. Household travel choices among the entire  D E S C R I P T I V E S T A T I S T I C S 74  Figure 4.8. Proportion of Active Travel by Distance  sample reflect much lower rates  of walking  than  the  Figure 4.9 Work  Census-Reported Mode of Travel to  children's 80%  travel to school. Over 55% never  70%  or rarely (less than one time per  60%  week) use a non-motorized form  50%  of travel, and only 11% use active  40%  transport more than 4 times per  30% 20%  week.  10%  T h e only census data that reflect travel  n  mode  preferences  are  0% C a r Driver  Carpool  P u b l i c transit  Walked  Bicycle  passenger  preferences fortravel to work. T h e populations in the seven catchment areas for this study demonstrate a clear preference for driving with 72% reporting being the primary driver and 8% being carpool passengers for their trips to work.  D E S C R I P T I V E S T A T I S T I C S 75  Table 4.2. Summary of Selected Travel Behaviour Variables (See complete details in Appendix F)  Full Sample 239  B'bank 33  Boundary 34  B'wood 33  Hatzic 20  M'brough 47  Mission 20  Moberly 52  48.5  27.3  41.2  51.5  40  61.7  50  56  school  42.3  63.6  47.1  39.4  % active at least [one w a y favourite m o d e '(mode)  50  29.8  45  35  63.6  54.5  55.9  63.6  60  70.2  50  75  walk  walk  walk  walk  walk  walk  driven  walk  Sample Size |Travel Choice % walk to s c h o o l % driven to  4.1.4 Perceptions of Safety and Travel Preferences  Only one third of parents strongly agree that their neighbourhood is a safe place for their child to walk, although over 55% somewhat agree with this statement (totaling over 86% with some level of agreement).  Parents show greater concern when questioned  about specific safety issues for their child walking to school. Sixty-nine percent strongly or somewhat agree that their child is safe from traffic.  Nearly the same have some  agreement about safety from strangers, although a greater amount only agree "somewhat". Figure 4.10 illustrates parental responses to each of the questions regarding perception of safety.  Figure 4.10 Parental Perceptions of Safety  D E S C R I P T I V E S T A T I S T I C S 76  F e w e r t h a n 1 5 % of c h i l d r e n a r e c o n c e r n e d a b o u t traffic in their n e i g h b o u r h o o d s , w i t h " a g r e e a lot" a n d " a g r e e a little" b e i n g e q u a l l y split at 4 3 % .  Children are much more  c o n c e r n e d a b o u t s t r a n g e r s a n d b u l l i e s with 3 0 % i n d i c a t i n g t h e y d i d not a g r e e , a n d o n l y 3 1 % i n d i c a t i n g t h e y " a g r e e a lot".  E v e n f e w e r c h i l d r e n - o n l y 2 2 % - s t r o n g l y a g r e e that  t h e y f e e l s a f e w a l k i n g a l o n e in their n e i g h b o u r h o o d , s u g g e s t i n g that m a n y of t h e c h i l d r e n w a l k i n g to s c h o o l w a l k with f r i e n d s o r a n adult. H a p p i l y , t h e s e f e a r s d i d not p r e v e n t n e a r l y t h r e e q u a r t e r s of c h i l d r e n f r o m a g r e e i n g that it is e a s y a n d f u n to w a l k .  F i g u r e 4.11  illustrates the c h i l d r e n ' s r e s p o n s e s to p e r c e p t i o n s o f safety.  Figure 4.11 Children's Perceptions of Safety 80 70 60 2  50  J!  • Agree a Lot  5 40  • Agree a Little  Sr  a OS  • Don't Agree  20 in  Traffic  Strangers/Bullies  Walking Alone  Easy and Fun  T h e r e is d i s a g r e e m e n t a m o n g p a r e n t s a b o u t their p a r e n t a l r e s p o n s i b i l i t y to d r i v e their c h i l d r e n to s c h o o l .  Thirty-three percent strongly a g r e e d , 3 2 % s o m e w h a t a g r e e d , a n d  o n l y 1 3 % s t r o n g l y d i s a g r e e d that d r i v i n g their c h i l d to s c h o o l is a n i m p o r t a n t part of their parental responsibility.  H o w e v e r , it is u n c l e a r if r e s u l t s of this q u e s t i o n m a y b e s k e w e d  b y a n interpretation that " m a k i n g s u r e m y c h i l d g e t s to s c h o o l is a n i m p o r t a n t "  parental  responsibility.  DESCRIPTIVE STATISTICS  77  Table 4.3 Summary of Selected Perception of Safety Variables. See Appendix F for complete details.  Sample Size Parent Perceptions Traffic Safety (mean) Stranger/Bullies (mean)  Reasons cited Child Perceptions Traffic Safety (mean) Stragner/Bullies (mean)  B'bank Full Sample 239 33 1=feelsafe 4=don't feel safe  Boundary 34  B'wood 33  Hatzic 20  M'brough 47  Mission 20  Moberly 52  2.12  2.11  2.12  2.3  1.95  2.26  2.2  2.12  2.33  2.11  1.94  2.45  1.95  2.5  2.35  2.33  convenience, easiest daily safety from convenience, convenience, schedule, convenience strangers/bulli convenience, convenience, convenience child's distance convenience , distance es distance , only option preference distance 1=feel safe 3=don't feel safe 1.67  1.57  1.68  1.97  1.7  1.65  1.8  1.67  2  1.91  1.82  2.24  2.2  1.98  1.95  2  4.1.5 Micro-Scale Pedestrian Environment Evaluation  Intersections Valid data were obtained for 192 intersections, exactly half of which are "t" intersections, and half are 4-way. Otherwise, the overall sample of intersections displays little variability among the micro-scale features used in this analysis.  Eighty percent of intersections  are controlled by at least one stop sign, 75% have no crosswalk markings, 85% have no crosswalk signage, and 90% have no pedestrian crossing button. This lack of variation is due to a combination of low variability in the measured characteristics as well as some weaknesses in the sensitivity of the measurement instrument (e.g. no .distinction between 2 way and 4 way stops - discussed further in Chapter 6). Figure 4.12 compares the level of variation among each of the measured intersection elements by illustrating how each potential response is proportionally distributed in the total sample. T h e dominant response for traffic control is a stop sign; the dominant response for both crosswalk markings and crosswalk signage is "none".  DESCRIPTIVE STATISTICS  78  Figure 4.12. Proportional Distribution of Intersection Characteristics The 120.00% -\  level  of  variation  increasessomewhatwhen comparing school  Figure  40.00%  different  neighbourhoods  against  60 00%  the  each 4.13a  other. highlights  that s t o p s i g n s d o m i n a t e 20 00%  the 0 00%  -I  ! '• Traffic Control  ,  '  —  X-Walk Marking  1  '•  intersections  in  all  the n e i g h b o u r h o o d s , with  X-Walk Score  Marlborough  exhibiting  the l o w e s t p r o p o r t i o n of 7 2 % . H a t z i c h a s the g r e a t e s t p r o p o r t i o n of i n t e r s e c t i o n s w i t h n o c o n t r o l at all ( 2 2 % ) , a n d M a r l b o r o u g h h a s the h i g h e s t p r o p o r t i o n of i n t e r s e c t i o n s c o n t r o l l e d b y traffic lights.  F i g u r e 4 . 1 3 b illustrates that the c a t c h m e n t a r e a s of M i s s i o n C e n t r a l a n d  W a l t e r M o b e r l y E l e m e n t a r y S c h o o l s both h a v e a h i g h p r o p o r t i o n of i n t e r s e c t i o n s with p e d e s t r i a n c r o s s i n g s i g n s c o m p a r e d to the o t h e r s c h o o l s .  Figure 4.13a Variation of Traffic Control Features by School  100%  90% 80% 70% 60%  H  • None • Yeild/Traffic C i r c l e l  50%  • Stop S i g n  40%  o Lights  30% 20% 10% 0%  m  Ln  n  J>  ni  DESCRIPTIVE STATISTICS  79  Figure 14.13b Variation of Crosswalk Signage by School 120% 100% • None  r  • 1 of 4  80%  • 1 of 3  it  I  I  • 2 of 4  6000  • 2of3 03CJ4  40% 20% in  0%  Street  a Ail  1 Dm  B'bank Boundary  •  B  BVCDCI  Ifla  Hatzic M'rxirrjugn Mission Moberty  Segments  V a l i d d a t a w e r e o b t a i n e d for a total of 1 9 8 d i s c r e t e s t r e e t s e g m e n t s . A m o n g the m e a s u r e d e l e m e n t s i n c l u d e d in this study, the g r e a t e s t v a r i a t i o n w a s f o u n d in the s t r e e t g r a d e , p r e s e n c e of s i d e w a l k s a n d e x i s t e n c e of buffer b e t w e e n the s i d e w a l k a n d r o a d . T h e p r e s e n c e of traffic c a l m i n g m e a s u r e s v a r i e s a little, with 7 5 % of s e g m e n t s h a v i n g n o traffic c a l m i n g a n d 20%) h a v i n g o n e traffic c a l m i n g e l e m e n t .  T h e r e w a s v e r y little v a r i a t i o n in the total n u m b e r of l a n e s , with  Figure 4.14 Proportional Distribution Characteristics.  of Street Segment 8 6 % having one lane in e a c h d i r e c t i o n .  100%  si  90% 80% 70%  Figure  4.14  is  c o m p a r a b l e to F i g u r e  60%  4.12;  it  illustrates  50% 40%  the  proportional  30%  d i s t r i b u t i o n of different  20%  characteristics  for  10%  e a c h street  0% Lanes  Slope  Traffic Calming  Buffer  segment  Sidewalk  variable. T h e sample DESCRIPTIVE STATISTICS  80  w a s d o m i n a t e d b y s t r e e t s with 2 l a n e s a n d n o traffic c a l m i n g m e a s u r e s . M o s t s t r e e t s h a v e s i d e w a l k o n 1 0 0 % of at l e a s t o n e s i d e of t h e street, w i t h t h e n e x t b i g g e s t g r o u p b e i n g s t r e e t s with n o n e . O v e r half t h e s t r e e t s m e a s u r e d h a d n o buffer, but n e a r l y 2 5 % h a d a buffer o n both s i d e s of t h e street. T h i s figure s h o w s that the s t r e e t g r a d e o r s l o p e w a s t h e v a r i a b l e s h o w i n g the most e v e n distribution.  Figure 4.15a Variation of Sidewalk Coverage by School Figures 4.15a and 4.15b  100% 90%  other  80%  of  70%  • o%  09 5  provide evidence  the  variation  between  schools.  • 1-25% • 26-50%  60%  T h r e e of t h e s e v e n  a 51-75% • 76-99% • 100%  neighbourhoods  30%  are  represented  20%  by only s e g m e n t s  10%  •  0% B'bank  Boundary  withnoorcomplete  n n BWood  Hatzic  M'borough  Mission  sidewalk coverage  Moberly  while  Figure 4.15b Elements  Variation  in the Presence of Traffic  Calming  t w o others  (Boundary  and  Marlborough) 90%  have only a small  80%  amount  70%  that  fall  outside  60%  a  o None |  50%  *  40%  p>  •  ?  this  category.  One  • Two  *  of streets  While  this  isn't a  huge  d i v e r s i t y of  • Three or More  30% 20%  sidewalk coverage,  4-  10% \ 0%  4?  hi  In  1 In  it two  does  create  very  distinct  groups  which  D E S C R I P T I V E S T A T I S T I C S 81  will  contribute to additional variation in the calculation of unique pedestrian friendliness scores. Hatzic Elementary School exhibits the greatest difference from the other neighbourhoods with almost no street segments with complete sidewalk coverage, over 60% without any sidewalk, and 30% with partial coverage. All of the schools have some street segments with some  Figure 4.16a Scores  Distribution  of  Pedestrian  Friendliness  traffic  elements. Hatzic  Both  and  45%  Elementary  40%  have  35% r  Mission Schools several  segments  r  calming  with  3  or  30%  to |  It  more  traffic  calming  25%  measures,  V>  •5  20%  although  Brentwood and Walter  * V  °" 1 5 %  Moberly  10%  highest  5% 0%  have  2  the  proportion  3  of  Walkability Score Ouaitiletl  segments  with  some kind of calming  Figure 4.16b Distribution FriendlinessScores  of  Lowest  Pedestrian  installed.  50%  Variation  45% 40%  \*\<r  in  urban  form was also more  35%  s 30%  pronounced  I  route by route basis.  25%  on  a  ° 20%  Scores  15%  the  10%  s '  based  equal  on  weighting  l 1f  5%  method ranged from  0% 2  3  1.55 to 6.42.  Scores  Lowest Walkability Oii.nlilcil  based weighting lowest score method ranged from 1 to 6.  on the  equal  Figures 4.16a and 4.16b illustrate  the distribution of pedestrian friendliness and lowest pedestrian friendliness scores after  D E S C R I P T I V E S T A T I S T I C S 82  q u a r t i l i n g the s c o r e s . A l t h o u g h the p r o p o r t i o n s of s t u d e n t s in e a c h s c o r e c a t e g o r y a r e similar, the p e d e s t r i a n f r i e n d l i n e s s s c o r e is not a p e r f e c t p r e d i c t o r of the l o w e s t p e d e s t r i a n friendliness score.  Figure 4.17a Pedestrian Friendliness Score Quartiled by School Figures  100.0%  4.17a  and  4 . 1 7 b illustrate h o w t h e  90.0% 80.0%  pedestrianfriendliness  70 0% 60.0%  s  a n d lowest pedestrian  H  friendliness  indices  40.0%  vary  school.  30.0%  Brooksbank  3  50.0%  *  20.0% 10.0% 0 0%  B'Bank  Boundary  B'wood  hi  Hatzic  M'borough  by  highest Mission  of  Moberly  has  the  concentration  low  scores  for  b o t h t h e i n d i c e s with  Figure 4.17b Lowest Pedestrian Friendliness Score Quartiled by School  Walter Moberly the  80% ,  o  1  o  2  • 3 • 4  and  Marlborough  most  have  scores  in  the upper ranges.  A  visual  comparison  between  the  school  pedestrian friendliness i n d i c e s a n d s c o r e s for the  characteristics  in  Figures 4.13 and 4.15 B'Bank  Boundary  B'wood  Hatzic  M'borough  Mission  Moberly  reveals For  some  example,  links. Walter  M o b e r l y a n d M a r l b o r o u g h h a v e a m o n g the h i g h e s t p r o p o r t i o n s of s i d e w a l k c o v e r a g e a n d l o w e s t p r o p o r t i o n s of u n c o n t r o l l e d i n t e r s e c t i o n s .  T h e y a r e a l s o t h e o n l y two s c h o o l s with  DESCRIPTIVE STATISTICS  83  scores in the highest quartiles for pedestrian friendliness.  Table 4.4. Summary of Selected Pedestrian Environment Scores. (For full details s e e Appendix F) Sample Size  Full Sample 239  Pedestrian Low=p6or Environment . pedestrian Scores environment Lowest 2 Highest 6.23 Average Quartiled Score 2.55  B'bank 33 High=good pedestrian environment 2 4.04 1.3  Boundary 34  B'wood 33  :'•  Hatzic 20  M'brough 47  Mission 20  Moberly 52  3.61 4.63  3.89 6.22  2.4  3.5  ". -v  3.15 4.7  3.26 4.67  2.66 4.34  3.5 . 5.83  2.29  2.09  2.2  3.06  '  However, the distribution of street segment scores in a catchment area is not necessarily reflective of the unique walkability scores.  This is because students' homes are often  clustered with some street segments appearing in numerous unique route equations and others (especially the major arterials on the catchment boundaries) appearing in only one or two.  D E S C R I P T I V E S T A T I S T I C S 84  4.2 Brooksbank Elementary School, North Vancouver ( S e e A p p e n d i x F for t a b l e s s u m m a r i z i n g this d a t a . )  B r o o k s b a n k E l e m e n t a r y S c h o o l in the N o r t h V a n c o u v e r S c h o o l District h a s a c u r r e n t e n r o l l m e n t of 3 4 3 s t u d e n t s f r o m  K i n d e r g a r t e n to g r a d e 7.  T h e c a t c h m e n t a r e a is  a p p r o x i m a t e l y 2 . 1 k m f r o m n o r t h to s o u t h , a n d 1.5 k m e a s t to w e s t at its w i d e s t point for a n e s t i m a t e d 2 . 5 k m ; t h e s c h o o l is l o c a t e d in the c e n t r a l - e a s t e r n p o r t i o n of the c a t c h m e n t 2  b o u n d a r y . T h e U p p e r L e v e l s H i g h w a y f o r m s t h e e a s t e r n b o r d e r of t h e c a t c h m e n t a r e a . G r a n d B o u l e v a r d a n d K e i t h R o a d a r e the two l a r g e s t s t r e e t s that a n y c h i l d in this s a m p l e p o p u l a t i o n w o u l d h a v e to c r o s s . K e i t h a c c o m m o d a t e s f a s t - m o v i n g traffic with t w o l a n e s in e a c h d i r e c t i o n ; s o m e i n t e r s e c t i o n s h a v e traffic lights. G r a n d B l v d E a s t h a s o n l y o n e w i d e l a n e in e a c h d i r e c t i o n but traffic m a y b e m o v i n g q u i c k l y g o i n g to o r f r o m h i g h w a y a c c e s s p o i n t s a n d L y n n V a l l e y R o a d . T h e r e is a linear p u b l i c p a r k to t h e w e s t s i d e that s e p a r a t e s G r a n d B l v d E a s t f r o m G r a n d B l v d W e s t ; t h e r e a r e limited p l a c e s for c a r s to cut t h r o u g h the p a r k a r e a w h i c h a r e c o n t r o l l e d b y 4 - w a y s t o p s .  Photo 4.1 Brooksbank Elementary School  DESCRIPTIVE STATISTICS  85  T h e B r o o k s b a n k c a t c h m e n t a r e a is d o m i n a t e d b y s i n g l e f a m i l y h o m e s , a n d is built o n a m o d i f i e d grid pattern of s t r e e t s with a n u m b e r of c u l - d e - s a c s b a c k i n g o n to t h e h y d r o c o r r i d o r b e s i d e t h e h i g h w a y to t h e e a s t of the s c h o o l . T h e r e is a s m a l l i n d u s t r i a l a n d retail district in the s o u t h - e a s t c o r n e r that d o e s not i n t e r s e c t with t h e r o u t e to s c h o o l of a n y c h i l d r e n i n v o l v e d in this study.  B r o o k s b a n k sits at t h e t e r m i n u s of a quiet r e s i d e n t i a l s t r e e t w h e r e t h e e n d of t h e r o a d b e c o m e s the s c h o o l ' s s m a l l p a r k i n g lot. T h e s c h o o l is s e t b e h i n d t h e p a r k i n g a r e a , with a l a r g e p l a y s t r u c t u r e a n d p l a y i n g f i e l d s to t h e s i d e . S e v e r a l i n f o r m a l p a t h w a y s c o n n e c t a d j a c e n t h o u s e s to t h e p l a y i n g f i e l d s , a n d a m u n i c i p a l trail r u n s for s e v e r a l k i l o m e t r e s t h r o u g h t h e c o r r i d o r b e t w e e n t h e r e a r of the s c h o o l a n d t h e U p p e r L e v e l s H i g h w a y .  Figure 4.18 Marked  Brooksbank Elementary Catchment Area with Evaluated Segments  Port / Burrard Inlet  DESCRIPTIVE STATISTICS  86  4.2.1 Demographics and Distance A total of 65 grade 4 and 5 students from Brooksbank submitted signed consent forms to participate in the Action Schools! B C research program (including the walkability survey). Thirty-five (53%) of these responded and live within the catchment boundary.  T h e Brooksbank sample has 20 boys and 15 girls. Two of these are 11 years old, with the rest almost evenly divided between 9 and 10 years. T h e respondents live in relatively high income households; fewer than 20% report earning under $50,000 per year and more than 30% earning over $80,000. The approximate average income falls just above $60,000, compared to approximately $71,000 reported in the 2001 census. There are no households earning less than $30,000.  Likewise household vehicle ownership is high,  with every household owning at least one car, 57% owning 2 cars and over 17% owning 3 or more cars. Over 90% of respondents live within 1.5 km of the school and 3 1 % are within 500 metres.  4.2.2 Travel Behaviour T h e vast majority (66%)  of responding parents indicated their child is driven to school  most of the time, with 26% walking to school. However, the split is reversed for the return from school trip when 51.4% of parents reported their child walks most of the time and only 4 3 % are picked up by vehicle. No children ride a bicycle either to or from school. However, most Brooksbank students would prefer to be active, with 51 % indicating walking as their favourite way to get to school and 9% indicating they prefer to bike. Sixty percent of children indicated they have been encouraged by teachers to use non-motorized travel for coming to school. Short distances between home and school appear to be factors in children walking as nearly 75% of parents either "somewhat" or "strongly" disagreed that the school is too far for their child to walk.  T h e top two reasons cited for using these travel modes were e a s e of scheduling (37%) and convenience (34%), followed by distance and safety from strangers and bullies (23% each).  Personal preference of the child and opportunity for exercise both ranked high  D E S C R I P T I V E S T A T I S T I C S 87  (14% and 17% respectively) while safety from traffic was selected as an influencing factor by only 5.7% of responding parents.  Motorized travel is clearly the predominant choice for household trips with 66% indicating they choose non-motorized travel either never or less than one time per week; 30% use active travel 1-3 times per week.  4.2.3  Perceptions of Safety  Both parents and children at Brooksbank feel their neighbourhood is relatively safe. Only 1 (of 33) parents "somewhat disagreed", and none "strongly disagreed" with the statement that their neighbourhood is a safe place for their child to walk. However, when asked specifically about their child walking to school, this number increased with 26% "somewhat disagreeing" or "strongly disagreeing" that their child is safe from traffic, and 20% either "somewhat" or "strongly" disagreeing that their child is safe from strangers or bullies. Almost half the children agreed "a lot" that they feel safe from cars, with less than 6% disagreeing; significantly fewer felt safe from strangers or bullies, with 20% not agreeing, and 51 % agreeing only a little. Slightly more disagreed with feeling safe walking by themselves.  Despite these apprehensions, two thirds of the children agreed "a lot"  and none disagreed that walking is easy and fun.  Parents were divided regarding driving and their responsibility as a parent; over 60% selected "strongly" or "somewhat" agree; 29% "somewhat disagree"; less than  9%  "strongly" disagreed that driving is an important parental responsibility.  4.2.4 Micro-Scale Pedestrian Environment Evaluation Valid data was collected for 31 discrete street segments, as indicated in Figure 4.18. Most (94%) of the streets were 2 lanes wide - one lane in each direction - with the remaining 2 street segments having 3 lanes. T h e area is quite hilly, and 84% of all segments had at least some slope; 29% had a moderate grade steep and 20% were very steep. Deliberate measures to calm traffic were found on one quarter of the street segments, with 10%  D E S C R I P T I V E S T A T I S T I C S 88  having more than one calming element. Sixty-one percent of streets had sidewalk along the entire length of at least one side, but only 21 % of these (13% of total street segments) have a buffer between the sidewalk and the street.  In the Brooksbank catchment 32 intersections were evaluated. Almost two-thirds of the intersections were 4-way, with the rest being 3-way or "T" intersections.  Ninety-one  percent have either a stop sign or stop lights, but less than 10% have any kind of crosswalk marking either on the roadway or with signage.  D E S C R I P T I V E S T A T I S T I C S 89  4.3 Boundary Community Elementary School, North Vancouver ( S e e A p p e n d i x F for t a b l e s s u m m a r i z i n g this d a t a . )  B o u n d a r y C o m m u n i t y E l e m e n t a r y S c h o o l in the N o r t h V a n c o u v e r S c h o o l District h a s a c u r r e n t e n r o l l m e n t of 2 9 2 s t u d e n t s f r o m K i n d e r g a r t e n to g r a d e 7. c a t c h m e n t a r e a is 2 . 2 k m at its l o n g e s t w i d t h a n d 1.5km  at its t a l l e s t point o r a p p r o x i m a t e l y  2 . 3 k m ; the s c h o o l is l o c a t e d a l m o s t in the c e n t r e of the c a t c h m e n t . 2  T h e oddly s h a p e d  L y n n V a l l e y R o a d is  a m a j o r t h r o u g h - f a r e with traffic e n t e r i n g a n d c o m i n g f r o m the U p p e r L e v e l s H i g h w a y .  A  f e w s t u d e n t s in the s a m p l e p o p u l a t i o n h a v e to c r o s s this r o a d ; traffic lights a r e l o c a t e d at William St. a n d Lynn Valley. 2 9  t h  A v e n u e is a l s o a s i g n i f i c a n t s t r e e t in that the l a n e s a r e  w i d e a n d traffic m o v e s fairly q u i c k l y . T h e r e a r e limited p l a c e s to c r o s s w i t h the 4 - w a y s t o p at W i l l i a m a n d 2 9  t h  b e i n g the m o s t c o n t r o l l e d .  Photo 4.2 Boundary Community Elementary  T h e s c h o o l b u i l d i n g is s i t u a t e d c l o s e to the s i d e w a l k o n a q u i e t r e s i d e n t i a l s t r e e t , with t w o s m a l l p a r k i n g lots at the front a n d s i d e . T h e r e is a l a r g e p l a y a r e a b e h i n d the s c h o o l , i n c l u d i n g a b a s e b a l l d i a m o n d (with n o outfield) a n d a c l i m b i n g a p a r a t u s . T h r e e i n f o r m a l  DESCRIPTIVE STATISTICS  90  p a t h w a y s c o n n e c t f r o m t h e r e a r of t h e p l a y a r e a to a d j a c e n t s t r e e t s , p r o v i d i n g s h o r t c u t s to a d j a c e n t s t r e e t s a n d h o m e s .  T h e B o u n d a r y c a t c h m e n t a r e a is a n e x c l u s i v e l y r e s i d e n t i a l a r e a of s i n g l e f a m i l y h o m e s with a r o u g h grid p a t t e r n i n t e r r u p t e d b y c r e s c e n t s t r e e t s . A s e r i e s of f o r m a l a n d i n f o r m a l p a t h w a y s h o r t - c u t s c o n n e c t t h e c r e s c e n t s t r e e t s r e a s o n a b l y w e l l to t h e a d j a c e n t g r i d ; e x a m p l e s include short cuts between 2 6  t h  Street a n d T e m p e C r e s c e n t , a n d between  Tempe Crescent and Tempe Knoll.  Figure 4.19 Boundary Community Catchment Area  Catchment Area Boundary  .3.1  Demographics and Distance  A total of 5 7 g r a d e 4 a n d 5 s t u d e n t s f r o m  Evaluated  Boundary  street segments:  Observed  s u b m i t t e d s i g n e d c o n s e n t f o r m s to p a r t i c i p a t e in t h e A c t i o n  s h o r t  C u t s  .  S c h o o l s ! B C r e s e a r c h p r o g r a m ( i n c l u d i n g the w a l k a b i l i t y survey).  Thirty-four c o m p l e t e s u r v e y pairs w e r e returned  f r o m s t u d e n t s living w i t h i n the c a t c h m e n t a r e a .  T h e g e n d e r of r e s p o n d e n t s w a s split a l m o s t 6 0 : 4 0 in f a v o u r of g i r l s .  O v e r half t h e c h i l d r e n  w e r e 10 y e a r s o l d at t h e t i m e of the s u r v e y with 4 4 % b e i n g 9 y e a r s o l d , a n d o n l y 1 b e i n g 8  DESCRIPTIVE STATISTICS  91  (likely a child with a birthday late in the year.) The majority of students report living quite close to the school; 44% are less than half a kilometer away, 94% less than a kilometer, and 100% less than 1.5 kilometres.  Income distribution varies dramatically among respondents, with the most frequent response (32%) being $100,000 or greater, but a nearly equal amount reporting household income below $50,000. T h e approximate average income falls just above $60,000, compared to $85,000 in the census. Nearly 20% of households earn less than $30,000, contrasting with Brooksbank where no families were in the bottom two categories. Household vehicle ownership closely follows income; 30% own only one vehicle, 4 1 % have two vehicles, and nearly 30% of households own 3 or more vehicles. There are no households reporting 0 vehicles.  4.3.2 Travel Behaviour Forty-seven percent of the children are driven to school, and only 4 1 % driven home. Active modes of transport (including walking) are the second favourite option at 44%, rising slightly to 50% for the journey home. A s with Brooksbank, many children who are currently driven would prefer to use an active mode of transport; less than 9% indicated that being driven is their favourite way to get to school with the remainder preferring to walk or use another non-motorized mode of travel.  More than three quarters of respondents  indicated that their teacher encouraged them to use non-motorized travel for coming to school, which may be an influencing factor. Eighty percent of parents strongly disagreed that their child's school is too far away to walk or bike, suggesting (not surprisingly) that distance is not the only consideration in travel mode choice. Just under half (46%) of participating families reported using some non-motorized mode of travel for non-school trips one or more times per week.  Parents at Boundary Community cited convenience (38%) and distance (26%) as the top reasons for their travel mode choice, followed by easiest daily schedule (24%). Eighteen percent of parents felt that traffic safety was a significant influence while only 12% felt  D E S C R I P T I V E S T A T I S T I C S 92  that strangers and bullies were a primary influence.  More parents selected opportunity  for exercise and child's preference than safety from strangers and bullies.  4.3.3 Perceptions of Safety and Travel Preferences Most (88%) parents felt their neighbourhood is safe for their child to walk, although traffic was somewhat of a concern to parents, and children were particularly uneasy about strangers and bullies. Less than 6% of children said they "don't agree" to feeling safe from cars, while 24% "don't agree" to feeling safe from strangers and bullies.  Sixty-  eight percent of parents either somewhat or strongly agreed that their child is safe from traffic while walking to school, while over 85% felt the s a m e about safety from strangers or bullies. Despite this concern for their safety, 85% of children agreed "a lot" that it is easy and fun to walk, supporting their stated preferences for walking or cycling to school rather than being driven.  There was no agreement in parental opinion regarding their  responsibility for driving their children to school.  4.3.4 Micro-Scale Pedestrian Environment Evaluation Valid data were collected from 28 discrete street segments as marked in Figure 4.19. Only three (89%) of the street segments measured had more than 2 lanes, each of which had two lanes in each direction.  Street grade varied from flat to steep, but with most  segments having only a slight (61 %) or moderate (21 %) grade. Traffic calming measures were installed on 4 (14%) of the segments, with one segment having two calming elements. Sixty-four percent of the segments had sidewalks along 100% of at least one side, while 32% had no sidewalk at all. A buffer was recorded on only one of the segments with sidewalk.  Valid data were collected from 26 intersections. Three-way T-type intersections dominate the area, comprising over 65% of all intersections surveyed. Over 90% of intersections have some kind of traffic control, but three quarters have no kind of on-road crosswalk marking and only 15% have any lights or signage to designate them as cross-walks. Only two of the intersections surveyed had any kind of button-controlled pedestrian crossing indicator. D E S C R I P T I V E S T A T I S T I C S 93  4.4 Brentwood Park Elementary School, Burnaby (See Appendix F for tables summarizing this data.)  Brentwood Park Elementary School, located in the City of Burnaby has a current enrollment of approximately 400 students from Kindergarten to grade 7.  T h e catchment  area is relatively small, extending 1-5km north-south and 1.2km east-west with an area of 1.9 k m . Brentwood Elementary is in the centre of the catchment, situated on a minor 2  through-street. T h e school backs onto a community park and is surrounded by the back laneway for the residential crescent immediately adjacent. T h e school's website reports a culturally and socio-economically diverse population with 15% of all students receiving English as a S e c o n d Language ( E S L ) instruction.  1  Photo 4.3 Brentwood Park Elementary School  T h e Brentwood catchment area contains a combination of single family and multi-family residences. T h e Brentwood Mall is located at the corner of the catchment area with some high-density residential adjoining it. T h e major streets are in a rough grid pattern, but an area of concentric crescent streets dominates the area to the west of the school.  The  southern part of the Brentwood catchment is industrial (close to the railroad tracks), but no students from the sample live in that area. T h e Lougheed Highway cuts through the  D E S C R I P T I V E S T A T I S T I C S 94  c a t c h m e n t a r e a , but d e v e l o p m e n t to t h e s o u t h of this is p r i m a r i l y c o m m e r c i a l / i n d u s t r i a l ; t h e r e a r e n o s t u d e n t s in t h e s a m p l e that h a v e to c r o s s t h e h i g h w a y . W i l l i n g d o n A v e n u e a n d S p r i n g e r A v e n u e S o u t h a r e b o t h s u b s t a n t i a l t h r o u g h s t r e e t s but t h e y f o r m the b o u n d a r i e s of the c a t c h m e n t a n d n o c h i l d r e n c r o s s t h e s e either.  P a r k e r S t . to t h e north is t h e next  l a r g e s t a n d s o m e c h i l d r e n a r e r e q u i r e d to c r o s s it; it is r e s i d e n t i a l w i t h a h i g h s c h o o l a n d o n e w i d e l a n e of traffic in e i t h e r d i r e c t i o n . I n t e r s e c t i o n s a r e c o n t r o l l e d b y s t o p s i g n s , e x c e p t for traffic lights at S p r i n g e r a n d W i l l i n g d o n .  Figure 4.20 Brentwood Park Elementary Catchment Area  MAP LEGEND Streets: Street N a m e s :  Grand Av  School Location: Catchment A r e a Boundary: Evaluated Street S e g m e n t s : Observed Short Cuts:  m i n i m i unit  4.4.1 Demographics and Distance  A total of 53 g r a d e 4 a n d 5 s t u d e n t s f r o m B r e n t w o o d P a r k s u b m i t t e d s i g n e d c o n s e n t f o r m s to p a r t i c i p a t e in t h e A c t i o n S c h o o l s ! B C r e s e a r c h p r o g r a m . T h i r t y - t h r e e c o m p l e t e s u r v e y p a i r s w e r e r e t u r n e d f r o m s t u d e n t s living w i t h i n t h e c a t c h m e n t a r e a .  T h e g e n d e r d i s t r i b u t i o n is a l m o s t e q u a l l y split w i t h o n l y o n e m o r e b o y t h a n girl a m o n g DESCRIPTIVE STATISTICS  95  respondents. Over 90% of the children are 9 or 10 years old; two (6%) are 11 years old. No children live greater than 1.5km away from school; 15% are less than 500 metres away and 85% are under 1km.  Income distribution is skewed towards the lower end of  the scale with nearly 50% of households earning less than $40,000; a mid-size cluster of households reported income between $50-$69,000 (24%)  and 6%> reported over  $100,000. T h e approximate average for the group is between $45-$50,000, compared to $56,000 reported in the census.  Vehicle ownership is moderate, with 60% of households reporting only one vehicle. Nonetheless, nearly 9% of the households reported 3 or more vehicles.  4.4.2 Travel Behaviour Half of the Brentwood students reported walking to school in the morning, a figure that rises to 58% for the journey home. Forty percent are driven to school, but only 30% picked up by car. T h e remainder selected multiple responses.  Brentwood students also express  a preference for active modes of travel, with 83% reporting walking, bicycling, or another active mode as their favourite way to get to school, and only 12% preferring to be driven. Less than half half indicated their teachers encouraged them to use non-motorized travel to come to school. Travel choice for non-school trips is almost evenly split between never or rarely (<1 time per week), and 3 or more times per week.  4.4.3 Perceptions of Safety and Travel Preferences A strong majority  (85%)  of parents either strongly or somewhat agreed that their  neighbourhood is a safe place for their child to walk, but this changed dramatically when they were questioned about specific dangers for their child walking to school. Only 9% strongly agreed and 55% somewhat agreed that their child is safe from traffic; 12% strongly and 4 7 % somewhat agreed their child is safe from strangers and bullies. Childrens' perceptions of safety were mixed, with feelings of safety from cars almost evenly divided between agreeing a lot, agreeing a little, and not agreeing. Children were  D E S C R I P T I V E S T A T I S T I C S 96  more apprehensive about strangers and bullies with 39% disagreeing that they feel safe, and only 15% agreeing a lot. O n c e again, the children's preferred modes of travel did not reflect any safety concerns, with 67% agreeing "a lot" and 27% "agreeing a little" that it is easy and fun to walk.  There was no agreement in parental opinion regarding their responsibility for driving their children to school. Sixty-four percent strongly disagreed that the school was too far away for their child to walk, while only 3% strongly agree with that statement.  4.4.4 Micro-Scale Pedestrian Environment Evaluation Valid data were obtained for 28 discrete street segments in the Brentwood catchment as marked in Figure 4.20.  Eighty-nine percent have one lane in each direction; two  streets have 4 lanes, and one segment (Willingdon at Brentlawn) has 6 lanes (3 in each direction). The area is relatively flat, with 65% of the segments being flat or having only a slight grade; only 2 segments (7%) were considered steep.  More than one third of  street segments have at least one traffic calming element. Sidewalk coverage is good with 89% of segments having sidewalk on 100% of at least one side; however only 18% of the segments have any kind of buffer.  Valid data were obtained for 28 intersections in the Brentwood catchment area. Fortythree percent of the intersections were 3-way and 57% are 4-way, and over 96% of them have either a stop sign or traffic lights. Only 18% of intersections have any crosswalk marking, half of which (3 intersections) are marked on all legs; there are no pedestrian crossing signs, but 4 intersections do have have a pedestrian crossing button.  D E S C R I P T I V E S T A T I S T I C S 97  4.5 Hatzic Elementary School, Mission ( S e e A p p e n d i x F for t a b l e s s u m m a r i z i n g this d a t a . )  H a t z i c E l e m e n t a r y S c h o o l in M i s s i o n h a s a c u r r e n t e n r o l l m e n t of a p p r o x i m a t e l y 2 5 0 s t u d e n t s f r o m K i n d e r g a r t e n to g r a d e 7. T h e c a t c h m e n t a r e a is o v e r 4 k m l o n g a n d 2 . 2 k m w i d e ; the total a r e a is o v e r 4 . 5 k m , m a k i n g it t h e l a r g e s t c a t c h m e n t a r e a of a n y s c h o o l 2  i n c l u d e d in this s t u d y .  T h e s c h o o l is l o c a t e d in t h e s o u t h - c e n t r a l portion of t h e total  c a t c h m e n t , but is t o w a r d the n o r t h e r n portion of t h e m a i n H a t z i c s e t t l e m e n t . T h e s c h o o l b u i l d i n g is l o c a t e d c l o s e to t h e street o n a m a i n t h r o u g h - r o a d w i t h l a r g e p l a y a r e a s b e h i n d a n d b e s i d e a n d a limited a m o u n t of p a r k i n g in front of t h e s c h o o l . T h e r o a d h a s a g r a v e l s h o u l d e r but n o s i d e w a l k . D e w d n e y T r u n k R o a d is t h e l a r g e s t s t r e e t that c u t s t h r o u g h t h e c a t c h m e n t a r e a , w i t h o n e w i d e l a n e of traffic in e a c h d i r e c t i o n .  Photo 4.4 Hatzic Elementary School  T h e H a t z i c c o m m u n i t y is s o m e w h a t i s o l a t e d f r o m t h e m a i n t o w n of M i s s i o n a n d is e x c l u s i v e l y r e s i d e n t i a l e x c e p t for a m o n a s t e r y a n d o n e s m a l l c o n v e n i e n c e s t o r e . D e v e l o p m e n t is a m i x of s e m i - r u r a l ( m u l t i - a c r e lots with a g r i c u l t u r a l l a n d or w o o d e d a r e a s ) a n d s i n g l e - f a m i l y d w e l l i n g s at s u b u r b a n d e n s i t i e s . T h e r e a r e l o n g e r b l o c k s a n d l a r g e r r e s i d e n t i a l lots t h a n t h e o t h e r s c h o o l s in t h e study, a n d a pattern of m o r e c u r v i l i n e a r a n d d e a d - e n d s t r e e t s .  DESCRIPTIVE STATISTICS  98  Figure 4.21 Hatzic Elementary Catchment Area  4.5.1 Demographics and Distance A total of 4 7 g r a d e 4 a n d 5 s t u d e n t s f r o m H a t z i c E l e m e n t a r y s u b m i t t e d s i g n e d c o n s e n t f o r m s to p a r t i c i p a t e in t h e A c t i o n S c h o o l s ! B C r e s e a r c h p r o g r a m ( i n c l u d i n g the w a l k a b i l i t y survey).  T w e n t y c o m p l e t e s u r v e y p a i r s w e r e r e t u r n e d f r o m c h i l d r e n living w i t h i n t h e  catchment area.  A s p e c i a l i z e d arts p r o g r a m at t h e s c h o o l likely d r a w s s t u d e n t s f r o m  o u t s i d e t h e c a t c h m e n t , but o n l y c h i l d r e n within t h e c a t c h m e n t w e r e i n c l u d e d in the study.  R e s p o n d e n t s i n c l u d e 9 b o y s a n d 11 girls. T h e p o p u l a t i o n is s l i g h t l y y o u n g e r t h a n at the p r e v i o u s s c h o o l s with 6 5 % b e i n g o n l y 9 y e a r s o l d at t h e time of t h e s u r v e y ; 3 0 % w e r e 1 0 y e a r s o l d , a n d 5 % ( o n e s t u d e n t ) w e r e 11. D e s p i t e t h e l a r g e c a t c h m e n t a r e a , 3 0 % of live less than 500 metres from school, and an additional 2 5 % under 1km.  Three students  ( 1 5 % ) live b e t w e e n 2 a n d 2 . 5 k m .  T h e H a t z i c p o p u l a t i o n h a s h o u s e h o l d s reporting in a l m o s t e v e r y i n c o m e b r a c k e t , but o n l y 3 ( 1 5 % ) r e p o r t e d e a r n i n g l e s s t h a n $ 5 0 , 0 0 0 ; 3 0 % fall b e t w e e n $ 6 0 - $ 6 9 , 0 0 0 ; 2 0 % e a r n  DESCRIPTIVE STATISTICS  99  greater than $100,000 per year. T h e approximate average falls between $60-$70,000, compared to $71,500 in the census. Every family has at least one vehicle, with 55% having 2, and 30% having 3 or more vehicles.  4.5.2 Travel Behaviour Travel to school is evenly divided between being driven and active modes.  O n e child  (5%) switches from driving to walking for the afternoon journey. Seventy percent of the children like to be active on the way to school, with only 30% preferring to be driven. Just over half indicated their teacher had encouraged them to walk or bicycle to school.  Over half (55%)  of participating families reported using some non-motorized mode of  travel for non-school trips one or more times per week.  4.5.3 Perceptions of Safety and Travel Preferences Ninety-five percent of parents either strongly (50%) or somewhat (45%) agreed that the Hatzic neighbourhood is a safe place for their child to walk., Although expressions of concern increased slightly when questioned specifically about traffic and strangers/bullies, there remained a strong overall trend of parents feeling their neighbourhood is safe for children to walk; only 10% strongly disagreed that their child is safe from traffic while none strongly disagreed about their child's safety from strangers or bullies. Children showed similarly low levels of concern about traffic, with only 10% not agreeing they feel safe from cars; a higher proportion (35%) are concerned about strangers or bullies. A s before, a very high proportion of children agree it is easy and fun to walk (80% agree a lot; 10% agree a little).  A strong majority of parents either somewhat (45%) or strongly (15%) agree that driving their child to school is an important part of their parental responsibility. Only 25% somewhat or strongly agree that the school is too far for their child to walk or cycle.  DESCRIPTIVE STATISTICS  100  4.5.4 Micro-Scale Pedestrian Environment Evaluation In the Hatzic catchment, valid data were obtained for 23 discrete street segments, as marked in Figure 4.21.  All the streets have only one travel lane in each direction. T h e  area is generally flat (48% of segments), but with some moderate (22%)  and steep  (17%) hills. Seventeen percent of the segments have some traffic calming element, with two segments (including Draper in front of the school having three.  However, sidewalk  coverage is very poor with 65% of streets having no sidewalk, and an additional 13% having no more than 25% sidewalk on either side. Less than 5% of street segments have sidewalk on 100% of at least one side. Data indicate more segments have buffers than have sidewalks (a situation that is by definition impossible); unfortunately it was not possible to return and double check these scores.  Valid data were collected from 23 intersections.  Less than 20% of the surveyed  intersections are 4-way. Stop signs or stop lights are present at 74% of the intersections, although fewer than 10% have any kind of crosswalk marking and only 1 has a pedestrian crosswalk sign. None of the intersections have a pedestrian crossing button.  DESCRIPTIVE STATISTICS  101  4.6 Marlborough Elementary School, Burnaby ( S e e A p p e n d i x F for t a b l e s s u m m a r i z i n g this d a t a . )  M a r l b o r o u g h E l e m e n t a r y S c h o o l is the l a r g e s t s c h o o l in this s t u d y with 1 0 5 0 s t u d e n t s r a n g i n g f r o m K i n d e r g a r t e n to g r a d e 7.  T h e relatively s m a l l c a t c h m e n t a r e a (for t h e  p o p u l a t i o n ) is 2 . 1 k m l o n g by 1 . 5 k m w i d e a n d a total a r e a of 1.9 k m . T h i s r e f l e c t s the 2  h i g h - d e n s i t y r e s i d e n t i a l t o w e r s n e a r the K i n g s w a y R o a d a n d a d j a c e n t M e t r o t o w n M a l l , a s w e l l a s a n influx o f s t u d e n t s f r o m o u t s i d e t h e c a t c h m e n t for t h e F r e n c h i m m e r s i o n program.  T h e s c h o o l p r o p e r t y o c c u p i e s a l m o s t the entire b l o c k s u r r o u n d e d b y R o y a l  O a k , D o v e r , N e l s o n , a n d S a n d e r s . S a n d e r s is t h e o n l y of t h e f o u r b o r d e r s t r e e t s that is not a s i g n i f i c a n t t h r o u g h - f a r e ; the o t h e r s m a y p r e s e n t a b a r r i e r to c h i l d r e n w a l k i n g , a l t h o u g h t h e r e a r e traffic lights at all f o u r c o r n e r s .  K i n g s w a y f o r m s t h e c a t c h m e n t b o r d e r to t h e  s o u t h a n d h a s 2 to 3 l a n e s in e i t h e r d i r e c t i o n ; it c a r r i e s h i g h v o l u m e s of f a s t m o v i n g traffic but n o c h i l d r e n in t h e s a m p l e a r e r e q u i r e d to c r o s s this s t r e e t . T h e s c h o o l b u i l d i n g s a r e s u r r o u n d e d by p l a y i n g f i e l d s a n d s o m e p a r k i n g a r e a s (off of N e l s o n ) . A o n e - w a y street c u t s into t h e p r o p e r t y b e t w e e n R o y a l O a k a n d D o v e r a n d a c t s a s a d r i v e w a y for a d r o p off/pick-up facility. A l t h o u g h l a r g e l y s u r r o u n d e d by a c h a i n - l i n k f e n c e , t h e r e a r e p e d e s t r i a n a c c e s s p o i n t s to t h e s c h o o l y a r d f r o m all s i d e s of t h e b l o c k .  Photo 4.5 Marlborough Elementary School  DESCRIPTIVE STATISTICS  102  T h e M a r l b o r o u g h c a t c h m e n t a r e a h a s a mix of s i n g l e f a m i l y a n d h i g h d e n s i t y r e s i d e n t i a l d w e l l i n g s , a n d is b o r d e r e d by t h e K i n g s w a y R o a d w i t h s o m e s t r e e t - o r i e n t e d retail o n the north side, a n d the large Metrotown s h o p p i n g mall/office/Skytrain c o m p l e x o n the south side. T h e northern c a t c h m e n t b o u n d a r y cuts through D e e r L a k e P a r k . T h e street network is a m o d i f i e d grid with r e a s o n a b l y c o n n e c t e d r o a d s , but m a n y t h r e e - w a y i n t e r s e c t i o n s .  T h e h o r s e - s h o e s h a p e d O a k m o u n t C r e s c e n t ( e a s t of R o y a l O a k ) is b i s e c t e d n o r t h to s o u t h b y a l i n e a r p a r k that c o n n e c t s t h e t w o h a l v e s of t h e c r e s c e n t w i t h a p u b l i c s t a i r c a s e l e a d i n g to the i n t e r s e c t i o n of O a k l a n d / D o v e r a n d R o y a l O a k .  P a t h w a y s from adjacent  multi-family d e v e l o p m e n t s i n t e r s e c t the park, m a k i n g it a w e l l - t r a v e l e d a r e a a n d a p l e a s a n t off-road short cut l e a d i n g a l m o s t directly to the s c h o o l .  4.6.1  Demographics and Distance  A total of 1 5 8 g r a d e 4 a n d 5 s t u d e n t s f r o m M a r l b o r o u g h s u b m i t t e d s i g n e d c o n s e n t f o r m s to p a r t i c i p a t e in the A c t i o n S c h o o l s ! B C r e s e a r c h p r o g r a m ( i n c l u d i n g t h e w a l k a b i l i t y s u r v e y ) . O n l y 4 7 c o m p l e t e p a i r s w e r e r e t u r n e d f r o m s t u d e n t s living w i t h i n t h e c a t c h m e n t a r e a ,  DESCRIPTIVE STATISTICS  103  reflecting the school's French Immersion program.  T h e Marlborough gender balance is split almost 60:40 in favour of boys. Just over half were 10 years old, 44% were 9 years old, and 4% (2 children) were 8 years old at the time of the survey. All of the students in the sample live less than ,1km from school, with 70% being less than 500 metres away. Nearly all income brackets are represented, however over 4 5 % earn less than $40,000 while 67% earn less than $50,000. T h e approximate average income is between $40-$49,000 per year, compared to $48,000 reported in the census. No families report more than 2 vehicles, while nine percent of (4 families) have none, and 57% have only one vehicle.  4.6.2 Travel Behaviour Marlborough has the highest number of students walking to school; 63% walk and only 28% are driven; the number of walkers rises to 70% for the return trip. There is a high latent demand for cycling to school with 13% selecting this as their favourite mode, and only 11% of students preferring to be driven. Only 26% indicated their teachers had ever encouraged them to walk or use some other active mode of travel to get to school, but this may reflect the high number of students already walking within the sample - or the difficulty in discouraging driving to school with a high proportion of the total student population living far outside the catchment.  4.6.3 Perceptions of Safety and Travel Preferences Overall, nearly 85% of responding Marlborough parents somewhat or strongly agreed that their neighbourhood is a safe place for their child to walk. This perception dropped to only 66% when questioning safety from traffic on the way to school, and only 55% for safety from strangers. Many children also reported feeling safe from traffic with 44% agreeing a lot, and 48% agreeing a little. Like their parents, children showed more concern about safety from strangers or bullies; 26% indicated they did not agree with this statement and only 28% agreed a lot. T h e Marlborough students' interest in walking reflects their reported favourite modes of travel to school; only 1 student (2.2%) did not agree that it is  DESCRIPTIVE STATISTICS  104  easy and fun to walk, and 72% agreed a lot.  Despite the high number of children who walk, most parents strongly (33%) or somewhat (37%) agreed that driving their child to school is an important parental responsibility. This raises the question of how this statement was interpreted by some parents; it could have been interpreted as "making sure my child gets to school is an important responsibility as a parent." Over three quarters of parents "strongly disagreed" that it is too far for their child to walk to school, while none "strongly agreed" and less than 7% somewhat agreed.  4.6.4 Micro-Scale Pedestrian Environment Data Valid data were collected from 29 discrete street segments as marked in Figure 4.22. T h e number of lanes demonstrates the diversity of road types within the Marlborough catchment, and thus the various traffic conditions that children must encounter en route to school. Two-thirds (19) of the street segments have only 2 lanes, but 2 1 % (6) have 4 (2 in each direction), 2 segments have 3 lanes, one has 5 and one (on Kingsway) has 6 lanes. T h e topography is generally flat with 65% of segments being flat or a slight grade, 31% moderately steep, and only 1 segment considered very steep. Traffic calming is present on almost one quarter of the segments and sidewalk coverage is very good. Eighty-six percent of street segments have sidewalk on 100% of at least one side; 10% have no sidewalk at all. Buffers are not as prevalent, with 45% of the streets having no buffer, and 14% having a buffer on only one side.  Valid data were collected from 29 intersections in the Marlborough catchment area. Fiftynine percent of the intersections are 3-way intersections and the remaining 4 1 % are 4way.  Ninety-three percent have either a stop sign or stop light, but only 3 1 % have any  kind of crosswalk marking. Only one intersection has any crosswalk signage, but 28% have one or more pedestrian crossing buttons.  DESCRIPTIVE STATISTICS  105  4.7 Mission Central Elementary School, Mission ( S e e A p p e n d i x F for t a b l e s s u m m a r i z i n g this d a t a . )  M i s s i o n Central E l e m e n t a r y S c h o o l h a s a current  enrollment  of 3 0 6 s t u d e n t s  from  K i n d e r g a r t e n to g r a d e 7. T h e c a t c h m e n t a r e a is a p p r o x i m a t e l y 1 . 5 k m l o n g b y 2 k m w i d e with a n a r e a a p p r o x i m a t e l y 2 0 2 k m . T h e s c h o o l is the s c h o o l l o c a t e d t o w a r d the s o u t h 2  e a s t portion of the c a t c h m e n t o n a quiet r e s i d e n t i a l s t r e e t with a s t e e p r a v i n e a n d a c r e e k s e p a r a t i n g it f r o m h o m e s b e h i n d it (on a n d a r o u n d M u r r a y S t r e e t ) .  T h e r e is a s m a l l  p a r k i n g a r e a in front of the s c h o o l , a n d a l a r g e p l a y i n g field i m m e d i a t e l y to t h e s o u t h . A s t e e p s e t of p u b l i c s t a i r s c r e a t e s a c o n n e c t i o n up t h e hill f r o m 2  n d  A v e n u e at W e l t o n ,  directly to the s c h o o l y a r d . A s e c o n d ( m u c h s m a l l e r ) s e t of s t a i r s c o n n e c t s t h e s c h o o l y a r d to h o m e s o n 5  t h  A v e n u e ( E a s t of W e l t o n ) . 7  t h  A v e n u e a n d G r a n d S t r e e t a r e the t w o r o a d s  that m a y p r e s e n t b a r r i e r s to s o m e c h i l d r e n w a l k i n g to s c h o o l . 7  t h  A v e has a combination  of r e s i d e n t i a l a n d c o m m e r c i a l u s e s with o n e to t w o l a n e s in e a c h d i r e c t i o n ( d e p e n d i n g o n the street s e g m e n t ) . f i e l d s north of 7 1  st  A v e a n d r e s i d e n t i a l to the s o u t h .  t h  A v e n u e and 7  G r a n d S t r e e t is of s i m i l a r s i z e w i t h s e v e r a l o u t d o o r p u b l i c p l a y i n g  t h  Traffic lights a r e in p l a c e o n l y at  A v e n u e , but t h e r e a r e s e v e r a l z e b r a - s t r i p e d p e d e s t r i a n c r o s s i n g s in  between.  Photo 4.6 Mission Central Elementary School  DESCRIPTIVE STATISTICS  106  T h e M i s s i o n C e n t r a l c a t c h m e n t a r e a h a s a tight grid pattern of s t r e e t s w i t h p r e d o m i n a n t l y short blocks.  T h e a r e a i n c l u d e s s t r e e t - o r i e n t e d retail a n d m i x e d - u s e d e v e l o p m e n t , a s  w e l l a s s i n g l e a n d multi-family r e s i d e n c e s . It is b o r d e r e d to t h e s o u t h b y the L o u g h e e d H i g h w a y a n d t h e t o w n ' s i n d u s t r i a l port district. T h e terrain i n c l u d e s n u m e r o u s s t e e p hills ( m o s t l y rising f r o m s o u t h to north). T w o s e t s of p u b l i c s t a i r s a r e p a r t i c u l a r l y i m p o r t a n t for t h e s t u d e n t s in this s a m p l e to a c c e s s t h e s c h o o l ; o n e ( d e s c r i b e d a b o v e ) f r o m 2  n d  A v e to  t h e s c h o o l y a r d , t h e o t h e r c o n n e c t i n g t h e w e s t a n d e a s t p o r t i o n s of 1 A v e ( n e a r M a p l e ) . st  Figure 4.23 Mission Central Elementary Catchment Area  4.7.1 Demographics and Distance A total of 6 3 g r a d e 4 a n d 5 s t u d e n t s f r o m M i s s i o n C e n t r a l s u b m i t t e d s i g n e d c o n s e n t f o r m s to p a r t i c i p a t e in t h e A c t i o n S c h o o l s ! B C r e s e a r c h p r o g r a m . O n l y t w e n t y c o m p l e t e p a i r s w e r e r e t u r n e d f r o m s t u d e n t s living within the c a t c h m e n t a r e a , r e f l e c t i n g the F r e n c h I m m e r s i o n p r o g r a m that d r a w s s t u d e n t s f r o m far o u t s i d e the c a t c h m e n t .  T h e s a m p l e i n c l u d e s n e a r l y t w i c e a s m a n y girls a s b o y s .  Half the children w e r e 10  y e a r s o l d at the t i m e of t h e s u r v e y a n d a n o t h e r 4 5 % w e r e 9 y e a r s o l d ; o n l y 1 w a s 8. A l l r e s p o n d e n t s live l e s s t h a n 2 k m f r o m s c h o o l , w i t h 2 0 % b e i n g l e s s t h a n 5 0 0 m , a n d a n a d d i t i o n a l 5 0 % b e i n g l e s s t h a n 1 k m . R e p o r t e d h o u s e h o l d i n c o m e s a r e c l u s t e r e d in high DESCRIPTIVE STATISTICS  107  and low income brackets; 55% earn less than $50,000 per year while 25% earn more than $80,000. T h e approximate average income is $40-$49,000, compared to $49,000 reported in the census. (10%)  Household vehicle ownership reflects this with 2 households  reporting no vehicle and 4 5 % having only one;  5% of households report three  vehicles but none have more than 3.  4.7.2 Travel Behaviour Fifty percent of respondents walk to school, with 4 5 % driving by car and one student (5%) taking a school bus. In contrast to the other 6 schools in the study, the number of children using motorized modes of travel increases for the journey home. Only 30% of respondents walk home, while half are driven and 3 (15%) take a school bus. None reported bicycling or using another active mode of transport for the trip to or from school. However, half of all children use an active mode for at least one of their trips to or from school. This is also the only school sample with a latent demand for being driven to school; 55% of Mission Central children prefer to be driven while only 30% prefer to walk and 15% would like to bicycle or use another active mode. Seventy-five percent of students indicated their teachers had never encouraged them to use an active mode of travel to get to school - a factor again (like Marlborough) potentially influenced by the large proportion of the school population that travels long distances to attend the French Immersion program.  Somewhat reflecting travel mode to school, 50% of parents indicated they never or rarely (<1 time per week) use a non-motorized mode for non-school trips. Thirty-five percent use an active mode 1-3 times per week, and 3 families (15%) indicate using an active mode 4 or more times per week (reflecting the 2 families who do not own any vehicles).  4.7.3 Perceptions of Safety and Travel Preferences Seventy-five percent of parents somewhat or strongly agree that their neighbourhood is a safe place for their child to walk, and nearly as many (70%) believe their child is safe from traffic. The strong and somewhat agreement of safety drops to only 60% when considering strangers and bullies. The children's perceptions of safety reflect their parent's views with  DESCRIPTIVE STATISTICS  108  only 25% disagreeing that they feel safe from traffic, and 35% disagreeing about safety from strangers or bullies. Despite the stated preference for being driven to school, only one student disagreed that it is easy and fun to walk; 70% strongly agreed.  Parents opinions were completely divided on whether driving their child to school is an important responsibility, with strong opinions each garnering a 20% response, and the "somewhat" opinions each 30%.  However, most parents (80%)  either somewhat or  strongly disagreed that they live too far from school for their child to walk.  4.7.4 Micro-Scale Pedestrian Environment Data Valid data were obtained from 30 street segments as marked in Figure 4.23. volume streets with only 2 lanes represent 25 (83%)  Small-  of the segments measured; 4  segments have 3 lanes and 1 segment (on Grand Street) has 4 lanes. T h e topography is mostly flat and slight grade (67%), but with several moderate (17%) and steep hills. Twenty percent of segments have at least one traffic calming measure.  (17%)  Just over  half the segments have 100% sidewalk on at least one side, but the rest have none at all; buffers are present on all but one segment with sidewalks.  Sidewalks are inconsistent,  being present on one block and missing on the next block of the same street.  Valid data were collected from 30 intersections in the Mission Central catchment. Twothirds of the intersections are 4-way, and one-third are 3-way; 80% of the intersections are controlled a stop sign.  Marking of crosswalks is inconsistent among the sampled  intersections; 4 3 % have no markings, 13% have markings on all legs. Crosswalk signage is similarly varied, although half of the intersections have crosswalk signage on at least one leg. Pedestrian buttons are installed at only 2 of the intersections - both along Grand Street.  D E S C R I P T I V E STATISTICS  109  4.8 Walter Moberly Elementary School, Vancouver ( S e e A p p e n d i x F for t a b l e s s u m m a r i z i n g this d a t a . )  W a l t e r M o b e r l y E l e m e n t a r y S c h o o l in the C i t y of V a n c o u v e r h a s a c u r r e n t e n r o l l m e n t of o v e r 7 7 0 s t u d e n t s f r o m K i n d e r g a r t e n to g r a d e 7.  T h e s c h o o l is v e r y culturally d i v e r s e ,  with 6 9 % of s t u d e n t s e n r o l l e d in E n g l i s h a s a S e c o n d L a n g u a g e ( E S L ) p r o g r a m s a n d 9 3 % living in h o u s e h o l d s w h e r e E n g l i s h is not s p o k e n at h o m e . T h e r e is a s m a l l a s p h a l t p l a y a r e a at t h e front, w i t h p a r k i n g at the s i d e . T h e r e m a i n d e r of t h e b l o c k b e t w e e n R o s s a n d P r i n c e A l b e r t is a m u n i c i p a l p a r k with s e v e r a l p l a y i n g f i e l d s a n d a b a s e b a l l d i a m o n d . T h e c a t c h m e n t a r e a is t h e s m a l l e s t in the s t u d y g r o u p , m e a s u r i n g a p p r o x i m a t e l y  1.2km  f r o m north to s o u t h ( d i s c o u n t i n g the industrial a n d river a r e a to the s o u t h ) a n d o n l y 1 k m e a s t to w e s t for a total of 1.1 k m . T h e s c h o o l is r o u g h l y in the c e n t r e of the c a t c h m e n t at 2  the i n t e r s e c t i o n of t w o r e s i d e n t i a l s t r e e t s .  Photo 4.7 Walter Moberly Elementary School  T h e W a l t e r M o b e r l y c a t c h m e n t a r e a is largely c o m p r i s e d of s i n g l e f a m i l y h o m e s , with small commercial/industrial clusters along Knight Street a n d S o u t h E a s t Marine Drive. K n i g h t S t r e e t c o n n e c t s to a b r i d g e c r o s s i n g the F r a s e r R i v e r a n d is a n i m p o r t a n t t r u c k i n g route with h i g h v o l u m e s of h i g h s p e e d traffic.  F r a s e r Street a n d South E a s t Marine are  DESCRIPTIVE STATISTICS  110  l i k e w i s e b u s y , but with f e w e r l a r g e t r u c k s a n d better buffers. F o r t u n a t e l y , f e w s t u d e n t s in t h e s a m p l e a r e r e q u i r e d to travel a l o n g or c r o s s a n y of t h e s e t h r e e r o a d s .  Figure 4.24 Walter Moberly Elementary Catchment Area  MAP LEGEND Streets: Street Names:  G r a n d Av  School Location: Catchment Area Boundary Evaluated Street Segments: Observed  t  Short Cuts:  4.8.1 Demographics and Distance A total of 119 g r a d e 4 a n d 5 s t u d e n t s f r o m W a l t e r M o b e r l y s u b m i t t e d s i g n e d c o n s e n t f o r m s to p a r t i c i p a t e in t h e A c t i o n S c h o o l s ! B C r e s e a r c h p r o g r a m ( i n c l u d i n g the w a l k a b i l i t y s u r v e y ) . Fifty-two c o m p l e t e s u r v e y p a i r s w e r e r e t u r n e d f r o m s t u d e n t s living w i t h i n t h e c a t c h m e n t a r e a . T h e h i g h E S L p o p u l a t i o n at the s c h o o l m a y h a v e a f f e c t e d this r e s p o n s e rate w i t h p a r e n t s u n a b l e to c o m p l e t e the s u r v e y .  T h e s a m p l e i n c l u d e s slightly m o r e girls ( 5 5 % ) t h a n b o y s . T h e i r a g e s r a n g e f r o m 9 to 11 w i t h 9 y e a r o l d s r e p r e s e n t i n g 4 5 % a n d 1 0 y e a r o l d s 4 9 % . A l l s t u d e n t s live v e r y c l o s e to t h e s c h o o l w i t h 5 8 % b e i n g u n d e r 5 0 0 m , 4 2 % b e t w e e n 5 0 0 m a n d 1 k m , a n d n o n e living g r e a t e r t h a n 1 k m f r o m s c h o o l . T h e a p p r o x i m a t e a v e r a g e i n c o m e of r e s p o n d e n t s is b e t w e e n $ 3 0 a n d $ 4 0 , 0 0 0 p e r y e a r , s i g n i f i c a n t l y l o w e r t h a n t h e c e n s u s e s t i m a t e of $ 5 2 , 5 0 0 .  Seventy-  t h r e e p e r c e n t of h o u s e h o l d s e a r n l e s s t h a n $ 5 0 , 0 0 0 p e r y e a r , a n d 2 7 % e a r n l e s s t h a n $20,000.  T h r e e of t h e r e s p o n d i n g h o u s e h o l d s (6%) e a r n m o r e t h a n $ 8 0 , 0 0 0 p e r y e a r .  V e h i c l e o w n e r s h i p is h i g h e r t h a n m i g h t b e e x p e c t e d g i v e n t h e i n c o m e d i s t r i b u t i o n . O n l y 1 h o u s e h o l d h a s n o v e h i c l e , 5 3 % h a v e 1, a n d 4 1 % h a v e two v e h i c l e s ; t w o f a m i l i e s report three or more vehicles.  DESCRIPTIVE STATISTICS  111  4.8.2 Travel Behaviour Walter Moberly has the second highest proportion of students walking with 57% walking to school and 65% walking home. Thirty-three percent of students are driven to school, and one takes a school bus; this drops to 28% and zero respectively for the afternoon trip. Three quarters of students use an active mode for at least one of the journeys to/from school. T h e children's favourite ways to get to school reflect their actual travel modes with 63% preferring to walk and 29% preferring to be driven; 3 children would prefer to ride their bike or use another active mode to get to school. Half indicated that their teachers had ever encouraged them to use a non-motorized way to get to school.  Household travel habits do not reflect the mode of travel to school with less than one third of respondents indicating their family uses an active mode for a non-school trip at least once per week. T h e lack of amenities such as a grocery store within the catchment area may explain this discrepancy.  4.8.3 Perceptions of Safety and Travel Preferences Over 80% of parents feel their neighbourhood is a safe place for their child to walk. Although specific concern for traffic on the way to school is somewhat higher, 70% of parents still somewhat or strongly agreed that their child was safe, and only 9% strongly disagreed. Half of the children agreed a lot that they are safe from cars, with 35% agreeing a little. Concern about strangers and bullies was more divided among parents, with 65% somewhat or strongly agreeing their child is safe, but 22% strongly disagreeing. Children were divided about feeling safe from strangers and bullies with 39% agreeing a lot but the same number not agreeing.  Only 16% of children agreed a lot that they feel safe  walking by themselves, while 4 5 % did not agree with this statement. Nonetheless, 75% of children still agreed a lot that it is easy and fun to walk, while only 1 did not agree.  Despite the high number of children walking to school at Walter Moberly, 57% strongly agreed and 26% somewhat agreed that driving their child to school is an important parental responsibility. A s discussed for Mission Central, this may reflect a misinterpretation of  DESCRIPTIVE STATISTICS  112  the statement where parents feel that making sure their child gets to school is important (independent of travel mode).  This interpretation may have been particularly prevalent  here with Walter Moberly's high E S L population. Alternatively, these parents may strongly feel they should drive their child to school but they are limited in choice due to vehicle ownership. Only 12% of parents felt they live too far away for their child to walk, with 88% somewhat or strongly disagreeing that their house is too far away.  4.8.4 Micro-Scale Pedestrian Environment Evaluation Valid data were collected from 29 discrete street segments as marked in Figure 4.24. Most (86%) street segments were only two lanes, but the larger streets had 4 (2 segments) and 6 (2 segments) lanes. The land slopes from north to south toward the river, with eastwest streets being reasonably flat. This produced a diverse topographic measure with 66% recorded as flat or slight grade, 24% moderate and 10% recorded as steep. Traffic calming was prevalent with measures on over one third of the streets, including mostly signage and traffic circles. Inverness Street is a north-south bike route for this part of the city, although there is no designated bike lane. Sidewalk coverage is excellent with 90% of sampled street segments having 100% sidewalk on at least one side, and only 3.4% having no sidewalk at all. T h e sidewalk network is supported by buffers on both sides of 79% of the street segments, and on one side for 14% of the segments.  Valid data were collected from 24 intersections in the Walter Moberly catchment area. Sixty-two percent of these are 4-way intersections and 38% are 3-way. Stop signs or traffic lights are present at 92% of the intersections, but only 20% have any kind of crosswalk marking. Twenty-five percent of the intersections have crosswalk signage, in at least one direction, but only 3 (12.5%) of them have a pedestrian crossing button (those located on Fraser, Knight, and S E Marine).  D E S C R I P T I V E S T A T I S T I C S 113  C H A P T E R 5 - ANALYTICAL STATISTICS Chapter 4 illustrated the range and diversity of responses within the study population. This chapter follows with an inferential analysis to determine if and where statistically significant relationships exist between travel behaviour, perceptions of safety, and the micro-scale pedestrian environment while controlling for the demographic variables of gender, age, household income and household vehicle ownership.  Dichotomous Travel Mode Variable For the inferential analysis, travel modes from the travel survey were condensed to create a dichotomous variable. A child was considered "active" if their parent reported that they usually walked, bicycled, or used another form of non-motorized transportation on their trip to school, their trip home from school, or both. (This dichotomous variable is reported in Chapter 4 and Appendix F under the heading "Active Travel".)  This strategy served  an important purpose of highlighting which children were achieving desired behavioural outcomes of daily physical activity and helping to reduce vehicular traffic in the vicinity of schools.  For the reader's reference, Tables 5.1a and 5.1b on the following page provide a glossary of all the variables used in this inferential analysis. Recall that scores used for discrete micro-scale variables in the chi square test represent the average of scores from the segments and intersections along each child's walk to school. T h e pedestrian friendliness and lowest pedestrian friendliness scores for each child represent the sum of the averages for each variable as measured along their route.  ANALYTICAL STATISTICS  114  Table 5.1a Glossary of Variables (Travel Survey)  V A R I A B L E NAME  TYPE AND DESCRIPTION  POSSIBLE V A L U E S  Gender  Dichotomous  Male / Female  Age  Continuous  All between 8 to 11 years old  Distance  Ordinal; distance from home to school based on empirical measure of shortest possible route  1=0-500m 2=500m-1km 3=1 - 1.5km 4=1.5-2km 5= 2-2.5km  Household Income  (HH)  Ordinal; reported by parents in increments of $10,000  1= <$20,000 2=$20-$30,000  9=$90-$100,000 10=>$100,000  Neighbourhood Income  Ordinal; represents Census Canada average income for the catchment areas of each school  Income range assigned s a m e categories as Household Income; s a m e value assigned to all students at the same school  Number of H o u s e h o l d (HH)Vehicles  Ordinal; parents.  0= no cars  reported  by  1=1 car 2=2 cars 3= 3 cars 4= 4 or more cars  Travel Mode  Dichotomous  1 = active mode at least 1 way 0 = no active mode  A N A L Y T I C A L S T A T I S T I C S 115  Table 5.1a Glossary of Variables (Travel Survey)  continued  Parental Perceptions of Safety Neighbourhood is a safe place for child to walk  Ordinal; reported by parents on 4-point Likert Scale  Child is safe from traffic while walking to school  Ordinal; reported by parents on 4-point Likert Scale  Child is safe from strangers/bullies while walking to school  Ordinal; reported by parents on 4-point Likert Scale  Children's Perceptions neighbourhood Feel safe from cars  Feel safe from strangers/bullies  Feel safe alone  walking  of  Safety  while  Ordinal; reported by children on 3-point Likert Scale  Ordinal; reported by children on 3-point Likert Scale  Ordinal; reported by children on 3-point Likert Scale  1 = strongly agree child is safe 4 = strongly disagree child is safe  1 = strongly agree child is safe 4 = strongly disagree child is safe  1 = strongly agree child is safe 4 = strongly disagree child is safe  walking  or  biking  in  their  1 =agree alot they feel safe 3=don't agree they feel safe  1 =agree alot they feel safe 3=don't agree they feel safe  1= agree alot they feel safe 3=don't agree they feel safe  ANALYTICAL STATISTICS  116  Table 5.1b Variable Glossary (Micro-Scale Survey) Variable Name  Rank in Original Data  Standardized Score (Equal Weighting Method)  Number of Lanes  2 3 4 6  lanes lanes lanes lanes  1 0.67 0.33 0  Street Grade  0 1 2 3  -  1 0.67 0.33 0  Traffic Calming  0 1 2 3  elements element elements elements  Buffer  None 1 side both sides  0 0.5 1  Sidewalk (amount on side with longest)  None 1-25% 25-50% 50-75% 75-99% 100%  0. 0.2 0.4 0.6 0.8 1  Traffic Control  None Yeild Traffic circle Stop sign Traffic Light  0 0.5 0.5 1 1  Crosswalk Marking  None 1 of 4 legs 1 of 3 legs 2 of 4 legs 2 of 3 legs 3 of 4 legs All legs  0 0.25 0.33 0.5 0.67 0.75 1  Crosswalk Signage  None 1 of 4 legs 1 of 3 legs 2 of 4 legs 2 of 3 legs 3 of 4 legs All legs  0 0.25 0.33 0.5 0.67 0.75 1  flat slight slope moderate slope steep slope  0 0.33 0.67 1  ANALYTICAL STATISTICS  117  Indexed Scores  How Calculated  Range of Scores  Unique micro-scale variable scores (for each child)  Average of the scores for that variable from all the segments/intersections along that child's route to school.  Ranges from 0 to each variable.  Pedestrian Friendliness Score (Quartiled)  The sum of the unique averaged micro-scale variable scores for the child's route to school.  Ordinal; Ranges from 1 (poor score) to 4 (excellent score) because of quartiling.  Lowest Friendliness  T h e sum of the values for the lowest scoring segment and lowest scoring intersection along the child's route to school.  Continuous; R a n g e s from 1 (worst score) to 6 (least poor score)  Pedestrian  1 for  5.1 Factors Influencing Travel Mode 5.1.1 Determining Relationships A m o n g Independent Variables  T h e first step in the inferential analysis was to understand how groups of variables are interrelated. Demographic data were collected in the parent's travel surveys. correlations between  Strong  demographic variables may influence the selection of control  variables in later regression analysis. Table 5.2 shows the results of a Spearman's Rank Correlation showing the strength and direction of relationship between  demographic  variables. (Spearman's Rank treats the data as ordinals rather than continuous values which best describes the variables in question.) Not surprisingly there is a strong relationship between household income and vehicle ownership, as well a s median neighbourhood income (as reported by the C e n s u s ) and vehicle ownership.  T h e positive correlation  between distance from school and neighbourhood income is merely coincidental since all respondents from the same school were assigned the same neighbourhood income value.  ANALYTICAL STATISTICS  118  Table 5.2 Correlation of Demographic Variables Gender  Age  Distance MOOm)  HH Income  Gender Spearman's .041 .047 .012 Correlation Sig. (2-tailed) .525 .465 .856 Age Spearman's .041 -.036 -.079 Correlation Sig. (2-tailed) .525 .579 .222 D i s t a n c e ( 1 0 0 m ) .047 -.036 .119 Spearman's Correlation Sig. (2-tailed) .579 .465 .066 HH Income Spearman's .012 -.079 .119 Correlation Sig. (2-tailed) .856 .222 .066 Nbhd Income Spearman's .032 .003 .374(**) .188(") Correlation Sig. (2-tailed) .626 .967 .004 .000 HH Vehicles Spearman's .035 -.049 .426(**) .173(") Correlation Sig. (2-tailed) .590 .455 .007' .000 ** Correlation is significant at the 0.01 level (2-tailed).  Table 5.3  Nbhd Income  HH Vehicles  .032  .035  .626  .590  .003  -.049  .967  .455  .188D  .173(")  .004  .007  .374(**)  .426(**)  .000  .000 .365(**) .000  .365(**) .000  describes the results of a Spearman's Correlation between  perceptions of safety. safety variables.  respondents'  It illustrates significant correlations between all the perceptions of  It is not surprising that parents who are concerned about traffic safety  are frequently also concerns about other sources of risk; neither is it surprising that the perceptions of elementary school children are similar to those of their parents.  Finally, demographic and perception of safety variables were correlated.  T h e results in  Table 5.4 demonstrate that parental concerns over traffic safety for their child walking to school increase significantly with the travel distance. They also show that as household income increases, parental perceptions of overall safety and safety from strangers/bullies while walking to school improves. Income is not associated with perception of safety from traffic.  Parents in households with more vehicles are less concerned about their  child's safety from strangers/bullies while walking to school; however this relationship is  ANALYTICAL STATISTICS  119  confounded by the strong correlation between income and vehicle ownership.  Table 5.3. Correlations between perceptions of safety variables. Parents Perceptions  Parent'.? Nbhd  Nbhd Safe  Safe  Safe from  Safe from  Safe from  Safe  to Walk  •from  Strangers/  Cars  Strangers/  Walking  Traffic  Bullies  Bullies  Alone  Perceptions Safe  to  Walk .553(")  .579D  .278(")  .204(**)  .112  .000  .000  .000  .002  .085  ,553(**)  ,525(")  .239(")  .173(**)  .115  .000  .000  .000  .007  .077  S p e a r m a n ' s Correlation S i g . (2-tailed) Safe  from  Traffic  S p e a r m a n ' s Correlation S i g . (2-tailed) Safe from  Children's Perceptions  Strangers/ Spearman's  Bullies  .579(**)  .525(**)  ,238(**)  .300(**)  .151(*)  .000  .000  .000  .000  .020  .278(")  .239(**)  .238(")  .541(")  .274(")  .000  .000  .000  .000  .000  .204(**)  ,173(")  .300(**)  .541(")  .183(")  .002  .007  .000  .000  .004  Correlation S i g . (2-tailed) Children's Safe  Perceptions from  Cars  S p e a r m a n ' s Correlation S i g . (2-tailed) Safe from  Strangers/ Spearman's  Bullies Correlation  S i g . (2-tailed) Safe  Walking  Alone  S p e a r m a n ' s Correlation  .112  .115  .151 (*)  ,274(**)  .183(**)  S i g . (2-tailed)  .085  .077  .020  .000  .004  ** C o r r e l a t i o n is significant at the 0.01 level (2-tailed). * C o r r e l a t i o n is significant at t h e 0 . 0 5 level (2-tailed).  Table 5.4. Correlations Between Demographics and Perceptions of Safety  Nbhd Safety  Traffic  Safety from  Safety  Strangers/ Bullies  Distance  (100m)  S p e a r m a n ' s Correlation  .156(*)  .269(")  .039  S i g . (2-tailed)  .016  .000  .551  S p e a r m a n ' s Correlation  -.1630  -.033  -.154(*)  S i g . (2-tailed)  .011  .612  .017  S p e a r m a n ' s Correlation  -.164(*)  -.065  -.205(")  S i g . (2-tailed)  .011  .319  .001  -.047  .089  -.174(")  .473  .169  .007  HH Income  Nbhd Income  HH Vehicles S p e a r m a n ' s Correlation S i g . (2-tailed)  ** C o r r e l a t i o n is significant at the 0.01 level (2-tailed). * C o r r e l a t i o n is significant at t h e 0 . 0 5 level (2-tailed).  ANALYTICAL STATISTICS 120  Measuring the  correlations  between  the  micro-scale measures of the  pedestrian  environment is an important way to illustrate that certain characteristics co-vary in s p a c e . Table 5.5 describes the results of a Pearson's Correlation between the pedestrian environment scores (using the equal weighting method) for the evaluated street segments and their associated intersections. T h e Pearson's Correlation was selected in this case because the pedestrian environment scores are continuous rather than ordinal. (Note: This sample is limited to only 181 segments and intersections because missing data prevented some segments and intersections from being paired.)  Highlighted values  indicate significance of 0.05 or better.  Table 5.5: Correlation Between Micro-Scale Variables Number of Lanes Number of Lanes Pearson R Sig- (P) Slope Pearson R sig. (p) T r a f f i c Calming Pearson R Sig- (P) Buffer Pearson R Sig. (P) Sidewalk Pearson R Sig. (p) T r a f f i c Control Pearson R Sig. (P) Crosswalk Marking Pearson R Sig. (P) Crosswalk Signage Pearson R Sig- (P)  Slope  Traffic Calming  .007 .928  .076 .307  -.095 .202  .120 .109  .092 .217  .132 .077  .098 .191  .181 .015.  .149 .046  .023 .756  .093 .215  .042 .571  .167 .025  .176 .017:  .093 .211  -.058 .435  .126 .092  .143 .055  .162 .029  .238 .001  .109 .143  -.001 .993  -.015 .844  .007 .928  Buffer  Sidewalk  -.224 . . . .002,  Traffic Control  -.077 .301  .076 .307  .120 .109  -.095 .202  .092 .217  .023 .756  -.224 .002  .132 .077  .093 .215  .093 .211  -.077 .301  .098 .191  .042 .571  -.058 .435  .167 .025  .126 .092  .238 .001  -.001 .993  .176  .143 .055  .109 .143  -.015 .844  -.364 .181 .ooo- ' .015  :  -.006 .936  .  .149 .046  ;  017  .  .162 .029  Crosswalk Marking  Crosswalk Signage  -.364 .000  -.006 .936  .555 000  .555 .000  ANALYTICAL STATISTICS  121  This table shows a strong inverse relationship between the lane score and the presence of crosswalk markings (larger streets are more likely to have crosswalk markings).  It  indicates that more continuous sidewalks, more distinct traffic control measures, and the presence of crosswalk markings tend to be found together. A n association between traffic control measures and crosswalk markings may have been obscured by assigning the same score to traffic lights and stop signs.  5.12  Pairwise  Relationships  With Travel  Mode  A Chi Square test was used as a preliminary test of relationships between the dependent and independent variables because it is more appropriate than the correlation for use with a dichotomous variable.  Chi Square indicates whether the relationship  between  variables is significantly non-random, but does not suggest the direction or magnitude of the relationship. Table 5.6 lists the variables analyzed against travel mode with the Chi Square test.  T h e s e Chi Square results give a good indication of which variables might be influential in the next stage of analysis - the binary regression. For example, distance and number of household vehicles will be important control variables, but household income will not. The insignificant relationship with age is due to the small age range of the study population; a study comparing children from a greater diversity of ages may have different results.  Table 5.6 Chi Square relationships with Active / Not Active Travel Mode Independent Variable  Chi Square  Chi Square  Value  Sianificance (D)  54.743 33 221 18.749 6.69? 1.13 2.777  .000 .000 .001 .669 .288 .427  17.856 35.055 17.741  .000 .000 .000  DemoaraDhics  Parent  Distance (100m) Distance (500m) # HH Vehicles HH Income Gender Ane PerceDtions of Safetv Neighbourhood Safety From Traffic From Strangers/Bullies  ANALYTICAL STATISTICS  122  Table 5.6 Chi Square relationships with Active / Not Active Travel Mode (continued) Children's  Perceotions  of Safetv From Cars From Strangers/Bullies Walkina Alone Micro-Scale Variables Lane Score Traffic Calming Score Sidewalk Score Crosswalk Marking Score Crosswalk Signage Score Slope Score Buffer Score Traffic Control Score  11.OBS 1.978 9.643  .004 .37? 008  37.884 64.036 67.143 65 560 55.319 79.603 32.842 23.935  .025 .009 .000 .057 .009 121 .167 .121  Segment Index Ouartiled Intersection Index Ouartiled Pedestrian Friendliness Index  7.189 14.795 12.008  .066 .002 .007  14.519 12.863 17.109  .002 .005 .001  Ouartiled Lowest Segment Ouartiled Lowest Intersection Ouartiled Lowest Pedestrian Friendliness Ouartiled  T h e pedestrian friendliness index was recalculated to remove variables not significant in the Chi square, but this actually decreased the significance of the chi square for pedestrian friendliness so the original quartiled scores were retained as above. A likely explanation for this is that each variable by itself is not highly influential, but when several low-scoring variables appear in one child's score their cumulative impact is enough to make the overall index significant.  For example, a poor buffer score by itself is not enough to be  significant, but when it is accompanied by low scores for cross-walk markings and traffic controls the overall effect becomes significant. This explanation follows the correlations in Table 5.5; it also follows the literature which suggests that pedestrian  environment  characteristics co-vary in space and that they have synergistic effects on the safety and enjoyment of walking. Other modified indices were also tried to increase the weighting of certain variables but none were as significant as those above.  T h e insignificant Chi Square result with respect to household income is contrary to travel choice research among adults. Potential explanations for this are discussed in Chapter 6. ANALYTICAL STATISTICS  123  5.1.3  Creating  a Statistical  Model - Binary  Regression  Analysis  T h e Chi Square test indicated whether or not relationships between two variables are random or not, but only when the variables are considered independently of one another. In order to calculate the degree to which independent variables explain whether children walk or not, and how these variables interact with each other, it is necessary to conduct a regression analysis. Logistic regression was selected because of its ability to deal with non-linear relationships among variables that do not fit along a normal curve (both of 1  which are the c a s e with this dataset). A binary  logistic regression (where the dependent  variable has only two possible values - active or not) was used because it will compare the relative influence of each explanatory variable on the probability of a "successful" outcome - in this c a s e the outcome that a child is active on their way to or from school. 2  Binary logistic regression models were run in S P S S using different combinations of variables, in particular testing the influence of the various pedestrian environment indices in combination with all the demographic and perceptual variables. Table 5.7 presents the result of tests using the pedestrian friendliness index (quartiled) and the lowest pedestrian friendliness index (which was more significant than in its quartiled form). A few definitions are appropriate here to help explain the tests results.  .  T h e B is the regression coefficient.  .  The  odds ratio (OR) is the exponentiation of B. In this c a s e the O R is used to  predict the how much the odds of a child walking will change for a one unit change in that variable.  .  The  95% Confidence Intervals (Cl) for the odds ratio indicate the range within  O R could fall for the true population mean.  A C l that crosses 1 (i.e. the lower  estimate is <1 and the upper estimate is >1) indicates that the variable is not a good predictor for whether or not a child will walk to s c h o o l .  •  The  3  Hosmer and LemeshowTest is a measure of "goodness of fit" of each model. ANALYTICAL STATISTICS  124  A good model is indicated by a high significance (p) value; if the p-value is less than 0.05 then the model does not adequately fit the data.  The  4  Model Summary Statistics provide similar information to the R value in 2  multiple linear regression. T h e C o x & Snell R Square and Nagelkerke R Square 5  present (respectively) upper and lower estimates of how much variance the model can account for.  6  Model #2 has a Hosmer and Lemmeshow significance score  of 0.899, indicating the model is a good fit for the data. T h e R square measures suggest this model can account for between 28% and 38% of the variation in active versus non-active travel.  Classification tables compare the observed values to those that would be expected if the model was a perfect predictor. They indicate the proportion of c a s e s for which the model makes an accurate prediction. In comparison, a no-model estimate is based on which outcome (walk or not) is the most prevalent in the sample. In this case, in the absence of knowledge of other predictors, predictions that a child will walk are expected to be accurate 63% of the time because 63% of the children in the study sample are active.  Results of the classification tables are listed as  "Model accurately predicts outcome X X % of the time".  ANALYTICAL STATISTICS  125  Table 5.7  Results of Binary Logistic Regression Models  Model #1 (Distance-100m and Demographics)  Gender Age Distance (100m) HH Income Nbhd Income HH Vehicles Constant  B -.147 -.197  Sig. .623 .436  OR .863 .821  -.241 .042 .034 -.471 4.784  .000 .511 .781 .024 .057  .786 1.043 1.034 .624 119.636  95% C. . for OR Lower Upper .480 1.552 .500 1.348 .716 .921 .815 .414  .863 1.181 1.312 .941  Hosmer and Lemeshow G o o d n e s s of Fit Test Chi-snuare 13.956  df 8  Sia. .083  Model Summary -2 Log Cox & Snell Nagelkerke R likelihood R Snuare Sauare 267.547(a) .175 .239 a Estimation terminated at iteration number 5 because parameter estimates changed by less than .001.  Model accurately predicts the outcome 69% of the time.  ANALYTICAL STATISTICS  126  Model #2 (Distance-100m, Demographics, Perceived Safety)  Gender Age Distance (100m) HH Income Nbhd Income HH Vehicles Parent - Nbhd safety Parent - Traffic Safety Parent - Safety from Strangers/ Bullies Child - Safety from Cars Child - Safety from Strangers/ Bullies Child Safe Walking Alone Constant  95% C. for OR Lower Upper .467 1.730 .381 1.160  B -.106 -.409  Sig. .750 .150  OR .899 .665  -.220 .052 -.089 -.609 .010  .000 . .453 .503 .011 .973  .802 1.053 .915 .544 1.010  .725 .919 .705 .339 .572  .888 1.207 1.187 .872 1.782'  -.587  .014  .556  .348  .887  -.533  .038  .587  .355  .970  -.407  .174  .666  .371  1.197  .257  .325  1.293  .775  2.157  -.143  .555  .867  .539  1.393  10.408  .001  33130.216  Hosmer and Lemeshow Test Chi-sauare 3.500  df 8  Sig. .899  Model Summary -2 Log Cox & Snell Nagelkerke R likelihood R Souare Souare .279 235.100(a) .382 a Estimation terminated at iteration number 5 because parameter estimates changed by less than .001.  Model accurately predicts the outcome 76% of the time.  ANALYTICAL STATISTICS  127  Model #3a (Distance-100m, Demographics, Perceived Safety, Pedestrian Friendliness Quartiled)  95% C I for O R B  Sig.  OR  Lower  Gender  -.107  .748  .898  .466  1.730  Age  -.409  .150  .665  .381  1.160  Distance (100m)  -.221  .000  .801  .719  .893  .052  .462  1.053  .918  1.208  Nbhd Income  -.091  .517  .913  .692  1.203  HH Vehicles  -.607  .013  .545  .338  .879  HH Income  Parent  Upper  -  Nbhd  .012  .968  1.012  .571  1.791  Parent -  Traffic  -.587  .014  .556  .348  .887  Strangers/  -.534  .037  .586  .355  .970  -  -.408  .174  .665  .369  1.198  .257  .325  1.294  .775  2.159  -.141  .564  .868  .538  1.402  -.012  .957  .988  .635  1.537  10.454  .001  34687.506  safety • Safety Parent from  Safety  Bullies Child  Safety  from Cars Child  -  from  Strangers/  Safety  Bullies Child  -  Safe  Walking Alone Pedestrian Friendliness (Quartiled) Constant  Hosmer and L e m e s h o w Test df  Chi-sauare 3.951  Sip. 8  .862  Model Summary -2 Log  Cox & Snell  Nagelkerke R  likelihood  R Snuare  Snuare  235.097(a)  .279  .382  a Estimation terminated at iteration number 5 because parameter estimates changed by less than .001.  Model accurately predicts outcome 76% of the time.  ANALYTICAL STATISTICS  128  Model #3b (Distance-100m, Demographics, Perceived Safety, Lowest Pedestrian Friendliness) 95% C. for OR Lower Upper .474 1.770 .383 1.169  Gender Age  B -.088 -.402  Sig. .793 .158  Distance (100m) HH Income Nbhd Income HH Vehicles  -.207 .056 -.072 -.614 -  .001 .425 .599 .011  .813 1.057 .930 .541  .722 .922 .710 .337  .916 1.213 1.218 .869  Parent - Nbhd safety Parent - Traffic Safety Parent-Safety from Strangers/ Bullies Child - Safety from Cars Child - Safety from Strangers/ Bullies Child - Safe Walking Alone Lowest Pedestrian Friendliness Constant  -.013 -.571 -.535  .964 .018 .037  .987 .565 .586  .553 .352 .354  1.761 .907 .969  -.393 .247  .191 .345  .675 1.280  .375 .766  1.217 2.140  -.153 .092  .530 .673  .858 1.096  .532 .715  1.384 1.681  9.858  .003  19105.488  OR .916 .669  Hosmer and L e m e s h o w Test Chi-snuare 4.193  df 8  Sig. .839  Model Summary -2 Log Cox & Snell Nagelkerke R likelihood R Souare Souare 234.921(a) .280 .383 a Estimation terminated at iteration number 5 because parameter estimates changed by less than .001.  Model accurately predicts outcome 76% of the time.  ANALYTICAL STATISTICS  129  Model #4 (Distance-500m, Demographics, Perceived Safety)  Gender Age Distance (500m) HH Income Nbhd Income HH Vehicles Parent Nbhd safety Parent Traffic Safety Parent - Safety from Strangers/ Bullies C h i l d - S a f e t y from Cars C h i l d - S a f e t y from Strangers/Bullies Child Safe Walking Alone Constant  95% C. . for OR Lower Upper .449 1.645 .380 1.143  B -.151 -.418  Sig. .648 .137  OR .860 .659  -.946 .027 -.056 -.661 .030  .000 .692 .672 .006 .918  .388 1.027 .946 .516 1.030  .249 .899 .730 .321 .586  .606 1.175 1.225 .829 1.812  -.593  .013  .553  .346  .882  -.529  .039  .589  .357  .973  -.445  .131  .641  .359  1.142  .288  .264  1.333  .805  2.207  -.137  .568  .872  .545  1.395  10.777  .001  47912.715  Hosmer and Lemeshow Test Chi-souare 2.872 |  df 8  Sio. .942  Model Summary -2 Log Cox & Snell Nagelkerke R likelihood R Snuare Sauare 238.172(a) .270 .370 a Estimation terminated at iteration number 5 because parameter estimates changed by less than .001.  Model accurately  predicts  outcome  76.6%  of the  time.  ANALYTICAL STATISTICS  130  Model #5 (Only variables significant in previous models; Distance-100m)  Distance (100m) HH Vehicles Parent - Traffic Safety Parent - Safety from Strangers/ Bullies Constant  95% O. . for OR Lower Upper .724 .884 .368 .848  B -.223 -.582  Sig. .000 .006  OR .800 .559  -.599  .006  .549  .357  .844  -.500  .025  .607  .391  .940  5.630  .000  278.570  Hosmer and Lemeshow Test Chi-snuare 2.803  df  Sin 8  .946  Model Summary Cox & Snell -2 Log Nagelkerke R likelihood R Souare Souare 241.009(a) .261 .358 a Estimation terminated at iteration number 5 because parameter estimates changed by less than .001.  Model accurately  predicts  outcome  74.5%  of the  time.  Model #6 (Only variables significant in previous models; Distance-500m)  Distance (500m) HH Vehicles  95% C. . for OR Lower Upper .247 .592 .343 .793  B -.961 -.652  Sig. .000 .002  OR .383 .521  -.612  .005  .542  .353  .834  -.485  .030  .616  .397  .954  5.949  .000  383.454  Parent Traffic Safety Parent - Safety from Strangers/ Bullies Constant  Hosmer and Lemeshow Test Chi-snuare 3.094  df 8  Sia. .928  Model Summary -2 Log Cox & Snell Nagelkerke R likelihood R Souare Souare 244.164(a) .252 .344 a Estimation terminated at iteration number 5 because parameter estimates changed by less than .001.  Model accurately  predicts  outcome  76.2%  of the  time. ANALYTICAL STATISTICS  131  T h e s e results show that all the models except for #1 (including only distance and demographic data) have a good fit with the data (Hosmer-Lemeshow Test significance of over p=0.8), but that only distance, vehicle ownership, and parental perception of safety variables provide significant predictive power after controlling for other variables.  Neither  of the pedestrian environment indices was significant when distance from school was included in the equation.  Distance (measured in 100m increments) was consistently the most influential variable in all the tests with increased distance resulting in decreased probability of walking.  Not  surprisingly, distance measured at 500m increments (Model #4) was more significant and has a lower odds ratio (producing a larger change in the odds of walking), but does not significantly change the odds ratios for parental perceptions of safety from traffic or strangers and bullies; it also does not alter the estimated accuracy of predictions.  Although neither the  pedestrian friendliness nor the lowest pedestrian  friendliness  measures were significant after considering distance and household vehicles, lowest pedestrian friendliness had a much lower significance score than pedestrian friendliness. This suggests that a short distance or one intersection of poor walking conditions can influence an overall travel decision (although not significantly after considering other factors).  Another model was applied (not shown in the tables) that tested the effects of including only the extreme values of the sidewalk score. C a s e s in the middle ranges were excluded from the analysis so that n=191. T h e significance of the sidewalk score was p=0.172; a great improvement over the pedestrian environment scores in Models #3a and #3b but still not significant enough to retain in the model. This result is likely affected by the lack of variation in sidewalk scores since the quartiling technique excluded only 48 c a s e s from the sample and 82% of the remaining cases fell in the highest quartile.  ANALYTICAL STATISTICS  132  Making  Predictions  Using  Odds  Ratios  T h e odds ratios from this binary regression c a n be used to estimate the degree to which each significant variable influences travel mode choice. For this purpose, the results from Model #5 were used because this model produced the highest score for the goodness of fit test (p=0.946).  From the odds ratios, it can be deduced that a 100m increase in the  distance between home and school will have an effect of 0.8 on the chance of a child walking to school. In other words, all other things being equal, the odds of walking to or from school for a child living 600m away from school is lower by a factor of 0.8 compared to a child living only 500m from school. Interpreting the odds ratios for all variables in the model, it can be stated that assuming all other variables remain constant, the odds that a child will be active on the way to or from school will decrease by a factor of:  •  0.8 for every additional 100 metres the child lives away from school;  .  0.56 for each additional vehicle in the child's household;  .  0.55 for every unit increase in their parent's concern over safety from traffic; and 0.61 for every unit increase in their parent's concern over safety from strangers and bullies.  T h e s e statements are made assuming the incremental difference is the s a m e for each additional unit of measurement, which is unlikely to be the case. For example, the change in the likelihood of walking will be different as a household decreases from 2 cars to 1 car compared to the change decreasing from 1 to 0 cars.  T h e incremental change in  probability over varying distances may be relatively equal for a limited distance but will drop dramatically after crossing a threshold of (perhaps) a half-hour walking distance (a theory supported by the literature).  Unfortunately this analysis is unable to provide  estimates at that level of detail.  Due to the significant influence of distance in the equation, the sample was divided by this variable for further analysis. Sufficient data were available to conduct a binary regression analysis for three distance categories divided by 500 metre increments from 0 to 1.5 kilometres from school.  Results of this test are described in Table 5.8.  Under  these circumstances, the lowest pedestrian friendliness score was significant (p=.028) for A N A L Y T I C A L S T A T I S T I C S 133  c h i l d r e n in t h e g r o u p living c l o s e s t to s c h o o l . K e e p i n g o t h e r v a r i a b l e s c o n s t a n t , f o r e v e r y o n e unit i n c r e a s e in t h e l o w e s t p e d e s t r i a n f r i e n d l i n e s s s c o r e , a c h i l d ' s o d d s o f w a l k i n g more than doubled ( O R = 2.031).  F o r this g r o u p , p e r c e i v e d s a f e t y f r o m traffic w a s not  influential, b u t p e r c e p t i o n o f s a f e t y f r o m s t r a n g e r s w a s q u i t e i m p o r t a n t ( O R = 0 . 4 1 9 ) , p=0.031).  However, pedestrian environment variables w e r e not significant for a n y other  distance group.  It is a l s o i m p o r t a n t to n o t e that after c o n t r o l l i n g f o r p e r c e p t i o n s o f s a f e t y  a n d the pedestrian environment, the n u m b e r of h o u s e h o l d v e h i c l e s r e m a i n e d significant o n l y f o r c h i l d r e n living within 5 0 0 m e t r e s o f s c h o o l .  Table 5.8 Binary Regression By Distance Distance Controlled Model #1 (Vehicles) 95.0% Cl.for OR Distance <500m (n=95) 500m-1km (n=110) 1-1.5km (n=24)  B  Sig.  OR  -.585  1  .051  .557  Constant  2.452  1  .000  11.615  H H Vehicles  -.422  1  .094  .656  Constant  1.070  1  .022  2.917  H H Vehicles  -.420  1  .469  .657  1  .905  1.156  1  .442  4.000  1  .295  .063  Constant  1.5-2km (n=7)  df  H H Vehicles  .145  HH Vehicles  1.386  Constant  -2.773  Lower  Upper  .310  1.002  .400  1.075  .211  2.048  .117  136.957  Hosmer and Lemeshow Test Distance  Chi-souare  <500m (n=95) 5 0 0 m - 1 km (n=110) 1-1.5km (n=24) 1.5-2km  df  Sin  1.708  1  .191  2.669  1  .102  7.540  2  .023  .000  0  (n=7)  Model Summary  Distance <500m 500m-1km 1-1.5km 1.5-2km  -2 Log likelihood  Cox & Snell R Sauare  Nagelkerke R Sauare  88.432(a)  .039  .063  145.931(b)  .026  .035  30.004(c)  .023  .031  7.777(d)  .082  118  A N A L Y T I C A L STATISTICS 134  Distance Controlled Mode #2 (Vehicles, Perceived Safety) 95.0% C l . for OR Distance <500m n=95  500m-1 km n=110  1-1.5km n=24  B HH Vehicles Parent-Nbhd Safety Parent-Traffic Safety Parent-Safety Strangers/ Bullies Child-Traffic Safety Child-Safety Strangers/ Bullies C h iId-S afe Walking Alone Constant HH Vehicles Parent-Nbhd Safety Parent-Traffic Safety Parent-Safety Strangers/ Bullies Child-Traffic Safety Child-Safety Strangers/ Bullies Child-Safe Walking Alone Constant HH Vehicles Parent-Nbhd Safety • Parent-Traffic Safety Parent-Safety Strangers/ Bullies Child-Traffic Safety Child-Safety Strangers/ Bullies Child-Safe Walking Alone Constant  df  -0.894  Sig 1  .019  OR .409  Lower  Upper  .194  .862  -.027  1  .958  .973  .351  2.698  -.055  1  .894  .947  .422  2.121  .056  .410  .164  1.024  1  .365  1.746  .523  5.836  -.238  1  .631  .788  .299  2.080  -.518  1  .239  .595  .251  1.412  1  .000 .099  386.190 .603  .331  1.099  .150  1  .688  1.161  .560  2.410  -.897  1  .009  .408  .207  .802  .517  .805  .417  1.552  1  .067  .508  .246  1.047  .044  1  .894  1.045  .545  2.003  .160  1  .606  1.173  .639  2.154  1  .001 .310  71.934 .369  .054  2.523  -.634  1  .677  .530  .027  10.454  -2.395  1  .100  .091  .005  1.577  .686  .635  .070  5.753  .273  .282  .029  2.709  .078  10.369  .772  139.308  1  .778  .741  .092  5.969  1  .164  1681.828  -.892 .558  5.956 -.506  1  1  -.217 -.677  4.276 -.996  1  -.455 -1.266  1  2.339 -.300 7.428  ANALYTICAL STATISTICS  135  Hosmer and Lemeshow Test Distance  Sten  <500m  1  11.093  df 8  .196  500m-1km  1  7.635  8  .470  1-1.5km  .1  5.081  8  .749  Chi-snuare  Sig  Model Summary -2 Log  Cox & Snell  Nagelkerke R  likelihood  R Souare  Souare  Distance  Sten  <500m  1  77.604(a)  .143  .230  500m-1km  1  123.958(b)  .202  .273  1-1.5km  1  19.980(c)  .356  .495  Distance = 0-500m: Model accurately predicts the outcome 81% of the time. Distance = 500m-1km: Model accurately predicts the outcome 73.6% of the time. Distance = 1km-1.5km: Model accurately predicts the outcome 75% of the time. Distance Controlled Model #3a (Vehicles, Perceived Safety, Pedestrian Friendliness Quartiled) 95.0% Cl.for OR Distance <500m n=95  B HH Vehicles Parent-Nbhd  Df  Sig.  OR  Lower  Upper  -.866  1  .025  .421  .198  .895  -.176  1  .751  .838  .282  2.493  -.032  1  .940  .969  .424  2.213  -.869  1  .067  .419  .166  1.062  .597  1  .346  1.816  .525  6.288  -.281  1  .576  .755  .282  2.023  -.567  1  .208  .567  .235  1.371  .449  1  .187  1.567  .804  3.053  4.933  1  .003  138.834  1  .089  .592  .323  1.084  .204  1  .588  1.227  .585  2.573  -.879  1  .011  .415  .211  .819  -.221  1  .510  .801  .415  1.549  -.713  1  .055  .490  .236  1.016  .041  1  .902  1.042  .543  1.997  Safety Parent-Traffic Safety Parent-Safety Strangers/ Bullies Child-Traffic Safety Child-Safety Strangers/ Bullies C h i Id - S a f e Walking Alone P e d e s t r i a n Friendliness Ouartiled Constant  500m-1 km n=110  HH Vehicles Parent-Nbhd  -.525  Safety Parent-Traffic Safety Parent-Safety Strangers/ Bullies Child-Traffic Safety Child-Safety Strangers/ Bullies  ANALYTICAL STATISTICS 136  C h i  I  d - S a f e  .205  1  .515  1.228  .662  2.277  .438  1.388  Walking Alone P e d e s t r i a n Friendliness  -.249  1  .397  .779  4.742  1  .001  114.705  -1.042  1  .338  .353  .042  2.977  .083  1  .962  1.086  .036  32.647  -3.461  1  .103  .031  .000  2.023  -1.224  1  .436  .294  .014  6.389  -1.914  1  .170  .148  .010  2.271  3.178  1  .083  24.004  .661  872.122  .516  1  .709  1.676  .111  25.237  .324  .236  .013  4.169  .136  49782.618  Ouartiled Constant  1-1.5km n=24  HH Vehicles Parent-Nbhd Safety Parent-Traffic Safety Parent-Safety Strangers/ Bullies Child-Traffic Safety Child-Safety Strangers/ Bullies C h iI d- S a f e Walking Alone P e d e s t r i a n Friendliness  -1.443  Ouartiled Constant  1  10.815  Hosmer and Lemeshow Test Dist actual nms  Chi-snuare  <500m 500m-1km 1-1.5km  df  Sia.  8.888  8  .352  13.458  8  .097  2.166  8  .976  Model Summary  Dist actual gros <500m 500m-1km 1-1.5km  -2 Log  Cox & Snell  Nagelkerke R  likelihood  R Souare  Snuare  75.818(a)  .159  .255  123.235(b)  .208  .280  18.866(c)  .385  .535  Distance = 0-500m: Model accurately predicts the outcome 79% of the time. Distance = 500m-1km: Model accurately predicts the outcome 73.6% of the time. Distance = 1km-1.5km: Model accurately predicts the outcome 83.3% of the time.  A N A L Y T I C A L S T A T I S T I C S 137  Distance Controlled Model #3b Friendliness Quartiled)  (Vehicles, Perceived Safety, Lowest Pedestrian  9 5 . 0 % C.I. for O R  Distance <500m n=95  B H H Vehicles Parent-Nbhd  df  Sig.  OR  Lower  Upper  -.799  1  .045  .450  .206  .983  -.325  1  .577  .723  .230  2.265  .197  1  .659  1.218  .507  2.925  -1.098  1  .031  .334  .123  .906  .638  1  .333  1.893  .520  6.896  -.259  1  .616  .772  .281  2.120  .230  .570  .227  1.428  1  .028  2.031  1.080  3.819  Safety Parent-Traffic Safety Parent-Safety Strangers/ R u l l i e s Child-Traffic Safety Child-Safety Strangers/ B u l l i e s C h i I d - S a f e  -.563  Walking Alnne LowestPedestrian  .709  .  1  Friendliness Constant  500m-1 km n=110  H H Vehicles Parent-Nbhd  1  .037  37.749  -.552  1  .078  .576  .311  1.064  .215  1  .570  1.240  .590  2.610  -.920  1  .008  .398  .202  .785  -.225  1  .503  .799  .413  1.542  -.735  1  .051  .479  .229  1.005  .086  1  .798  1.090  .563  2.111  .208  1  .513  1.231  .661  2.293  -.268  1  .384  .765  .418  1.399  5.071  1  .002  159.389  -1.005  1  .307  .366  .053  2.523  -.474  1  .785  .622  .021  18.860  -2.510  1  .116  .081  .004  1.852  -.573  1  .659  .564  .044  7.204  -1.370  1  .291  .254  .020  3.231  2.452  1  .099  11.617  .632  213.571  -.209  1  .857  .812  .084  7.859  -.257  1  .851  .774  .053  11.293  8.070  1  .209  3197.485  3.631  Safety Parent-Traffic Safety Parent-Safety Strangers/ B u l l i e s Child-Traffic Safety Child-Safety Strangers/ B u l l i e s C h i I d - S a f e Walking Alone LowestPedestrian Friendliness Constant  1-1.5km n=24  H H Vehicles Parent-Nbhd Safety Parent-Traffic Safety Parent-Safety Strangers/ B u l l i e s Child-Traffic Safety C h iId - S afe t y Strangers/ B u l l i e s C h i I d - S a f e Walking Alone LowestPedestrian Friendliness Constant  ANALYTICAL STATISTICS  138  Hosmer and L e m e s h o w Test Dist actual pros 1.00 2.00 3.00  Sten 1 1 1  Chi-square 6.423 22.628 4.914  df  -2 Log likelihood 72.138(a) 123.199(b) 19.945(c)  Cox & Snell R Sauare .191 .208 .357  8 8 8  Sig. .600 .004 .767  Model Summary  Dist actual arns 1.00 2.00 3.00  Sten 1 1 1  Nagelkerke R Sauare .307 .280 .496  Distance = 0-500m: Model accurately predicts the outcome 83.2% of the time. Distance = 500m-1km: Model accurately predicts the outcome 71.8% of the time. Distance = 1km-1.5km: Model accurately predicts the outcome 79.2% of the time.  A final test was conducted to explore the relationship between distance and pedestrian friendliness scores.  It was hypothesized that children living closer to school would  inherently have higher pedestrian friendliness scores for several reasons. First, school zones are given special treatment with regard to posted speed limits and may also have more pedestrian amenities (particularly sidewalks, traffic calming, and pedestrian crossings) than other areas. T h e routes of children living close to or within these zones could have a higher ratio of pedestrian amenities along their route than those living farther away.  In addition, the majority of schools in the sample are located on quiet residential  streets (Marlborough being a key exception). Secondly, larger more traveled roads must exist somewhere and the farther away a child lives from school, the greater the chance they will encounter one or more of them in their journey to school.  In order to test this hypothesis, a linear correlation was conducted comparing distance (measured in 100m and 500m increments) and both the equal weight and lowest pedestrian friendliness scores.  Table 5.9 indicates the results of these tests.  Significant negative  correlations (p=.000) were found between both measures of pedestrian friendliness and both increments of distance, indicating that as distance increases, the level of pedestrian friendliness decreases.  T h e strongest correlation (R=-585) was between the lowest  pedestrian friendliness score and distances measured in 100m increments. A N A L Y T I C A L S T A T I S T I C S 139  Table 5.9 Distance Correlations with Pedestrian Friendliness Scores 500m Distance and PF Score Ouartiled Pedestrian Friendliness Ouartiled  Distance Distance (500m increments) Pedestrian Friendliness Quartiled  Pearson Correlation  1  Sig. (2-tailed) Pearson Correlation  -.383(**) .000  -.383(**) Sig. (2-tailed)  1  .000  100m Distance and PF Score Quartiled Pedestrian Friendliness Ouartiled  Distance noomi Distance ( 1 0 0 m increments)  Pedestrian Friendliness Quartiled '  Pearson Correlation 1  Sig. (2-tailed) Pearson Correlation  -.366(")  .000 -.366(")  Sig. (2-tailed)  1  .000  500m Distance and Lowest PF Score Quartiled Distance r500m) Distance (500m increments)  Pearson Correlation Sig. (2-tailed)  1  Lowest Pedestrian Friendliness  Pearson Correlation Sig. (2-tailed)  -.543(**) .000  Lowest Pedestrian Friendliness -.543(**) .000 1  100m Distance and Lowest PF Score Quartiled Lowest Pedestrian Friendliness  Distance HOOm) Distance ( 1 0 0 m increments) L o w e s t Pedestrian Friendliness  Pearson Correlation 1 Sig. (2-tailed) Pearson Correlation  .000 -.585(**)  Sig. (2-tailed)  -.585(")  1  .000  A N A L Y T I C A L S T A T I S T I C S 140  5.2 Factors Influencing Parental Perceptions of Safety It is hypothesized that elements of the pedestrian environment may have an influence on how parents perceive the safety of their neighbourhood, which in turn influences their willingness to allow their children to walk to school. T h e first step in testing this hypothesis was to conduct a Chi Square comparing the pedestrian environment indices against the three measures of parental perception of safety (overall neighbourhood safety, safety from traffic while walking to school, safety from strangers while walking to school). T h e only paired comparison for which the Chi Square was significant was the lowest pedestrian friendliness score and parental perception of safety from traffic (p=0.025).  Table 5 . 1 0 : Chi Square Comparing Perceived Safety to Pedestrian Environment Measures S Pedestrian Friendliness Chi Square Value Sig (p) L o w e s t Pedestrian Friendliness Chi Square Value Sig (p)  a  f  e Safe from Traffic  Neighbourhood  Safe From Strgrs/ Bullies  8.815 .455  6.941 .643  118.312 .177  135.201 ,025 1  10.787 .291  ;  112.640 .288  T h e relationship between perception of safety from traffic and the lowest pedestrian friendliness score was explored further using a bivariate correlation.  T h e resulting  correlation coefficient was R = -0.170 (p=0.009). This indicates that as the "lowest" overall pedestrian friendliness score increases, parents are more likely to perceive their child to be safe from traffic while walking to school, although the relationship is not very strong.  Finally, c a s e s in the mid-range of responses ("somewhat agree" and "somewhat disagree") to the three parental perceptions of safety were excluded, leaving samples of n=90, n=78, and n=68 respectively. Successive binary regression analyses were run using the perceptions of safety as the dependent variables and the two indices of the pedestrian environment as the explanatory variables.  O n c e again, the only significant relationship ANALYTICAL STATISTICS  141  was found between the lowest pedestrian friendliness score and parental perception of safety from traffic. T h e results of this regression are shown in Table 5.11. Although the pedestrian environment score was found to be significant at the 0.05 level, the model's classification tables predicts that accuracy will be lower (70.5%) than without the use of the model (71.8%) and only accounts for between 8 and 12% of the variation in the data.  Table 5.11  Binary Regression Measuring the Effect of the Lowest  Pedestrian  Environment Score on the High and Low Perceptions of Safety from Traffic. 95.0%C.l.forOR B  df  OR  Sip.  Lower  Upper  L o w e s t Pedestrian  -.590  1  .017  .555  1.048  1  .207  2.853  .342  .899  Friendliness Constant  H o s m e r and L e m e s h o w Test Chi-souare  df  Sia.  5.930  6  .431  Model S u m m a r y  -2 Log  Cox & Snell  Nagelkerke R  likelihood  R Snuare  Sauare  86.200(a)  .081  .117  5.3 Conclusions Drawn from Statistical Analysis  Chapters 4 and 5 have described the sample population and the pedestrian environments through which they travel to school.  It is known that over 63% of study participants  are regularly active for at least one direction of their home to school journey.  All of the  students live within 2.5 kilometers of school but distance is nonetheless a very important influencing factor on whether they are active or not in their travel to/from school. T h e s e findings are consistent with parental opinion; 28% of parents indicated distance was a primary decision making factor in the mode of travel to school for their child. Regression analysis indicates the number of household vehicles and parental perceptions of safety are also significant factors, but household income is not. "Convenience" and "easiest A N A L Y T I C A L S T A T I S T I C S 142  daily schedule" were selected as primary reasons for travel mode by 38% and 16% of parents respectively. However data on the influence of convenience were not collected in a way conducive to inclusion in the regression analysis. It was encouraging to find a latent demand for non-motorized travel and bicycling in particular; less than 2% of respondents reported bicycling to school but 15% indicated this is their preferred mode of travel. Pedestrian friendliness index of the micro-scale pedestrian environment is not a significant influencing factor, but the "lowest pedestrian friendliness" index is highly significant for children living within a 500m network radius of their school.  For these children, a 1 unit  increase in the lowest pedestrian friendliness score will more than double their odds of walking to or from school.  Household vehicle ownership remains significant after controlling for distance, as does parental perception of safety from traffic. Holding all other factors constant, the odds of a child walking to school decrease by a factor of:  • 0.8 for each additional 100 metres between their home and school, • 0.56 for each additional vehicle in their household, • 0.55 for each unit of increase in their parent's concern over safety from traffic, • 0.61 for each unit of increase in their parent's concern over safety from strangers and bullies.  However, the influence of distance is confounded by the close relationship  between  distance and parental perception of safety, and distance and pedestrian friendliness scores. This demonstrates that distance is more complicated than a simple limitation on a child's physical ability to walk, or even the travel time required to do so.  Finally, the micro-scale characteristics measured in this study do influence  parental  perceptions of their child's safety from traffic while walking to school - specifically the "lowest pedestrian friendliness" street segments and intersections along the route. T h e s e measures do not influence parental perceptions of safety from strangers and bullies, nor  ANALYTICAL STATISTICS  143  do they affect perceptions of overall neighbourhood safety.  T h e initial hypothesis of this study was that micro-scale pedestrian environment variables would influence the use of non-motorized transportation for travel to/from school after controlling for income and vehicle ownership. It was thought that this influence would be heavily modified by distance, perceptions of safety, and convenience. Results indicate that the pedestrian environment is significant for children living within a 500m radius of school, but that the influence of distance masks this factor for children living farther away.  Vehicle ownership and parental perceptions of safety from traffic and strangers  and bullies remain significant across the entire sample. Measures of convenience were not included in the regression analysis, although numerous parents indicated it was a primary decision factor.  T h e next chapter will discuss these findings in the context of the existing travel to school literature.  It will consider why the original hypothesis was not found to be true  after controlling for distance, and will make recommendations for further research to improve understanding of factors influencing travel to school and improve the research methodology.  ANALYTICAL STATISTICS  144  CHAPTER 6 - DISCUSSION AND CONCLUSION "These two variables [of income and vehicle ownership] individually and together may have a strong enough influence on mode choice to overwhelm other factors favouring walk trips, such as short distance to and from school."  Ewing et al., 2004  6.1 Overall Trends A s described in Chapter 4, nearly 50% of children in this study used an active mode of transport en route to school and 56% on the way home for a total of 63.6%  who are active  on a regular basis as part of their journey to or from school. Seventy percent of students living less than a kilometre from school are active, but only 30% who live between 1 and 2.5  kilometres engage in active commuting to school.  T h e s e results are slightly lower  than the national G o for Green study which reported walking among 86% of children living within 1 kilometre and among 50%  of those living within 1 to 3 kilometres.  1  However,  results from the current study are much higher than in the United States where only 30% of students living within one mile (1.6 km) report walking , and in the Gainsville study 2  where fewer than 8% (all distances) were active. There could be many reasons for these 3  differences.  S o m e of the additional walking in the G o for Green study is likely due to  that study's inclusion of children of all ages; older children may be considered more able to walk by themselves, but the (lower) U.S. rates also include all ages so the age range can not explain all the differences. Region-specific variation in climate, average vehicle ownership and personal preferences for walking may play a role. It is also likely that the average pedestrian conditions across the United States are less conducive to walking than the limited variation in the pedestrian environment found within this study's sample, and that different school districts have lower distance thresholds for providing school bus service.  Twenty percent of the sample population - or nearly one-third of students who use an  D I S C U S S I O N A N D C O N C L U S I O N 144  active mode - is active for only one half of their trip; two-thirds of these are active only on the way home, and one-third only on the way to school. This suggests that for these children distance, pedestrian environment, and safety of the route are not barriers to walking to school but that other factors prevent them from being active for both halves of the round-trip. Convenience is one possible factor and was mentioned by 38% of parents as one of the two most important influences on their child's travel mode to school.  A  further 16% cited the related factor of "easiest daily schedule", although respondents were asked to choose two factors so there is some overlap between the two responses. Two studies in the U.K. report that car journeys to school are frequently combined with other trips such as driving to work or dropping off children at multiple locations , which 4  also supports the idea that convenience is a strong influencing factor.  T h e issue of convenience is complex and was not explored in detail in this study. T h e perceived convenience of different travel modes will vary depending on the type of trip and the individual; exploring how different parents define convenience is an important topic for further research. How many parents consider walking convenient? What about parents who drive their children?  Is driving considered more convenient compared to  the child walking by themselves, or compared to walking with the child (in which case safety might actually be the real issue). How do demographics influence the perception of convenience? What about parking conditions at the school?  6.2 Distance Distance between home and school was by far the most significant factor influencing travel mode choice across the entire study sample - a result that supports the extensive literature linking distance to non-motorized transportation choice.  5  Predictions were  made from the odds ratios that suggest for every 100 metre increase in distance between home and school, the odds of that child walking to or from school decrease by a factor of 0.8.  However this outcome should be interpreted with caution. Although the logistic  regression model was selected for its ability to  address non-linear relationships, the  results are presented as linear (i.e. having an equal increment of influence between each  D I S C U S S I O N A N D C O N C L U S I O N 145  unit of the measured variable).  It is more likely in the study sample that each 100 metre  increase in distance has a relatively small impact on the odds of walking for children in relatively close proximity to school, but that the odds of walking change dramatically after certain threshold levels. Other research on children's travel to school suggests that such a threshold distance is around 1km. Results from the current study support this; 69% of 6  students living within a kilometre of their school were considered "active" compared to only 29% of those living more than a kilometre away.  However, this study suggests that  500 is also an important threshold; over 80% of children living less than half a kilometre from school walked to school while less than 60% living between 500m and 1km reported being active.  T h e 500 metre threshold is further supported by the distance controlled  regression analysis which demonstrated that the pedestrian environment has a significant influence on walking to school for children living within 500 metres of school, but that it is not influential for those living farther away.  T h e effect of distance is more complicated than simple physical ability to walk since less than 15% of parents indicated that their child's school was too far from home for them to walk or bike. T h e influence of distance is confounded by strong correlations with both measures of pedestrian friendliness and parental perceptions of safety. Longer distances are associated with lower pedestrian friendliness scores and higher parental perception of risk from traffic; higher perceptions of risk from traffic are also associated with lower pedestrian friendliness scores.  T h e s e relationships are understandable; as distance  increases so does the child's level of exposure, or probability of encountering dangerous traffic conditions (e.g. larger streets) along the way. They suggest that the micro-scale pedestrian environment has a higher influence on the use of active travel modes than what the binary regression indicates, but that the synergistic relationships between the variables results in distance masking the strength of the influence of the pedestrian environment. The influence of distance may also be associated with convenience since greater distances mean longer walking times - a concept that could be explored in further research as discussed above.  D I S C U S S I O N A N D C O N C L U S I O N 146  6.3 Household Income and Vehicle Ownership Contrary to research on adult travel patterns, household income was not found to be significant in this study - in fact it was not significant in the Chi Square test for nonrandomness or in regression models where income was the only explanatory variable. O n e explanation for this is the uncertainty introduced with the high imputation rate for household income.  However, this theory was rejected when after repeating the Chi  Square excluding the imputed c a s e s (n=199) with similarly insignificant results (p=.802). A n alternative explanation could be a prevalence of non-working adults (e.g. a parent or grandparent) living in moderate to high income households who are available to accompany children walking to school.  It could also be that the short home to school  distances in this sample (compared to potential trip lengths to other destinations) have increased the incidence of walking among children from higher income households.  T h e accepted explanation for the relationship between income and travel choice is a c c e s s to vehicles. In this study sample, household vehicle ownership was closely correlated with household income (R= .454, p=.000), and vehicle ownership is significantly associated with non-motorized travel to school. In this respect, a relationship with household income is retained.  Vehicle ownership was found to be significant to travel choice regardless  of distance with every additional vehicle decreasing the odds of walking by a factor of 0.56.  This finding supports Ewing et al. who concluded that vehicle ownership (along  with income) can be enough to overwhelm even the influence of short distances. Similar 7  to distance, it is unlikely that every additional vehicle in the household will have the same incremental influence on the odds of walking to school. Increasing the number of household vehicles from none to one will have a much stronger influence on that household's travel patterns than increasing the number of vehicles from 2 to 3 (particularly if the number of licenced drivers remains constant). Consequently the odds ratios from this model should be interpreted with caution.  6.4 The Influence of the Pedestrian Environment T h e existing literature on children walking to school is inconclusive with respect to the  D I S C U S S I O N A N D C O N C L U S I O N 147  influence of macro-scale variables such as population density; intersection density, and mix of land u s e ; some studies have found some of these to be significant, but others 8  9  concluded that income, distance, and vehicle ownership are overwhelmingly influential.  10  T h e current study hoped to determine whether a stronger relationship existed between children's mode of travel to school and micro-scale elements of the pedestrian environment. Results revealed that the micro-scale characteristics selected for analysis were significant when considering the lowest pedestrian score for children living within half a kilometre of school. Neither index of pedestrian friendliness was significant for other distance groups or in models of the entire sample controlling for distance at 100m or 500m increments.  There are several potential explanations for this. First it appears that 500m is an important threshold distance for walking to school among the children in this sample (as discussed in section 6.2). T h e cause of this threshold is most likely a combination of walking ability, travel time, and parental perception of safety (from traffic and from strangers and bullies). It is likely that after half a kilometre, the influence of these factors combine to overwhelm even a relatively attractive pedestrian environment in the decision to walk to school. S e c o n d , both the pedestrian friendliness scores were significantly negatively correlated with distance between home and school, indicating that higher scores tend to be clustered closer to the schools.  It may be that the threshold level at which the lowest-pedestrian  friendliness score becomes significant lies among the highest scores of the index and that within this sample, this threshold was only crossed within the 500m radius around the school.  Finally the lack of significance of either of the pedestrian friendliness scores in the regression of the entire sample is likely influenced by the variation in the overall sample of the pedestrian environment. T h e school catchment areas in this study are quite small, predominantly residential, and most major roads are located along the boundaries of the catchments. This is a wise decision by the school boards involved as it minimizes the number of students who must negotiate major roads on their way to school.  The  consequence for research is that this also minimizes the variation of pedestrian conditions  D I S C U S S I O N A N D C O N C L U S I O N 148  within a catchment area.  Significant similarities also existed between the catchments  selected related to the predominance of residential uses. Eighty-six percent of the streets had only 2 lanes; 75% had no traffic calming; 80% of all intersections were controlled by stop signs; 75% had no crosswalk markings. There are clearly certain thresholds beyond which the pedestrian environment would be significant deterrents to children walking. This fact is demonstrated by the existence of "hazard bussing" policies where children live close to school but physical dangers stimulate the school board to pay for their transportation.  11  Multiple thresholds may exist (similar to the 500m and 1km thresholds  identified for distance).  Although there may be a threshold passed among the higher  pedestrian friendliness scores found within 500m of the schools, it is likely that a broader diversity of pedestrian environment characteristics would reveal further threshold levels regardless of distance. Increasing the level of variation in the pedestrian environment is an important objective for future research.  Section 5.2.1 highlighted the finding that although s o m e variables were not significant in chi square tests, they made an important contribution to the significance of the overall pedestrian friendliness indices.  It was postulated that this was due to the cumulative  effects of micro-scale variables in creating a pedestrian friendly street-scape and that the tendency for micro-scale environment features to co-vary in space means that single street segments will often exhibit a similar range of scores (high, medium, low) across all variables. This suggests that as the number of micro-scale features in one index increases, so should the gap between high and low scores, thereby increasing the significance. It would be valuable to test this hypothesis through further analysis of the existing dataset by incorporating a broader range of variables into the pedestrian friendliness indices.  In  particular, variables thought to influence safety from strangers and/or crime would be of interest to compliment the current study.  6.5 Perceptions of Safety Five of the six questions on perceptions of safety from children and parents were significant in pair-wise chi square tests (children's perception of strangers and bullies was not), but  D I S C U S S I O N A N D C O N C L U S I O N 149  only two (parental perception of safety from traffic and safety from strangers and bullies) were significant in the regression analysis. Consistent with the literature,  12  parents on  average expressed more concern about strangers and bullies on the way to school than they did about traffic, but in this study concern over traffic and strangers/bullies each have about the s a m e level of influence in the regression. T h e data on perception are worth exploring further; for example this study has not analyzed the children who do use active transportation to determine which of these is accompanied by an adult or sibling which would mitigate safety concerns.  T h e only significant relationship between  perception of safety and the micro-scale  environment was between safety from traffic and the "lowest pedestrian friendliness" score. This makes s e n s e because the pedestrian environment features selected for analysis in this study are more intuitively related to safety from traffic.  Safety from strangers  and bullies was not significant, but that is intuitively more associated with variables such as "eyes on the street" and visible building interiors, presence of graffiti, and building setbacks which were not included in the pedestrian friendliness index. The volume of other pedestrians on the street could also influence perception of safety from strangers and bullies, but this was not measured in the micro-scale survey.  T h e lack of significance with the perceptions of overall neighbourhood safety is interesting to note for the design of future surveys. It may be that parents differentiate between safety in their neighbourhood (which might include their street and those immediately adjoining it) and safety along the entire route between their home and the child's school (which could be substantially farther). Also, perceptions of neighbourhood safety (as phrased in the parental survey) likely include a combination of issues related to traffic and strangers or bullies which would obscure a relationship between perceived neighbourhood safety and admittedly traffic-centric pedestrian environment variables. This differentiation between the neighbourhood and the route to school may also account for the finding that children's perceptions of safety are not significant in the regression analysis. Alternatively, it could simply be that parental opinions consistently overwhelm those of children in travel mode  D I S C U S S I O N A N D C O N C L U S I O N 150  choice decisions.  6.6 Observations on Methods Chapter 3 described the N Q L S micro-scale survey for inventorying features of the pedestrian environment.  W h e n this tool was selected it was known that data obtained  through its use had not been analyzed in a significant way, nor had it ever been tested in the Greater Vancouver region. Research objectives for this study included assessing the utility of the survey tool itself. T h e N Q L S survey had several significant benefits:  1) The survey tool was pre-developed by experts in the field of non-motorized transportation research; . 2) Survey questions covered a very  broad range  of micro-scale urban  form  characteristics thought to influence rates of walking; 3)  R e s p o n s e s were standardized in an objective way that enabled reasonable consistency in data collection across a large number of evaluators;  4)  R e s p o n s e s were coded directly into software on a hand-held computer, thus facilitating data entry;  5)  R e s p o n s e codes were very specific - most were entered in a binary yes/no format. This enables the individual analyzing the data to combine the binary responses to a level of detail suitable for a specific type of analysis while retaining a high level of detail in the raw data.  6) T h e survey is completed by individuals physically walking along each street segment which enables detailed data collection on a scale appropriate for pedestrian travel;  Reflecting on the process of data collection and analysis using this survey, it is clear there are certain limitations to quantifying the micro-scale pedestrian environment.  Despite  the extensive list of questions and possible responses, there are always details that are not fully captured by the survey. Nonetheless, the survey (and others like it) remains a valuable measurement tool that can provide a larger sample of data and a different type  D I S C U S S I O N A N D C O N C L U S I O N 151  of analysis than could be done through more qualitative (e.g. image-based) research methods.  Having said this, the use of the micro-scale survey for this study revealed  s o m e notable limitations. T h e s e are not thought to undermine the quality of the current analysis, but addressing them will improve data quality in future use of the survey tool. There is a high probability that refinements to the data collection and analysis methods will not produce more significant results in a regression analysis in the absence of a much more diverse sample of street types.  1. Road Width and Number of Lanes T h e nature of the micro-scale survey is such that roads with dramatically different driving conditions (and thus different pedestrian environments) can receive very similar combined scores. The number of lanes is the variable with the greatest influence on this problem - an issue that may have arisen due to unique conditions in Greater Vancouver. This region has an abundance of streets that were constructed with only travel lanes but where local by-laws now allow on-street parking. This situation leaves only one functional lane width on streets with two-way traffic.  Vehicles are obviously more constrained than on  streets with two lanes in each direction plus an additional parking lane.  However, both  receive the s a m e score (one lane on each side plus on-street parking). Photos 6.1a, b and c illustrate s o m e streets with identical scores but a different overall look and feel due to their road width.  Photo 6.1a Draper Street in front of Hatzic Elementary School (Mission) has one lane of travel in each direction and no sidewalks. A paved should and adjacent gravel parking strip widen the street significantly for the purposes of crossing, and encourage higher speeds. (Photo: Ren Thomas)  D I S C U S S I O N A N D C O N C L U S I O N 152  Photo 6.1b  Calverhall St. looking  south from Kennard (Brooksbank, North Vancouver). Vehicular travel is allowed in both directions and there is no sidewalk. However, parking on either side of the street restricts the width of travel to only one lane when parking on both sides is utilized. The reduced s p a c e and visibility may singificantly decrease vehicle s p e e d s compared to Photo 6.1a. Pedestrian safety is also compromised by forcing pedestrians to walk directly in the vehicle space. (Photo: Peter Giles)  Photo 6.1c Willet St. is a short d e a d end street in the Hatzic catchment area. It has no sidewalks, allowance for travel in both directions, and on-street parking allowed by municipal by-law. The speed of traffic on this street will be restricted due to its short length. Traffic volumes will also be dramatically lower than Photos 6.1a and b b e c a u s e there are only 2 houses on the street.  A possible solution to this problem is to add an overall road width measure to the survey, and/or a lane width measure - perhaps mid-segment as well as at the intersection.  Road  and lane widths can influence the time required to cross an intersection, the average speed of traffic, and the amount of space available for cyclists.  DISCUSSION AND C O N C L U S I O N  153  2. Traffic Controls at Intersections  T h e survey requires data regarding crosswalk markings, crosswalk signage, and a c c e s s for wheeled mobility aids for each separate leg of an intersection.  This is particularly  useful in Greater Vancouver b e c a u s e there are many intersections where major and minor streets intersect and the crosswalk treatments are different depending which street is being crossed. However the survey only records the type of traffic control once for the intersection rather that for each leg. This makes it unclear whether a stop-sign is 1-way (at a t-intersection), 2-way (at a 4-way intersection), or all-way. T h e Lower Mainland also has a lot of intersections with lights in one direction and stop signs in another. Although the survey allows for recording more than one traffic control device, it is unknown which street crossing has which type of control device. Photos 6.2a and 6.2b illustrate two different intersections that would receive the s a m e traffic control score with the current survey. Photo 6.2c illustrates an intersection controlled by both lights and stop signs.  Photo 6.2a This 4-way intersection in the Walter Moberly catchment has a stop sign only in the north-south direction.  Photo 6.2b This 4-way intersection in the Boundary catchment area has stop signs in all directions. T h e intersections in these two photos differ in other ways (e.g. crosswalk markings) but the difference between the 2way and 4-way stops is the most significant.  D I S C U S S I O N A N D C O N C L U S I O N 154  Photo  6.2c  The  i n t e r s e c t i o n of G r a v e l e y a n d W i l l i n g d o n in t h e B r e n t w o o d catchment illustrates the c a s e ( c o m m o n in G r e a t e r Vancouver) where vehicles t r a v e l i n g o n t h e m a j o r street are controlled by lights ( a c t i v a t e d by a p e d e s t r i a n button), but t h e r e is o n l y a s t o p s i g n for v e h i c l e s at the c r o s s street.  C h a n g i n g the s u r v e y to i n c o r p o r a t e l e g - s p e c i f i c traffic c o n t r o l d a t a s h o u l d not b e difficult s i n c e m o s t o t h e r v a r i a b l e s a r e a l r e a d y c o l l e c t e d at that l e v e l of d e t a i l . T h i s l a c k of d e t a i l r e g a r d i n g traffic c o n t r o l s l e d to a d e c r e a s e d variability of i n t e r s e c t i o n s c o r e s .  Combining  l e g - s p e c i f i c traffic c o n t r o l d a t a with G I S t e c h n o l o g y c o u l d d r a m a t i c a l l y i n c r e a s e t h e s p e c i f i c i t y of route e q u a t i o n s for e a c h c h i l d b y i n d i c a t i n g the e x a c t p o i n t s at w h i c h t h e y c r o s s c e r t a i n s t r e e t s . T h e d r a w b a c k to m o r e d e t a i l e d i n t e r s e c t i o n a n a l y s i s is that it w o u l d b e c o m e m o r e difficult to i m p u t e d a t a b e t w e e n i n t e r s e c t i o n s .  3.  Geo-Reference  Points  T h e s u r v e y tool is l i n k e d to a G e o g r a p h i c a l P o s i t i o n i n g S y s t e m ( G P S ) d e v i c e w h i c h p r o v i d e s g e o g r a p h i c a l c o o r d i n a t e s for t h e l o c a t i o n of e a c h s t r e e t s e g m e n t a n d i n t e r s e c t i o n . T h e c o o r d i n a t e r e f e r e n c e is t a k e n at t h e start of the s e g m e n t a n d a g a i n h a l f w a y t h r o u g h t h e s u r v e y , but it is not c l e a r if t h e s e c o n d r e f e r e n c e is m e a n t to b e at t h e e n d of t h e s t r e e t s e g m e n t . W i t h o u t a b e g i n n i n g a n d e n d r e f e r e n c e point it is i m p o s s i b l e to c o m p a r e c e r t a i n f e a t u r e s of t h e m i c r o - s c a l e s u r v e y .  F o r e x a m p l e , t h e n u m b e r s t r e e t lights, t r e e s , a n d  furniture will v a r y d e p e n d i n g o n s t r e e t s e g m e n t l e n g t h , r e g a r d l e s s of their f r e q u e n c y p e r unit of d i s t a n c e . G I S t e c h n o l o g y w a s not u s e d in t h e c u r r e n t a n a l y s i s s o this o b s e r v a t i o n d o e s not h a v e i m p l i c a t i o n s for t h e quality of r e s u l t s . It s h o u l d b e n o t e d h o w e v e r that this  DISCUSSION AND CONCLUSION  155  additional level of detail (and every additional variable included in the analysis) makes data imputation between street segments more difficult to complete with any accuracy.  4. Fitting the Data to the  Methodology  Previous research on walking for transportation and recreation has assigned unique builtform scores based on average scores for a specific network radius around an individual's home. The current study is the first to examine travel mode choice based on one specific route between the origin and destination. Working at this scale and level of detail, there is a risk that assumptions regarding route choice are too specific for the level of detail available in the data. The lack of leg-specific traffic control information is one example of this where the difference between a 4-way and a 2-way stop on a major street could impact the comfort level of the pedestrian. Another example is that street segment scores were not adjusted to reflect their relative lengths.  Nonetheless, it is believed that the  approach used in this analysis is a good start to understanding the opportunities and limitations of a route-specific scoring system for the pedestrian environment.  Further  refinement of the micro-scale survey tool, combined with effective use of GIS technology will produce more accurate pedestrian environment scores - which may or not may not produce more significant results.  6.7 Summary and Recommendations for Further Research  This study has applied a route-specific research methodology focusing on microscale urban form that is unique within the existing literature on travel choice. Results are consistent with the literature on children's travel, and travel choice in general that distance  13  and vehicle ownership  14  are very significant influences on the choice to use  non-motorized forms of transport. A s in other studies , parental perceptions of safety 15  from traffic and strangers and bullies are also significant influences, but to lesser degree than the influence of distance. Parental perceptions of safety from traffic are significantly associated with the lowest pedestrian friendliness score in this study. Improvements to  D I S C U S S I O N A N D C O N C L U S I O N 156  the micro-scale pedestrian environment may alleviate these fears and increase rates of walking - particularly among children living less than half a kilometre from school.  Previous research on children's travel to school is inconclusive about the overall effect of macro-scale urban form variables on rates of walking ; one recent study on children's 16  travel for all purposes found macro-scale measures to be significant.  17  T h e s e contrasting  results suggest that the non-discretionary nature of the journey to school, and other factors such as the time of day at which it takes place may make the travel to school unique' compared to more discretionary journeys throughout the day. This study found the links between micro-scale variables and children's travel to school to be significant at distances of 500m or less, but may be more significant at longer distance when considering trips for all purposes. T h e literature suggests that the influence of certain variables differs between age g r o u p s . A study sample that includes a broader age range of children is 18  likely to reveal relationships not identified for the age 9 and 10 cohorts.  T h e finding that children's travel to school is influenced by a wide range of variables is consistent with the ecological model of behaviourthat recognizes the overlapping influences of intra- and inter-personal factors, environmental factors, and trip characteristics. This 19  underscores the importance of applying a multi-faceted a p p r o a c h  20  to increasing the  number of children walking to school by simultaneously addressing each of the significant variables to encourage more children to walk to school.  Decreasing the barriers and  increasing the incentives to walk will require complimentary strategies to improve the micro-scale pedestrian environment, alleviate parental safety concerns, and overcome the habitual nature of automobile use.  Further research should aim to find neighbourhoods with a broader diversity of microscale urban form measures to further test the threshold levels of significance for the microscale environment. In addition perception of safety variables and convenience should be explored in more detail to understand how parents define these concepts and the degree to which they influence mode choice for travel to school. Sub-components of safety and  D I S C U S S I O N A N D C O N C L U S I O N 157  convenience include whether a child has an adult or older sibling available to walk with them and the influence of such a chaperone on the decision to use an active travel mode. With respect to convenience, further research should explore the role of trip-chaining before and after school (e.g. to coincide with sports or other extra-curricular activities and the travel needs of other members of the family).  All of these questions could begin to  be explored to some degree with the existing dataset, although refinement of the travel survey and further data collection would also be valuable.  T h e use of this Micro-Scale Survey tool is still quite new and it would be educational to attempt to calibrate it against actual pedestrian safety data and the opinions of various user groups. This could be done using survey methods or focus groups to respond to representative photos; for example asking parents to rate their perceptions of safety for themselves and for their children on street segments and at intersections that manifest different combinations of the measured characteristics. Would they allow or encourage their child to walk in this place?  Calibration could also be conducted by comparing  the intersection scores to actual traffic accident data to see which factors (if any) are empirically linked to accidents. This strategy may improve the scoring system used to develop quantitative scores from the categorical pedestrian environment data.  Finally, the U.S. state and national Safe Routes to School programs have resulted in some studies empirically examining the affect of micro-scale infrastructure improvements on the safety and numbers of children walking to s c h o o l .  21  It would also be valuable from  a public investment perspective to empirically evaluate the outcomes of walk to school programs based more on social-marketing strategies.  6.8 Policy Recommendations T h e intent of this study was to better understand the factors influencing travel mode choice for children's trips to school.  Main policy recommendations arising from this study are  directed at increasing the number of children using non-motorized modes of transportation in some or all of their journey to school. Recommendations are differentially addressed to  D I S C U S S I O N A N D C O N C L U S I O N 158  the 7 schools included in the study and school administrations in general.  To encourage more children to be active en route to school, schools included in this study should:  •  Focus on activities to identify and address perceived safety concerns (as well other issues identified by local parents) that are currently barriers to children walking to school.  •  Identify specific street segments and intersections within a 500m radius of the school to target for infrastructure improvements. T h e s e targets could be based on the "lowest pedestrian friendliness score" utilized in this study.  Where  necessary, work with local municipal governments on the implementation of these infrastructure improvements.  Ensure that the improvements and how  they will make children safer en route to school are communicated effectively to parents of students attending the schools.  School boards and local governments in all jurisdictions should:  •  Apply a multi-faceted approach to encourage more children to be active in traveling to school.  Develop multi-stakeholder committees to discuss the  specific barriers to walking faced by children in each community and apply a combination of institutional, programmatic, and infrastructural tactics to increase rates of walking. •  Require  new  developments  to  include .pedestrian  and  cyclist-friendly  transportation routes from the start, particularly connecting to schools. •  Require the installation of sidewalks, crosswalks, and other pedestrian and cycling amenities in conjunction with any major maintenance projects (such as road resurfacing) to leverage opportunities for retrofits; incorporate the need for pedestrian amenities into criteria for prioritizing such maintenance or retrofit projects.  D I S C U S S I O N A N D C O N C L U S I O N 159  •  Design new  neighbourhoods in a way that maximizes the proportion of  prospective students living within 500 metres of the school, followed by within 1km of the school. •  Incorporate opportunities for children to walk to school into long-term strategic planning for school boards.  This may involve (for example) prioritizing the  preservation of local neighbourhood schools over building larger centralized schools.  Although the 500 metre network radius around schools is the key target for pedestrian environment improvements related to children walking to school, it is reasonable to assume that similar improvements in all residential areas will increase children's non-motorized travel for trips for all purposes.  Local governments are recommended to invest in high-  quality pedestrian micro-scale environments and to require pedestrian amenities in new private developments regardless of proximity to schools or other destinations frequented by children.  Applying the multi-faceted approach advocated by the ecological model of environment,  22  policies to increase the proportion of children walking to school would include a combination of social-marketing  programs and pedestrian infrastructure improvements.  Schools, school boards, and parental advisory committees should advocate for funding and collaborate with local and higher-order governments to achieve these complimentary objectives.  Unfortunately the lack of any national or (excepting  British Columbia)  provincial funding in C a n a d a for safe routes to school programs suggests that lower-cost alternatives are a more immediate priority.  In Toronto the cost of installing new traffic  lights at one intersection is estimated to be $100,000. S u c h an investment may improve walking conditions for a small proportion of children at one school, while the s a m e money could provide a year of funding for a social marketing program that stimulates activities at numerous schools in one jurisdiction and leverages the work of community leaders (police officers, school officials) and parent volunteers. Considering the current funding environment, pursuing social-marketing programs would appear to be the best strategy  D I S C U S S I O N A N D C O N C L U S I O N 160  for the immediate term, while maintaining advocacy efforts to influence the nature of pedestrian environments in existing and new developments.  Finally, there is a moral obligation to protect the safety of children (and adults) already using non-motorized transportation, regardless of the degree to which improved pedestrian infrastructure might increase rates of walking. Despite the decline in recent d e c a d e s in the rates of children walking to school, children and youth still represent the most significant proportion of people using non-motorized transport. In the Greater Toronto Area children and youth account for more than 50% of weekday walking and cycling trips, and over 20% of weekday transit trips. T h e design of any municipal transportation infrastructure project 23  should be evaluated from the perspective of pedestrian safety and convenience.  D I S C U S S I O N A N D C O N C L U S I O N 161  ENDNOTES CHAPTER 1  CHAPTER 2 •  1 Crider and Hall, 2005; Tudor-Locke et al., 2001 2 Gilbert and O'Brien, 2005 3 BC Ministry of Transportation and GVTA, 2005 4 Go for Green, 1998 5 Crider and Hall, 2005 6 Dellinger and Staunton, 1999; Ewing et al., 2005 7 Morris, 2001. 8 Carlin etal., 1998 9 Ewing et al., 2005; Kouri, 1999 10 Ewing et al., 2005 11 Go for Green, 1998 12 Katzmarzyk, 2002; Raine, 2004 13 Frank et al., 2004. 14 USDHHS, 1996; PHAC, 2003 15 Andersen, 2000; Carriere, 2003 16 Bruce and Katzmarzyk, 2002; Craig et al., 1999 17 Tremblay and Willms, 2000 18 Cooper etal., 2003; Cooper etal., 2005; Mackett et al., 2004; Tudor-Locke et al., 2002 19 Heelan et al., 2005 20 Cooper etal., 2003; Cooper etal., 2005; Mackett etal., 2004 21 Mackett et al., 2004 22 USDHHS, 1996 23 ICBC, 2006 24 Agran etal., 1996 25 Mackett et al., 2004; Roerty and Staats, 2002 26 International Centre for Technology Assessment , 2000 27 Canadian Institute of Child Health, 2000 28 Ontario Medical Association, 2005 29 Black et al., 2001 30 Moore, 1986; Tranter, 1995; Tranter and Pawson, 2001 31 David and Weinstein, 1987; Proshansky and Fabian, 1987; Siegel et al., 1978 32 Appleyard, 2005 33 Battistich and Horn, 1997 34 Mackett et al., 2004 35 Armstrong, 1993; Bradshaw et al., 1998 36 Kowie and Kennedy, 2004 37 Boarnet et al., 2005 38 Frank and Engelke, 2000; Frank et al., 2003 39 McMillan, 2005 40 Frank and Engelke, 2000; Frank et al., 2003; Ewing and Cervero, 2002 41 McMillan, 2005; Ewing et al., 2004 42 www.nqls.org  1  Bates, 2000; Hanson, 1995; Meyer and Miller, 1984 2 Frank and PPHEAL, 2006 3 Ibid.; Maat et al., 2005 4 Meyer, 1984 5 Bates, 2000 6 Meyer, 1984 7 Hoehner et al., 2003 8 Meyer and Miller, 1984 9 Sallis et al., 1998; Sallis and Owen, 2002 10 Moudon and Lee, 2003 11 Sallis et al., 1998; Sallis and Owen, 2002 12 Moos, 1980 13 McLeroy et al., 1998 14 Frank, Saelens, et al., forthcoming 15 Moudon and Lee, 2003 16 Ibid. 17 Frank et al., 2006; Handy, 2006 18DiGuiseppi etal., 1998; Eichelberger et al., 1990; McMillan, 2005. 19 Cooper et al., 2003; Heelan et al., 2005; Mackett etal., 2004; Tudor-Locke et al., 2002; -. 20 Kouri, 1999 21 Black etal., 2001; Boarnet et al., 2005; Carlin et al., 1998; Evenson et al., 2003; Ridgewell et al., 2005; Timperio et al., 2004; 22 Ewing etal., 2004 23 Sirard et al., 2005 24 Braza etal., 2004 25 Ibid. 26 Ibid. 27 Sirard et al., 2005 28 Ewing et al., 2004; Kouri, 1999 29 Ewing et al., 2004 30 Ibid. 31 Ibid. 32 Ridgewell et al., 2005 33 Ewing etal., 2005 34 Boarnet etal., 2005 35 Ewing et al., 2005 36 Boarnet et al., 2003; Boarnet et al., 2005 37 Boarnet etal., 2003 38 Ibid. 39 Hess et al., 1999; Murakami and Young, 1997; Pucher and Renne, 2003; Stead, 2001 40 Carlin, 1998; Evenson et al., 2003; Ewing et al., 2005 41 Braza et al, 2005 42 Carlin etal., 1998 43 Black et al., 2001; Carlin et al., 1998; Ewing et al., 2004; Timperio et al., 2004; 44 Timperio et al., 2004 45 Ewing et al., 2004 46 Ibid. 47 Morris et al., 2001 48 Ampt, 1995; Sarkar, 2002;Tranter, 1995; 49 Anderson et al., 2002; Morris et al., 2001; . Preston, 1994 ENDNOTES-162  50 LaScala, 2004 51 Bradshaw, 1995; Dellinger and Staunton, 2002; Timperio et al., 2004; 52 Timperio etal., 2004 53 Appleyard, 2005 54 Godfrey etal., 1998 55 Morris et al., 2001; Informa Market Research, 2001 56 Dellinger and Staunton, 2002 57 Informa Marketing Research, 2001; Bradshaw, 1995 58 Loukaitou-Sideris, 2006 59 Timperio et al'., 2004 60 Frank et al., 2006 61 Frank et al., 2005 62 Zlot and Schmid, 2005 63 Saelens et al., 2003a; Sallis et al., 2004; Frank and Pivo, 1995; Frank and Engelke, 2000; Ewing and Cervero, 2002; Handy et al., 2002 64 Saelens et al., 2003b 65 Frank etal., 2003 p. 119 66 Braza et al., 2004; Ewing et al, 2004 67 Frank, Kerr et al., forthcoming 68 Braza et al. 2004 69 Ewing et al., 2004 70 Braza et al., 2004 71 MacMillan, 2002 72 Gilbert and O'Brien, 2005; Tranter, 1995 73 Ewing et al., 2004 74 Frank, Kerr et al., forthcoming 75 Black et al., 2001; Bradshaw, 1995; Dellinger and Staunton, 2002; Ewing et al., 2004; Go for Green, 1998; Kockelman, 1997; Saelens et al., 2003a; 76 Go for Green, 1998 77 Ibid. 78 Dellinger and Staunton, 1999 79 Go for Green, 1998 80 Black et al., 2001; Ewing et al.,2004; Mackett et al., 2004; Morris etal., 2001 81 Crider and Hall, 2005; Ewing et al., 2004 82 Braza et al.2004; Kouri et al., 1999; Morris et al., 2001 83 Ewing et al., 2004 84 Gilbert and O'Brien, 2005 85 Go for Green, 1998 86 Black etal., 2001 87 Dellinger and Staunton, 1999. 88 FHA, 1972 89 Kouri, 1999 90 Cooper et al, 2005; Frank et al., 2003 ch.9; Parsons Brinkerhoff Quade and Douglas Inc., 1993 91 Frank, L.D., 2000 92 Gilbert and O'Brien, 2005; Boarnet et al., 2005; Loukaitou-Sideris, 2006 93 Ewing et al., 2004 94 Gilbert and O'Brien, 2005 95 Boarnet etal., 2003  96 Boarnet et al., 2005 97 Safe Kids Canada, 2006 98 Gilbert and O'Brien, Vanderslice, 2003 99 ITE, 2004. 100 Davis, 2001;NHTSA, 2000 101 Anderson et al., 1997 102 Province of British Columbia, 1996. 103 Tester et al„ 2004; NHTSA, 2000 104 King etal., 2003 105 Bradshaw etal., 1998 106 Gilbert and O'Brien, 2005 107 Vanderslice, 2003 108 Gilbert and O'Brien, 2005 109 Ewing et al., 2004; Black et al., 2001 110 Frank et al., 2003 111 Kitamura etal., 1994 112 Krizek, 2003 113 Frank, Saelens, et al., forthcoming 114 Go for Green, 1998 115 O'Brien, 2000 116 Moudon and Lee, 2003 CHAPTER 3 1 www.nqls.org 2 Ibid. 3 O'Brien, 2000 4 http://www.drjamessallis.sdsu.edu/ 5 Kalton and Kasprzyk, 1986 6 Ibid. 7 www.gmap-pedometer.com 8 Kalton and Kasprzyk, 1986 9 www.mapquest.com 10 Emery et al., 2003; Moudon and Lee, 2003; Pikora et al., 2003 11 Moudon and Lee, 2003 12 Province of British Columbia, 1996 13 www.nqls.org 14 Bakeman and Gottman, 1997 15 Ibid. 16 Hoogendoorn and Bovy, 2004 17 Frank et al., 2004, Frank et al., 2005 18 Frank et al., 2004 CHAPTER 4 1  http://brentwood.sd41.bc.ca/  CHAPTER 5 1 Garson, Year Unknown 2 Agresti and Finlay, 1997 3 Garson, Year Unknown 4 Brace, Kemp, and Snelgar, 2003 5 Ibid. 6 Ibid.  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Walking and Automobile Traffic Near Schools: Data to Support an Evaluation of School Pedestrian Safety Programs. Institute of Transportation Studies. University of California, Irvine.  BIBLIOGRAPHY-169  Pikora, T, Giles-Corti, B., Bull, F., Jamrozik, K., and Donovan, R., 2003. Developing a Framework for Assessment of the Environmental Determinants of Walking and Cycling. Social Science and Medicine. Vol.56:1693-1703  Saelens, B.E., Sallis, J.F., arid Frank, L.D., 2003a. Environmental Correlates of Walking and Cycling: Findings from the Transportation, Urban Design, and Planning Literatures. Annals of Behavioural Medicine. Vol. 25(2):80-91  Proshansky, H.M. and Fabian, A.K., 1987. The development of place identity in the child. In: C.S. Weinstein & T.G. David (eds), Spaces for Children: The built environment and child development, p.2140. New York, Plenum. Cited in Crider, L.B., and Hall., A.K.,2005. Street Wise Part I: Promoting Safe Bicycling and Walking to School. Teaching Elementary Physical Education. May, 2005:8-11  Saelens, B.E., Sallis, J.F., Black, J.B., and Chen, D., 2003b. Neighbourhood-based differences in physical activity: An environment scale evaluation. American Journal of Public Health. Vol. 93(9): 15521558  Province of British Columbia, 1996. Motor Vehicle Act [RSBC 1996] Chapter 318. Section 146: Speed Limits. Copyright Queen's Printer, Victoria, B.C. PHAC - Public Health Agency of Canada, 2003. Physical Activity Guide. Ottawa. Available on-line at: http://www.phac-aspc.ac.ca/pau-uap/paguide/ intro.html Pucher, J. and Renne, J.L., 2003. Socioeconomics of urban travel: evidence from the 2001 NHTS. Transportation Quarterly. Vol.57:49-77 Cited in: Frank, L.D., Andersen, M., Schmid, T.L., 2004. Obesity Relationships with Community Design, Physical Activity, and Time Spent in Cars. American Journal of Preventive Medicine. Vol. 27(2):87-96 Raine, K., 2004. Overweight and Obesity in Canada: A Population Health Perspective. August 2004. Commissioned by the Canadian Population Health Initiative of the Canadian Institute for Health Information. Ridgewell, C , Sipe, N, and Buchanan, N., 2005. School Travel Modes in Brisbane. Urban Research Program Research Paper 4. Griffith University, Brisbane Australia. Roerty, S., and Staats, P., 2002. International Walk to School: Why is it important? Why should my school participate?. Voorhees Transportation Policy Institute. Edward J. Bloustein School of Planning and Public Policy, Rutgers University. Available online at: http://policy.rutgers.edu/publications.html Safe Kids Canada, 2006. Pedestrian Safety Fact Sheet. Hospital for Sick Children, Toronto. Available at: http://www.sickkids.ca/SKCForPartners/custom/ SafeKidsPEDenfactsheet.pdf Sarkar.S., Kaschade, C , and de Faria.F., 2002. How well can child pedestrians estimate potential traffic hazards? California Institute of Transportation Safety, Department of Civil and Environmental Engineering. San Diego State University, California.  Sallis, J.F., Bauman, A., and Pratt, M., 1998. Environmental Policy Interventions to Promote Physical Activity. American Journal of Preventive Medicine. Vol.15(4):379-387 Sallis, J.F., Haskell, W.L., Fortmann, S.P., Wrznizan, K.M., Taylor, C.B., and Solomon, D.S., 2004. Predictors of Adoption and Maintenance of Physical Activity in a Community Sample. Preventive Medicine. Vol.15(4):331-341 Sallis, J.F. and Owens, N., 2002. Ecological Models of Health Behaviour, in Glanz, K., Lewis, F.M., Rimer, B.K., (eds) Health Behaviour and Health Education. 3rd Edition, p.462-484 Schlossberg, M., Phillips, P.P., Johnson, B., and Parker, B., 2005. Planning, Practice & Research. Vol.20(2):147-162 Siegel, A.W., Kirasic, K.C., and Kail, R.V. Jr., 1978. Stalking the elusive cognitive map: the development of children's representations of geographic space. In I. Altman & J.F. Wohlwill (eds), Children and the environment: Human behaviourand the environment. Vol.3:223-58. New York: Plenum Press. Sirard, J.R., Ainsworth, B.E., Mclver, K.L., and Pate, R.R., 2005. Prevalence of Active Commuting at Urban and Suburban Elementary Schools in Columbia, S.C. American Journal of Public Health. Vol. 95:236-237 Stead, D., 2001. Relationship between land use, socioeconomic factors, and travel patterns in Britain, Environment and Planning B. Vol.28:499-528. Cited in: Frank, L.D., Andresen, M., Schmid, T.L., 2004. Obesity Relationships with Community Design, Physical Activity, and Time Spent in Cars. American Journal of Preventive Medicine. Vol. 27(2):87-96 Tester, J., Rutherford, G.W., Wald, Z., and Rutherford, M.W., 2004. A Matched Case-Control Study Evaluating the Effectiveness of Speed Humps in Reducing Child Pedestrian Injuries. American Journal of Public Health. Vol.94(4): 646-651  BIBLIOGRAPHY-170  Timperio, A., Crawford, D., Telford, A., and Salmon, J., 2004. Perceptions about the local neighbourhood and walking and cycling among children. Preventive Medicine. Vol. 38:39-47  Zlot, A.L, and Schmid, T.L., 2005. Relationships among community characteristics and walking and bicycling for transportation or recreation. American Journal of Health Promotion. Vol.19(4):314-17  Tranter, P., 1995. Children's Independent Mobility and Urban Form in Australasian, English and German Cities. 7th World Conference on Transport Research, Sydney: 7th WCTR proceedings, pp.3144. cited in Morris, J., Wang, F., and Lilja, L, 2001. School Children's Travel Patterns - A Look Back and a Way Forward. Transport Research Centre. Royal Melbourne Institute of Technology (RMIT) University. Available on-line at: http://mams.rmit.edu.au/ fqg4obh5V8u4z.pdf Tranter, P., and Pawson, E., 2001. Children's access to local environments: a case study of Christchurch, New Zealand. Local Environment. Vol.6:27-48. Cited in Kearns, R.A., and Collins, D.C.A., 2003. Crossing Roads, Crossing Boundaries: Empowerment and Participation in a Child Pedestrian Safety Initiative. Space and Polity. Vol.7(2): 193-212 Tremblay, M., Willms, J.D., 2000. Secular trends in the body mass index of Canadian children. Canadian Medical Association Journal. Vol. 163(11): 1429-33 Tudor-Locke, C , Ainsworth, B.E., and Popkin, B.M., 2001. Active commuting to school: an overlooked source of children's physical activity? Sports Medicine. Vol. 31(5):309-13 Tudor-Locke, C , Neff, L.J., Ainsworth, B.E., Addy, C.L., and Popkin, B.M., 2002. Omission of active commuting to school and the prevalence of children's health-related physical activity levels: The Russian Longitudinal Monitoring Study. Child Care Health Development. Vol. 28(6):507-12 USDHHS - U.S. Department of Health and Human Services, 1996. Physical Activity and Health: A Report of the Surgeon General. Centres for Disease Control and Prevention, National Centre for Chronic Disease Prevention and Health Promotion. Cited in Frank, L.D., Engelke, P.O., and Schmid, T.L., 2003. Health and Community Design: The Impact of the Built Environment on Physical Activity. Island Press, Washington. Vanderslice, E., 2003. Creating Safe Built Environments for Children. America Walks. September 2003. Available on-line at: http://www. americawalks.org/resources/downloads/Creating_ Safe_Built_Env.pdf  BIBLIOGRAPHY-171  A P P E N D I X A: P A R E N T A N D CHILD T R A V E L S U R V E Y S SURVEY FOR PARENTS - Fall 2005  Please respond in relation to your child who is participating in the Action! Schools BC Physical Activity Questionnaire.  Child's Name:  Child's School:  1.  What is your postal code?.  2.  Is your child:  3.  How old is your child who is participating in this survey?  4.  What is the distance (in kilometres) between your house and your child's school?  5.  0 male  0 female  0  Less than !4 kilometre (500 metres)  0  Vz to 1 kilometres  0  1 to 2 kilometres  0  2 to 3 kilometres  0  more than 3 kilometres  How many vehicles does your household own?  Include all cars, trucks, vans, SUVs, and  motorcycles.  Onone  01  0 2  0 3  0 more than three  A P P E N D I X A-172  6.  How many people in your household have a driver's license?  0 none  7.  01  0 2  0 3  0 more than three  How do you usually get to work? ("Usually" means 3 or more times per week.)  0 walk  0 ride a bicycle  0 roller blade/skateboard/scooter/other physical activity  0 drive by myself  0 carpool (as driver)  0 carpool (as passenger)  0 public transit (Translink or West Coast Express)  0 work from home  0 don't work outside the home  0 other  8.  How does your child usually get to school? ("Usually" means 3 or more times per week.)  0 walks by him/herself  0 walks with a brother/sister/friend  0 walks with a parent or other adult  0 rides his/her bicycle  0 roller blades, scooters, or skateboards  0 walks to the school bus stop  0 driven to the school bus stop  0 public transit (Translink)  0 driven to school by him/herself or with brothers and sisters 0 driven to school with friends (carpool)  0 other  A P P E N D I X A-173  9.  How does your child usually get home from school? ("Usually" means 3 or more times per week.)  0 walks by him/herself  0 walks with a brother/sister/friend  0 walks with a parent or other adult  0 rides his/her bicycle  0 roller blades, scooters, or skateboards  0 walks to the school bus stop  0 driven to the school bus stop  0 public transit (Translink)  0 driven to school by him/herself or with brothers and sisters 0 driven to school with friends (carpool)  0 other  10.  What are the TWO MAIN R E A S O N S that your child usually gets to/from school this way?  0 convenience  0 cost  0 only option  0 safety from traffic  0 distance  0 opportunity for exercise  0 safety from strangers or bullies  0 better for the environment  0 easiest way to organize daily schedules  0 my child prefers this way  0 other  11.  If your child is driven to school, does the person driving usually...  0 only drive the child to school 0 drive the child to school on their way to work 0 drive the child to school on their way to somewhere else (not work)  A P P E N D I X A-174  12.  If your child takes the school bus or Translink, what is the distance from your home to your child's  school bus or Translink stop?  0 less than 0.2km (200m)  0 0.2 to 0.5km (200-500m)  O 0.5 to 1.0 km (500m - 1 km)  O greater than 1 km  13.  Does your family ever use walking or jogging, riding bicycles, roller-blading, skateboarding, or use  a  scooter to get places other than school?  O Yes - less than 1 time per week  O Yes - 1 to 3 times per week  O Yes - 4 or more times per week  O No - we never get to places in these ways  14.  Have you ever talked with your child about the safest way for them to walk or ride their bicycle to  school? O Yes  15.  O No  Use the numbers below to show how much you agree with the following statements about your  neighbourhood.  I believe...  1  2  2  3  strongly  some  some  strongly  agree  what  what  disagree  agree  disagree  My neighbourhood is a safe place for my child to walk. My child is safe from traffic while walking to school or  O O  O O  O O  O O  waiting for the school bus/public transit. My child is safe from strangers and bullies while  O  O  O  O  walking to school or waiting for the school bus/public transit.  A P P E N D I X A-175  1 I believe...  2  2  3  strongly  some  some  strongly  agree  what  what  disagree  agree  disagree  Walking to school is a good way for my child to learn  O  O  O  O  independence and get exercise. Driving my child to school is a good opportunity for us  0  0  0  . 0  0  0  0  0  0  0  0  0  to talk because we are often busy. Driving my child to school is an important part of my responsibility as a parent. Our house is too far away from school for my child to walk or ride their bicycle.  16.  Please comment on any other factors that influence your decisions on how your child gets to  school.  17.  What is your approximate annual household income?  0 under $19,999  O $20,000 - $29, 999  O $30,000 - $39,999  0 $40,000 - $49,999  O $50,000 - $59,999  O $60,000 - $69,000  0 $70,000 - $79,999  O $80,000 - $89,999  O $90,000-$99,999  O $100,000 or greater  APPENDIX A-176  Barriers to walking and biking to school for your child  Please circle the answer that best applies to your child. 1a. Is your child's school within a 30 minute walk or bike from your home? 1b. Does your child walk or bike to school, either alone or with someone (at least once week)?  Yes Yes  No No  Do you agree or disagree with the following statements: It is difficult for my child to walk or bike to school (alone or with someone) because...  1  2  3  4  strongly  somewhat  somewhat  strongly  disagree 1 1 1 1 1 1  disagree 2  2  agree 3 3 3 3 3 3  agree 4 4 4 4 4 4  1 1 1  2 2 2  3 3 3  4 4 4  strongly  somewhat  somewhat  strongly  10. It's not considered cool to walk or bike 11. My child has too much stuff to carry 12. It is easier for me to drive my child' here  disagree 1 1 1  disagree 2 2 2  agree "3 3 3  agree 4 4 4  on the way to something else 13. It involves too much planning ahead 14. It is unsafe because of crime (strangers,  1 1  2 2  3 3  4 4  gangs, drugs) 15. My child gets bullied, teased, harassed 16. There is nowhere to leave a bike safely 17. There are stray dogs  1 1 1  2 2 2  3 3 3  4 4  18. It is too far  1  2  3  2. 3. 4. 5. 6. 7.  There are too many hills along the way There are no sidewalks or bike lanes The route is boring The route does not have good lighting There is too much traffic along the route There is one or more dangerous  crossings 8. My child gets too hot and sweaty 9. No other children walk or bike to school  ? ? 2  ?  4 4  APPENDIX A - 1 7 7  For the next few questions, tell us how much you agree or disagree with each statement. Please circle your answers  19. Other kids my child's age walk or bike to school by themselves 20. Other kids my child's age walk or bike to school with a parent or other adult 21. Other kids my child's age think walking or biking to school is "cool" 22. At my child's school, the older kids think walking or biking to school is "cool" 23. My child enjoys walking or biking to school  24.  My child enjoys walking or biking to school with  friends 25. My child enjoys walking or biking to school with a  strongly  somewhat  somewhat  strongly  disagree  disagree 2  agree 3  agree 4  2  3  4  2  3  4  2  3  4  2  3  4  2  3  4  2  3  4  1  1  1  1  1  1  1  parent or other adult  APPENDIX A-178  The Active Transportation Collaborator SURVEY FOR KIDS - Fall 2005  Name:  School:  Are you a: 0 Boy  0 Girl  How do you usually get to school?  0 walk by myself  0 walk with a brother/sister/friend  0 walk with a parent or other adult  0 ride my bicycle  0 roller blade, scooter, or skateboard  0 walk to the school bus stop  0 driven to the school bus stop  0 public transit (Translink)  0 driven to school by myself or with my brothers/sisters 0 driven to school with friends (carpool) 0 other  3.  How do you usually get home from school?  0 walk by myself  0 walk with a brother/sister/friend  0 walk with a parent or other adult  0 ride my bicycle  0 roller blade, scooter, or skateboard  0 walk to the school bus stop  0 driven to the school bus stop  0 public transit (Translink)  0 driven to school by myself or with my brothers/sisters 0 driven to school with friends (carpool) 0 other  APPENDIX A-179  If you ever walk, bike, roller blade, scooter, or skateboard to school, how many days per week do you it? days per week  How did you get to school today?  0 walk by myself  0 walk with a brother/sister/friend  0 walk with a parent or other adult  0 ride my bicycle  0 roller blade, scooter, or skateboard  0 walk to the school bus stop  0 driven to the school bus stop  0 public transit (Translink)  0 driven to school by myself or with my brothers/sisters  (  0 driven to school with friends (carpool)  0 other  If today was different from how you usually get to school, why was it different?  If you are driven to school, does the person driving you usually... 0 only drive you to school 0 drive you to school on their way to work 0 drive you to school on their way to somewhere else (not work)  Is the person that takes you to school your parent? OYes  ONo  A P P E N D I X A-180  8.  What is your favourite way to get to school?  0 walk by myself  0 walk with a brother/sister/friend  0 walk with a parent or other adult  0 ride my bicycle  0 roller blade, scooter, or skateboard  0 walk to the school bus stop  0 driven to the school bus stop  0 public transit (Translink)  0 driven to school by myself or with my brothers/sisters 0 driven to school with'friends (carpool) 0 other  9.  Do you ever walk or jog, ride your bicycle, roller blade, skateboard or use a scooter to get to places  other  than school?  10.  0 Yes - less than 1 time per week  0 Yes - 1 to 3 times per week  0 Yes - 4 or more times per week  0 No - I never go places this way  Have the teachers at your school ever encouraged you to walk, bike, jog, roller blade, skateboard,  or use a scooter to get to school? 0 Yes  0 No,  11.  Have you ever talked with your parents or teacher about the safest way to walk or ride your bicycle  to  school?  0 Yes  0 No  APPENDIX A-181  12.  Use the numbers 1, 2, or 3 to show how much you agree with the following statements about walking  or  biking to your school.  1 - means you agree a lot 2 - means you agree a little 3 - means you don't agree at all  When I walk or bike in my neighbourhood...  1  2  3  Agree a lot  Agree a little  Don't agree  I feel safe from cars.  0  0  0  I feel safe from strangers and bullies.  0  0  0  It is easy and fun to walk.  0  0  0  It is easy and fun to ride my bicycle.  0  0  0  I feel safe walking by myself.  0  0  0  It is boring.  0  0  0  It takes too long to get places.  0  0  0  Other kids make fun of me.  0  0  0  A P P E N D I X A-182  A P P E N D I X B: M I C R O - S C A L E BUILT E N V I R O N M E N T S U R V E Y A. INTERSECTION 1. Intersection design. Check one answer. T-shaped (3 legs) = 1 Cross-shaped (4 legs) = 2 Star-shaped (5 legs) = 3 2. Type of Traffic Control. Check all that apply. Yes = 1; No = 0 No traffic control Stop sign Traffic signal Yield sign Roundabout or traffic circle 3. Special Use Lanes. Check all that apply. Yes= 1; No= 0 No special use lanes Right turn lane Continuous right turn lane Single left turn lane Double left turn lane Bike Lane Dedicated bus lane Taxi queue Other: specify 4. Crosswalk Characteristics: Ask Questions A-D for number of intersection legs based on Question #1, Intersection Design. A. Crosswalk Marking for Intersection Leg X. Check all that apply. Yes= 1; No= 0 None Designated or marked Raised Textured pavement B. Crosswalk Setback for Intersection Leg X. Check one answer. 0 feet =1 1 - 4 feet =2 > 4 feet =3  CONTINUED.  A P P E N D I X B-183  C. Crosswalk Signage for Intersection Leg X. Check all that apply. Yes= 1; No= 0 None Flashing lights Pedestrian caution sign a. Is there a pedestrian signal? Yes No Yes= 1; No^ 0 b. Is it button activated? Yes No Yes= 1; No= 0 1. Signal Timing - Number of Seconds of Solid Time 2. Signal Timing - Number of Seconds of Flashing Time  seconds seconds  D. Crosswalk Curb condition for Intersection Leg X. Check all that apply. Yes= 1; No= 0 None Raised median or island Curb cuts /wheelchair ramps B. ROADWAY 1a. Left Street Segment: Number of Vehicular Travel Lanes in one direction. Check one answer. 0 lanes = 0 1 lane = 1 2 lanes = 2 3 lanes = 3 4+ lanes =4 1b. Right Street Segment: Number of Vehicular Travel Lanes in one direction. Check one answer. 0 lanes = 0 1 lane = 1 2 lanes = 2 3 lanes = 3 4+ lanes -4 2a. Left Street Segment: Number of Driveways. Check one answer. 0 driveways = 0 1 - 2 driveways = 1 3 - 5 driveways -2 > 5 driveways = 3 2b. Right Street Segment: Number of Driveways. Check one answer. 0 driveways = 0 1 - 2 driveways = 1 3 - 5 driveways =2 > 5 driveways = 3 3a. Left Street Segment: Type of Curb. Check all that apply. Yes= 1; No= 0 No curb Right angle or square Rolled 3b. Right Street Segment: Type of Curb. Check all that apply. Yes= 1; No= 0 No curb Right angle or square Rolled  CONTINUED... APPENDIX B-184  4a. Left Street Segment: Parking. Check all that apply. Yes- 1; No= 0 No parking Angled parking On-street 90 degree Parallel to curb Surface parking in front of building Surface parking on the side of building Surface parking behind building Parking garage Pay or metered parking 4 b . Right Street S e g m e n t : P a r k i n g . C h e c k all that apply. Y e s = 1; N o =  0  No parking Angled parking On-street 90 degree Parallel to curb Surface parking lot in front of building Surface parking lot on the side of building Surface parking lot behind building Parking garage Pay or metered parking 5. Roadway g r a d e . C h e c k o n e a n s w e r .  No grade or flat = 0 Slight grade = 1 Moderate grade = 2 Steep grade = 3  •  C. TRAFFIC CALMING 1. Presence of Speed Table or Hump. Check one answer. Present = 1 Not present = 0 2. Presence of Signs to Reduce Speed. Check one answer. Present = 1 Not present = 0 3. Presence of Traffic Circle. Check one answer. Present = 1 Not present = 0 4. Presence of Curb Extension. Check one answer. Present = 1 Not present = 0 5. Presence of Textured Pavement. Check one answer. Present = 1 Not present = 0 6. Presence of Full or partial Road Closure. Check one answer. Present = 1 Not present = 0 7. Presence of Neckdown or Narrowing of road mid-block. Check one answer. Present = 1 Not present = 0  CONTINUED....  APPENDIX  B-185  D. BUFFER Is there a Buffer on the left side of the street? Yes No  Yes= 1; No= 0  1a. Left Street Segment: Types of Buffers between vehicular and pedestrian areas. Check all that apply. Yes= 1; No= 0 Brick Dirt Grass Shrubs Trees Paved shoulder Gravel shoulder 2a. Left Street Segment: Percentage of Street with Buffer. Check one answer. 1 - 25% = 1 26 - 50% =2 51 - 75% = 3 76 - 99% = 4 100% = 5 3a. Left Street Segment: Buffer Width. Check one answer. < 4 feet = 1 4 - 6 feet = 2 >6 - 8 feet = 3 > 8 feet =4 Is there a Buffer on the right side of the street? Yes No Yes= 1; No= 0 1b. Right Street Segment: Types of Buffers between vehicular and pedestrian areas. Check all that apply. Yes= 1; No= 0 Brick Dirt Grass Shrubs Trees Paved shoulder Gravel shoulder 2b. Right Street Segment: Percentage of Street with Buffer. Check one answer. 1 - 25% = 1 26-50% =2 51 - 75% = 3 76-99% = 4 100% = 5 3b. Right Street Segment: Buffer Width. Check one answer. < 4 feet = 1 4 - 6 feet = 2 >6 - 8 feet = 3 > 8 feet = 4  CONTINUED....  A P P E N D I X B-186  E. STREET FURNITURE 1a. Left Street Segment: Street Furniture. Check all that apply. Yes= 1; No= 0 None of these Benches Bike racks Bollards Bus shelters Bus stops Drinking fountains Flower planters Kiosks Newspaper boxes Pay telephones Pedestrian oriented maps v  None of these Public Art Public toilet facilities Sidewalk cafe or food vendor Street lighting Street name signs Trash or recycling cans Utility / electric poles Other: specify 1b. Right Street Segment: Street Furniture. Check all that apply. Yes= 1; No= 0 None of these Benches Bike racks Bollards Bus shelters Bus stops Drinking fountains Flower planters Kiosks Newspaper boxes Pay telephones Pedestrian oriented maps None of these Public Art Public toilet facilities Sidewalk cafe or food vendor Street lighting Street name signs Trash or recycling cans Utility / electric poles Other: specify 2a. Left Street Segment: Spacing of Street Lights. Check one answer. 0 lights = 0 1 light = 1 Evenly spaced = 2 Irregularly spaced = 3 3a. Left Street Segment: Number of Street Lights. Please fill in answer. Number of street lights on street segment: CONTINUED....  APPENDIX  B-187  2b. Right Street Segment: Spacing of Street Lights. Check one answer. 0 lights = 0 1 light =1 Evenly spaced = 2 Irregularly spaced = 3 3b. Right Street Segment: Number of street lights. Please fill in answer. Number of street lights on street segment: F. TREES and SHADING 1a. Left Street Segment: Number of Trees in buffer. Check one answer. 0 or 1 tree = 0 2 - 5 trees =1 6 - 10 trees =2 11 -20 trees = 3 21+trees = 4 2a. Left Street Segment: Tree Spacing in the buffer. Check one answer. Evenly spaced = 1 Irregularly spaced = 2 3a. Left Street Segment: Percentage of the Total Area of the Walkway that is covered by Tree Canopy, Awnings, or Other Structures. Check one answer. No coverage = 0 1- 25% = 1 26 - 50% = 2 51 - 75% = 3 76.- 100% = 4 1b. Right Street Segment: Number of Trees in buffer. Check one answer. 0 or 1 tree = 0 2 - 5 trees = 1 6 - 10 trees - 2 11 -20 trees = 3 21+trees = 4 2b. Right Street Segment: Tree Spacing in the buffer. Check one answer. Evenly spaced = 1 Irregularly spaced = 2 3b. Right Street Segment: Percentage of the Total Area of the Walkway that is covered by Tree Canopy, Awnings, or Other Structures. Check one answer. No coverage = 0 1-25% = 1 26 - 50% = 2 51 - 75% = 3 76- 100% = 4 G. SIDEWALKS 1a. Left Street Segment: Percentage of street with Sidewalk. Check one answer. No sidewalk = 0 1 - 25% = 1 26 - 50% =2 51 - 75% = 3 76-99% = 4 CONTINUED.... 100% = 5 A P P E N D I X B-188  2a. Left Street Segment: Predominant Sidewalk Material. Check one answer. Asphalt = 1 Concrete = 2 Brick = 3 Stone = 4 Dirt path = 5 ' Gravel shoulder = 6 Multiple materials = 7 2a1. Left Street Segment: Surface Continuity. Check one answer. Some portion paved or surfaced =1 Mostly paved or surfaced = 2 Continuously paved or surfaced = 3 3a. Left Street Segment: Sidewalk Quality. Check all that apply. Yes= 1; No= 0 Mainly broken surface material Small areas of broken surface materials Uneven surface Uniform 4a. Left Street Segment: Sidewalk Width not including buffer. Check one answer. < 4 feet = 1 4 - 6 feet = 2 >6 - 8 feet = 3 > 8 feet = 4 5a. Left Street Segment: Sidewalk Obstructions. Check one answer. No sidewalk obstructions = 0 Permanent = 1 Temporary = 2 Permanent and temporary = 3 1b. Right Street Segment: Percentage of Street with Sidewalk. Check one answer. No sidewalk = 0 1 - 25% = 1 26 - 50% =2 51 - 75% = 3 ' 76 - 99% = 4 100% = 5 2b. Right Street Segment: Predominant Sidewalk Material. Check one answer. Asphalt =1 Concrete = 2 Brick = 3 Stone = 4 Dirt path = 5 Gravel shoulder = 6 Multiple materials = 7 2a2. Right Street Segment: Surface Continuity. Check one answer. Some portion paved or surfaced - 1 Mostly paved or surfaced - 2 Continuously paved or surfaced - 3 3b. Right Street Segment: Sidewalk Quality. Check all that apply. Yes= 1; No= 0 Mainly broken surface material Small areas of broken surface material Uneven surface Uniform  CONTINUED.... APPENDIX  B-189  4b. Right Street Segment: Sidewalk Width not including Buffer. Check one answer. < 4 feet = 1 4 - 6 feet = 2 >6 - 8 feet - 3 > 8 feet =4 5b. Right Street Segment: Sidewalk Obstructions. Check one answer. No sidewalk obstructions = 0 Permanent = 1 Temporary -2 Permanent and temporary = 3 H. PRIVATE DEVELOPMENT 1a. Left Street Segment: Smallest Setback From Walkway. Check one answer. No building =0 < 10 feet =1 10-20feet=2 21 -50 feet =3 51-100 feet =4 > 100 feet =5 2a. Left Street Segment: Largest Setback. Check one answer. < 10 feet =1 10 -20 feet =2 21-50=3 51 -100 feet =4 > 100 feet =5 3a. Left Street Segment: Setback Consistency. Check one answer. Mostly consistent =1 Mostly inconsistent =2 4a. Left Street Segment: Setback Usage. Check all that apply. Yes= 1; No= 0 None of these Private yard Awning Bike racks Building ledge or benches Driveways for delivery vehicles Dumpster Fences or walls (can see through) Fences or walls (obstructing view) Landscaping or planter boxes Outdoor patio for restaurant or cafe Park/open space Parking lot or space Pedestrian walkway Signs Other: specify 5a. Left Street Segment: Shortest Building Height. Check one answer. 1-2 stories =1 3 - 5 stories -2 6 - 1 5 stories =3 16 + stories =4 CONTINUED....  APPENDIX  B-190  6a. Left Street Segment: Tallest Building Height. Check one answer. 1 - 2 stories =1 3 - 5 stories -2 6 -15 stories =3 16 +stories =4 7a. Left Street Segment: Facade Step Back. Check one answer. Yes=1 No =0 8a. Left Street Segment: Percentage of Buildings in Disrepair. Check one answer. 0% =0 1 - 25% =1 26-50% =2 51 - 75% =3 76- 100% =4 9a. Left Street Segment: Percentage of Visible Street Level Interior. Check one answer. 0% =0 1 - 33% =1 ' 34 - 66% =2 67-100%=3 10a. Left Street Segment: Perceived Eyes on Street from Windows, Porches, and Verandas. Check one answer. 0%=0 1 - 33% =1' 34 - 66% =2 67- 100% =3 11a. Left Street Segment: Building Uses. Check all that are present. Yes= 1; No= 0 None of these ATM free standing Auto-oriented stores (car parts, car repairs, etc) Bank Bar Cafe or coffee shop Chain convenience store Community center ^ Convenience store "Mom and Pop" Day care Dry cleaning/coin laundry Dwelling - single-family Dwelling - multi-family Food Market  CONTINUED.  APPENDIX  B-191  11a continued... None of these Furniture or appliance store Gas station Grocery store Hotel Library Liquor Store Multiple commercial uses Offices - government Offices - unspecified/misc Photocopy store Post office Professional services (doctor, lawyer, etc) None of these Retail store - big box large chain Retail store - small chain Salon, barber shop School Specialty shop/ local gift Video store Other: specify 12b. Left Street Segment: Number of Fast Food Uses. Write in Number observed: 12c. Left Street Segment: Number of Food Drive-Thru Windows. Write in Number: 1b. Right Street Segment: Smallest Setback From Walkway. Check one answer. No building =0 < 10 feet =1 10-20feet=2 21 - 50 feet =3 51-100 feet =4 > 100 feet =5 2b. Right Street Segment: Largest Setback. Check one answer. < 10 feet =1 10-20 feet =2 21 - 50 =3 51 -100 feet =4 > 100 feet =5 3b. Right Street Segment: Setback Consistency. Check one answer. Mostly consistent =1 Mostly inconsistent =2  CONTINUED.  A P P E N D I X B-192  4b. Right Street Segment: Setback Usage. Check all that apply. None of these Private yard Awning Bike racks Building ledge or benches Driveways for delivery vehicles Dumpster Fences or walls (can see through) Fences or walls (obstructing view) Landscaping or planter boxes Outdoor patio for restaurant or cafe Park/open space Parking lot or space Pedestrian walkway Signs Other: specify 5b. Right Street Segment: Shortest Building Height. Check one answer. 1 - 2 stories =1 3 - 5 stories =2 6 - 1 5 stories =3 16 + stories =4 6b. Right Street Segment: Tallest Building Height. Check one answer. 1-2 stories =1 3 - 5 stories =2 6 - 1 5 stories =3 16 +stories =4 7b. Right Street Segment: Facade Step Back. Check one answer. Yes=1 No =0 8b. Right Street Segment: Percentage of Buildings in Disrepair. Check one answer. 0% =0 1 - 25% =1 26 - 50% =2 51 - 75% =3 76-100% =4 9b. Right Street Segment: Percentage of Visible Street Level Interior. Check one answer. 0% =0 1 - 33% =1 34 - 66% =2 67- 100% =3 10b. Right Street Segment: Perceived Eyes on Street from Windows, Porches, and Verandas. Check one answer. 0% =0 1 - 33% =1 34 - 66% =2 67-100%=3  CONTINUED....  APPENDIX  B-193  11b. Right Street Segment: Building Uses. Check all that are present. Yes= 1; No= 0 N o n e of t h e s e A T M free standing Auto-oriented stores (car parts, c a r repairs, etc) Bank Bar C a f e or coffee s h o p C h a i n c o n v e n i e n c e store C o m m u n i t y center C o n v e n i e n c e store " M o m a n d P o p " D a y care Dry cleaning/coin laundry Dwelling - single-family Dwelling - multi-family F o o d Market N o n e of t h e s e Furniture or a p p l i a n c e store G a s station G r o c e r y store Hotel Library Liquor Store Multiple c o m m e r c i a l u s e s Offices - government Offices - unspecified/misc P h o t o c o p y store P o s t office P r o f e s s i o n a l s e r v i c e s (doctor, lawyer, etc) N o n e of these Retail store - big box large c h a i n g Retail store - s m a l l chain S a l o n , barber s h o p School Specialty s h o p / local gift V i d e o store Other: specify  12b. Right Street Segment: Number of Fast Food Uses. Write in N u m b e r o b s e r v e d :  12c. Right Street Segment: Number of Food Drive-Thru Windows. Write in N u m b e r o b s e r v e d :  I. COMMUNITY OPEN SPACE 1a. Left Street Segment: Types of Open/Public Space Adjacent to the Street. Check all that apply. Y e s = 1; No= 0 None A park A community g a r d e n A courtyard R e c r e a t i o n facilities, courts, or playing fields Agricultural land Forest  CONTINUED....  A P P E N D I X B-194  1b. Right Street Segment: Types of Open/Public Space Adjacent to the Street. Check all that apply. Yes=1;No=0 None A park A community garden A courtyard Recreation facilities, courts, or playing fields Agricultural land Forest 2a. Left Street Segment: Open/Public Space Amenities Accessible From the Street. Check all that apply. Yes= 1; No= 0 None Benches Drinking fountains Play structures Tennis courts Swimming pool Walking path, paved or unpaved Bike path, paved or unpaved 2b. Right Street Segment: Open/Public Space Amenities Accessible From the Street. Check all that apply. Yes= 1; No= 0 None Benches Drinking fountains Play structures Tennis courts Swimming pool Walking path, paved or unpaved Bike path, paved or unpaved 3a. Left Street Segment: Presence of Other Pedestrian Routes Connected to the Sidewalk. Check all that apply. Yes= 1; No= 0 No other routes Path/ alley thru park/ vacant lot Alley between buildings Path from end of cul-de-sac 3b. Right Street Segment: Presence of Other Pedestrian Routes Connected to the Sidewalk. Check all that apply. Yes= 1; No= 0 No other routes Path/ alley thru park/ vacant lot Alley between buildings Path from end of cul-de-sac  CONTINUED.  APPENDIX  B-195  J. NEGATIVELY PERCEIVED CHARACTERISTICS 1a. Left Street Segment: Presence of Incivilities. Check all that apply. Yes= 1; No= 0 None Graffiti Posters/stickers (unauthorized) 1b. Right Street Segment: Presence of Incivilities. Check all that apply. Yes= 1; No= 0 None Graffiti Posters/stickers (unauthorized) 2a. Left Street Segment: Maintenance and Cleanliness. Check all that apply. Yes= 1; No= 0 None Structures with cosmetic disrepair Substantial litter Abandoned, boarded-up buildings Abandoned vehicles 2b.Right Street Segment: Maintenance and Cleanliness. Check all that apply. Yes= 1; No= 0 None Structures with cosmetic disrepair Substantial litter Abandoned, boarded-up buildings Abandoned vehicles  A P P E N D I X B-196  A P P E N D I X E: S U M M A R Y OF INTER-RATER RELIABILITY (KAPPA) TESTS I  1 = 100% agreement (when calculated, and when both were constants) Yellow'marked cells are calculated as simple % agreement (one variable was constant)  By.number of cases i kappa score B'BANK BOUNDARY ^B'WOOD HATZIC MBOROUGH MISSION MOBERLY 70.00 100% 57.00 74.00 68.00 63.00 53.00 61.00 80-99% 1.00 0.00 1.00 1.00 3.00 2.00 65-80% 1:00 0.00 2.00 0.00 1.00 5.00 0.00 3.00 9.00 2.0CT <65% 4.00 2.00 9.00 11.00 couldn't calculate 5.00 14.00 1.00 7.00 13.00 10.00 6.00 80.00 80.00 80.00 80.00 80.00 80.00 80.00 By percent of cases 1 kappa score B'BANK BOUNDARY B'WOOD HATZIC MBOROUGH MISSION MOBERLY 100% 0.88 0.71 0.85 0.79 0.66 0.76 o.sa n ni 80-100% 0.01 0.00 0.01 0.01 0.04 0.03 65-80% 0.01 0.00 0.03 0.00 0.01 0.06 0.00 <65% 0.04 0.11 0.03 0.05 0.03 0.11 0.14 couldn't calculate 0.06 0.18 U Ul 0.09 0.16 0.13 0.08 I  Variable Name  B'BANK BOUNDARY B'WOOD HATZIC MBOROUGH MISSION MOBERLY 1.00 1.00 1.00 1.00 1 00 1.00 TOO  Intersection Type  3-Leg Intersections Traffic Control Type 0 Type 1 Type 2 Type 3 Type 4  1.00  r  XW Marking - Leg 1 Type Type Type Type  1.00 1.00 1.00  1.00 1.00 • 1.00 1.00  0 1 2 3  1.00 1.00 1.00 1.00  j oo  • 0.91  1.00 1.00 1.00 1.00 1.00  0.28 0.30 1.00 1.00 1.00  1.00 1.00 1.00 1.00 1.00  1.00 1.00 1.00 1.00 1.00  i;oo  1.00  0.91  1.00 T.oo 1.00 1.00  T.OO  1.00 1.00 1.00 1:00  1.00 1.00  1.00 1.00  1.00 0,91  1.00 1.00 1.00 1.00  1.00 1.00 1.00  0.91 1.00 0.91  1.00 1.00 i .00  1.00 1.00 1.00  , 0.83 1.00 0.83  1.00 1.00 1.00  0.57 1.00 0.57  1.00  1.00  1.00  1.00  1.00  1.00  1.00  1  0.91  ~ f o o  i.bo  1.00 1.00 1.00  XW Signage - Leg 1 Type 0 Type 1 Type 2  Pedestrian Button Leg 1  h  —  A P P E N D I X E-200  Variable Name BBANK XW Marking - Leg 2 Type 0 Type 1 Type 2 Type 3  BOUNDARY  1.00 [ 1.00 1.00 1.00  BWOOD  HATZIC MBOROUGH MISSION  1  0.62 0.62 1.00 1.00  1.00 1.00 1.00 1.00  1.00 1.00 1.00 1.00  1.00 1.00 1.00 1.00  1 IX! 1.00 1.00  ' 0 . 6 2 1.00 0.62  1.00 1.00  0.82 1.00 0.82  1.00  1.00  1.00  1.00 1.00 1.00 1.00  1.00 1.00 1.00 1.00  1.00 1.00 1.00 1.00  1.00 1.00 1.00  1.00 l _ 1.00 1.00  1.00  1.00  •  MOBERLY  0.60 0:60 1.00 1.00  1.00 1.00 1.00 1.00  1.00 1,00 1.00  1.00 1.00  1.00  1.00 1.00 1.00  1.00  1.00  1.00  1.00  1.00 1.00 1.00 1.00  0.57 0.57 1.00 1.00  iTxT 1.00 1.00 1.00  1.00 1.00 1.00 1.00  1.00 1.00 1.00  1.00 1.00 1.00  1.00 1.00 1.00  0 55 1.00 0.55  1.00 1.00 1.00  1.00  1.00  1.00  1.00  1.00  1.00 0.25 1.00 CO 1 .00  XW Signage - Leg 2 Type 0 Type 1 Type 2  Pedestrian Button Ley 2 XW Marking - Leg 3 Type 0 Type 1 Type 2 Type 3  :  i .00 1  r  1  XW Signage - Leg 3_ ' _ Type 0 T y p e .1 Type 2  Pedestrian Button - Leg 3 4-Leg Intersections Traffic Control  1  j i  0.33 0.43 ,1.00 •0.92 1.00  1.00 1.00 1:00 I . 1.00j 1.00  1.00 0.60  1.00 1.00 1.00 1.00  1.00 '  1.00  1.00 1.00 1.00 1.00 1.00  1.00 1.00 1.00 1.00 1.00  0 67 0.27 1.00 1 00 " 1.00  1.00 1.00  1.00 1.00 1.00 1.00  1.00 1.00 1.00 1.00  1.00 1.00 1.00 1.00  1.00 1.00 1.00 1.00  1.00 1.00 1.00 1.00  0.80 1:00 0.80  1.00 1.00 1.00  1.00 1.00 1.00  0.71  • • " ; :•' 0.71 1.00  0.61 0.89 1.00  0.61  Type 2  1.00 1.00 1.00  Pedestrian Button Leg 1  0.92  1.00  0.60  1.00  1.00  1.00  1.00  1.00 1.00 1.00 1.00 |  0.55 0.55 1.00 1.00  0.71 0.71 1.00 1.00  1.00 1.00 1.00 1.00  1.00  0.36 0.36 1.00 1.00  1.00 1.00 1.00 1.00  Type 0 Type 1 Type 2 Type 3 Type 4  r  1  0  0  1  XW Marking Leg 1 Type 0 Type 1 Type 2 Type 3  1.00  1  XW Signage Leg 1 Type 0 Type 1  XW Marking Leg 2 Type 0 Type 1 Type 2 Type 3  I  1.00 1.00  1:00 0.61  A P P E N D I X E-201  V a liable Name XW Signage Leg  B'BANK  BOUNDARY  B'WOOD HATZIC  M B O R O U G H MISSION  MOBERLY  2 Type 0 Type 1 Type 2 Pedestrian Button : Leg  2  .  _  XW Marking Leg 3 Type 0 Type 1 IXP_e2 Type 3 XW Signage Leg  1.00 " 1 00 1.00  0.80 1.00J 0.80  •1.00 1.00 1.00  1.00  0.80  1.00  _ TOO  1.00  1.00  1.00  1.00 1.00 L 1.00 1.00  1.00  1.00 1.00  1.00 1.00 1.00 1.00  0.77 0.77 1.00 1.00  0.61 0.61  1.00 1.00  1.00 1.00 1.00 1.00  1.00 1.00 1.00  '0.80 1.00 0.80  1.00 1.00 1.00  1.00 1.00 1.00  0.86 U.8B 1.00  0.60 0 89 0.61  1.00 1.00 1.00  1.00 1.00 1.00 1.00  1.00 1.00 1.00 1.00  1.00 1.00 1.00 1.00  1.00 1.00 1.00 1.00  1.00 1.00 1.00 1.00  0.77 0.77 1.00 1.00  1.00 1.00 1.00 1.00  1.00 1.00  1.00 1.00 1.00  1.00 1.00 1.00  1.00 1.00 1.00  0.71 . 0,71 1.00  0.55 0.89 0.77  0.61" 0.89 1.00  1.00 1.00  1.00 1.00  1.00 1.00  0.18 0.45  1.00 1.00  1.00 0.81  1.00 1.00  1.00  0.64  1.00  1.00  0.92  1.00  0.81  1.00  1.00  1.00  1.00  0.83  1.00  0.81  0.70  0/4  1.00  .0.92  U.92  0.81 .  0.89  0.86  0.89 0.36 1.00 1.00 0.95 1.00 1.00 0.95 0.48 1.00  1.00 0.92 1.00 0.54 1.00 1.00 1.00 r TOO 1.00 1.00 0.94 1.00 1.00 1.00 1.00 " 1 . 0 0 0.85 0.811 1.00 1.00  0.92 0.77 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00  0.87 0.36 1.00  1  0  0  0.71 0.71 1.00  1.00  • 1.00 ' "TOO  1.00 1.00  . '  0.78 0.89 0.89  0.61 0.89  .  1.00  j  1.00 1.00  3 Type 0 Type 1 type 2 XW Marking Leg 4 Type 0 Type 1 Type 2 Type 3 XW Signage Leg 4 Type 0 Type 1 Type 2  (  0 0  Street Segments Buffer - Left Side Buffer - Right Side Number Lanes Left Side Number Lanes Right Side > Percent Sidewalk Left Side Percent Sidewalk Right Side Street Grade  r ~ 0.53  Traffic Calming Traffic Circle Curb Extension Road Closure Traffic Hump Neck Down Slow Speed Signs Textured Pavement  1.00 0.93 1.00 0.93 1.00 1.00 0.33 1.00  _  ".  i  1,00 . ;  TOO 1.00  TOO  1  1.00 0.92 1.00  0.89 0.54 1.00 0.83 I.OOl 0.94 1.00 1.00 0.34 1.00  A P P E N D I X E-202  Variable Name B B A N K [BOUNDARY B'WOOD HATZIC MBOROUGH MISSION Other Pedestrian i j Routes - Left Side I Type 0 0.57 -0.22 0.88 | 0.85 0.64 0.68 -0.09 0.94 0.85 0.40 0.44 Type 1 __ _ •• 0.87 Type 2 0.70 r ~ o.o8 0.88 ( 1 . 0 0 0.57 1.00 Type 3 0.93 1.00 1.00 1 1.00 0.92 0.44 i Other Pedestrian i i Routes - Right Side Type 0 0.86 i 1.00 : 0.53 0.57 0.69 0.22 Type 1 0.93 0.35 0.82 i 0.35 0.40 0.81 Type 2 0.86 0.95 1.00 | 1.00 0.58 1.00 Type 3 | 1.00 0.95 .:. 1.00 .0.92 0.63 0.92 :  MOBERLY j  ! h  0.89  |  -0.06 0.89 0.94  i  !  |  0.89  !  0.33  ]  0.77 1.00  | !  A P P E N D I X E-203  A P P E N D I X F: S U M M A R Y OF DESCRIPTIVE STATISTICS  TOTAL SAMPLE N=239  ! v i [  7  " ~ "  —  " ~ '  Variable  Gender Age_  Distance From School  HH Income  Number HH Vehicles  ';•  Demographics  -Category  - ' ~ ~ " ~ •• "•' :  "Frequency  Percent  Boys Girls 8 9 10 11  117 122 4 112 115 8  49.0 51.0 1.7 46.9 48.1 3.3  <500m 500m-1km 1-1.5km 1.5-2krn 2-2.5km  95 110 24 7 3  39.7 46.0 10.0  <$19,999 $20,000-$29,999 $30,000-$39,999 $40,000-$49,999  25 28 31 35  10.5 11.7 13.0 14.6  $50,000-$59,999 $60,000-$69,999 $70,000-$79,999  28 27  11.7 11.3 5.9  Central Tendency  n/a Mean = 9.61  Mode = 5001km  2.9 1.3  $80,000-$89,999  14 13  $90,000-$99,999 >$100,000  11 27 .  4.6 . 11.3  None 1 vehicle 2 vehicles 3 vehicles 4 or more vehicles  7 103  2.9 43.1  101 20 8  42.3  Mean = $40$49,000  5.4  Mean = 1.49 Mode = 1  8.4 3.3  APPENDIX F-204  TOTAL SAMPLE N=239  Travel Behaviour Variable  Category  Frequency  Percent  Walk  116  48.5  Driven  101  42.3  School Bus  2  0.8 1.3  Central Tendency  M o d e of Travel To School  Other Active Mode  3  Public Transit  0  0.0  Other  1  0.4  Multiple Selections  16  6.7  Walk  134  56.1  Driven  84  35.1  School Bus  3  Other Active Mode  2  \3_ 0.8  0  0.0  1  0.4  Multiple Selections  15  6.3  Walk  140  58.6  Drive  56  23:4  M o d e = walk  M o d e of Travel From School  Public Transit Other  _  M o d e = walk  _  Favourite M o d e of Travel  School bus  1 '  Bike or other active mode Multiple responses Active Travel  0.4  36 6 .  M o d e = walk  15.1 ... _  2  _  5  Active one or two ways  152  63.6  Never active  87  36.4  convenience  91  38.1  only option  22  9.2  distance  66  27.6  49  20.5  39  16.3  n/a  R e a s o n s Cited for Travel C h o i c e  safety  from  strangers or bullies  easiest daily schedule cost  ' 1  0.4  safety from traffic  30  12.6  opportunity for exercise  39  16.3  better for environment  9  3.8  child's preference  33  13.8  other  1  0.4  never  53  22.2  < 1 time per week  81  33.9  1-3 times per week  78  32.6  4 or more times per week  27  11.3  Active N o n S c h o o l Trips  M o d e = <1 time per week  APPENDIX F-205  TOTAL SAMPLE N=239  Parental Perception Questions V tillable  Neighbourhood safe for child to walk.  Category  Frequency  Percent  1 - strongly agree ,  80  33.5  2 - somewhat agree  127  53.1  3 - somewhat disagree  22  9.2  strongly disagree  10  4.2  strongly agree  56  23.4  somewhat agree  110  46.0  somewhat disagree  51  21.3  4 - strongly disagree  22  9.2  1 - strongly agree  40  16.7  2 - somewhat agree  124  51.9  3 - somewhat disagree  47  19.7  4 - strongly disagree  23  11.7  strongly agree  79  33.1  somewhat agree  77  32.2  somewhat disagree  52  21.8  strongly disagree  31  13.0  strongly agree  12  5.0  somewhat agree  22  9.2  somewhat disagree  50  20.9  strongly disagree  115  48.1  4 Child safe from 1traffic while 2walking to school. 3Child safe from strangers/bullies while walking to school.  Driving my child is 1 an important 2responsibility as a 3parent. 4 Our house is too 1 far from school for 2my child to walk 3or ride their 4 bicycle.  :  Central  Mean = 1.86  Mean = 2.12  Mean = 2.33  Mean = 1.65  Mean = 3.37 .  Child's Percepti an Questions  Have your Yes teachers encouraged you to walk, cycle or other active mode to get to school? No..  111  46.4  n/a  -  128  53.6  Agree a lot  103  43.1  Agree a little  103  43.1  Don't agree  33  13.8  Agree a lot  73  30.5  Agree a little  92  38.5  Don't agree It is easy and fun Agree, a lot to walk. Agree a little  74  31.0  176  73.6  55  23.0  8  3.3  52  21.8  107  44.8  80  33:5  When 1 walk hi my neighbourhood:  1 feel safe from cars 1 feel safe from strangers and bullies.  Don't agree 1 feel safe walking Agree a lot by myself. Agree a little Don't agree  Mean - 1.67  Mean = 2.00  Mean = 1.27  Mean = 2.29  APPENDIX F-206  TOTAL SAMPLE  Street Segments  MICRO-SCALE BUILT ENVIRONMENT n=198  Variable  Category  Frequency.  Mean  Total Lanes  2 3 4 5 6 Flat Slight Moderate Steep  171 8 14  2.280  0.786  2.280  0.964  0.303  0.587  0.692  0.86149  3.430  2.267  Street Grade  Traffic Calming  Buffer  ~ i ~ ™ 4 52 75 48 23 149 40 7 2 113 33 52  No elements 1 element 2 elements 3 elements None One side Both sides  Sidewalk (longest side) None 1-25% 26-50% 51-75% 76-99% 100%  Intersections  "  "  56 4 3 1 3 131  n=192  Variable  Gate go iv  Intersection Type  T-type 4-way None Yeild or roundabout Stop sign Lights  Traffic Control  "~  Std Dev  Crosswalk Marking (proportion of legs with) None 1 of4 1 of 3 2 of 4 2 of 3 3 of 4 All Crosswalk Signage (proportion of legs with) None 1 of 4 1 of 3 2 of 4 2 of 3 3 of 4 All  Std Dev  Frequency  : Mean  96 96 14 5 154 19  1.500  0.501  1.927  0:643  145 9 8 7 3 3 17  15.451  163 12 5 5 4 1 2  6.554  31.238  17.82866  APPENDIX F-207  TOTAL SAMPLE  Intersections Continued Variable  Category  Frequency  Mean  172  7.899  Std Dev  I  Pedestrian Button (proportion of legs with) None 11 of 3 2 of 4 2 of 3 All  •—  :  ——  Built Environment Scores n=239 Variable Ouaililed Score Walkability Score (Quartiled) 1 2 3 4 Lowest Walkability Score (Quartiled) 1 2 . - - • 3 4  5 i ii  24.88688  1  -  Cential Tendency Std Dev  Frequency Frequency  Percent , Mean  25 101 70 43  10.5 42.3 29.3 Tgg  Mean = 2.55  15.9 43.9 ~ 14 2 ~13.4  Mean = 2.38  38 105""" ~ 34 " ~ 32  A P P E N D I X F-208  BROOKSBANK ELEMENTARY N=33  DEMOGRAPHICS Variable Gender  Category Boys Girls  Age .  .  .  Distance From School  HH Income  Number HH Vehicles  Central Tendency N/A  Frequency  Percent 57.6 42.4  8 9 10 11  19 14 0 15 16 2  <500rn  3  9.1  500m-1-km  17  51.5  1-1.5km 1.5-2km 2-2.5krn  10  30.3  3  9.1  0  0.0  <$19,999 $20,000-$29,999 $30,000-839,999 $40,000-$49,999 $50,000-$59,999 $60,000469,999 $70,000-$79,999 $80,000-$89,999 $90,000-$99,999 >$100,000  0  0.0  0  0.0  .3 3  9.1  8  24.2  5 '  15.2  4  12:1  3  9.1  3  9.1  4  12,1  0  0.0  Mean = 1.94  9  27.3  Mode = 2  19  57.6  4  12.1  1  3.0  None 1 vehicle 2 vehicles 3 vehicles 4 or more vehicles  0.0  Mean = 9.57  45.5 48.5 6.1  500-1 km  Mean = $60$69,000  9.1  APPENDIX F-209  BROOKSBANK ELEMENTARY N=33  T R A V E L BEHAVIOUR  Variable  Category  Frequency  Mode of Travel To School Walk  Mode of Travel From School  '•<  Percent ,  9  27.3  Driven  21  63.6  School Bus  0  0.0  Other Active M o d e P u b l i c Transit  0  oo *  0  0.0  Other  1  3.0  Multiple S e l e c t i o n s  2  6:1  Walk  17  51 5  Driven  14  42.4  0  0.0  . 0  0.0  School Bus Other Active M o d e P u b l i c Transit O  t  h  e  r  ~  "  Multiple S e l e c t i o n s  0  0.0  0  0.0  2  6.1  Favourite Mode o f Travel Walk  17  51.5  Drive  Active Travel "  12  36:4  S c h o o l bus  1  3.0  B i k e or other active m o d e  2  6:1  Multiple r e s p o n s e s  1  3.0  Active one or two w a y s  18  54.5  N e v e r active  15  45.5  12  34.3  Reasons Cited for Travel Choice convenience,  —  -•—  Active NonSchool Trips  —  only option  1  2.9  distance  8  22.9  safety from strangers or bul  8  22.9  e a s i e s t daily s c h e d u l e  13  37.1  cost  G  0  safety from traffic  2  5.7  opportunity for e x e r c i s e  6  17.1  better for environment  2  5.7  child's preference other  5  14.3  0  0  never  9  27.3  < 1 time per w e e k  12  36.4  1-3 t i m e s per w e e k  11  33.3  4 or m o r e t i m e s per w e e k  1  3.0  Central Tendency Mode = driven by car  Mode = walk  Mode = walk  n/a  Mode = < 1time per week  APPENDIX  F-210  BROOKSBANK ELEMENTARY N=33 PERCEPTION OF SAFETY .'" Variable  Category  Parental Perception Neighbourhood 1 safe for child to 2 walk. 3 -  Percent  Tendency  strongly a g r e e  9  27.3  Mean = 1.74  somewhat agree  23  Questions  somewhat disagree  4 - strongly d i s a g r e e Child safe from 1 - strongly a g r e e traffic while 2 - somewhat agree walking to school. 3 - somewhat disagree 4 - strongly d i s a g r e e Child safe from strangers/bullies while walking to school.  •  69.7  1  3.0  0  0.0  7  21.2  17  51.5  7  21.2  2  6.1  1 - strongly a g r e e  4  12.1  2 - somewhat agree  23  69.7  3 - somewhat disagree  5  15.2  4 - strongly d i s a g r e e  1  3.0  Driving my child is 1 - strongly a g r e e an important 2 - somewhat agree responsibility as a 3 - somewhat disagree parent. 4 - strongly d i s a g r e e Our house is too 1 - strongly a g r e e far from school for 2 - somewhat agree my child to walk 3 - somewhat disagree or ride their 4 -strongly disagree hinvcle n Child's Perceptio Questions Have your Yes teachers encouraged you to walk, cycle or other active mode to get to school? No When 1 walk in > ny neighbourhood: 1 feel safe from A g r e e a lot cars A g r e e a little  8  24.2  12  36.4  10  30.3  3  9.1  2  6.1  7  21.2  6  18.2  18  54.5  13  39.4  20  .  45.5  16  48.5  Don't a g r e e  2  5.7  A g r e e a lot  10  30.3  A g r e e a little  16  48.5  Don't a g r e e It is easy and fun A g r e e a lot to walk. A g r e e a little  7  21.2  • 22  66.7  11  33.3  0  0.0  12  36.4  14  42.4  7  21.2  Don't a g r e e 1 feel safe walking' A g r e e a lot by myself. A g r e e a little Don't a g r e e  Mean = 2.11  Mean = 2.1.1  Mean = 2.14  Mean = 3.20  n/a  60.6  15  1 feel safe from strangers and bullies.  Central  Frequency  Mean = 1.57  Mean = 1.91  Mean = 1.31.  Mean = 1.89  APPENDIX F-211  BROOKSBANK ELEMENTARY •  MICRO-SCALE BUILT ENVIRONMENT  Street Segments n=31  -  Variable  Category  Total Lanes  2 3 4 5 6 Flat Slight Moderate Steep Mo elements 1 element 2 elements 3 elements None One side Both sides  Street Grade  Traffic Calming  Buffer  '•  •  '  ;  >-  -  Std Dev  Frequency  Mean  29 2 0 0 0 5 11 9 6 23 5 3 0 27 4  2.060  0.25  1.516  0.996  0.355  0.661  0.129  11341  12 -'0 0 0 0 19  3.065  2.476  12 20 2 1 28 1  1.630  0.492  1.875  0.554  29 1 1 0 1 0 0  3.906  13.551  1.823  7.251  Z..Z'"~°"  Sidewalk (longest side) None 1-25% 26-50% 51-75% 76-99% 100% Inteisections •n=32 Intersection Type T-type 4-way Traffic Control None Yeild or roundabout Stop sign Lights Crosswalk Marking (proportion of legs with) None 1 of 4 1 of 3 2 of 4 2 of 3 3 of 4 All Crosswalk Signage (proportion of legs with) None 1 of4 " ~ — — 1 of 3 2 of 4 2 of 3 3 of4 ~ ~ "~ " All  "  "  ~  ~"  :  :  30 1 1 0 0 o ~ 0  -  _ __  APPENDIX  F-212  BROOKSBANK ELEMENTARY Intersections Continued •  Category  Variable Pedestrian Button (proportion of legs with) None  1 of 3 2 of 4 2 of 3 All • •  .  , •  2 3 4 Lowest Walkability Score (Quartiled) 1 12 3 4  Mean  31 1 0 0 0  1.042  • •  Built Environment Scores n=33 Walkability Score (Quartiled)  Frequency  Sttl Dev  5.893  Central Tendency :  Frequency  Percent  23„ 10 0 0  69.7 30.3 0.0 0.0  1,3  21 11 1  63.6 33.3 3.0 0.0  1.4  •o  •  "1  A P P E N D I X F-213  BOUNDARY ELEMENTARY N=34  DEMOGRAPHICS Variable Gender  Category  Frequency 14 20 1 15 18 0  Boys Girls 8 9 10 11  Age  Distance From School  15 17 .2 .0 0  <500m 500m-1km 1-1.5km 1.5-2km -  HH Income  2  _ - — - -  -. -  ~ -  :  -  2 2 1 5 2 3 3 3 2 11  <$19,999 $20,000-$29,999  -  -  -  - —  $30,000 $39.99.9 r  $40,000-$49.999 $50,000-$.59.99.9 $60,000-$69,999 $70,000-$79.999 $80,000-$89,999  —  Number HH Vehicles  :  -  _____  -  $90,000 $99,999  None 1 vehicle 2 vehicles 3 vehicles 4 or m o r e v e h i c l e s  Percent 41.2 58.8... 2.9 44.1. 52.9 0.0'  •  .0 10 14 7 3  44.1 •50.0 5.9 g._o 0.0  ...Central Tendency n/a Mean = 9.5  Mode = -< 500m  ;  Mean = $605.9 $69,000 5.9 2.9, — "14:7 5.9 8.8 . 8.8 8.8 • 5.9 . . 32.4 0.0 29,4' 41.2 20.6: 8.8. .  Mean = 2.09 Mode = 2  APPENDIX F-214  BOUNDARY ELEMENTARY N=34 TRAVEL BEHAVIOUR  Frequency  Percent  Central Tendency  14  41_.2_  Mode = Driven by car  Driven  16  47.1  School Bus  0  0.0  Other Active M o d e P u b l i c Transit  1  2.9  0  0.0  Other  0  0.0  Multiple S e l e c t i o n s  3  8.8  Walk  17  50.0  Driven  14  41.2  School Bus  0  0.0  Other Active M o d e  .0  0.0  P u b l i c Transit  0  0.0  Other  0  0.0  Multiple S e l e c t i o n s  3  8.8  21  61.8  Drive  3  8.8  S c h o o l bus  0  0.0  B i k e or other active m o d e Multiple r e s p o n s e s  10  29.4  0  •0.0  A c t i v e one or two w a y s  19  55.9  N e v e r active  15  44.1  Reasons Cited for Travel Choice convenience  13  38.2  Variable  Category  Mode of Travel To School Walk ~ ™  "  Mode o f f ravel From School  "  Favourite Mode of Travel Walk  Active Travel  Active NonSchool Trips  _  .  only option  2  5.9  distance  9  26.5  safety from strangers or bul  4  11.8  e a s i e s t daily s c h e d u l e  8  23.5  cost  0  0.0  safety from traffic  6  17.6  opportunity for e x e r c i s e  5  14.7  better for environment  4  11.8  child's p r e f e r e n c e other  5  14.7  0  0.0  never  5  14.7  < 1 time per w e e k  13  38.2  1-3 t i m e s per w e e k  12  35.3  4 or m o r e t i m e s per w e e k  4'  11.8  Mode = walk  Mode = walk  n/a  Mode = <1 time per week  APPENDIX  F-215  BOUNDARY ELEMENTARY N=34 •  PERCEPTION OF SAFETY Central Tendency  o  Variable Category Parental Perception Questions  Frequency "<•-,"• \ Percent  Neighbourhood  1 - strongly a g r e e  15  44.1  safe for child to walk.  2 - somewhat agree  15  _44.1  3 - somewhat disagree  4  4-strongly disagree Child safe from  ' _o.  1 - strongly a g r e e  traffic while 2 - somewhat agree walking to school.  _  ____11.8_ _____  0.0  10  29.4  ______  38.2  3 - somewhat disagree  8  23.5  4 - strongly d i s a g r e e  3  8.8  Child safe from  1 - strongly a g r e e  7  .20.6  strangers/bullies while walking to school.  2 - somewhat agree  22  64.7  3 - somewhat disagree  5  14.7  0  0.0  A - strongly d i s a g r e e  _  Driving my child is 1 - sttongly a g r e e an important 2 - s o m ewh at a g re* responsibility as a 3 - somewhat disagree parent. Our house is too far from school for my child to walk or ride their hinvnlfi  7  __  7  j _ strongly a g r e e :  0  0.0  2 - somewhat agree  1  2.9__  _  5  1.4.7 82.4  Have your  28  82.4  No When 11 walk in my neighboiiihood:  6  17.6 00  1 feel safe from  A g r e e a lot  13  38.2  A g r e e a little  19  55.9  Yes  Don't a g r e e  .2  5.9 .  1 feel safe from  A g r e e a lot  14  41.2  strangers and bullies.  A g r e e a little  .12  35.3  It is easy and fun  A g r e e a lot  29  85.3  to walk. •  A g r e e a little  4  11.0  Don't a g r e e  1.  2.9  _  Don't a g r e e  _B  —  Mean = 2.47  Mean = 3.79  n/a  ':;i ?  . T _  y  _  1.68  1.82  23.5  5 _____  • -  00  teachers encouraged you to walk, cycle or other active mode to get to school?  Agfejjajjttle  Mean = 1.94  20.6  28  1 feel safe walking A g r e e a lot by myself.  -  26.5  9  4 - strongly d i s a g r e e  Don't a g r e e  -  32.4  4- strongly d i s a g r e e "Child's Peiceptio n Questions ;  cars  Meanf_j2_J2  20.6  "11  3 - somewhat disagree-  Mea]ij=J_68_  19. 10  14.7 _  .  1.18  2J5  55.9 29.4  APPENDIX F-216  BOUNDARY ELEMENTARY MJCRO-SCA Street Segments n=31 Variable Category . Total Lanes -  -  Street Grade  Traffic Calming  Buffer  --  2 3 4  Frequency.  Mean  25 0 3 0 0 3 17 6 2  2.2  •  B Flat Slight. Moderate Steep No elements 1 element 2 elements 3 elements None One side Both sides  24 3 1 0 27 1 0  Sidewalk (longest side) None 1-25% 26-50% 51-75% 76-99% 100%  9 0 1 0 0 18  Std Dev 0.63  - - :  ~  ~  1.250  0.7514  0.179  0.4756  0.036  0.189  3.286  2.37  —-  —  Intersections  r-26 Intersection Type T-type 4-way Traffic Control None Yeild or roundabout Stop sign Lights Crosswalk Marking (proportion of legs with) None 1 of 4 1 of 3 2 of 4 2 of 3 3 of 4 All  I  Crosswalk Signage (proportion of legs with) None 1 of 4 1 of 3 ,  .  2 of 4 2 of 3 3 of 4 All  __  17 9 2 0 22 2  1.4  20 1 2 0 1 0 2  13.782  29.901  8.013  20.613  22 0 2 0" 1 1 0  0.485 0.628 _  -  - -  APPENDIX F-217  BOUNDARY ELEMENTARY  Intersections Continued Variable  .  Category  Pedestrian Button (proportion of legs with) None 1 of3 2 of4 2 of3 All  Frequency  21 0 1 0 '3"  .  Std Dev  Mean  6.410 .  23:131  !  i Built Environment Scores n=34  Frequency  Percent  o  Walkability Score (Quartiled) 1. 2 3 4  24 10 0  0.0 70.6 29.4 0.0 .  Lowest Walkability Score (Quartiled) 1 2 3 4 •  3 20. 11 0  8.8 58.8 32.4 0.0.  Central Tendency  Mean = 2.29  \ -  Mean = 2.23  APPENDIX F-218  BRENTWOOD PARK ELEMENTARY  N=33  DEMOGRAPHICS  Variable Gender Age —  ;  Distance From School  HH Income  -  Category Boys Girls 8 9 10 11 <500rn  5  500m-1km  23  1.5.2 69.7  1-1.5km  5  15.2  1.5-2km 2-2.5km  0  0.0  0  0.0  <$ 19.999. $20,000-$29,999  3  9.1  6  18.2  $30,000-$39,999  9  ,27.3  $40,000-$49,999  3  9,1  4  12.1  A \  12 1  $70,000-$79,99.9  0  0.0  $80,000-$89,999  1  3.0  $90.000499.999 >$ 1 0 0 , 0 0 0  1  3.0  2  6.1  None  0  0.0  Mean = 1.52  1 vehicle  19  57.6  Mode =.1  2 vehicles  11  33:3  3 vehicles  3  9:1  4 or m o r e v e h i c l e s  0  0.0  $50,000-$59;999 -  Number HH Vehicles  Central Tendency n/a  Frequency 17 '16 0 15 16 2  $60,000-$69,999  :  Percent . 51.5 48 5 0.0 45.5. 48.5 :  ™ B . ) "  Mean =9.6 —  —  —  Mode = 500m 1km  Mean = $40$49,000  •  APPENDIX F-219  BRENTWOOD PARK ELEMENTARY N=33 TRAVEL BEHAVIOUR  Frequency  Percent  Central Tendency  17  51.5  Mode = walk  Driven  13  39.4  School Bus  0  0.0  Other A c t i v e M o d e P u b l i c Transit  0  0.0  0  0.0  Other  0  0.0  Multiple S e l e c t i o n s  3  9.1  Walk  19  57.6  Driven  10  30.3  Variable  Category  Mode of Travel To School Walk  Mode of Travel From School  !  _  School Bus  0  0.0  Other A c t i v e M o d e  0  0.0  P u b l i c Transit  0  0.0  Other  0  0.0  Multiple S e l e c t i o n s  4  12.1  Favourite Mode of Travel Walk  Active Travel  20  60.6  Drive  4  12.1  S c h o o l bus  0  0.0  B i k e or other active m o d e  7  21.2  Multiple r e s p o n s e s  2  6.1  Active one or two w a y s  21  63.6 _  N e v e r active  12  36.4  convenience only option  14  42.4  2  6 1  distance  8  24.2  safety from strangers o r b u l  9  27.3  e a s i e s t daily s c h e d u l e  3  9,1  cost  0  0.0  safety from traffic  4  12.1  opportunity for exerci s e  7  21.2  better for environment  1  3.0  child's p r e f e r e n c e other  3  9.1  0  0.0  Mode = walk  Mode = walk  n/a  R e a s o n s Cited for Travel Choice  Active NonSchool Trips  never  7  21.2  < 1 time p e r w e e k  10  30.3  1-3 t i m e s p e r w e e k  14  42.4  4 or m o r e t i m e s per w e e k  2  6.1  Mode = <1 time per week  APPENDIX F-220  BRENTWOOD PARK ELEMENTARY N=33 - -  PERCEPTION OF SAFETY  Variable Category Parental Percept ion Questions  Frequency -.  •  "  -  •  Neighbourhood  1 - strongly a g r e e  9  27.3  safe for child to walk.  2 - somewhat agree  19  57.6  3- s o m e w h a t d i s a g r e e  4  12.1  4 - strongly d i s a g r e e  1  3.0  Child safe from  1 - strongly a g r e e  3  9.1  traffic while 2 - s o m e w h a t agree. walking to school.  18  54.5  3 - somewhat disagree  11  33.3  4- strongly d i s a g r e e  1  3.0  Child safe from  1 - strongly a g r e e  strangers/bullies while walking to school.  2 - somewhat agree  4  12.1  .16  48.5  3 - somewhat disagree  7  21.2  4- strongly d i s a g r e e  6/  18.2  Driving my child is 1 - strongly a g r e e an important 2 - somewhat agree responsibility as a 3 - somewhat disagree parent.  4 - strongly d i s a g r e e  Our house is too  1 - strongly a g r e e  11_  Central Tendency:  Percent  M e a n = 1.91  Mean = 2^30  Mean = 2.45  _ 33.3  9  27.3  9  2/3  4  12.1  1  3.0  5  15.2  far from school for 2 - somewhat agree my child to walk 3 - somewhat disagree or ride their 4 - strongly d i s a g r e e hirvcle  6  18.2  21  63.6  Have your  16  48.5  No When 1 walk in my neighbourhood:  17  51.5  i feel safe from  A g r e e a lot  11  33.3  cars  A g r e e a little  12  36.4  Don't a g r e e  1Q  30.3  1 feel safe from  A g r e e a lot  5  15.2-  strangers and bullies.  A g r e e a little  15  45.5  Don't a g r e e  13  39.4  It is easy and fun  A g r e e a lot  22  66.7  to walk.  A g r e e a little  9  27.3  Don't a g r e e  2  6.1  6  18.2  A g r e e a little  17  51.5  Don't a g r e e  10  30.3  Mean = 2.18  Mean = 3.42  Child's Perceptio ii Questions Yes "  teachers encouraged you to walk, cycle or other active mode to get to school?  1 feel safe walking A g r e e a lot by myself.  n/a  1.97  2.24  •  APPENDIX  1.39  2.12  F-221  BRENTWOOD PARK ELEMENTARY MICRO-SCALE BUILT ENVIRONMENT Street Segments n=31 Variable -Category Total Lanes  Fiequency  2 3  4  Street Grade  Traffic Calming  Buffer  5 6 Flat Slight . Moderate Steep No elements 1 element 2 elements 3 elements None One side Both sides  Sidewalk (longest side) None 1-25% 26-50% 51-75% 76-99% 100% . n-28 •:• Intersections Intersection Type T-type 4-way Traffic Control None Yeild or roundabout Stop sign Lights Crosswalk Marking (proportion of legs with) None 1 of 4 1 of 3 2 of 4 2 of 3 3 of 4 All Crosswalk Signage (proportion of legs with) None 1 of 4 1 of 3 2 of 4 2 of 3 3 of 4 . All  ~"  25 0 2 0 1 6 13 7 2 18 " 9 1  Mean  Stcl Dev  2.290  0.897  1.179  0.863  0.56695 —  ~  23 5 0  0.179  0.39  3 0 0 0 0 25  4.464  1.575  12 16. 1 0 23 4  1.570  0.504  2.071  0.539  13.393  32.262  23 1 0 1 0 0 3  ;  28 0 0 0 0 0  _____  0.000  0  o "" APPENDIX F-222  BRENTWOOD PARK ELEMENTARY  Intersections Continued Variable  Category  Frequency  Mean  24 0 1 0 3  12.500  Frequency  Percent  0 30 3 0  0.0 90.9 9.1 0.0  Pedestrian Button (proportion of legs with) None 1 of 3 2 of 4 2 of 3 All  Built Environment Scores n=33  Walkability Score (Quartiled) 1 2 3 4~ Lowest Walkability Score (Quartiled) 1 2 ,: _ . 3 A  0 23 w " "  ~  o  0.0 69.7 ~"30.3"~ 0.0  Std Dev  32.275  Central Tendency  Mean = 2,09  Mean = 2.30 —  -  A P P E N D I X F-223  HATZIC ELEMENTARY N=20  ..  DEMOGRAPHICS Variable Gender [Age  Distance From School  Category Boys Girls 8 9 10 11  Number HH Vehicles  :  t  Central Ten<lency Percent 45.0 n/a 55.0 0.0 Mean = 9.4 65.0 30.0 " " 5.0  :  <500m  6  30.0  500m-1km  5  25.0  1-1.5km  4  20.0  2  10.0  3  15.0  •1:5-2km 2-2.5km HH Income  _ _  Fiequency 9 11 0 13. 6 ' t  • -  ~ . " " " ~ "  <$19,999  _ _ . _J  .  50  $20,000-$29,999  0  $30,000-$39.999  1  5.0  $40,000-$49,999  1  5.0  $50,000-$59.999  2  10.0  $60,000-$69,999  6  30.0  T  5.0  $80,000-$89,999~~""  3 .  15.0  1  >$100,000  A  None 1. vehicle 2 vehicles  __  Mean = $60$69,000  0.0  $70,000-$79,999 $90,000-$99.999  Mode = <500rh  5.0 20.0  ...  0  0.0  Mean = 2.3  . 3  15.0  Mode = 2  11  :  55.0  3 vehicles  3  15.0  4 or m o r e v e h i c l e s  3  15.0  APPENDIX F-224  HATZIC ELEMENTARY  N=20  (  TRAVEL BEHAVIOUR " : Variable  j I  Category  Frequency  Percent  .8  40.0  Driven  10  50.0  School Bus  0  0.0  Other Active M o d e  2  10.0  P u b l i c Transit Other  0  0.0  0  0.0  Multiple S e l e c t i o n s  0  0.0  Walk  9  45.0  Driven  9  45.0  School Bus  0  0.0  Other Active M o d e  2  10.0  P u b l i c Transit  0  0.0  0  0.0  0  0.0  10  50.0  Drive  6  30.0  S c h o o l bus  0  0.0  B i k e or other active m o d e  4  20.0  Multiple r e s p o n s e s  0  0.0  Active one or two w a y s  12  60.0 .  N e v e r active  8  40.0  11  55.0  Mode of Travel To School Walk  —  Mode of Travel From School  Other Multiple S e l e c t i o n s Favourite Mode of Travel Walk  Active Travel  Reasons Cited for Travel Choice convenience  —  . . — _  Active NonSchool Trips  —  _  only option  3  15.0  distance  7  35.0  safety from strangers or bul  4  20.0  e a s i e s t daily s c h e d u l e cost  2  10.0  0  0.0  safety from traffic  2  10.0  opportunity for e x e r c i s e  4  20.0  better for environment  0  0.0  child's preference other  3  15.0  0  0.0  never  6  30.0  < 1 time per w e e k  3  15.0  1-3 t i m e s per w e e k  10  50.0  4 or m o r e t i m e s per w e e k  i  5.0  Central Tendency Mode = Driven by car  Mode = walk/drive tied -  Mode = walk  n/a  —  — - —  Mode = 1-3 times per week  A P P E N D I X F-225  HATZIC ELEMENTARY N=20 PERCEPTION OF SAFETY Variable Category Parental Perception Questions  Frequency  Percent  Neighbourhood  1 - strongly a g r e e  10  50.0 '  safe for child to walk.  2 - somewhat agree  9  45.0  3 - somewhat disagree  1  5.0  0  0.0  6  30.0  11 .  55.0  4 - strongly d i s a g r e e Child safe from  -  1 - strongly a g r e e  traffic while 2 - somewhat agree walking to school.  3 - somewhat disagree  4 - strongly di s a g r e e Child safe from strangers/bullies while walking to school.  - 1  _ ;  2  _  ; _  5  25.0 55.0  3 - somewhat disagree  4  20.0  4- strongly d i s a g r e e  0  0.0  I  Driving my child is 1 - strongly a g r e e an important 2 - somewhat agree responsibility as a 3 - somewhat disagree parent.  3  15.0  9  45.0  4  20.0  4 - strongly d i s a g r e e  4  20.0  Our house is too  1 - strongly a g r e e  2  10.0  3  15.0  far from school for 2 - s o m e w h a t a g r e e my child to walk 3 - somewhat disagree or ride their  3  15.0  4- strongly d i s a g r e e hirvrlp. . -Child's Perception Questions  12  60.0  Have your  11  55.0  No When 1 walk in my neighbourhood:  9  45.0  1 feel safe from  A g r e e a lot  8  40.0  cars  A g r e e a little  10  50.0  Don't a g r e e  2  10.0  1 feel safe from  A g r e e a lot  3  15.0  strangers and bullies.  A g r e e a little  10  50.0  Don't a g r e e  7  35.0  It is easy and fun  A g r e e a lot  16  80.0  to walk.  A g r e e a little  2  10.0  Don't a g r e e  2  10.0  5  25.0  A g r e e a little  7  35.0  Don't a g r e e  8  40,0  Yes  Mean = 1.95  5.0  11  e  Mean = 1.55  10.0  2- s o m e w h a t a g r e e  Iz.Mi° OQJy §9E.§._.  Central Tendency  Mean = 1.95  -  —  Mean = 2.45  Mean = 3.25  n/a  teachers encouraged you to walk, cycle or other active mode to get to school?  1 feel safe walking A g r e e a lot • by myself.  Mean = 1.70  Mean = 2.20  M e a n = 1.30  Mean = 2 . 1 5  APPENDIX F-226  HATZIC ELEMENTARY .  MICRO-SCALE BUILT ENVIRONMENT  Street Segments n=31 • Variable Category Total Lanes 2 3 4 5 6 Street Grade Flat Slight Moderate Steep Traffic Calming No elements 1 element 2 elements 3 elements Buffer None One side Both sides Sidewalk (longest side) None 1-25% 26-50% 51-75% 76-99% 100% = ,^•r.--y..^ Intersections Intersection Type T-type 4-way Traffic Control None Yeild or roundabout Stop sign , Lights Crosswalk Marking (proportion of legs with) None 1 of 4 1 of 3 2 of4 2 of 3 3 of 4 All Crosswalk Signage (proportion of legs with) None 1 of4 1 of 3 2 of 4 2 of 3 3 of 4 All ri  23  frequency 23 0 0 0 0 11 3 5 4 19 3 0 1 9 " ~ ' "  •  -  Mean  Std Dev  2.000  0  1.087  1.203  0.261  0.689  0.957  0.878  0.913  1.564  19 4 5 1 17 0  1.170  0.388  1.522  0.846  21 0  5.797  21.677  4.348  20.851  6 8 15 3  r  1 2 1 ,. y 7  1 0 0 0 1  22 0 0 0 0 0  ~"~T~"" ~ APPENDIX F-227  HATZIC ELEMENTARY  Intersections Continued Variable  ,  Category  Frequency  Mean  23 0 . 0 ' 0' • 0  0.000  Frequency  Percent  Pedestrian Button (proportion of legs with) None 1 of 3 2 of 4 2 of 3 All  Built Environment Scores n=20 Walkability Score (Quartiled) 1 2 3  4 Lowest Walkability Score 1 (Quartiled) 2 3  4  _  2 12 6 "  10.0 60.0 30.0  o  oo  9 11 0 0  45.0 55.0 0.0 0.0  St.l Dev  0  Central Tendency  Mean = 2.2  Mean = 1.55  A P P E N D I X F-228  MARLBOROUGH ELEMENTARY N=47  DEMOGRAPHICS Variable Gender Age  Distance From School  HH Income:  Category Boys Girls 8 9 10 11  Frequency 28 19 ' 2 20 25 0  <500m  32  68:1  5.00m-1km 1-1.5km  15  31:9  0  0.0.  1,5:2km  0  0.0  2-2:5km  _0 6  12.8  $20,000429,999  8  17.0  $.30,000439,999'  8  17.0  $40,000449,999"  10  21.3  $50.000459,999  3  6.4  $60,000-$69,999  •6 .2  12.8  $90,000499.999 >$ 1 0 0 , 0 0 0  0  _ .  ,2 .  Central . Tendency n/a Mean = 9.48  Mode = <500m  0.0. .  <$19..999  $70,000-$79,999 $80,000489,999  Number HH Vehicles  Percent 59.6 40.4 4.3 42.6 53.2 ' "576"  Mean = $40$49,000  "4.3 0.0 4.3. 4.3  2  None  '4.  8.5  Mean =1.26  1 vehicle  27  5/.4J  Mode. = 1  2 vehicles  ___16_  ._  34.0  3 vehicles  0  0.0  4 or more v e h i c l e s  0  0.0  APPENDIX F-229  MARLBOROUGH ELEMENTARY  N=47  TRAVEL BEHAVIOUR  Variable  Category  Mode of Travel To School Walk  '  Frequency  61.7  Driven  14  29.8  School Bus  0  0.0  Other Active M o d e  0  0.0  P u b l i c Transit  0  0.0  Other  0  Multiple^  4  8.5  Walk  32  fin  Driven  13  27.7  School Bus  0_  0.0  Other Active M o d e  0  0.0  P u b l i c Transit  0  0.0  Other  0  LIU  Multiple S e l e c t i o n s  2  4.3  Favourite Mode of Travel Walk  33  70.2  Drive  6  12.8  -  Mode of Travel From School  —  _ ;  0.0  1  S c h o o l bus  0  0.0  B i k e or other active m o d e  6  12.8  Multiple r e s p o n s e s  2  4.3  Active one or two w a y s  33  70.2  N e v e r active  14  29.8  Reasons Cited for Travel Choice convenience  20  43.5  Active Travel  Active NonSchool Trips  only option  2 _  4.3  distance  20  43.5  safety from strangers or bul  10  21.7  e a s i e s t daily s c h e d u l e  8  17.4  cost  1  2.2  safety from traffic  8  17:4  opportunity for e x e r c i s e  7  15.2  better for environment  0  0.0  child's preference other  0  0.0  0  0.0  never  4  8.5  < 1 time per w e e k  17  36.2  1-3 t i m e s per w e e k  19  40.4  4 or m o r e t i m e s per w e e k  7  14.9 •  '  Central f entlency  Percent  29  —  '  i''  Mode = walk  —  :  -  Mode = walk  Mode = walk  n/a  Mode = < 1 time per week  APPENDIX F-230  MARLBOROUGH ELEMENTARY  N=47  PERCEPTION OF SAFETY Variable Category Parental Perception Questions Neighbourhood 1 - strongly a g r e e safe for child to 2 - somewhat agree walk. 3 - somewhat disagree 4 - strongly d i s a g r e e  Percent  10  21.3  29  61.7  6  12.8 4.3  9  19.1  21  44.7  12  25.5  4 - strongly d i s a g r e e  5  10.6  1 - strongly a g r e e  4  8_5_ _  2 - s o m e w h a t agre<  22  46.8  3 - somewhat disagree  14  29.8  4 - strongly d i s a g r e e Driving my child is 1 - strongly a g r e e an important 2 - somewhat agree responsibility as a 3 - somewhat disagree parent. 4 - strongly d i s a g r e e Our house is too 1 - strongly a g r e e far from school for 2 - somewhat agree my child to walk 3 - somewhat disagree or ride their 4- strongly d i s a g r e e hir.ynle Child's Perceptio n Questions Have your Yes teachers encouraged you to walk, cycle or other active mode to get to school? No When 1 walk in n iy neighbourhood: 1 feel safe from A g r e e a lot cars A g r e e a little 1 feel safe from strangers and bullies.  Frequency  2  Child safe from 1 - strongly a g r e e traffic while 2 - somewhat agree walking to school. 3 - somewhat disagree Child safe from strangers/bullies while walking to school.  ,  7  14.9  15  31.9  17  36.2  8  17.0  7  14.9  0  0.0  3  6.4  8  17.0  36  76.6  12  25.5  35  74.5  20  42.6  23  48.9  Don't a g r e e  4  8:5  A g r e e a lot  13  27.7  A g r e e a little  21  44.7  Don't a g r e e  13  27.7  It is easy and fun A g r e e a lot to walk. A g r e e a little Don't a g r e e 1 feel safe walking A g r e e a lot by myself. A g r e e a little Don't a g r e e  34  72.3  12  25.5  1  2.1  12  25.5  20  42.6  15  31.9  Central Tendency Mean = 1.98  Mean = 2.26  Mean = 2 : 5 0  Mean = 2.13  Mean = 3.70  n/a  Mean = 1 . 6 5  M e a n = 1.98  Mean = 1.30  Mean = 2.07  APPENDIX F-231  MARLBOROUGH ELEMENTARY MICRO-SCALE BUILT ENVIRONMENT | Street Segments ri=3T • Variable ,'Category Total Lanes  Street Grade  Traffic Calming —  Buffer  —  - —  Sidewalk (longest side) None 1-25% 26-50% 51-75% i 76-99% 100% Intersections 11=29 Intersection Type t-type 4-way Traffic Control None Yeild or roundabout Stop sign Lights Crosswalk Marking (proportion of legs with) None 1 of 4 1 of 3 2 of 4 2 of 3 3 of 4 All Crosswalk Signage (proportion of legs with) None _. . _ 1 of 4  •  '  Frequency  Mean  19 2 6 1 1 8 11 9 1 22 6 1 0 13 4 12  2 7/0  0.966  0.944  3 1 0 0 0 25 -  4.345  1.675  17 •12 1 1 21 6  1.4  0.501  2.103  IZZZZMil  2 3 4 5 6 Flat Slight Moderate Steep No elements 1 element 2 elements 3 elements None One side Both sides  1 of 3 2 of 4 2 of 3 3 of 4 All  '  20 0 • 3 0 0 0 6  28 0 0 0 1 0 0  St<l Dev 1.131 -  1.103  0.86  0.276 -  0.52757  24.138  40.724  2.299  —-•-  12.38  --  ;  A P P E N D I X F-232  MARLBOROUGH ELEMENTARY  Intersections Continued Variable.  Category  Frequency  Mean  21  19.540  Pedestrian Button (proportion of legs with) None  Std Dev  35.931  -2 2 0 4  2 of 4 2 of 3 All  j Built Environment. Scores n=47  Percent  0 11 22 14  0.0 23.4 46.8 29.8  Mean = 3.06  0 20 14 13  0.0 42.6 29.8 27.7  Mean = 2.85  Walkability Score (Quartiled) 1  r  "  n 3 4  Lowest Walkability Score (Quartiled) 1 \2 3 4  Central Tendency  Frequency  ,  A P P E N D I X F-233  MISSION CENTRAL ELEMENTARY N=20  DEMOGRAPHICS Variable Gender Age  .  Distance From School  -  HH Income  Number.HH Vehicles.  Category Boys Girls 8 9 10 11  Frequency 7 13 1 9 10 0  Percent 35.0 65.0 5.0 45.0 50.0 0.0  Central Tendency n/a Mean = 9.45  <500m  4  20.0  5 0 0 m - Tkm  10  50:0  1-1.5km  3 ,  15.0  1,5-2km  3  15.0  2-2.5km  0  0.0  <$ 1 9 , 9 9 9  4  20.0  $20,000-$29,999  3  15.0  $30,000-$39,999:  2  10.0  $40.000-$49.999  •2  10.0  $50,000-159,999  3  15,0  $60,000-$69,999  0  0.0 _  $70,000-$79,999  1  5.0  $80,000-$89,999  2  10 0 .  $90,000-$99,999  1  5^0  >$100,000  .2  10.0  None  2  10.0  Mean = 1.4  1 vehicle  9  45.0  Mode = 1  2 vehicles  8 .  40.0  3 vehicles  1  5.0  4 or m o r e v e h i c l e s  0  0,0  500-1 km  Mean = $40$49,000  A P P E N D I X F-234  MISSION CENTRAL ELEMENTARY N=20 T R A V E L  Variable  B E H A V I O U R  Category  Mode of Travel To School Walk  Mode of Travel From School  10  50.0  9  45.0''  School Bus  1  5.0.  Other Active M o d e  0  0.0  P u b l i c Transit Other  0  Multiple S e l e c t i o n s  0  0.0  Walk  6  30.0  Driven  10  50.0 "  School Bus  3  15.0  Other Active M o d e  0  0.0  P u b l i c Transit  0  0.0  Other  0  0.0  Multiple S e l e c t i o n s  1  5.0  6  30.0  Drive  11  55.0  S c h o o l bus.  0  0.0  B i k e or other active m o d e Multiple r e s p o n s e s  3  15.0  0  0.0  Active one or two w a y s  10  50:0  N e v e r active  10  50.0  6  30.0  only option  5  25.0  distance  4  20.0  safety from strangers or bul  3  15.0  e a s i e s t daily s c h e d u l e  2  10.0  cost  2  10.0  safety from traffic  1  5.0  Reasons Cited for Travel Choice convenience  Active NonSchool Trips  Percent  Driven  Favourite Mode of Travel Walk  Active Travel  Frequency  0  Central Tendency Mode = walk  0.0 _  O.U  opportunity for e x e r c i s e  1  5.0  better for environment  4  20.0  child's p r e f e r e n c e other  0  0.0  1  5.0  never  5  25.0  < 1 time per w e e k  5  25.0  1-3 t i m e s per w e e k  7  35.0  4 or m o r e t i m e s per w e e k  3  15.0  Mode = driven by car  Mode = driven  n/a  M o d e = 1-3 times per week  A P P E N D I X F-235  MISSION CENTRAL ELEMENTARY N=20 PERCEPTION OF SAFETY Variable Category Parental Perception Questions  Frequency  Percent  Neighbourhood  1 - strongly a g r e e  6  30.0  safe for child to walk.  2 - somewhat agree  9  45.0  Child safe from  3 - somewhat disagree  2  10.0  4 - strongly d i s a g r e e  3  15.0  1 - strongly a g r e e  •6  30.0  traffic while 2 - somewhat agree walking to school.  8  40.0  3 - somewhat disagree  2  10.0  4 - strongly d i s a g r e e  4  20.0  Child safe from  1 - strongly a g r e e  4  20.0  strangers/bullies while walking to school.  2 - somewhat agree  8  40.0  3 - somewhat disagree  .5  strongly d i s a g r e e  3  4.-  Driving my child is 1 - strongly a g r e e an important 2 - somewhat agree responsibility as a 3 - somewhat disagree parent. Our house is too far from school for my child to walk or ride their hinvrle  _  Mean = 2.20 -  Mean = 2.35  15.0  4  20.0  6  30.0  6  30.0  4  20.0  1 - strongly a g r e e  3  15.0  2 - somewhat agree  1  5.0  4  20.0  4 - strongly d i s a g r e e Child's Peiceptio n Questions  12  60.0 0.0  Have your  5  25,0  No When 1 walk in my neighbourhood:  15  75.0 0.0  1 feel safe from  A g r e e a lot  9  45.0  cars  A g r e e a little  6  30.0  Don't a g r e e  •5  25.0  Yes  Mean = 2.10  25.0 _  4 - strongly d i s a g r e e  3 - somewhat disagree  Central Tendency  Mean = 2.50  Mean = 3.25  ,  (  n/a  teachers encouraged you to walk, cycle or other active mode to get to school?  1 feel safe from  A g r e e a lot  strangers and bullies.  A g r e e a little  It is easy and fun to walk.  8  40.0  .5  25.0  Don't a g r e e  7  35.0  A g r e e a lot  14  70.0  A g r e e a little  5  25.0  Don't a g r e e  1  5.0  4  20.0  A g r e e a little  10  50.0  Don't a g r e e  6  30.0  i feel safe walking A g r e e a lot by myself.  Mean = 1 . 8  M e a n = 1.95  M e a n = 1.35  Mean = 2.10  APPENDIX F-236  MISSION CENTRAL ELEMENTARY MICRO-SCALE BUILT ENVIRONMENT Street Segments n=31 Variable Category Total Lanes  Street Grade  Traffic Calming  Buffer  2 3 4 5 6 Flat Slight Moderate Steep No elements 1 element 2 elements 3 elements None One side Both sides  "  Mean  25 4 1 0 0 6 14 5 5 24 " 0 1 12 9  2.200  0.484  1.300  0.988  0.3EJ7  0.639  0.900  0.845  5  Sidewalk (longest side) None 1-25% 26-50% 51-75% 76-99% 100% Intersections h=30 Intersection Type T-type 4-way Traffic Control None Yeild or roundabout Stop sign Lights Crosswalk Marking (proportion of legs with) None 1 of4 1 of3 2 of4 2 of3 3 of4 All Crosswalk Signage (proportion of legs with) None 1 of4 1 of3 2 of4 2 of3 3 of4 All  St<l Dev  Frequency  -  —  13 0 0 0 0 25  2.830  2.52  10 20 .3 0  1.670  0.479  1.900  0.712  11.458  25.515  9.722  18.169  24 3  13 5 ~ ~  1 3 1 3 4  15 9 1 . 2 2 0 1  APPENDIX F-237  MISSION CENTRAL ELEMENTARY Intersections Continued Variable  Category  Mean  28 0 0 0 1  8.333  Frequency  Percent  0 12  Mean = 2.4  0  0.0 60.0 40.0 0.0  5 12 3 0  25.0 60.0 15.0 0.0  Mean = 1.9  Pedestrian Button (proportion of legs with) None 1 of 3 2 of 4 2 of 3 All  -  Built Environment Scoies n=20 Walkability Score (Quartiled) 1 2 3~ 4 Lowest Walkability Score (Quartiled) 1 2 3 4  "  Std Dev  Frequency  '  24.077  Central Tendency  A P P E N D I X F-238  WALTER MOBERLY ELEMENTARY  N=52  DEMOGRAPHICS Vvi liable Gender Age  Distance From School  Category Boys Girls 8 9 10 11  Fiequency 24 .28 . 0 24 ' .25, " 3  Pei cent 46.2 53.8 0.0 46.2 48.1 . 5J3;  <500m  31  59.6  5 0 0 m - 1 k m '•  21  1-1.5km  I I  1 .5-2km 2-2.5km  _  Central Tendency n/a iy^n'=~T61  Mode = < 500rn :  40.4 o__ ' _  :  -o  0  0  9  17.3  10  19.2  $40,000-$49,999  7 11  13.5 21,2  $50,000-$59,999  6  $60,000-$69,999' $70,000-$79,999 $80,000-$89,99.9  3  11.5 5.8  Mean = $30HH Income  <$19.999 $20,000-$29,999 $30,000-$39,999  $90.0004.99.999 >$ 1 0 0 , 0 0 0 Number HH Vehicles  3 1 1 1  '  None  27  2 vehicles  .21 2  .3 v e h i c l e s _ _ . .' 4 or m o r e v e h i c l e s  ___'„_  1  -  5.8 ' 1.9 T.9 1.9  1  1 vehicle  i?§.fflO._  .  Mean = 1.49_.  1.9 51,9  Mode = 1  .40.4 __J3JL_ 1.9  APPENDIX F-239  WALTER MOBERLY ELEMENTARY N=52 -  TRAVEL BEHAVIOUR  Variable  Category  Frequency  Percent  29  55.8  Driven  18  34.6  School Bus  1.  1.9  Other. Active M o d e  0  0.0  PujDli c^.Transit  0  • 0.0  Other  0  0.0  Multiple S e l e c t i o n s  4  7.7  Mode of Travel To School Walk  Mode of Travel From School  Walk  __34  65.4  Driven  14  26.9  School Bus  0  0.0  Other A c t i v e M o d e  0  0.0  P u b l i c Transit  0  0.0  Other  1  1.9  Multiple S e l e c t i o n s  3  5.8  Favourite Mode of Travel Walk  32  61.5  Drive  15  28.8  S c h o o l bus  0  0.0  B i k e or other active m o d e  4  7.7  Multiple r e s p o n s e s Active one or two w a y s  1  1.9  39  75.0  N e v e r active  13  25.0  Reasons Cited for Travel Choice convenience  15  29.4  Active Travel  only option  Active NonSchool Trips  _ 7  13.7  distance  9  17.6  safety from strangers or bul  11  21.6  e a s i e s t daily s c h e d u l e  3  5.9  cost  0  0.0  safety from traffic  5  98  opportunity for e x e r c i s e  9  17.6  better for environment  1  2.0  child's preference other  13  25.5  1  2.0  never  17  32.7  < 1 time per w e e k  20  38.5  1-3 t i m e s per w e e k  6  11.5  4 or m o r e t i m e s p e r w e e k  9  17.3  Central Tendency Mode = walk  Mode = walk _  Mode = walk  n/a  Mode - <1 time per week  APPENDIX F-240  WALTER MOBERLY ELEMENTARY N=52 PERCEPTION OF SAFETY. Variable Category P.iiental Perception Questions Neighbourhood safe for child to walk.  Child safe from  ' •;'  Frequency  Percent  1 - strongly a g r e e  21  40.4  2 - somewhat agree  22  42.3  3 - somewhat disagree  5  9.6  4 - strongly d i s a g r e e  4 .  7.7  1 - strongly a g r e e  15  28.8  21  40.4  3 - somewhat disagree  11  21.2  4 - strongly d i s a g r e e  5  9.6  traffic while 2 - somewhat agree walking to school.  Child safe from  1 - strongly a g r e e  12  23.1  strangers/bullies while walking to school.  2 - somewhat agree  21  40.4  3 - somewhat disagree  8  15.4  4- strongly d i s a g r e e  11  21.2  Driving my child is 1 - strongly a g r e e an important 2 - somewhat agree responsibility as a 3 - somewhat disagree parent.  30  57.7  13  25.U  7  13.5  4 - strongly d i s a g r e e  2  3.8  Our.house is too  1 - strongly a g r e e  4  7.7  2  3.8  far from school for 2 - somewhat agree my child to walk 3 - somewhat disagree or ride their 4 - strongly d i s a g r e e hinvnle  Child's Perceptio ii Questions Have your Yes  teachers encouraged you to walk, cycle or other active mode to get to school?  17  32.7  29  55.8  25  48.1  No When 1 walk in my neighbourhood:  27  1 feel safe from  A g r e e a lot  26  50.0  cars  A g r e e a little  18  34.6  Don't a g r e e  8  15.4  1 feel safe from  A g r e e a lot  20  38.5  strangers and bullies.  A g r e e a little  12  23.1  Don't a g r e e  20  38.5  It is easy and fun  A g r e e a lot  39  75.0  to walk.  A g r e e a little •  12  23.1  •  Don't a g r e e  M e a n = 1.86  Mean = 2.12  Mean = 2.33  Mean = 1.65  Mean = 3.37  n/a  51.9 .  -  1  1.9  8  15.4  A g r e e a little  21  40.4  Don't a g r e e  23  44.2  1 feel safe walking A g r e e a lot by myself  '  Central Tendency  Mean = 1.67  Mean = 2.00  M e a n = 1.27  Mean = 2.29  APPENDIX  F-241  WALTER MOBERLY ELEMENTARY MICRO-SCALE BUILT ENVIRONMENT  j i.  •  1 Street Segments n=31 |Variable Cateqoiy Total Lanes  Street Grade  Traffic Calming  Buffer  2 3 4 5 6 flat Slight Moderate Steep  "  '  ~  No elements__ 1 element 2 elements 3 elements None One side Both sides  Sidewalk (longest side) None 1-25% 26-50% 51-75% 76-99% 100%  Frequency;  Mean  25 0 2 0 2 13 6 7 3 19 9 1 0 2' 4 23  2.410  Std Dev 1.119  1.000  1.069  0.379  0.561  1 0 1 0 1 26  4.690  9 15 0 2 19 3  1.630  0.495  2.042  0.464  1.724  _  1073  ;-"^v.Z  Intersections n=24 Intersection Type T-type 4-way Traffic Control None Yeild or roundabout Stop sign Lights Crosswalk Marking (proportion of legs with) None 1 of 3 2 of 4 2 of 3  19 1 0 3 0  3 of 4 All  0 1  1 of 4  Crosswalk Signage (proportion of legs with) None 1 of 4 1 of 3 2 of 4 2 of 3 3 of 4 All  18 2 1 3 0 0 0  -  —  -.  11.458  -  25.515  -  9.722  18.169  APPENDIX F-242  WALTER MOBERLY ELEMENTARY Intersections Continued Variable  Category  Pedestrian Button (proportion of legs with) None  1 of 3 2 of 4 2 of 3 All  Built Environment Scores n=52 Walkability Score (Quartiled) 1 2 3 4 Lowest Walkability Score (Quartiled) 1 2 3 4  Std Dev  Frequency  Mean  21 0 2 0 1  8.333  Frequency  Percent  Central Tendency  0  0.0  Mean = 3.5  2 . 21 29  3.8 40.4 55.8  0 8 25 19  0.0 15.4 48.1 36.5  24.077  Mean = 3.2  A P P E N D I X F-243  

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