The Impact of Safety on Walk-to-School Behavior:
Analysis of Local Safe Routes to School Program Data
Dissertation
Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy
in the Graduate School of The Ohio State University
By
Katherine Swidarski
Graduate Program in Public Health
The Ohio State University
2018
Dissertation Committee
Elizabeth Klein, PhD, MPH
Phyllis Pirie, PhD
Elisabeth Root, PhD, MPH
1
Copyrighted by
Katherine Swidarski
2018
2
Abstract Introduction: Lack of physical activity and unintentional injury are leading causes of morbidity among children and associated with significant disadvantages physically, socially and academically. Safety barriers and parental perceptions of safety can prevent children from obtaining the benefits of daily physical activity, like walking to school.
Programs that promote walking to school, such as the evidence-based Safe Routes to
School (SRTS) program, can alleviate physical barriers to safety in the environment and increase opportunities for being active. Supportive SRTS policies at all levels of government can design safer streets and lead to institutionalization of the program. The purpose of this study is to better understand objective and perceived safety factors that influence walk to school behavior among elementary school families and assess how policies may impact the opportunity for children to safely walk to school.
Methods: Multiple methods, motivated by a socioecological framework, were used to investigate safety factors, including speed of traffic, amount of traffic, sidewalk continuity, safety of intersections, and presence of registered sex offenders. Data on parental perceptions of safety (n=10,810) from cross-sectional SRTS surveys collected by a total of 82 schools in three locations, and corresponding objective safety from online repositories for the area within 1-mile of school locations, were used to quantify safety.
First, spatial distribution of safety was explored through a combination of spatial and non-spatial analyses using location data for parents, schools and safety factors. Then, multi-level logistic regression models were built to identify factors associated with the outcome of walking to school. Finally, a review of local, regional, state and federal ii education and transportation policies was conducted to measure inclusion of child pedestrian language and seven effective policy components adapted from a SRTS guide.
Results: Approximately half of parents’ perceptions were mismatched with the objective measure of safety for all factors except amount of traffic. All three programs had a high density of unsafe speed around schools, but the density of perceived lack of safety was consistent across factors and programs. Joint count analysis found spatial patterning of safety varied among SRTS programs. In logistic regression analyses, odds of walking to school (versus driving or using any other mode) changed significantly for a single unit increase/decrease in safety and salient safety factors differed across programs. Review of
SRTS policies revealed no school level policies directly addressing walking to school as a form of transportation and an absence of pedestrian-specific language within policies at all levels. Policies were also frequently missing at least one component for more effectively providing opportunities for children to safely walk to school.
Discussion: This study provides critical considerations about traffic, neighborhood and policy influences on safety. Objective and perceived safety need to be considered together to address barriers keeping children from safely walking to school. SRTS survey data can be useful in that process. These data reveal significant, location-specific factors that influence a family’s choice to walk. Results also indicate that policies need to be better designed to explicitly promote health and prevent injury of children.
iii Dedication This document is dedicated to my family.
iv Acknowledgments I would like to thank the committee, Dr. Klein, Dr. Pirie, and Dr. Root, for their guidance throughout the course of this research and for their enthusiasm toward the content.
Many thanks to the local Safe Routes to School program team members in San
Francisco, Miami-Dade County and Columbus for their efforts to create and promote safe routes for all.
I also want to extend my gratitude to friends, staff, faculty, and fellow doctoral students across all Divisions of the College of Public Health for their assistance and tremendous support.
v Vita
June 2005 ...... Cuyahoga Heights High School
2009...... B.A. Psychology, University of Rochester
2011...... M.P.H Epidemiology, University of Miami
2015 to 2017 ...... Graduate Teaching Associate, Department
of Health Behavior and Health Promotion,
The Ohio State University
Publications
McAdams RJ, Swidarski K, Clark RM, Roberts KJ, Yang J, Mckenzie LB. Bicycle- related injuries among children treated in US emergency departments, 2006-2015. Accid
Anal Prev 2018;118:11–7. doi:10.1016/j.aap.2018.05.019.
Fields of Study
Major Field: Public Health
vi Table of Contents
Abstract ...... ii
Dedication ...... iv
Acknowledgments...... v
Vita ...... vi
Publications ...... vi
Fields of Study ...... vi
List of Tables ...... xiii
List of Figures ...... xv
Chapter 1. Introduction ...... 1
Background and Significance ...... 1
Knowledge Gap ...... 5
Structure of the Dissertation ...... 9
Chapter 2. Background and Literature Overview ...... 11
Research Design and Methods of Previous Studies ...... 11
Safe Routes to School ...... 15
Spatial Analyses ...... 20
Multilevel Analyses ...... 22
vii Parental Perceptions of Traffic and Neighborhood Safety ...... 25
Traffic Safety Barriers for Walking to School ...... 27
Neighborhood Safety Barriers for Walking to School ...... 30
Personal Correlates of Walking to School ...... 31
Other Correlates of Walking to School ...... 33
Role of Policy to Support Promotion of Walking to School ...... 34
Summary of Literature ...... 36
Chapter 3. Overview of Research Framework, Data Sources and Approaches ...... 42
Conceptual and Theoretical Frameworks ...... 42
Social Ecological Model ...... 47
Hierarchy of Walking Needs ...... 47
Social Cognitive Theory ...... 51
Broken Windows Theory of Urban Decline ...... 51
Specific Aims ...... 53
Study Design ...... 54
Study Sample ...... 54
San Francisco Safe Routes to School, San Francisco, California ...... 57
WalkSafe Program, Miami-Dade County, Florida ...... 57
Columbus Safe Routes, Columbus, Ohio ...... 58
viii Sample of Schools from Selected Local SRTS Programs ...... 58
Measures and Data Collection Procedures ...... 59
Human Subjects Protection ...... 60
Confidentiality ...... 61
Dataset #1 Safe Routes to School Parent Survey...... 61
Safe Routes to School Parent Survey Overview ...... 61
Data Collection Procedures ...... 62
Potential Limitations from Data Collection ...... 65
Dataset #2 Environmental Factors ...... 66
Data Overview ...... 66
Environmental Safety Factors ...... 67
Potential Limitations from Data Collection ...... 69
Dataset #3 Safe Routes to School Policies ...... 70
Policy Data Overview ...... 70
Categories of Policy ...... 73
Data Collection Procedures ...... 75
Chapter 4. Manuscript #1 ...... 77
Introduction ...... 77
Methods...... 80
ix Study Design ...... 80
Study Sample ...... 80
Measures ...... 82
Data Analysis ...... 87
Results ...... 95
SFSRTS Objective Safety Barriers ...... 97
WalkSafe Objective Safety Barriers ...... 98
Columbus Objective Safety Barriers ...... 98
SFSRTS Perceived Safety Barriers ...... 100
WalkSafe Perceived Safety Barriers ...... 100
Columbus Perceived Safety Barriers ...... 101
Discussion ...... 106
Chapter 5. Manuscript #2 ...... 114
Introduction ...... 114
Methods...... 116
Study Design ...... 116
Study Sample ...... 116
Data Collection and Measures ...... 116
Data Analysis ...... 119
x Results ...... 122
Discussion ...... 135
Chapter 6. Manuscript #3 ...... 144
Introduction ...... 144
Research Methods ...... 147
Study Sample ...... 148
Data Source ...... 148
Measures ...... 149
Data Analysis ...... 155
Results ...... 157
Policy Inventory ...... 157
Policy Scoring ...... 164
Discussion ...... 167
Bibliography ...... 175
Appendix A. Sample of Schools ...... 203
Appendix B. Descriptive Characteristics of Included Schools ...... 206
Appendix C. Safe Routes to School Parent Survey ...... 212
Appendix D. Geoprocessing Technique Flow Process ...... 214
xi Appendix E. Summary of Descriptive Statistics of Variables for SFSRTS Parent Surveys
(%)...... 215
Appendix F. Summary of Descriptive Statistics of Variables for WalkSafe Program
Parent Surveys (%) ...... 217
Appendix G. Summary of Descriptive Statistics of Variables for Columbus SRTS
Program Parent Surveys (%) ...... 218
Appendix H. Grade Level Distribution of SRTS Parent Survey Responses ...... 220
Appendix I. List of Websites Searched for Policy Scan ...... 221
Appendix J. Inventory of Federal Policies ...... 226
Appendix K. Inventory of State Policies ...... 228
Appendix L. Inventory of Regional Policies ...... 232
Appendix M. Inventory of Local Policies...... 234
Appendix N. Inventory of District Policies ...... 238
Appendix O. Inventory of Parent Teacher Association (PTA) Policies ...... 239
Appendix P. Inventory of Relevant Language from Policies ...... 240
Appendix Q. Inventory of Vulnerable Populations Mentioned in Policies ...... 240
Appendix R. Inventory of Relevant Language from Parent Teacher Association Policies
...... 271
Appendix S. Inventory of Relevant Language from School District Wellness Policies 273
Appendix T. Results of Policy Scoring...... 274 xii List of Tables
Table 1. Overview of Safety in the Literature ...... 6
Table 2. Description of SRTS 6-E Model and Sample Program Activities ...... 17
Table 3. Programs and Locations Included in the Overall Study Sample ...... 55
Table 4. Characteristics of Study Locations ...... 57
Table 5. Safety Factors from the Safe Routes to School Parent Survey ...... 67
Table 6. Policy Classification Scheme...... 70
Table 7. Levels of Policy Included in Policy Scan ...... 72
Table 8. Summary of GIS Data Sources ...... 86
Table 9. Summary of Address Matching Process in ArcGIS ...... 88
Table 10. Summary of GIS Measures and Safety Classification for Mapping Purposes . 94
Table 11. Summary of Sample for Mapping ...... 96
Table 12. Join Count Test Result p-values by Dataset and Program (α = 0.05) ...... 103
Table 13. Percent Agreement Between Parental Perception and Objective Safety Datasets
...... 105
Table 14. Summary of Chi-Squared Analysis of Agreement Between Objective and
Perceived Data at the Program Level ...... 106
Table 15. Summary of School Characteristics by Program (Averages) ...... 122
Table 16. Participant Characteristics by SRTS Program ...... 127
Table 17. SFSRTS Multilevel Logistic Regression Model Results ...... 129
Table 18. WalkSafe Multilevel Logistic Regression Model Results ...... 130
Table 19. Columbus Safe Routes Multilevel Logistic Regression Model Results ...... 131 xiii Table 20. Summary of Three Level (Family, School and Program) Logistic Regression
Model Comparing Outcome of Walking to All Other Modes of Travel to School ...... 133
Table 21. Summary of Three Level (Family, School and Program) Logistic Regression
Model Comparing Outcome of Walking to School with Driving a Family Vehicle ...... 135
Table 22. Sample of Healthy People 2020 Topic Areas and Objectives [208] ...... 145
Table 23. Policy Scoring Tool ...... 154
Table 24. Summary of Inter-rater Agreement for Sample Scoring of Policies ...... 157
Table 25. Summary of Policy Scan ...... 159
Table 26. Sample of Relevant Language from Policies ...... 161
Table 27. Summary of School Level Policies ...... 163
Table 28. Summary of Policy Scoring Results ...... 164
Table 29. Results of Policy Scoring by Level...... 166
xiv List of Figures
Figure 1. Diagram of the Conceptual Framework of an Elementary-age Child's Travel
Behavior [83] ...... 24
Figure 2. Conceptual Model for Study ...... 46
Figure 3. Hierarchy of Walking Needs [170] ...... 48
Figure 4. Included Schools for Each Local SRTS Program: (a) SFSRTS, (b) WalkSafe,
(c) CSRTS ...... 59
Figure 5. Map of School Locations for the Local SRTS Programs: (a) SFSRTS, (b)
WalkSafe and (c) CSRTS ...... 82
Figure 6. Interactive Rematching Process Using GIS and Google Maps ...... 91
Figure 7. Visual Summary of Spatial Join to Create Study Area ...... 93
Figure 8. SFSRTS Density of Objective Safety for Speed, Intersections and Crime ...... 97
Figure 9. WalkSafe Density of Objective Safety for Speed, Intersections and Crime ..... 98
Figure 10. CSRTS Density of Objective Safety for Speed, Intersections and Crime ...... 99
Figure 11. SFSRTS Density of Perceived Barriers Speed, Intersections and Crime ...... 100
Figure 12. WalkSafe Density of Perceived Barriers Speed, Intersections and Crime .... 101
Figure 13. CSRTS Density of Perceived Barriers Speed, Intersections and Crime ...... 102
Figure 14. Policy Scan Data Tool ...... 150
xv Chapter 1. Introduction
Background and Significance
Safety concerns have contributed to a steep decline in the number of children and families that choose to walk to school.[1–3] Walking accounted for approximately 13-
29% of home-to-school trips of one mile or less among elementary and middle school children nationally in 2009 compared to 41% in 1969.[4] Walking is the usual mode of travel for only about 25% of elementary school children living within a half-mile of their schools, and has been measured to be as few as 10% on any given day.[5,6]
However, walking to school provides an opportunity for children to benefit physically, socially, emotionally and academically from incidental, daily physical activity.[7,8]
The decrease in utilitarian physical activity, such as walking to school, is one consistently identified factor in the decline in overall physical activity and health in elementary-aged children.[9–11] There have been at least four systematic reviews examining the relationship between active travel to school (walking or biking) and children’s physical activity. A total of 140 studies of moderate, or stronger, evidence were identified among the reviews. Conclusions from these analyses repeatedly found participation in active travel to school was significantly related to amount of physical activity among children and adolescents.[11–14] Individual studies found active travel to school, including walking, contributed to achievement of recommended amounts of physical activity and to participation in daily physical activity.[9,11,15]
Walking delivers both acute, short term effects and cumulative, long term effects, and has few, if any, consequences even as a person ages.[16] Participation in the activity 1 of walking is also protective against the development of chronic disease risk factors.[17]
Although the causes of overweight and obesity in children are complex and multifactorial, less physical activity than recommended contributes to the prevalence of this significant public health problem.[18] A robust comparative analysis, analyzing data from all 50 states and 47 of the largest cities in the US, found statistically significant results indicating active travel, including walking, influences physical activity. A higher frequency of walking trips contributes to more physical activity, overall, and reduces negative health outcomes.[19] Evidence shows that changes in body mass index (BMI) related to walking have influenced the prevalence of overweight and obesity in some populations, as well as the incidence of diabetes or other conditions that may result from increased BMI.[9,18,19] These benefits have also been established as independent of the effects from more vigorous activity, such as swimming or running.[9,11] An increase in the proportion of school-aged children that can and do walk to school regularly can have population level impacts on reductions of BMI and sedentary behavior, especially if the behavior continues over time.[20–22] In addition to receiving 10-15 minutes of physical activity from the home-to-school journey, school-aged children who walk to school are more likely to be more physically active than their peers during out of school time.[15,23]
Parents driving their children to school, even distances of 1-mile or less, has the potential for a cascade of negative health effects, both immediately and across their lifetime.[24–27] Childhood obesity is associated with higher risk of disease, including diabetes, hypertension, asthma, and psychological stress. Conditions may develop already
2 in childhood, or later in adulthood.[28–31] Daily sedentary behavior, such as riding in a vehicle to school, has also been shown to negatively impact children’s health. More time spent sedentary leads to higher risk of obesity.[32] Therefore, not only the limited participation in physical activity but the additional time spent sedentary may contribute to childhood morbidity.[33,34]
Beyond physical health, there are social and academic benefits associated with walking to school. Social benefits include development of social skills through interaction with peers during out-of-school time and community cohesion through increased visibility of neighborhood residents.[35–37] Walkability of a neighborhood is associated with higher likelihood of knowing neighbors, trusting others and being socially engaged.[35] Walking, and other forms of physical activity, supports psychological and emotional well-being.[16,38,39] Indirect benefits to children’s academic performance from the walk-to-school behavior include fewer absences and improved focus during class time. Both of these outcomes have shown evidence of contributing to better grades among children that walk to school compared to peers that are less active.[7]
Safety, however, is one major barrier to children’s participation in the walk-to- school behavior. Lack of safety, either measured or perceived frequently lowers parents’ willingness to allow children to walk to school.[1,40] The physical presence of safety barriers in the environment and the perception of their presence have both been shown to influence the decision to drive children to school instead of walk.
3 Safety of the environment between home and school also affects children that already walk to school. Children without the option to not walk are repeatedly exposed to observable safety risks on their way to school.[41–43]Unintentional traffic-related injuries is a leading cause of injury-related death among children 14 years of age and younger.[44] In urban environments, localized congestion of motor vehicles around schools creates hazardous conditions for children and families traveling by non- motorized modes, such as walking.[45] Other safety barriers, such as the presence of incivilities (e.g., drug sale or use, presence of gangs, and discarded needles), often affect the population of children that are most likely to walk to school.[46]
Amelioration of environmental barriers to walking to school supports the safety and health of all children. Results can also have community-wide impacts from immediate changes, such as improvement in the neighborhood design, and long-term changes, such as improvements to policy. The changes may lead to healthier travel and physical activity habits for all residents, contributing to overall improved quality of life.[41,47,48] Despite efforts to encourage walking to school, parents continue to perceive a lack of safety in the environment between home and school.[3,49,50]
Environments may also be objectively measured as unsafe, which can contribute to and confirm parental fears.[42,51,52] Optimizing safety conditions and parental perceptions of those conditions is a potentially valuable approach to increasing the number of children that walk to school, as parents are the gatekeepers of children’s travel choice.[1,53,54]
4 Knowledge Gap
Environmental interventions have been recognized as a promising strategy for population-level changes that help sustain behavior change over the long term.
Knowledge, however, of the effect of individual environmental factors, as well as an understanding of the combination of factors that lead to and support walking is needed.[55,56] Major obstacles include the lack of a clear definition of safety, problems with measurement of safety, and a disregard for the spatial attributes of safety. A growing body of literature has been developed around this topic and existing knowledge has demonstrated the utility of a social ecological approach to environmental interventions.
The social ecological model provided the framework for the study and illustrates the multiple levels of factors hypothesized to influence the decision to walk to school. The levels of factors identified for influencing walking to school include personal, interpersonal, environmental and policy.[57–60] Factors from each level also interact with each other. A focus on individual factors or use of non-generalizable target populations have limited the depth of discovery in previous studies.[9,51,61,62] Existing studies, however, have been able to determine that traffic safety factors (e.g., road type, presence of intersections, street lighting, marked pedestrian infrastructure, traffic density, presence of sidewalks, and presence of pedestrian crossing signals) influence rates at which children walk to school, but little work has integrated the analysis of factors with school-level variables and characteristics of the environment simultaneously, or to examine the relationship using specific, parent-identified barriers.[1,52,63,64]
5 The existing literature provides a wide variety of definitions for the concept of safety. Studies often use measures of safety that generally lack specificity or combine multiple factors into a global factor termed “safety” or “walkability”.[65] An overview of ways that safety has been measured and defined in recent literature is provided in Table
1, adapted from a previously compiled table.[66] The lack of clarity and specificity in the definition of safety has limited knowledge gains in the field.
Table 1. Overview of Safety in the Literature
Research Methods Environmental Factors Oral histories Distance Proximity to destinations Open interviews, Focus groups Bullies Stranger danger Crime Surveillance Crossings Traffic danger Distance Traffic congestion Dogs Visibility Driveways Questionnaires Crime Neighborhood Travel diaries Crossings children Objective measures Incomplete sidewalks Population density Surveys Infrastructure Stranger danger Intersections Traffic danger
Examples of these “problems” with measuring safety can be found in well- designed studies in the United States and other countries. The Neighborhood Impact on
Kids study in King County, Washington and San Diego, California included survey items asking about family rules that are enforced with the children. The example rule provided was “my child must stay close to or within sight of the parent”, which was intended to represent crime danger.[40] This assessment, however, does not appear to be compatible 6 with other research on crime which uses measures of violence and victimization to assess crime.[1,67,68] A sub-sample from that same study using only residents in San Diego measured parental perceptions of neighborhood crime using nine survey items categorized as stranger danger, or general crime and disorder. Items included fear of child being hurt or taken (on streets, in the yard, and in a local park). Additional items captured presence of stray dogs and perceptions of crime.[52] The categorization of crime used in the study improved upon the previous approach but neighborhood, in both studies, was defined by census block group. While this reduced the complexity in statistical analysis and provided useful preliminary findings, it perpetuates the problem of neighborhood definitions. Census block group is not a consistently useful scale at which to measure the neighborhood between home and school.
A Dutch study represented the concept of safety as “social safety” and parents responded to question on lighting, crime and visibility of pedestrians using a Likert-type scale.[69] A similar survey was used in a study to compare child and parent perceptions of the environment. Perception of safety was measured by Likert scale in response to three items: the neighborhood is at high risk for crime, the neighborhood is attractive, and children can play outside without danger.[64] The meaning of terms such as “attractive” and “danger”, however, are likely interpreted differently by individual respondents to surveys and responses to forced choice survey questions provide no new information about what in the environment can be modified to improve safety. The phrase “play outside” could refer to a location at-home, near-home or away from home and the survey design does not capture parents’ thought processes while responding to the survey.
7 Understanding of the physical environment requires both objective and subjective measurement. The perception of safety and support for walking by parents influences their decision to allow or not allow their children to walk to school. Existing studies have been problematic because of separate exploration of objective measurements of the built environment and perceptions of those environments by users. For example, a 2008 systematic review of environmental determinants of active travel among youth included
21 studies that measured the environment separately with objective (11) or self-report measures (10); only three studies used both objective and self-reported methods of measuring the environment together.[70] Studies using objective or subjective measures, alone, may influence the findings in a relationship with walking.[71–75]
Sociological research has shown an indirect relationship between perception and objective measure of the environment. Individual characteristics, experiences and other situational factors can cause two people to perceive the same environment differently and report on different factors of the environment related to safety.[76] Consistency in survey questions that clearly define a context and outcome of interest are critical to correctly capturing perception data. Studies also need to consider individual characteristics and social factors in analysis in order to accurately interpret parental perceptions.
More recent evidence addresses some limitations of earlier studies, such as examining walking to school as a main outcome and using a multi-level approach that includes individual, school and environmental factors. These studies, however, fail to explore the local nuances of travel to school that can be captured by acknowledging spatial relationships.[3,77,78] Consideration for location in the relationship between
8 safety and walking to school has frequently been absent from research in this area.
Failure to account for the influence of location on the relationship can lead to incorrect conclusions that may over or undervalue the importance of certain factors.
In summary, understanding and addressing the concept of ‘safety’ is a prerequisite for successful intervention efforts. The present study contributes substantially to existing literature about objective and perceived environmental barriers that prevent participation in walk-to-school behavior among elementary school children. Results provide an empirical foundation for implementing infrastructural changes. That foundation allows for the design of promotional activities that maximize the opportunity for children to safely walk to school and that minimize factors in the environment that create unsafe traffic and neighborhood conditions for the journey from home to school.
Structure of the Dissertation
This dissertation attempted to address the paucity in knowledge, described in the previous section, by using a multistate, multisite project to comprehensively examine the safety of environments between home and school. In addition, policies that iteratively inform and are informed by the environment were examined. Chapter 1 has provided a brief introduction about the significance of this topic. Chapter 2 will review the growing body of literature on the relationship between the environment and walking to school.
The literature reviewed in Chapter 2 was used to identify and define the concept of safety and related variables in this dissertation. The relevance of theories from city planning and public health are examined in Chapter 3. Then, a general conceptual framework and research aims are presented, followed by an introduction of the study sample, data
9 sources, and approaches. Chapter 4 is the first manuscript within the dissertation, an exploratory spatial analysis, which used observed geographic information systems (GIS) and self-reported parent survey data to inspect the relationship between measured and perceived safety barriers in the environment between home and school. Chapter 5 is the second manuscript within the dissertation. This is a multilevel analysis using the observed and perceived safety barriers introduced in the first manuscript, along with family and school level covariates, to model and predict the outcome of walking to school. Chapter 6, the third and final manuscript within the dissertation, is an inventory and brief qualitative evaluation of policies related to walking to school. For each of the manuscript chapters, the research design, methods, results, and limitations are presented.
10 Chapter 2. Background and Literature Overview
Research Design and Methods of Previous Studies
A large body of research on walking, and other mode choice decisions, comes from the transportation planning community and the study of adult populations.
Researchers were interested in knowing factors that influenced the selection of one mode of transportation over all others in order to shift adults from use of personal automobile trips to the use of transit, biking or walking.[79] Factors that influence walking among adults include high population density, mixed land use, high connectivity and adequate design for walking (e.g., continuous sidewalks).[80]
At least two major conceptual frameworks have been developed using results of research on these factors. The neighborhood environment framework, from the planning and transportation literature, summarizes walkability among adults with two dimensions, destination and route. Destinations, organized by type (utilitarian and non-utilitarian), are then evaluated on presence and quality to examine how these aspects of the destination are related to walking. Route is organized into individual factors: sidewalks, street connectivity, aesthetics, traffic, and safety.[81] These factors are consistent with previous reviews.
The second major conceptual framework on the behavior of walking was developed by Pikora (2003) to “collate” relevant environmental factors. One key contribution of the collated factors was the organization by walking purposes, which included walking for transport.[82] The “items”, which are at the lowest level of the framework (e.g., volume of traffic, lighting surveillance, sights along route) are posited to 11 be the modifiable factors that influence the broader factors above them (elements and features) which then affect the outcome of walking. [82] The framework provided a useful beginning for the exploration of differences between walking behavior between adults and children.
Studies of children’s travel have steadily increased and there is now a robust but greatly varied literature on factors that influence a child’s mode of travel. In particular, the interest in understanding factors related to children walking to school has grown considerably.
The relationship between physical activity and environmental factors, particularly in a neighborhood context, however, has been consistently been found to be significant.[80] Discussions and implications from these studies, however, are limited due to differences in approaches. Age of study participants impact assumptions of independent mobility and is one example of how studies have produced such varied findings. Urban planning studies found the magnitude of influence of objectively measured factors of the built environment are a significant influence on children’s travel to school but less than factors at other levels. [83] Evidence shows, though, objectively measured physical environment factors work together with significant factors at other levels to influence children’s travel. This supports development of comprehensive interventions that address the multiple levels of the social-ecological model.[17,58,83]
There have been few systematic reviews of walking that summarize findings on the influence of the built environment, specifically addressing elementary school children. A recent review (2012) identified only one other review in the existing literature
12 that addressed walking rather than active travel (walking and biking) or physical activity, in general; the authors had searched a single database and reviewed articles published from 1985 through 1995.[51] More is known on active travel to school for a general population of children 18 years of age and younger. Nearly 500 variables to be tested for correlation with active travel were identified from 42 research studies in a single systematic review.[84] The review was not limited to environmental factors. However, urban form factors were discussed. Urban form factors that frequently appeared in the literature were distance to school, infrastructure for pedestrians and bicyclists, route barriers, network connectivity, land use mix, density, walkability, and urbanization. Each of these factors, was represented by several variables. For example, infrastructure for pedestrians and bicyclists had 25 different variables, including presence of sidewalks in neighborhood, parental perception of sidewalk being near to traffic and lack of bike storage at school.[84]
The Neighborhood Quality of Life Study (2006) used both objective measures and parental perceptions to examine the association with active travel to school.[53] The strong design of the study makes it useful as evidence to inform the present research.
Participants in the study were adults with children, between 4 and 18 years of age, living in their household; the mean age of children on which parents reported was 11 years of age. The environment around participants’ homes was characterized dichotomously as having high-walkability or low-walkability based on an index calculated for the census block group in which the participant lived. An additional walkability index was calculated using the participants’ geocoded home addresses and 0.62-mile (1-km) radius
13 of that location.[53] The index considered net residential density, intersection density, retail floor area (ratio of amount of floor space used for retail to the total lot area), and land use mix. Parental perceptions were captured using the validated Neighborhood
Environment Walkability Scale which assessed residential density, access to retail, street connectivity, walking or biking facilities, aesthetics, pedestrian traffic safety and crime safety.[53,85] Parents reported the number of days per week, in an average week, the child traveled by each mode to school (e.g., walk, bike, car, school bus or transit).
Walking or biking to and from school at least once per week was used as the measure of active travel in analyses, which included 25% of children on which parents reported.
Overall, objective measures of environment and parental perceptions of the environment were each significantly related to children’s active travel to school.[53] Among objectively measured variables, neighborhood walkability was significantly associated with active travel and among perceived variables, street connectivity, availability of walk and bike facilities and parental concerns were all significantly associated with active travel. The authors of the study suggested identification of consistent correlates with strong associations to active travel could inform school and city planning policies that would have permanent and widespread impacts on the environment.[53]
A Canadian study (2014) used objective measures to explore physical and social environmental correlates with walking among children living within walking distance from school and that currently walk to school.[86] Children included in the study ranged from pre-kindergarten to sixth grade selected from elementary schools in Toronto.
Environmental factors were identified by literature review and mapped onto school
14 attendance boundaries. The focus of this analysis was on roadway features and therefore classified environmental factors into the categories of density, diversity and design, which have been established based on studies with adults. School-level design variables included school crossing guard presence, perceived speed of traffic along roads adjacent to the school, dangerous intersection near school, measured speed exceeding speed limit, volume of traffic (traffic/minute), and presence of safe pedestrian infrastructure (flashing lights, crosswalks, sidewalks, traffic calming features, density of traffic lights). The final model indicated significant positive associations between walking to school and design variables, including pedestrian crossings, presence of traffic signals,and presence of a school crossing guard. Presence of school crossing guard exhibited some evidence of effect modification. The study looked only at objectively measured environmental factors and suggested that the use of both objective measurements together with parental perceptions of the environment is important to explaining travel behavior.[86]
Safe Routes to School
The Safe Routes to School Program (SRTS) is a federally funded program authorized by a 2005 federal transportation bill, the Safe, Accountable, Flexible, Efficient
Transportation Equity Act: A Legacy for Users (SAFETEA-LU).[1–3] The two initial aims of the program were to (1) create environments to enable and encourage children, including those with disabilities, to walk or bicycle to school and (2) make the journey safer and more appealing.[1,3] Federal funding was allocated to each state department of transportation to be awarded to local communities in order to create environments with the necessary infrastructure to make walking and biking to school feasible for school-
15 aged children, enforcement to add surveillance to the areas near schools and to encourage participation in walking and biking to school with education and incentives. The program goal was to address equity in transportation and safety of the journey from home-to- school. Emphasis was placed on access to SRTS program participation in rural and low- income communities due to existing evidence of increased pediatric pedestrian morbidity and mortality with decreased resources.[4,5] The program developed more specific health-related goals to decrease injury, increase physical activity and reduce obesity as national priorities began to align with the program’s aims. [3,6] The program operates with a “6-E” model (Table 2 [7]), of engineering, enforcement, education, encouragement, equity and evaluation to promote the use of walking and biking as the primary modes of travel to and from school.[2,7]
16 Table 2. Description of SRTS 6-E Model and Sample Program Activities
Component of Description Sample “6-E” model activity Engineering Creating operational and physical improvements to Installation of the infrastructure surrounding schools that reduce new sidewalk speeds and potential conflicts with motor vehicle blocks traffic, and establish safer and fully accessible crossings, walkways, trails and bikeways Enforcement Partnering with local law enforcement to ensure that Placement of traffic laws are obeyed in the vicinity of schools crossing (this includes enforcement of speeds, yielding to guard at pedestrians in crosswalks and proper walking and major bicycling behaviors) and initiating community intersection enforcement such as crossing guard programs and student safety patrols Education Teaching children about the broad range of In-class transportation choices, instructing them in important curriculum on lifelong bicycling and walking safety skills and pedestrian launching driver safety campaigns in the vicinity of safety schools Encouragement Using events and activities to promote walking and Walk and bicycling and to generate enthusiasm for the Roll to School program with students, parents, staff and Day event surrounding community Evaluation Monitoring and documenting outcomes, attitudes Student and trends through the collection of data before and Travel Tally after the intervention(s) Equity Supporting safe, active and healthy opportunities for Prioritization children and adults in low-income communities, of communities of color and all communities by underserved addressing obstacles, access and safety that may or differentially impact outcomes disadvantaged schools
The SRTS program provides a useful backdrop for the study as it aligns with at least two major national public health campaigns, (1) The 2015 campaign “Step it up!
The Surgeon General’s Call to Action to Promote Walking and Walkable Communities” and (2) Healthy People 2020 (healthypeople.gov) that have specific objectives 17 emphasizing safety and promotion of walking. The SRTS program was first implemented in Marin County, California and Arlington, Massachusetts as part of pilot programs funded by The National Highway Traffic Safety Administration (NHTSA) but is now implemented nationally.[88] Recently, SRTS programming has been implemented and institutionalized at school districts around the country to fill in the gaps left by reductions in school-provided transportation.[91,92] Thirty-six states currently monitor the number of funded schools or programs participating in SRTS; a report compiling data from these
36 states found SRTS had reached more than 15,000 schools in all 50 states and
Washington, D.C. as of 2012.[88] The number of schools reached by SRTS programming has since increased to 19,035 with an average of 322 schools or programs ever funded in each state. Local SRTS programming is estimated to be benefitting 6.8 million students, nationally.[93] The actual number of funded programs varies from state-to-state, with a range from 3,279 funded schools or programs in California, to 29 in each Hawaii and
South Carolina.[94]
The SRTS program’s goal to “reverse the decline in children walking and bicycling to schools, increase kids’ safety and reverse the alarming nationwide trend toward childhood obesity and inactivity” is measured using a variety of transportation, injury and physical activity outcomes.[95] These outcomes include (1) the number and proportion of students at participating schools that walk or bike to school, changes in (2) minutes of physical activity, (3) pedestrian-involved collision prevention, (4) pedestrian safety knowledge, and (5) pedestrian safety behavior. The number of completed pedestrian infrastructure projects has also been used as a measure of program impact.
18 Mode shift in the number of children that walk or bike to school is measured using the National SRTS program’s Student Travel Tally form.[96] A brief in-class activity asks children how they arrived to school that morning and how they plan to depart from school that afternoon. Students raise their hands to respond to the tally. Data generated from the Student Travel Tally have contributed to the assessment of mode shift at three different levels of program implementation: school, local program and state.[96–
98] These data have also contributed to measurement for the national evaluation of mode shift, aggregating Student Travel Tally results from multiple states.[4,48] Evaluation of study results at each of these levels have, generally, confirmed findings that participation in the SRTS program has a positive impact on walk mode share.[4,97–99] The influence on mode shift, however, appears to have been more modest than expected due to concerns over safety.
A national study, including four states and Washington, D.C., was conducted using data collected over time (2007 through 2012) from 801 schools, both with and without SRTS programs. A limitation of the study, however, was that walking and bicycling were combined as active travel and the proportion of walking to school, alone, cannot be determined. At baseline, 18% of children at schools with SRTS programs walked or bicycled to school. The proportion increased in a dose-response relationship; more years of participation in the SRTS program led to higher increases in the proportion of walking and biking to school. After one year of participation, schools with SRTS programming had an average rate of 20% of walking and bicycling trips to school and after five years of participation, the rate increased to 31%. [48] The Local School Project
19 (2010) selected schools from eight states to evaluate mode shift, in addition to other program outcomes. Measurement of the mode share of walking to school was collected using the Travel Tally prior to implementation of infrastructure projects affecting the selected school sites and again post-project.[100] The overall estimated mean mode share of walking for the sample pre-project was 20.4% and 20.3% post-project. A multi-state evaluation of SRTS estimated walk mode share to be 9.8% prior to the implementation of programming at participating schools in four states; the proportion of children that walk to school was measured again post-implementation and had increased to 14.2%, overall.
The analysis included a total of 33 schools for which both the pre- and post- implementation data were available.[4]
Despite the widespread implementation of SRTS programming, distribution of these programs is not uniform and participation in the programs, in many places, is lower than expected among the target population. There are differences in implementation for programs between urban/rural, high/low-income and strong/weak parental involvement.
Rural or low-income communities, which also tend to have weaker parental involvement at schools, participate less in SRTS programming.[43,101–103]
Spatial Analyses
Awareness of the importance of the relationship between the environment and health has grown substantially. As a result, spatial analyses have been utilized with increasing frequency to study neighborhood environments. For example, GIS variables have been used previously to collect objective measures of the neighborhood environment to study successful aging in place among older adults.[8] A French study
20 interested in the outcome of active commuting to and from work measured the neighborhood with a total of 15 objective variables, representing both the social and physical environments. Variables included distance to nearest public transport station, percent of home owners and percent of vegetation cover.[9] A more relevant study integrated perception into the objective analysis of transportation safety. Police-reported data on the locations of pedestrian-hit-by-car crashes were combined with a survey of college students’ perceptions of locations where pedestrians are most at-risk for crash.
The results showed that perceptions differ from actual risk. The process of including perception survey data with the crash data identified factors related to pedestrian risk, similar to the factors to be included in the study (i.e., amount of traffic, incomplete sidewalks and pedestrian infrastructure).[10]
Panter et al. (2010) demonstrated objectively measured environmental factors are associated with walking and biking to school.[11] Assessment of the neighborhood environment was computed using GIS based on children’s geocoded home addresses.
Each child’s neighborhood was defined using street network as the area within an approximate 10-minute (1/2-mile) walk of their home. A total of 13 environmental factors which might support, or restrict, walking and biking were measured and included in the study. The factors used in the study had either been hypothesized to be associated with adult’s walking or biking or associated with active commuting in the existing evidence-base. Environmental factors included in the study were road type outside child’s home (major or minor), road density, streetlight density, traffic collisions per kilometer, socioeconomic deprivation, presence of main road along route, presence of crossing
21 guard, traffic calming features, pedestrian crossing near school entrance. Overall, these studies have found that a statistical approach which explicitly utilizes location, reveals spaces and factors which can be targeted for public health interventions.[12]
The use of spatial analytic techniques in this study were used to understand presence of objective and perceived safety factors in the environment between homes and schools that potentially prevent walking to school. Knowledge gained from the study will assist researchers and practitioners in multiple disciplines in understanding how to modify environments to address safety and increase the walk-to-school behavior among children living within 1-mile of their assigned schools.
Multilevel Analyses
Safety has been defined variably in the literature using terms such as general safety, crime safety, traffic safety and neighborhood safety, often including different factors within these terms.[13,14] Researchers’ definitions of safety have been created using both objective measures and the perceptions of adults or children. These definitions of safety have represented the multiple levels of direct and indirect influence on a child’s behavior (e.g., environmental, intrapersonal, and interpersonal). Environmental factors that influence children’s active travel were summarized in a review by Giles-Corti et al.,
(2009). Safety, described generally as real and perceived parental concerns about personal and traffic safety, was examined as a general category of influence as a result of the review.[15] Parental concerns among parents of elementary school children included traffic danger, lack of safe road-crossing infrastructure and exposure to traffic (e.g., volume of traffic and speed of traffic along roads), presence of visual obstructions (e.g.,
22 parked cars), stranger danger, bullying, presence of sidewalks (or other footpaths) along route, sidewalks and features (e.g., lack of physical obstructions and condition), surveillance, street lighting, crime rate and homes along route with windows facing the street. The authors of the review identified a need to capture parental perceptions of the environment and interactions between motives for walking and perceptions of the environment. Parental perception data on safety can help researchers to better understand mode choice decision-making. The authors suggested this strategy may offer explanations for inconclusive or counterintuitive findings reported in the existing literature.[15]
A more recent review by Stewart et al. (2011) applied a model adapted from the work by McMillan (2005) presented in Figure 1; the adapted model grouped variables found in the literature, and used the relationships hypothesized in the model to explain implications of study findings for programs that promote walking to school.[16,17]
Among the urban form variables, safety commonly appeared in the 42 studies that were reviewed and represented several of the 480 variables included. Safety was described most often by the outcome of pedestrian-involved motor vehicle collisions, either by number or rate. The frequency and rates of injuries or fatalities related to pedestrian- involved motor vehicle collisions was also a common measure for safety. Environmental factors categorized as ‘safety’ included pedestrian countermeasures commonly included in pedestrian infrastructure improvement projects (e.g., active police enforcement, physical traffic calming features, sidewalks, raised medians, signalized crossings, school zone flashing lights). Importantly, despite reductions in speed of approximately five
23 miles per hour as a result of installation of pedestrian countermeasures, vehicles continued to exceed the posted speed limit in school zones.[16] This is consistent with the frequent reporting of speed and amount of traffic along roadways as a safety concern elsewhere.[18–23]
Figure 1. Diagram of the Conceptual Framework of an Elementary-age Child's Travel
Behavior [83]
Lee et al. (2013) improved upon the cross-sectional design of previous studies by using matched-pairs to test for significant relationships between parental safety concerns and parental attitudes with children’s mode choice decisions for travel to school. Parents whose children walked to school were matched with parents that drove their children to school, according to distance from home to school.[14] Significant differences between drivers and walkers were found for the safety concerns of getting lost, being taken or hurt by a stranger and being hit by a car. These factors, however, were not significant in
24 multivariate analyses after controlling for demographic and household-related factors.
The study also found drivers more frequently perceived roads with busy traffic along the route to school (51.4%) compared to walkers (43.4%). These results offer additional support for two critical considerations in future research: (1) multiple levels of influence on, and (2) importance of perception in the travel decision-making process.
The present study focused on two aspects of the environment shown in the review of literature described above to be closely related to walking to school and frequently appearing as part of the definition of safety in both objectively measured and subjective perceptions reported by parents. The two aspects of the environment to be used in the study are traffic and neighborhood safety. This--more narrow--definition of safety will build upon what is known, while also offering methods and results that can be repeated by programs to address barriers and promote walking to school.
Parental Perceptions of Traffic and Neighborhood Safety
Perceptions of traffic and neighborhood safety have strong evidence as being key factors in travel decisions by parents.[24–26] Elements of the environment may provide visual cues that increase parents’ fear while in the environment. The physical presence of
“disorder”, or negative visual cues, such as trash and graffiti, is associated with higher levels of perceived crime and greater fear of crime.[24] A Texas study conducted with
1,635 parent-child dyads living within 2-miles of their schools found walking to school was significantly more likely when parents perceived safe street crossings and well- maintained sidewalks. Other factors associated with walking to school included speed of traffic along the route to school, amount of traffic along the route to school, presence of
25 crossing guards and safety of intersections. Those that walked to school were often
“captive walkers” with no family vehicle available (or one shared vehicle); this group was more likely to walk to school compared to their counterparts.[27] Similar findings of parental perceptions have been found in national studies. The National Evaluation of
Walk to School project obtained data on parental perceptions of safety from parents in 18 states living within 1-mile of their children’s schools. Parents selected their perceived barriers from a list, provided by the researchers, containing 22 commonly identified safety barriers. The parent-identified barriers: lack of sidewalks and crosswalks, speed of traffic, amount of traffic, and insufficient lighting were found to have a significant association with walking to school.[28]
A qualitative study using focus groups identified the major theme of safety in the environment. Parents of transportation ineligible children in grades 4 and 5 were recruited for participation and categorized by child’s school travel mode (active or not).
Focus groups were mixed, parents and children. Personal safety emerged as a theme among all focus groups conducted for the study, related to both the presence of safety as a facilitator and lack of safety as a barrier to walking to school. Characteristics of the physical environment included lack of adequate sidewalks, and traffic. For example, one parent whose child walked to school said “Given all the potential risks [to walking] that would really matter, I think it’s probably traffic I would worry about.”[29] Perceptions of the environment affect the distance and destinations to which parents will allow their children to walk. Findings from studies that have examined perceptions together with objective measures of the neighborhood and traffic environments have shown there is a
26 connection between the two. Perceptions are similar across sociodemographic characteristics. Existing research has identified potential relationships between factors such as lighting, sidewalks, pedestrian infrastructure, reduced traffic speed and low traffic volume with greater perceived safety. Paucity remains in our knowledge of the influence of these pedestrian level safety factors (e.g. lighting and sidewalks) on the mode choice decisions among families of elementary school children. Improved knowledge of which factors significantly predict walking to school, and to which other factors safety is related in influencing this outcome is needed.
Traffic Safety Barriers for Walking to School
Traffic crashes in the United States are one of the leading causes of death.[30]
There were an estimated 6,296,000 police-reported traffic crashes in 2015 with an average of one fatality every 15 minutes as a result.[31] Personal motor vehicles, including cars and trucks, represented the largest proportion of motor vehicle crash fatalities across all vehicle types. Their combined total amounts to 64% of motor vehicle crash fatalities, according to the most recent NHTSA data.[31] Unintentional injury by motor vehicle collision is also one of the ten leading causes of non-fatal injury among children in the United States.[32–34]. Urban traffic environments often have a larger presence of vulnerable road users, such as children, and increased likelihood of traffic collision, which contributes to children’s risk of injury as a pedestrian.[19,35–37]
Parental evaluations of walk-to-school programs have consistently cited traffic as a barrier to allowing children and adolescents to walk to school.[32,38,39] Individual level modeling of traffic-related safety factors using objectively measured items has
27 shown that children are less likely to walk to school if any section of the route involves crossing a freeway, highway or arterial-adjacent intersection, if there are no lights or marked crossings on the route, or if there is a high density of traffic.[23] The presence of sidewalks, intersections and signals are also important determinants of whether or not families choose to walk.[40–42]
Traffic congestion around school sites during the morning drop-off time also increases risk of collision.[43] A study conducted by Safe Kids Worldwide in 2015 found nearly one-third of drivers performed at least one unsafe drop-off behavior.
Distracted driving behavior, such as use of a mobile device, was more common in school zones with a speed maximum not limited to 20 miles per hour and at least 3% of distracted drivers were using more than one mobile device simultaneously.[44] Improper drop-off by parents can block the vision of other motorists and may cause a child to cross from the car to school at a mid-street, uncontrolled location.[45] Children exiting their parents’ vehicle at drop-off may perform other risky pedestrian behaviors, such as failure to stop and look for approaching traffic, creating further hazard.[44,45]
Vehicle speed has an established relationship with risk of collision. Data collected by the San Francisco Municipal Transportation Agency showed speed is one of the most common motorist violations, along with failure to yield, accounting for a total of 29% of traffic injuries.[46] A higher speed of travel increases risk of collision and subsequent injury, especially for children either as a vehicle occupant or pedestrian.[36,37] The risk of both injury and death to occupants of a motor vehicle during collision increase
28 exponentially with increase in speed. Distance required to stop increases as speed increases while the driver’s field of vision narrows and the time to react shrinks.[46]
Other issues include the contribution of families to the vehicle traffic on roadways and in the areas around schools during the morning commute. This can affect the health of children and communities, particularly by creating dense traffic around schools. First, riding in cars to school adds more sedentary time to children’s daily routine. Traffic on roadways also leads to poorer air quality for children. The release of harmful emissions while a higher than usual number of vehicles idle in traffic near schools can create a concentration of polluted air. The results of these two problems, increased sedentary time and decreased air quality, may also offset benefits individuals gain from physical activity.[18,47] Air quality is an important health risk factors for elementary-aged children; particulates in vehicle emissions are often a trigger for asthma. An estimated
8% of total childhood asthma cases in Los Angeles County were found to be related to regional air pollution from traffic along major corridors and likely resembles attributable burden in other metropolitan areas.[48] Nationally, approximately 14.2% of children 6 months to 11 years of age have been diagnosed with asthma and there are geographic and racial disparities in the prevalence.[49,50] Better air quality, from fewer vehicles on the road, can potentially minimize the effect on children with asthma, allowing for better control of asthma and fewer asthma-related absences from school.[51–53] Results from a study by the United States Environmental Protection Agency found better air quality around schools where most children walked or biked to school compared to schools where a majority were driven to school.[54] The report concluded with the suggestion
29 that a 13% increase in the number of children that walk or bike could reduce motor vehicle emissions by at least 15%.[54,55] A decrease in the proportion of families that travel by motor vehicle to school can help reduce emissions and improve air quality in the areas around schools where families live, work and play.
Neighborhood Safety Barriers for Walking to School
A substantial number of studies in the last decade have explored the role of neighborhood safety in overall health and participation in physical activity. Studies of neighborhood safety and physical activity have captured both objective measures and residents’ perceptions of the neighborhood environment.[56–58] Although studies often only captured data on physical activity, generally, they have had a narrow interest in the micro-environment. These investigations capture interaction between residents and spaces such as home and school, which address the contextual sensitivities of the present study. The micro-environment also provides a more appropriate level of detail than zip code level.
The effect of neighborhood safety, or absence of it, at the micro-scale on participation in walking behavior and other physical activities is not entirely clear from current literature. Overall, the daily stress of dangers such as crime, risk of personal safety and exposure to incivilities in the environment have been found to damage health.[59] However, failure to distinguish between different “sources of danger” and differences in methodological approach in existing studies have led to inconsistency of findings.[57,60,61] Community violence in the urban setting has been defined as “events in the local neighborhood involving crime, weapons use, and violence or potential
30 violence perpetuated by people outside of the immediate family.”[62] Crime or violence measured as actual crime (crimes per capita within a neighborhood) or perceived lack of safety have been used to determine the effects on parental perceptions of general crime and disorder. Persistent disadvantage in a neighborhood, measured by physical incivility in the area around residents’ homes, can exaggerate negative perceptions of neighborhood safety.[63] Environmental factors in the neighborhood have consistently found that the presence of unpleasant sights, such as trash, and a lack of physical features for walking, generate a perceived lack of safety and that the lack of specific features that promote a feeling of safety, such as lighting.[17,57,60] Studies using parent-reported data have consistently found “stranger danger” to be a predictor of driving to school. Three of eight variables to measure “crime” in a systematic review of findings from research on active transportation and the SRTS program were related to strangers (concern of abduction, parent concern about strangers, and child concerns about parents’ concern about strangers).[16]
Personal Correlates of Walking to School
A review of children’s active travel behavior identified individual, family and school predictors of children’s active travel to school supported by substantial literature.[64] Among different racial or ethnic groups, Hispanic and African American children are more likely than white children to actively travel to school. Sex of the child is also a predictor of active travel to school; boys are more likely to use active travel modes compared to girls. This is consistent with findings related to physical activity, in general.[64,65] Children whose parents walked or biked to school and who currently
31 actively commute to work are more likely to actively travel to school compared to their peers. [64] Children whose parents view physical activity positively are also more likely than their peers to actively travel to school. [64] School location influences the rate of walking to school but is most likely related to the average distance from home to school for children.[64]
Distance is the strongest predictor of a child walking to school.[64] In rural communities, the distance between home and school is often longer than in urban communities, which can limit the accessibility of walking. The lack of residential and intersection density in the physical environment between home and school in rural communities has also been found to negatively influence participation in walk-to-school behavior.[64,66] Analysis of National Household Travel Survey data showed rural respondents, five years of age and older, completed fewer minutes of walking per day than urban respondents. Data also showed there was no significant change in the frequency of participation in at least 30 minutes of walking per day by rural respondents during the 8-year study period but a significant increase in participation by urban residents.[66]
Although socioeconomic status (using household, school or neighborhood-level measures) has been suggested to influence walk-to-school behavior, after adjusting for distance and other demographic factors, no significant relationship has been consistently found.[64] Children’s attitude toward physical activity, unlike parental attitudes, is not associated with actively commuting to school.[64]
32 Other Correlates of Walking to School
The present study focused on specific, modifiable safety factors in the environment that influence parents’ decision to allow or not allow their child to walk to school. However, other factors of the built environment have been found to be related to utilitarian walking. Destinations, density, and design are three built environment factors most frequently found in the planning literature, known as the 3 D’s.[67] These are also often assessed together as a measure of walkability. Walkability can be defined as the support and encouragement provided for the pedestrian by the built environment.[19] The use of walkability alone to study mode choice decisions potentially overlooks the influence of pedestrian level factors of the environment, such as presence of lighting and sidewalks, that can more precisely determine which factors significantly influence the choice to walk to school.[68]
The behavior of walking to school among elementary school children represents a particular type of walking trip, involving both parents and children. These trips need to be investigated more closely than and as separate from other types of walking trips. In addition to differences in the purpose of the trip from other utilitarian travel, special considerations include age, limited independence in mobility, lack of control over selection of travel mode and the specificity of route, destination and arrival time for elementary school children.
33 Role of Policy to Support Promotion of Walking to School
Policy, defined by the SRTS National Partnership as “a high-level overall plan embracing the general goals and acceptable procedures especially of a governmental body”, is critical to the sustainability and expansion of SRTS programs to effectively address safety concerns and facilitate program participation.[51] Examples of policies that support SRTS at the local community level include pedestrian master plans, consideration for pedestrians in capital improvement plans and district-wide transportation plans that include alternatives to school buses and parent drop-off.[51] The inclusion of SRTS in school policies has been suggested by experts as one strategy to add permanence to the program at the local level.[69] Schools that implement supportive policies for walking to school are more likely to increase the proportion of students that walk to school regularly, over time.[70] Adoption of a supportive policy for walking to school aligns with the National School Lunch Program requirements for participating school districts. Schools in each participating district must have a school wellness policy that includes physical activity goals and opportunities for students to be physically active before school.[71]
The National Center for Education Statistics has estimated that approximately
55% of students are transported to school by bus, costing an average of $950 per student transported (2014-2015). The funding provided for school bus transportation for students is part of the overall education budget. Competition within the school system for funding from a limited budget has led to reductions in the number of bus routes and stops provided to students in many districts. By 2009, at least 20 states had implemented or
34 proposed budget cuts that would eliminate bus routes for students. Other factors, such as increasing fuel costs and changes to state-level budgets from economic considerations and property tax revenues, have impacted school budgets over time.[72]
National school transportation policy allows for each state and district to assess their own circumstances to make school transportation decisions. Some state level
Departments of Education have established distance-based eligibility policies for provision of school transportation. Although these distances vary slightly from district-to- district, often general education students living approximately 2-miles or less from their assigned school do not receive school-provided transportation. Revisions to the national student transportation policy added language in 2014 to include safety in the criterion for transportation eligibility. The guiding policy document states, “Safety must be the primary concern, and criteria should take into account the ages of students and potentially hazardous situations.”[73] Not all states or districts, however, include alternate options for students that may encounter hazardous conditions along the route to school.
Common safety hazards, such as lack of continuous sidewalks and traffic speeds greater than 30 mph, have been identified by previous studies with parents.[23,29]
Parental willingness to allow their children to walk may be diminished by perception of safety as a concern, resulting in transportation ineligible children being driven to school.
Children without the option to be driven to school, sometimes referred to as “captive walkers”, must endure those hazards. This emphasizes the need to address environmental factors, as they impact the health and safety of both children that do and children that do not currently walk to school.
35 An evaluation of the impact of local transportation policy on children’s participation in active travel to school, which includes walking, was conducted using data from 468 communities, collected from 2010 through 2012. The greatest proportion of children were living in communities with policies that addressed speed limits around schools (35%). SRTS policy affected the smallest proportion of children (5%). Another key finding of the evaluation was the disproportionate distribution of supportive SRTS- related policies. Supportive policies were more prevalent in higher income communities compared to low-income communities.[74] An analysis of school policies in Canada that supported different forms of physical activity, including walking to school, demonstrated a positive relationship between presence of school policies and participation in the walk- to-school behavior, among other forms of physical activity.[75]
Summary of Literature
Existing literature has shown little consistent empirical evidence that clearly defines and investigates the pathway from environmental exposure to the outcome of walking to school among children, as mediated by parental safety concerns, and there is even less evidence within the context of the SRTS program. Knowledge in the fields of transportation and public health about factors that influence travel behavior had been gained, primarily, from adults about their own behavior until around 2005 when the
SRTS program was first implemented. Exploration of the nature of the relationship between environment and safety was often explored by obtaining adult residents’ perceptions of disorder in the environment and the rate of crime in their neighborhoods.[76] Existing analyses of factors that influence parents’ travel mode
36 decisions for the journey to school have been limited by problems such as the use of a single geographic location, measurement of factors within large 2-mile boundaries around school sites, use of summary measures (e.g., walkability) rather than specific factors, or ignoring the spatial aspect of data on environmental factors.[19,55,77] Since the conception of the SRTS program, and its implementation nationally, there has been an increase in the study of children’s travel mode choices and factors impacting those decisions.[19,27,65,78–80] However, the lack of clarity in defining environmental factors has continued. Heterogeneity across existing studies with differing definitions of safety factors and differing contexts make it challenging to draw any useful conclusions about the relationship between environment and walking to school.
The variety of ways in which walking has been operationalized is one major problem. For example, studies of travel to school and evaluations of SRTS often combine walking and biking into a single category.[16,77,79,81,82] These two modes have also been further aggregated to the category of ‘active’ or ‘non-motorized’ modes, which may include skateboarding, roller blading or use of a scooter.[38] However, bicycling and other wheeled forms of non-motorized transportation differ from walking in the characteristics of users and the relationship with the environment.[83,84] Bicycles are vehicles in a traffic environment and follow different rules of the road than pedestrians, which is also an important difference in development of health promotion programming and policy.[30]
Different frequencies of the ‘usual’ travel mode used in analysis have also been problematic; a minimum number of times per week for the mode to be selected as ‘usual’
37 has been used in some studies, while others focus on the single day during which data were collected.[85,86] Measurement of overall physical activity rather than the specific activity of walking to school also affects the associations found.[15,87–89] These problems becomes especially challenging when seeking to understand which factors are key environmental factors for walking, according to certain age groups, or other sub- groups.
Research on factors that affect walking, whether for transportation or physical activity, has shown the decision to walk is influenced through the accumulation of factors. Several micro-scale factors together, such as volume of traffic, lighting and presence of natural sights, create the appropriate mix to encourage walking.[90] Safety is a feature of the composite environment considered most important to both adults and children in the decision to walk; although other factors also influence the decision, safety appears to be necessary, rather than simply supportive, for walking.[90]
Consistent with this finding, environmental interventions are one of the major strategic approaches to injury prevention and health promotion of pedestrians.[91] The
United States Department of Transportation created a guide for creating “safer communities”, which has identified common pedestrian safety problems related to the physical environment. The guide recognizes that proper identification of problems is necessary in order to resolve those problems with appropriate solutions. Although the types of problems identified in the guide are for both pedestrians and bicyclists, an overview is presented here specific to pedestrians and walking facilities. The nine major safety problems include: (1) no place to walk, (2) not enough space for walking, (3) poor
38 or damaged surfaces, (4) blocked pathways, (5) no buffer, (6) difficult street crossings,
(7) poor connectivity, (8) poor guidance, and (9) conflict between pedestrians and bicyclists.[92]
These identified safety problems are even more critical to understand in the context of this study. The walk from home to school is unique. Among trip types, it is narrowly focused on a specific destination. This eliminates considerations such as the density of destinations which would be of interest for journeys for shopping, recreation or accessing services. The decision-making for travel to school is also under the control of adults but with considerations for their children. Data on broad categories of safety factors, such as distance and density of intersections, have become more readily available due to GIS but data on more specific factors, such as presence and conditions of crosswalks at intersections, are more difficult to find from secondary sources.[79,93,94]
Therefore, these factors are less often studied and not as well understood as the broad categories of factors.
The present study examined environmental factors that contribute to safety to better understand what intervention strategies will impact walking to school among elementary-age children. Parental safety concerns have been found to have an inverse relationship with children’s participation in walk-to-school behavior.[27,95,96]
Therefore, lack of safety, both observed and perceived, by parents may constrain children’s participation in walk-to-school behavior despite children’s potential desire and ability to safely walk-to-school.[13,27,61,69,95–97] The use of spatial analytic
39 techniques to better understand the relationship between safety and walking to school is newly emerging and contributes substantially to the field.
Cut-backs in the provision of school transportation for families living within a 2- mile radius of their assigned schools have impacted transportation decisions for parents.
This change presents an opportunity for children living within that boundary to benefit from walking to school. Parents, however, are choosing to drive their children these short distances. Safety concerns, particularly related to the traffic and neighborhood environments, are frequently cited by parents as a barrier to choosing to walk to school with their children.[24,27,28,98] According to survey data collected by the SRTS program, lack of safety is the primary reason that parents still choose to drive their children to school.[99]
The need for favorable pedestrian environments to facilitate and promote walking has been demonstrated across a number of studies.[24,100–103] The use of data from these studies, however, to inform programs and interventions that encourage walking has been problematic. Data concerns relate to the way in which aspects of the environment have been defined, the strength of the evidence produced by cross-sectional studies and of methods used to measure the pedestrian environment. The lack of consistent data to confirm findings across studies has limited the ability of public health researchers and practitioners to make well-informed decisions to promote walking, especially among school-aged children. Data from local SRTS programs provide an opportunity gain insight into the barriers to walking to school by integrating parental perceptions of safety barriers with observed environmental data on those factors. The collection of data from
40 families enrolled at each participating school provide a nested sample of families within schools and schools within local programs. These three levels of data allow for a multilevel analysis that considers the appropriate context surrounding parental decisions about transportation to school for their children.
41 Chapter 3. Overview of Research Framework, Data Sources and Approaches
Conceptual and Theoretical Frameworks
The focus of the present research is on walking-to-school among elementary school children at schools participating in active transportation programming. Walking, generally, is considered a specific domain of physical activity related to an individual’s own behavior, but it is further specified here by trip type and trip destination.[104]
Walking to school, here, is a utilitarian trip and the child’s school is the only destination of interest. A challenge, but also a unique feature of the outcome, is the target population’s lack of control over the choice to perform the behavior. The positive benefits associated with walking to school are ultimately intended for elementary school children, however, the choice of transportation to school is controlled by parents. Parents of elementary school-aged children are therefore an important target audience to increase the walk-to-school behavior. Elementary school children are not encouraged by the SRTS program to walk alone to school (e.g., walk with a trusted adult, group of other children or under other supervision). However, the parental perceptions of safety have been captured in the present research inclusively.[105] Parents’ perspectives of safety may be based on allowing their child to walk alone, to walk with some other (e.g., trusted adult, friend or crossing guard), or walking together with their child to school.
The conceptual and theoretical frameworks used in the design of the study address these unique features of the research. Previous studies of walk-to-school behavior have often been limited by a lack of theoretical grounding or by lack of consideration for practical issues encountered by parents, especially those commuting with young children. 42 Conceptual and theoretical frameworks from transportation and health have been integrated into the study to address limitations identified previously from single- discipline approaches. There are many theories with the potential to help us to better understand, explain and change walking behavior. There is no attempt here to comprehensively address the fit or lack of fit of all theories from the various disciplines related to the study. There is an attempt, however, to make the theoretical grounding of the study more substantial than in previous research in this area by having defined explicitly and specifically the type of behavior, facets of the behavior and context for the behavior. This allows for the interrogation of a narrowly defined behavior.
Existing models of walking behavior, including one proposed by SRTS, were based on data collected from general adult populations without consideration for whether or not the adult was the parent of a school-aged child.[106,107] These models, without data from parents or the children themselves, suggested a simple, direct relationship between built environment and children’s travel behavior. According to existing models, the act of constructing a sidewalk would increase the safety and frequency of walking to destinations.[106] Beginning around 2005, researchers from the disciplines of planning and public health began to integrate their approaches to understanding the influence of the environment on travel behavior. A conceptual framework was introduced to address problems, such as adult and auto-centric approaches that treated the relationship between environment and travel behavior as direct (Figure 1). The present study is influenced by this framework.[17]
43 The conceptual framework proposed a relationship between the physical built environment and the parental decision to allow or not allow a child to walk to school.
Parents are modeled as the ultimate decision-makers for travel to school. The framework also improved upon previous models by acknowledging influence of perceptions of the environment and the interaction of characteristics of parents and neighborhoods on parental travel decision-making.[17] The author proposed that parents make decisions about transportation to school based on factors of the physical environment and its design, which then directly impact children’s travel behavior. According to this framework, the parents’ decision is also mediated by neighborhood and traffic safety factors, both real and perceived, and the available transportation options within the household. Interaction of these factors with individual level factors and the social or cultural norms also affect parental decision making about the trip to school.[17]
The framework also improved upon previous conceptualizations of the relationship between environment and travel choice by focusing on children and travel to school.[17] A limitation of the framework, and subsequent research utilizing this framework, is a lack of focus on a particular mode of transportation. The present study is framed by concepts from this revised model that capture the complexity of factors known to influence children’s travel to school.[23,40,108] The connection between these factors and walking to school has been demonstrated and studied previously using a conceptual model for SRTS operations developed by the National Center for SRTS.[70] Factors represented in the existing transportation and SRTS program-specific models lack
44 sufficient detail in their definition. Greater knowledge of these factors is considered critical for “moving from a conceptual to an empirical understanding”.[88]
A simple conceptual model for the study is shown in Figure 2 to highlight the components and relationships of interest from the complex parental decision-making process for travel to school. Conceptual and theoretical frameworks are described within the sections below.
45 Figure 2. Conceptual Model for Study
46 Social Ecological Model
A social ecological framework guided the exploration of factors in the environment associated with walking to school.[9] The research explored factors on multiple levels of the social ecological model that may interact to influence children’s mode choice for travel to school. The social ecological model has been used in a variety of behavior change contexts, including nutrition, physical activity, tobacco cessation and healthcare service utilization.[109] The social ecological model considers factors on a number of levels that influence behavior and opportunity for behavior change, including the environment, which is of particular focus in this study.[109,110] Specific barriers and facilitators to change exist for each level with different strategies to influence individuals to make a given behavior change.[110] The levels interact with each other in a reciprocal way, which assumes that individuals influence the factors around them and the factors around individuals influence them.[110]
Hierarchy of Walking Needs
The Hierarchy of Walking Needs (Figure 3) imitates Maslow’s theory on human motivation and provided a model of the walking decision-making process within the context of the social ecological framework.[111] The model proposed some of the walking needs are “more basic and fundamental than others” and are organized into five levels of walking needs (feasibility, accessibility, safety, comfort and pleasurability). The organization of the needs is supported by empirical evidence of macro-scale factors being most immediate and necessary while micro-scale factors (higher level needs) are less influential for the behavior.[68]
47
Figure 3. Hierarchy of Walking Needs [170]
The levels are not presented as a direct link to the behavior but rather as part of various moderators and as antecedents to the behavior of walking. The hierarchy alone, however, does not entirely explain the decision-making process leading to walking. The conceptual model also included a person’s perception. There are individual differences in the number of levels needing to be satisfied to support walking and the way individual circumstances contribute to perception of the needs being satisfied. Further, “individual-,
48 group-, and regional-level attributes may all moderate the relationship between the hierarchy of walking needs and a person’s decision to walk.”[111]
The Hierarchy of Walking Needs also demonstrates the variety of walking outcomes possible, which differ by duration and destination. This addresses the differences in needs that may occur depending on the type or purpose of the walking trip.[111] The framework guides prioritization of intervention to address needs level-by- level to effectively target efforts to increase walking. Addressing higher levels would not be useful if walking was not first feasible (or perceived as feasible). Thus, a community can assess which needs are deficient, identify the prime targets for intervention, and increase the effectiveness of the intervention.
The most basic level of need, according to the Hierarchy of Walking Needs is feasibility. In walking trips to a particular destination, such as the journey from home to school, factors of feasibility influence the decision-making process for mode choice, potentially limiting the options from which to choose. For example, if a household does not own a vehicle, the use a personal vehicle for the journey from home to school is not feasible. The feasibility of walking from home to school may be initially affected by school start time but vary daily or weekly depending on parental responsibilities.
The factors that influence accessibility include both the objective and perceived barriers to walking, including presence of sidewalks or other features that may be perceived as a place to walk. Perception of distance is an important factor at the level of accessibility, in particular for destination trips, such as the walk to school. Distance from home to school has been studied well as a factor in the parental decision-making process,
49 .[2,55,64,112,113] and results indicate that distance determines feasibility of the trip.
Perception of the distance as “too far” may lead immediately to the decision to use a travel mode other than walking to get to school.
The next level in the hierarchy is safety from the threat of crime. Safety, in this context, may be influenced by the presence of particular individuals (i.e., individuals that are homeless, drunk or known to be associated with a gang) or groups (i.e., gangs), the amount of disorder in the environment (i.e., trash, graffiti or abandoned buildings) or destinations along the route to school that are inappropriate for children (i.e., bars, liquor stores or nightclubs). Lighting along the route has been found to be negatively associated with fear of crime.[26,101]
Comfort is related to the safety of pedestrians from traffic and presence of street design features that reduce the speed and volume of traffic along routes (i.e., speed limits, narrow streets and buffers between sidewalks and streets). Implementation of features and tactics to reduce vehicle speeds and volume are related to an increase in the presence pedestrians and more walking.[11,22,77,106,114] Maintenance of sidewalks and pedestrian infrastructure also contribute to comfort.
Pleasurability is the final level of the hierarchy to be considered in the decision to walk and is “related to how enjoyable and interesting an area is for walking”.
Pleasurability is considered if the other needs are satisfied. This level has been explored in the literature mainly through preference. Preference for walking has been demonstrated for environments that are complex, decorated or unique in their aesthetics.[115]
50 Social Cognitive Theory
Social cognitive theory (SCT) is the most prominent theoretical underpinning for public health explanations of walking-related behavior.[116–119] The main construct, reciprocal determinism, has been best at explaining more recent research revelations about the relationship between people and their environments, acknowledging that behavior and environment are not strictly independent.[120] Reciprocal determinism proposes that people, their environments and their behaviors all interact causing changes to each other.[121] The shape of this relationship, represented as a triangle, implies indirect relationships among all three components. Therefore, behavior is connected to both perception of the world around us, and the physical and social environments around us. Subjective perception shapes our behavior.[122] Substantial literature has explored the role of cognition in the likelihood of physical activity, and separately, the influence of the environment and provided the necessary evidence to support use of SCT in application to the walk-to-school behavior.[98,123–125] The theory is useful in application to the context of transportation, fitting comfortably within the conceptual framework of the social ecological model.[116,119] Reciprocal determinism has been applied in the present study to demonstrate the flow of influence between the environment and parental perceptions, and between parental perceptions and the behavior of walking to school.
Broken Windows Theory of Urban Decline
Effects of the built environment on utilitarian physical activity, including walking, have been frequently modeled using the broken windows theory of urban
51 decline.[60,87,126] The theory operates on the environmental level of influences on physical activity (e.g., walking). Broken windows theory proposes that visual cues in the environment, such as graffiti, garbage and abandoned property (e.g., houses and cars) attract crime. The cues are indications to criminals that residents are not concerned with upkeep or protection of the neighborhood. Application of the theory to walking acknowledges both the direct and indirect influences of the built environment on physical activity with emphasis on the indirect influences. Like the construct of reciprocal determinism, urban decline purports flow of cause and effect between perception and the environment in both directions. The environment has an indirect influence on physical activity through visual cues. Indirectly, physical activity is influenced by disorder in the built environment. When individuals perceive disorder in the environment they are less likely to engage with that environment.[126] Direct influence on activity takes place through the physical form of the environment in such characteristics as well-connected street networks and short distances between destinations.[127] This theory, too, operates within a social ecological framework for the study.
Broken windows theory is one of a few mediation models that target factors which mediate participation in physical activity and aligns with the aims of the present study to address objective, as well as perceived, environmental barriers preventing walk- to-school behavior.[128,129] Characteristics that affect both the form of the physical street environment and the feelings evoked when in those environments are important for understanding how to encourage walk-to-school behavior. The theory also considers the role of individual level influences on perceptions, including sex, age, marital status,
52 education and employment status and studies have shown that safety factors are more salient for vulnerable populations, such as school-aged children.[24] Previously published studies with parents of school-aged children have frequently focused on individual and family level factors, such as parents’ level of physical activity or vehicle ownership.[78] While these relationships may be valuable to identify and study, they are not of interest within the conceptual framework of the current study. Individual and family level factors are not useful in targeting modifiable influences on the behavior and are beyond the scope of the SRTS programming.
Specific Aims
The present study applied a multi-level approach that bridged the previously described gaps in the existing research and practice related to safety of the environment for children walking to school. First, environmental factors that influence the choice, by parents of elementary school children, to use walking as the primary means of travel from home to school were selected as the independent variables of interest. Second, objectively measured data on environmental factors and parental perceptions of the environment were used to assess the relationship between safety and walking to school. Finally, a multistate, multisite study was conducted using a combination of analytic techniques offering robust results with strong external validity.
Specifically, the study addressed the following aims:
Manuscript #1: Investigate the spatial presence and patterning of objectively measured and perceived safety barriers that exist within 1-mile of schools and are known to impact walking to school.
53 Manuscript #2: Identify family, school and environmental level factors that predict the outcome of walking to school among families participating in SRTS programming.
Manuscript #3: Inventory and describe policies at multiple levels as they relate to walk-to-school behavior among elementary school children and their families at elementary schools and K-8 centers participating in SRTS.
Study Design
The study is an observational, cross-sectional, ecological study using secondary data from multiple sources.
Study Sample
A convenience sample of three local SRTS programs from different geographic regions of the United States were selected for the study (Table 3). Connectivity between the researcher and each of the local programs addressed feasibility of a national multi-site study involving multi-level analysis. The selected programs captured diverse geographic regions of the United States with diverse SRTS programs and offered a robust data set for each manuscript. Each of the selected local programs are associated with school districts considered large, urban school districts.[130,131] Two of the selected districts, San
Francisco and Miami-Dade, are county-wide. However, San Francisco is both a city and a county. Therefore, the selected SRTS programs also include two city-wide school districts. Despite the limitations in the choice to use a convenience sample, the study aims allowed for the exploration of what can be learned from data associated with these
54 programs and established these data as having utility to make contributions to the field of health promotion.
Use of local SRTS programs in mostly urban environments serving low-resource schools with diverse racial and ethnic populations will implicitly address major issues of equity in safety. Safety hazards, such as pedestrian-involved collisions with motor vehicles, are more likely to occur in low-income neighborhoods, and people of color are currently disproportionately represented among pedestrian injuries and fatalities.[132,133]
Table 3. Programs and Locations Included in the Overall Study Sample
Program name Location
San Francisco Safe Routes to School San Francisco California
WalkSafe Miami-Dade County Florida
Columbus Safe Routes Columbus Ohio
Descriptive characteristics for the locations of the individual programs are provided in Table 4. Despite the diversity of the locations, similarities included racially/ethnically and economically diverse populations, and proportion of children ages
5 through 14 years. As described above, the selected programs all serve large, urban school districts. The selected programs are a fair representation of the overall population of local SRTS programs in urban areas and the locations served by those programs. 55 Differences still exist that could lead to site-level differences that may affect the results of the studies. One key difference is average monthly temperature. The average high and low temperatures vary across locations. The potential impact of this difference is not clear from existing literature. Studies have inconsistently controlled for or considered weather.[19] However, a well-designed observational study on children’s active commute to school found that a change in temperature of one degree Fahrenheit changed the odds of active commuting (which includes walking) by 3%.[98] Much of the analyses in the present study were stratified by local SRTS program to allow results to differ according to location and consider site effects in the interpretation of results.
Differences in the resulting strength of relationships between individual factors and the outcome might also have been a result of the variation in these (and other, unaccounted for) characteristics. For example, characteristics of the location influence the type of person drawn to that location. Many of the key differences between and among the three sites have been accounted for in the study design and methods for analysis. For example, inclusion/exclusion criteria accounted for differences in the year each local SRTS program was established and length of participation in the program by individual program schools. Inclusion criteria limited the sample of schools to those with a program exposure length of two years. This allowed for the year the program was established to vary while controlling for length of exposure to the program. The scale of the study and included factors provided additional strength for site selection and control for possible site-level effects. These are discussed in greater detail in later sections.
56 Table 4. Characteristics of Study Locations
Location San Francisco, CA Miami-Dade County, FL Columbus, OH Population size 870,887 2,639,042 824,663 Population of children 5 to 9 years 30,488 (3.6%) 150,017 (5.7%) 53,426 (6.5%) 10 to 14 years 27,427 (3.3%) 150,725 (5.7%) 45,108 (6.5%) Land area 46.87 mi2 2,431 mi2 223.1 mi2 Schools in school district 133 392 109 Median age (years) 38.5 39.0 32.0 Racial compositionb Non-Hispanic White 346,732 (41.2%) 398,700 (15.1%) 479,231 (58.1%) Non-Hispanic Black 44.879 (5.3%) 444,590 (16.8%) 226,377 (27.5%) Hispanic 128,619 (15.3%) 1,731,733 (65.6%) 47,007 (5.7%) Asian 281,896 (33.5%) 40,265 (1.5%) 37.535 (4.6%) Other 3,941 (0.5%) 5,111 (0.2%) 2,925 (0.4%) Average monthly temperature high/lowc January (°F) 57/46 °F 76/60 °F 36/20 °F May (°F) 64/51 °F 87/73 °F 73/52 °F a Source: American Fact Finder, US Census (2015) Accessed from: https://factfinder.census.gov. Accessed on: 3 May 2017. b Reported based on single race data from ‘Hispanic or Latino and Race’ c Source: US Climate Data (2018). Accessed from: https://www.usclimatedata.com. Accessed on: 26 January 2018.
San Francisco Safe Routes to School, San Francisco, California
The San Francisco Safe Routes to School (SFSRTS) program serves schools from the San Francisco Unified School District (SFUSD). SFUSD is one of the eight agencies involved in facilitating the SFSRTS program (www.sfsaferoutes.org). The program was first implemented in the 2009-2010 school year.
WalkSafe Program, Miami-Dade County, Florida
The WalkSafe Program serves schools from Miami-Dade County Public Schools
(MDCPS) District (www.dadeschools.net). The program is housed at the University of 57 Miami Miller School of Medicine. The WalkSafe Program was first implemented as an education-only program in 2001 prior to the formation of the National SRTS Program and associated funding.
Columbus Safe Routes, Columbus, Ohio
The Columbus Safe Routes to School (CSRTS) Program serves schools from
Columbus City Schools (CCS) District (http://ccsoh.us). CSRTS was first offered district- wide in the 2015-2016 school year, after completion of a district-wide School Travel Plan to determine steps to integrate health impact assessment results with school transportation.
Sample of Schools from Selected Local SRTS Programs
Schools serving children in grades K through 5 (e.g., elementary schools, STEM academies and K-8 centers) were targeted for inclusion in the study. Although some local
SRTS programs provide programming to older children, middle and high schools have been excluded from the study sample as the transportation decisions for children in grades K through 5 are not yet independent of parental control. They are also impacted differently than other age groups by school district transportation policies and resulting options for travel to school. Schools from each local SRTS program included in the study sample were selected from K-5 schools that have ever or currently participate in SRTS programming. The exact number of schools from each SRTS program included in the study is given within individual manuscript chapters. Overall, schools from each program were excluded if they lacked data on variables of interest. A list of schools from each local SRTS program that were included in analysis is provided in Appendix A. However,
58 included schools varied slightly in each manuscript due to differing inclusion/exclusion criteria associated with the respective manuscript aim and analytic technique. The location of schools for the selected local SRTS programs are mapped in Figure 4, and descriptive characteristics of the schools have been provided in Appendix B.
Figure 4. Included Schools for Each Local SRTS Program: (a) SFSRTS, (b) WalkSafe,
(c) CSRTS
Measures and Data Collection Procedures
First, the definition of safety and how it was operationalized in the study is provided. Then, an overview of the measures used to capture data for the study and data collection procedures for each of the three main datasets are given here. Additional details to describe the data, collection procedures and scope of the analysis for each manuscript are provided within each manuscript chapter.
59 Safety was defined, overall, by two aspects in the study: (1) traffic and (2) neighborhood, which was then further defined by specific factors. The specificity of factors in defining traffic and neighborhood safety addressed the problem of varied representations of safety across the literature. Although the two selected aspects of safety were often referred to generally or interchangeably in the literature, here, the definition was guided by the SRTS context and the outcome of interest (walking to school). The study defined and described safety using selected environmental factors and measures of their presence within 1-mile of schools. The distance of 1-mile was considered the study area based on existing evidence this is a walkable distance for elementary school age children. Traffic safety factors related to a specific pedestrian-relevant physical threat of harm while making the journey from home-to-school, and neighborhood safety factors related to the physical environments through which children must travel on their way to school. The focus in these analyses was modifiable environmental factors, although additional relevant factors were included. The focus on modifiable factors, however, defined safety in a way that would allow for translation to actionable environmental and behavior change.
Human Subjects Protection
According to Institutional Review Board guidelines, the study was considered exempt. The research involved the collection and study of existing data. Human subjects’ data used in portions of the analyses did not contain identifying information that could be linked to participants.
60 Confidentiality
Results from each portion of the analyses have been reported in aggregate or non- individual level. At no point during data collection was any individually identifying information collected and no surveillance of data was kept at any of the participating school sites. There is no access available for the SRTS program or research teams to any specific information about children or families at participating schools that could lead to their identification.
Dataset #1 Safe Routes to School Parent Survey
Safe Routes to School Parent Survey Overview
The Safe Routes to School Parent Survey tool (Parent Survey) was used to capture data on parental perceptions and other family-level data (Appendix C). The survey was developed by the National SRTS Partnership to collect information on the knowledge, attitudes and beliefs of parents toward allowing their children to walk or bike to school. The survey tool also captures information on key safety-related factors that impact the decision to walk to school.[99] Details on the development and testing of the survey are published elsewhere.[3] The survey has been used nationally by all local
SRTS programs to evaluate the impact of the program on parents’ awareness of the program and willingness to allow their children to walk or bike to school after implementation of activities. Use of this programmatic evaluation tool facilitates collection of comparable data from multiple programs and provides the potential to look across data from all 50 states and several local programs in each state. The Parent Survey
61 has also been used to validate the other evaluation instrument required nationally by the
SRTS program, the Student Travel Tally.[134,135]
Data for analysis from the Parent Survey included home location information
(intersection nearest to home) and perceived barriers to walking to school. Parents’ home addresses were geocoded for analysis based on the home location information provided by parents on the Parent Survey. Six perceived barriers (distance, speed of traffic along route, amount of traffic along route, sidewalks or pathways, safety of intersections and crossings, and violence or crime) were included as binary variables in Manuscripts #1 and #2.
Data generated by the Parent Survey are stored online through the National Center for SRTS Data website (www.saferoutesdata.org). Data were downloaded from the website, coded and stored in Excel.
Data Collection Procedures
Parent Survey data were collected as part of funded activities in fulfillment of grant reporting requirements by the local SRTS programs. There are no national standards or guidelines for SRTS data collection procedures for the Parent Survey, however, suggested strategies have been published in well-known program reports and local programs follow regional recommendations.[136] SRTS Parent Survey forms were distributed to each child in all K through 5 classrooms at participating schools.
Instructions provided to schools for distribution and collection of Parent Survey forms were sent home with children to be given to parents. Surveys were distributed in a total of four different languages among the participating schools. These languages, English,
62 Spanish, Haitian-Creole and Cantonese, represent the major languages of families at participating schools. This data collection process takes place annually for each program.
Although the use of the forms was required for the programs, return of surveys by parents and schools was voluntary. More detail on the data collection procedures for each local
SRTS program are given here.
Data collection for the SFSRTS program was completed by the San Francisco
Department of Public Health (SFDPH). A single paid staff member of the SFDPH coordinated all aspects of data collection. Data collection materials were packaged according to the schools’ preferences by either: (1) providing the needed number of copies of the surveys to be sorted and distributed by parent volunteers or (2) packaging the needed number of copies of the surveys by classroom and providing them to individual classroom teachers. Surveys were distributed to families in English, Spanish and Cantonese. A modest incentive in the form of a grocery store gift card was offered to classroom teachers as a token of appreciation for distributing the forms. Teachers must receive a minimum response rate to the survey of 80% to receive the reward. Data collectors were contracted to assist with distribution and collection of surveys at the start and end of each school year during each year of data collection.
Data collection for the WalkSafe program was facilitated by its staff. Paid staff coordinated all aspects of data collection. Data collection materials were packaged by classroom for each school, according to classroom rosters. Data collection packages for all classroom teachers were provided to individual schools for distribution. Surveys were distributed to families in English, Spanish and Haitian-Creole. Enough surveys were
63 provided in English for every classroom; surveys in additional languages were distributed according to the total proportions of Spanish and Haitian-Creole language in each school.
A modest gift in the form of a branded multi-colored ink pen was provided in the data collection package for classroom teachers.
Data collection for the CSRTS program was led by Columbus Public Health. Two paid staff members from the department coordinated data collection with the Director of
Wellness at CCS. Data collection materials were packaged by classroom for each school, according to classroom rosters. Data collection packages for all classroom teachers were provided to individual schools for distribution. Surveys were distributed to families in
English. No incentive was provided to classroom teachers.
A brief letter to parents appeared on the Parent Survey form that instructed parents to complete only one survey per household. If more than one child in the household attended the same school, parents were instructed to respond to questions about the youngest child (and still only complete one form). Forms were returned to either the classroom teacher or the school’s main office and collected by program coordinators or data collectors.[99] All original surveys used in the sample were sent by mail to the National Center for SRTS Data, which is housed at the University of North
Carolina Chapel Hill in North Carolina. The design of the forms allowed them to be scanned and entered into an electronic database, from which data can be downloaded by users with access to the center’s website (www.saferoutesdata.org).
64 Potential Limitations from Data Collection
Data collection procedures for each program vary slightly, involving different data collectors (e.g., teachers or volunteers) or different collection strategies (e.g., mailed home to each family or sent home through students’ folders), which may have differentially encouraged participation from parents in each school district or at individual schools. Other differences in data collection may come from the gifts or incentives that are provided by the WalkSafe and SFSRTS programs to classroom teachers. Although parents’ participation in the survey is voluntary, classroom teachers may have treated it as a school assignment. Classroom teachers that managed distribution and collection of the Parent Survey form the same as a homework assignment may have received a higher response rate than those that did not encourage survey return.
The timing of data collection and length of exposure to SRTS activities differs among the three participating local SRTS programs. Sample selection was used to account for these differences in each manuscript by defining inclusion/exclusion criteria based on length of exposure to the SRTS program. For all manuscripts, schools that only had a single year of exposure were excluded. Clustering of data was also accounted for in the overall design of the study.
Survey data are often subject to response bias due to the likelihood of certain individuals to complete the survey compared to the rest of the eligible population. Bias in survey completion may have come from a lack of familiarity with the SRTS program.
Parents that were not familiar with the program or less involved with the program, for example, may have been less likely to complete the survey than parents who regularly
65 participated in program activities. Parents that participated more actively in SRTS programming may also have had a different level of knowledge of safety than the general population of parents at a particular school. Although the survey is provided in three different languages in each of the selected school districts, parents may not have been literate in the language in which the form was provided (or may not be literate above a basic level). The appearance of the form may have been off-putting for some parents. The form was designed to allow for automated data input using computer technology and did not have a user-friendly appearance. Privacy may also have impacted parents’ willingness to complete the survey; the survey contained some questions asking for personal information such as highest level of education completed. Parents may have refused to participate if they felt the survey was an invasion of privacy or felt it asked questions that may compromise their child’s safety.
Dataset #2 Environmental Factors
Data Overview
Secondary data on objectively measured environmental safety factors (GIS data), that were collected separately for non-research purposes, were used in Manuscripts #1 and #2.
The definition of safety in the study was guided by parental perceptions captured using the Parent Survey. Factors were identified based on the Parent Survey tool as well as using previous studies that tested and described the relationship between ‘safety’ and the outcome of walking to school among children. The review focused on identifying and selecting factors most relevant to the area 1-mile or less from schools, and on
66 measurement of those factors. The initial set of factors identified from the Parent Survey
(Appendix C) are shown in Table 5.
Table 5. Safety Factors from the Safe Routes to School Parent Survey
Distance Speed of traffic along route Amount of traffic along route Sidewalks or pathways Safety of intersections and crossings Violence or crime Convenience of driving Time Child’s before or after-school activities Adults to walk or bike with Weather or climate Crossing guards
Factors from the Parent Survey not readily modifiable through environmental intervention were excluded and not included in the review (convenience of driving, time, child’s before or after-school activities, adults to walk or bike with, weather or climate, and crossing guards). Fear of sexual offenders was identified through the review process for use in the study as a measure for the neighborhood safety factor of violence or crime.[17,22]
Environmental Safety Factors
Distance was calculated during analysis using geocoded address data for parents and schools. Parents reported the intersection nearest to their homes. Address data for
67 schools were publicly available online. School address data were collected by the investigator using the school district websites and confirmed by a school search on the
NCES website. These address data were compiled in Excel worksheets, then geocoded using GIS software for analysis for Manuscripts #1 and #2. Objective (estimated) distance between home and school was measured using a shortest distance analysis. The analysis estimated the distance of individual walking routes for each family from home to school based on the geocoded address data. The technique has been used frequently in studies of pedestrian decision-making, and comparison studies of shortest route with actual route for walking or bicycling to school found no significant difference in length.[79,137]
Data for traffic safety factors (speed of traffic, amount of traffic, sidewalks or pathways, and safety of intersections or crossings) related to the SFSRTS program were publicly available online at http://transbasesf.org. Data for these factors related to the
WalkSafe program were publicly available at http://gis-mdc.opendata.arcgis.com/.Data for these factors related to the CSRTS program were provided to the investigator as a geospatial database, which had been compiled from various sources by staff from the
Ohio Department of Transportation. Speed of traffic was measured as the posted speed limit along the routes between parents’ home addresses and school locations. Amount of traffic along the route was measured by AADT, which is a standard method of measurement for traffic volume nationally. The factor ‘sidewalks or pathways’ was measured. Data on the neighborhood safety factor (violence or crime) were available online through the county law enforcement. These data were collected and reported
68 online by responsible agencies as part of the regular duties. No new instrument was designed or tested for the measurement of environmental factors included in the study.
Potential Limitations from Data Collection
There were some concerns about limitations of the objective safety data used in the study. First, the usual limitations of secondary exist. Data were originally collected for other purposes and have been applied here for their utility in exploring a significant public health problem. The compliance of the agencies responsible for data collection with procedural standards was not possible to assess. Data were vulnerable to some human error in the data collection process, such as failure to correctly operate measurement instruments, but it was assumed to be no more than usual. Data collection instruments were operated by agency staff as part of usual job responsibilities, which required specialized knowledge and training common among traffic engineers. An additional limitation for these data was the timing of data collection. Data were collected years prior to the study being initiated. There may have been differences in the time of day or season in which data were collected. Only information on the year data were collected was available for most datasets. Data collection for the factors ‘sidewalks or pathways’ and ‘safety of intersections or crossings’ was most concerning because these were collected differently by each study site with no single measure used by all three sites. Not all collected data were made publicly available, which limited the accessibility of potential measures. This was particularly a problem at the local level for Columbus,
Ohio. Speed of traffic and amount of traffic along the route were uniformly measured among the three study sites according to the corresponding national standards. Sex
69 offender data, too, was uniformly reported as mandated by federal law. However, these data were stored dynamically online and updated daily. The investigator accounted for this issue in the process of capturing the data for use in the study to ensure that the timing of sex offender data collection was the same for all three study sites. Although multiple datasets to measure each of the selected factors were explored, the selected measures may have led to loss of important information for each factor. The use of GIS, too, can contribute to a loss of information due to the large amount of data being analyzed.
Objective safety data related to the SFSRTS program were available through a single website, which had general guidelines for use. The other two sites, however, did not have the same structure and availability of data. Despite these limitations, however, the investigator worked to select data aligned with the study aims and that allowed for the most consistent measurement across all three study sites.
Dataset #3 Safe Routes to School Policies
Policy Data Overview
Currently, there are no national repositories for school policies on active transportation. Data on policies used for analysis in Manuscript #3 were generated through review of online sources and input into an Excel workbook. An overview of the classification scheme for policies is given in Table 6, then further defined in the sections below.
Table 6. Policy Classification Scheme
Classification 70 Levels School District City (local) Region State Federal Categories Wellness Transportation City/Regional Master Plan Complete Streets Types Legislation Regulation Agency Action
Data included published policies from the schools included in Manuscripts #1 and
#2, their associated school districts, local jurisdictions, regions, and states, as well as federal policies. These levels of policy are outlined in the top row of Table 7.
71 Table 7. Levels of Policy Included in Policy Scan
Program School District Local Jurisdiction Region State SFSRTS San Francisco City & County of Bay Area California Unified School San Francisco District Walksafe Miami-Dade City of Hialeah Miami-Dade Florida County Public City of Homestead County Schools City of Miami City of Miami Gardens City of North Miami Beach City of Opa Locka Columbus Columbus City City of Columbus Mid-Ohio Ohio Safe Routes School District
Policies were grouped into three types in the policy scan: (1) legislation, (2) regulation, and (3) agency action. The grouping was used as a variable in analysis to capture descriptive information about the policies included in the scan. Here, legislation was defined as policies that have gone through a legislative review process for formal acceptance by an appointed body within government and considered enforceable by law.
In the policy scan, this includes titles such as act, bill and policy. Regulation refers to official guidance provided to responsible agencies on implementation or enforcement of legislation. Regulation in the policy scan included tax, standards, guidelines and plans.
Finally, agency action was defined as a governing body acting in a quasi-legislative capacity to create policy that advocates for or aligns the agency with a particular view.
Agency action in the policy scan included position statements and resolutions.
72 Categories of Policy
School Wellness Policies
The adoption of a school wellness policy is required by districts participating in the National School Lunch Program.[71,138] The wellness policies written by schools must include physical activity goals and address opportunities for students to be physically active before and after school, which can include SRTS. Model language has been provided at the national level of SRTS to guide local programs in writing consistent but tailored language to address walking to school.[139] Inclusion of walking options along with school transportation information is one other possible method for establishing SRTS policy within schools. For example, SFUSD offers ‘Alternatives to
Yellow Bus Transportation’ on the district website with information on free passes for youth to use the public transit system and links to the local SRTS program.[140]
Transportation Policies
California created the first state-level SRTS infrastructure program in the US in
1999. The program was created by authorization of a Bill allowing for the use of federal transportation funding to construct projects to increase the safety of child pedestrians and opportunities for them to be physically active on the way to school. The infrastructure program received support from professionals in multiple related disciplines, including transportation, physical activity, injury, and urban design, and has been reauthorized several times since its initial implementation.[17] The infrastructure program is most closely aligned with the vision and goals of Departments of Transportation at all levels of government (local, regional, state and federal). Relevant examples of major
73 transportation policies include the Transportation Element within City/Regional Master
Plans (or stand-alone Pedestrian Master Plan) and Complete Streets. These policies are described further in the sections below.
Transportation Element within City/Regional Master Plan
Pedestrian Master Plans are a framework for prioritizing pedestrian improvements. Pedestrian Master Plans are commonly devised at the city level but may be designed at the regional or state levels. The purpose of the Plan is to guide achievement of a decided vision for improvements to conditions for walking.[141–143]
The Pedestrian Master Plan is a detailed action plan with a measurable set of strategies and objectives as well as prioritization of improvements. Cities often implement a
Pedestrian Master Plan with expectation of achieving health, transportation, environmental, economic and social equity benefits.[143,144]
Complete Streets
The National Complete Streets Coalition is a program of Smart Growth America and the predominant resource of the planning, implementation and evaluation of
Complete Streets projects and policies. Complete Streets is an approach to city planning that “integrates the needs of people and place in the planning, design, construction, operation, and maintenance of transportation networks.”[145] The approach integrates transportation and public health to design and operate street networks that provide safe access for users of all transportation types and of all abilities.(https://smartgrowthamerica.org/completestreets) Policies are each unique to the
“community context” in which it is being implemented and may be implemented at any
74 level of government, including local, regional and state levels. The newest federal transportation bill encourages states and regional planning agencies to implement
Complete Streets design standards or policies. Federally-funded projects are required to use Complete Streets design standards in their conception; best practices are shared in a published report.[145]
Data Collection Procedures
Two main search strategies were used to ensure an exhaustive inventory of the levels and categories of policies described above. The first, was a manual search to find publicly available policies published online. The second strategy was a literature review of law databases. The policy scan was conducted independently first by the researcher.
The protocol was then provided to a research assistant to assess validity. The protocol was then iteratively applied to any additional policies that were identified by the research assistant during the review process. Each strategy is described in more detail below.
The manual search involved an online search of school, school district, city/municipal, regional, state, and federal websites. Specifically, the researcher reviewed each page of the individual school websites to identify any policy or language related to the categories listed above. At all other levels, transportation and education department websites were reviewed. Following manual review of the websites by the researcher, an internal search of the sites was conducted using the website search tool. The combination of these two techniques was used to limit the potential for relevant information to be overlooked. The search terms “walk” and “safe routes” were used. Any policies that were identified were downloaded or otherwise saved for further review.
75 In the second search strategy, review of literature from law databases, WestLaw and NexisLexis served as the sources from which policies were identified, accessed and reviewed. The same terms used in the manual search were used.
Policies were considered for further review if they discussed or related to the
SRTS program. Consequently, policies describing transportation, or education and wellness initiatives outside of the categories interest were excluded. The initial 245 policies identified for review were further reduced if duplication was found among policies at the same level. Other phases of elimination were based on the following exclusion criteria to ensure the final sample was most aligned with the purpose of the policy scan: (1) too conceptual or high-level (i.e., no influence on implementation of
SRTS); (2) restated higher level policy, or (3) spoke to the appropriation for funds for a policy that was already identified separately. A final sample of 86 policies were reviewed.
76 Chapter 4. Manuscript #1 Introduction
Children’s environments, where they live, and where they walk, can critically influence their health.[9,26,103,146] Neighborhood and the built environment is one of five key areas within the Healthy People 2020 framework and a major social determinant of health.[147] The conditions of the environment, including physical and social factors, affect health behaviors such as walking to school.[148–151] The proportion of elementary and middle school children that walked to school in 2009 had declined by approximately 20% compared to 1969.[38] Walking is the usual mode of travel for only about 25% of elementary school children living within a half-mile of their schools.[81,113]
A wide range of threats to safety, both objective and perceived, can exist within the environment between home and school.[33,101,106,148,152,153] For example, limited access to sidewalks is a physical barrier that creates a threat to safety for children walking to school in that environment. Parental perceptions of the environment, such as sidewalk presence, also affect school travel decisions.[27] Children that do not walk experience fewer health benefits of walking compared to their peers.[154] The health consequences of less time active, combined with more time sedentary, amplifies the potential negative health consequences for young children.[155,156] To address this problem, there has been a call for population level strategies to promote walking to school that make health promoting changes to the neighborhood and built environment.[157] Successful mitigation of safety barriers, including effective improvement of parental perceptions, can be most impactful with a targeted, location- 77 specific approach to assessing threats to safety within the environment between home and school.
The use of location data in analysis has been judged by leading researchers to be important for the advancement of social sciences.[158] Results of a public health review, too, encouraged use of spatial datasets to discover meaningful results.[159] Spatial analysis has been used in a variety of public health-relevant contexts, including environmental health and chronic disease prevention.[160–162] Spatial databases add a new dimension to health behavior analyses of relationships between predictors and outcomes. The explicit use of location is critical to better understanding prevalent and salient factors related to walking from home to school. Spatial analysis has the potential to reveal hidden patterns and relationships that may not be apparent from non-spatial data.[33,163,164] Spatial techniques allow for detailed analysis and the visualization of spatial patterns, as well as identification of areas with unusually high or low incidence of the factors and behavior of interest.[165] Beyond the location of individual factors, spatial techniques to analyze data can also explore the geographic relationships between factors.[166] For example, spatial datasets can be layered to determine locations where safety barriers occur together. Alternatively, locations with an absence of safety barriers can be highlighted with spatial analyses. The relatedness of factors in a geographic context, which assumes that conditions nearer to each other are more related than those more distant from the others, can also be analyzed.[166,167] Both of these are examples of how similarities and differences between the presence of objective and perceived barriers can be highlighted through spatial analyses. Identification of patterns can assist
78 both researchers and practitioners in developing targeted interventions. Locations where change is needed and identified patterns from spatial analyses can be used to prioritize necessary interventions.[33,168] Minimizing both measured and perceived safety barriers in the environment between home and school can lead to better physical, social, emotional and academic outcomes for children.
A robust accumulation of science to describe safety in the context of geography, environmental psychology and public health has helped to identify influential factors related to walking for transit among adult populations, youth and children of varying ages.[22,100,169] A review of common factors that influence walking among elementary school-aged children found distance, traffic and crime fears were among the most common.[16] High levels of traffic safety concerns among parents were persistent across different urban neighborhoods with varying socioeconomic levels.[170] Parental perceptions of those safety factors, too, are associated with walking to school. Parents are more willing to walk or allow their child to walk when they perceive greater safety.[27,28]
While research has recognized the interaction between place and health, the use of complementary data on modifiable safety barriers that prevent families from walking their children to school have not yet been fully studied.[16,24,40] The present study used a socioecological framework and theory-driven approach to explore an important emerging analytic technique in health promotion. The study builds on the existing literature by using exploratory spatial techniques on objective and perceived safety data to explore walk to school behavior. Safety factors were selected from established,
79 common factors of influence on the outcome of walking to school.[16] These analyses also extend the current literature by examining whether locations where safety concerns exist align with locations parents perceive to be unsafe. This has implications for effectively targeting barriers that limit participation in incidental physical activity and may increase the perceived lack of safety. To better understand the presence of safety barriers in the space between home and school and their locations, this study explored selected barriers for elementary school aged-children at schools participating in an active transportation promotion program. The purpose of the study was to investigate the spatial presence and patterning of both objective and perceived safety barriers, within 1-mile of schools, that may restrict walking to school.
Methods
Study Design
An observational, cross-sectional design was used to examine the prevalence of pedestrian level safety factors in the physical environment and parental perceptions of those factors as barriers to walking to school. The study area consisted of 1-mile buffers around the locations of schools included in the study. The timing of data collection for individual safety factors varied. However, data from the most recent collection between
2010 and 2015 were included.
Study Sample
Study participants were families of elementary school-aged children from three school districts in geographically diverse locations: San Francisco Unified School
District, Miami-Dade County Public Schools, and Columbus City Schools. Parents, and
80 the corresponding schools, were identified for participation through the Safe Routes to
School (SRTS) program. The study was limited to families that had been exposed to the
SRTS program for two years sometime between the 2008-2009 and 2014-2015 school years. The length of program exposure for inclusion was determined based on the timing of data collection among the local SRTS programs. The Columbus program only began collecting data in Spring 2014. Two years of exposure allowed for consistent length of exposure across the three programs, as well as to allow for the most robust possible analysis. Secondary data from the SRTS Parent Survey (Appendix C) were used to capture information on parental perceptions of safety. The Parent Survey is an annual evaluation tool implemented by the local SRTS programs. The three local programs that served the included school districts were San Francisco SRTS (SFSRTS), WalkSafe and
Columbus Safe Routes (CSRTS). A map of the final sample of schools for each program is presented in Figure 5.
81
Figure 5. Map of School Locations for the Local SRTS Programs: (a) SFSRTS, (b)
WalkSafe and (c) CSRTS
Measures
Measures used in the study included school and family locations, and safety characteristics of the areas between school and family locations. The study used secondary data collected on parental perceptions of traffic and neighborhood safety, and then sought to pair those safety constructs with objective GIS data for each construct.
These two data sets are each described in more detail within the subsections below, as well as additional data used in analyses. The geographical unit of analysis was the school level.
School Location: Study participants provided the name of the child’s school on the Parent Survey form (Appendix C). School location data were obtained from the
82 school district websites. School location data were geocoded. Available GIS data on road segments within 1-mile of the school site were included in the initial data acquisition to measure the objective safety of the study area.
Family Location and Parental Perceptions: Participants reported the name of two intersecting streets nearest to their home on the Parent Survey form. These intersections were treated as addresses when geocoded and included in analyses. Parent Survey data were also used to assess parental perceptions of safety for distance, speed of traffic along route, amount of traffic along route, sidewalks or pathways, and safety of intersections and crossings and violence/crime. The perceptions were measured on the survey using a simple check box (see page 2 of Appendix C). The safety factor was considered a barrier if the survey box was checked. All empty boxes were assumed to indicate the factor was not a barrier.
Objective Safety Barriers: The objective safety barriers included in the study were speed of traffic along route to school, amount of traffic along route to school, presence of sidewalks or pathways, safety of intersections or crossings, and violence or crime.
Measures of these barriers were posted speed limit among road segments between home and school, average daily traffic volume (AADT), sidewalk continuity (length of sidewalk/length of road segments), number of traffic lanes, and total number of registered sex offenders. Each of these measures captured available data within 1-mile of school locations. Measures for speed and amount of traffic along route to school aligned directly with the respective safety barriers. Presence of sidewalks or pathways was measured using continuity to allow for an aggregate measure representing the entire study area.
83 Number of traffic lanes was used to operationalize safety of intersections and crossings.
Violence or crime was operationalized as number of registered sex offenders residing in the area. Objective safety barrier datasets were created using geoprocessing techniques in
ArcGIS 10.2 Desktop software (ESRI 2011, Redlands, CA). All school and parent locations were added to the map document, then spatial joins were performed in ArcGIS to link the parental perceptions and the objective safety barrier datasets with the schools
(Appendix D). School polygons were defined by a 1-mile buffer around each included school. The 1-mile buffer served as the school study area boundary and is described further below.
A summary of GIS data sources and years of data collection for each program is provided in Table 8. GIS data for speed of traffic, amount of traffic, sidewalks, and intersections were obtained from online repositories maintained by the local, regional or state agencies for the SFSRTS and WalkSafe programs. Data on two safety factors (speed of traffic and safety of intersections or crossings) for the local San Francisco SRTS program were available at the time of analysis and accessed at http://transbasesf.org/transbase/. A database with the safety factor data for CSRTS was compiled and shared by email with the researcher by staff from the Ohio Department of
Transportation. Additional data for the Columbus program was retrieved through the City of Columbus GIS website. Home address data for registered sex offenders in each of the study sites were collected from government websites, which are listed in Table 8. Open data sites, including ArcGIS online, were also used in an attempt to obtain complete safety factor datasets for the three local programs. Requests were submitted by email to
84 individual agencies to obtain data which was not available online. However, some data were not available at the time of analysis.
85 Table 8. Summary of GIS Data Sources
Safety Factor Source (year data collected)
SFSRTS MDC Columbus
Speed of traffic http://transbasesf.or https://ftp.fdot.gov/fil Statutory Speed Limit g/transbase/ e/d/FTP/FDOT/co/pla (2014) (2015) nning/transtat/gis/TR ANSTAT_metadata/f unclass.shp.xml (2016) Amount of traffic Not available https://ftp.fdot.gov/f WGIS_AADT_SEG ile/d/FTP/FDOT/co/ MENTS planning/transtat/gis (2015) /TRANSTAT_meta data/aadt.shp.xml (2016) Sidewalks or Not available https://ftp.fdot.gov/fil http://apps.morpc.org/ pathways e/d/FTP/FDOT/co/pla sidewalks/ nning/transtat/gis/TR (2016) ANSTAT_metadata/si dewalk_barrier.shp.x ml (2016)
http://gis- mdc.opendata.arcgis .com/datasets/a7e94 49c8ec04bd39fb952 e66e341442_0 (2016) Safety of http://transbasesf.or http://www.fla- IntersectionsData intersections and g/transbase/ etat.org/est/metadat (2012) crossings (2015) a/number_of_lanes. htm (2014)
86 Data Analysis
Overall, an exploratory secondary data analysis of traffic and neighborhood safety factors that impact the decision to walk to school was conducted using ArcGIS 10.2
Desktop software (ESRI 2011, Redlands, CA). A GIS database was created to integrate the school, parent and objective safety factors data for analysis. Kernel density mapping was used to assess the spatial patterning among the perceived and objective datasets, separately. Then, analyses were applied to the data to measure the spatial co-occurrence of the data. Additional non-spatial analyses were used to assess agreement between the objective and perception datasets.
Geocoding Data. School names and addresses, including street address, city, state and zip code were entered into separate CSV files for each local SRTS program, then added to ArcGIS. School addresses for each local SRTS program were then geocoded, separately, using the ‘North America Locator 2015’ available through The
Center for Urban and Regional Analysis at The Ohio State University. [ https://cura.osu.edu/agol/training-resources/geocoding] For parent home address, exact street address was unknown. Intersections nearest to home were collected on the Parent
Survey instead. Street name data for the two streets nearest home within the existing
Parent Survey datasets were concatenated to create a single column containing parents’ address information. An iterative process was used to refine the percentage of matched addresses, including use of additional columns to further specify location (e.g., city, state and zip code) and lowered spelling sensitivity for street names. Each step of the process
87 was retested with a sample of Parent Survey addresses (n = 500). A summary of results from the matching process are given in Table 9.
Table 9. Summary of Address Matching Process in ArcGIS
Results of Matching (%) Matched Tied Unmatched San Francisco SRTS 3,642 (84) 623 (15) 26 (1) WalkSafe Program 1,016 (28) 2,587 (71) 60 (2) Columbus Safe Routes 2,296 (78) 423 (14) 209 (8)
Additional steps in the geocoding process were necessary to clean the WalkSafe
Program data, based on results from the matching process. Results for the WalkSafe program had a lower match percentage than the other two programs, which could be affected by the way data is collected by the WalkSafe program. The geocoding tool may also have been a source of error. Addresses that contained more than one segment label, such as 41st Ave Rd & NW 7 St (which are correct) failed to match initially. Participants’ primary language also influenced these results. Addresses written in Spanish failed to match. For example, when a respondent wrote “calle” (street), the geocoding tool did not recognize languages other than English. In these instances, translation was completed and exact matches were able to be found. From the sample, 60% of addresses were able to be rematched. This appeared to indicate a need for a more detailed review of address information. The dataset was revised to use ‘city = Miami’ for all entries, rather than the city name in which the corresponding school was located. This resulted in 23% (1,757) of
88 addresses matched, 56% (n = 4,315) tied, and 21% (1,651) unmatched, which more closely resembles the results of the other two programs.
89 Finally, unmatched addresses were manually reviewed by the investigator to identify appropriate matches, if possible, for the intersection data. Matching of data to locations was done using the interactive rematching tool in ArcGIS. Unmatched addresses were entered into Google Maps to help identify potential corrections for the intersection information. The process is displayed in Figure 6. Manual interactive rematching was conducted by reviewing a sample of ‘Unmatched addresses’ by entering the given intersection into Google Maps. Unmatched addresses were frequently parallel streets rather than intersections (e.g., Anza St & Balboa St), or addresses outside of the school district boundaries. Segment labels (st, dr, ave) or directional information (n,s,e,w) and zip codes that could be obtained from Google Maps were used to search in ArcGIS for a match candidate in the interactive rematching tool. The initial matched addresses with the additional rematched address were used in analyses.
90 91
Figure 6. Interactive Rematching Process Using GIS and Google Maps
91 Projections. Spatial data use projections to display data and minimize distortion. According to the ArcGIS website, a projection is a way to convert data corresponding to a geographic location on the curved surface of the Earth onto the flat surface, such as two-dimensional maps (http://pro.arcgis.com). Individual data sets were projected using the appropriate State Plane Coordinate System (NAD 1983) from the
‘Projected Coordinate Systems’ in ArcGIS. Some level of distortion is expected with any projection, however, the selected projection was used based on expert recommendation.
The State Plane Coordinate System is best-suited for the distance scale at which analyses and mapping took place. The three coordinate systems used included ‘NAD 1983
StatePlane California III FIPS 0403 (Meters)’ for the SFSRTS program, ‘NAD 1983
StatePlane Florida East FIPS 0901 (Meters)’ for the WalkSafe program, and ‘NAD 1983
StatePlane Ohio South FIPS 3602 (Meters)’ for the Columbus Safe Routes program.
Study Area: The study area boundaries were established at the school level by creating a buffer with a radial distance of 1-mile around each included school. This restricted the study area to the desired 1-mile “walk zone” around each school.
A study area boundary around each school was created using buffer operations in
ArcGIS. Each school was at the center of the buffer with a circular boundary extending 1- mile in every direction. There was some overlap in school study areas when school locations were within 1-mile of each other. However, data were analyzed separately for each school and its associated study area. Geoprocessing in ArcGIS was used to ‘clip’ each of the individual data layers to the study area boundary. A visual summary of this
92 process is shown below in Figure 7. Data were aggregated to the school study area for analyses.
Figure 7. Visual Summary of Spatial Join to Create Study Area
Mapping. Datasets were added to ArcGIS one at a time, projected, then clipped to the study area boundary. Initially, objective safety datasets were dichotomized to replicate the data categories for the perception dataset. Objective measures that demonstrated a barrier to safety (unsafe) were coded as ‘1’. Measures that did not demonstrate a barrier to safety (safe) were coded as ‘0’. Established cut-points or cut- points published in similar studies were used to determine the threshold between safe and unsafe. A summary of the unit of measure for the objective data, and the definition of
‘unsafe’ category, are provided in Table 10. Distance, however, was not dichotomized. 93 The study area boundary was placed 1-mile from the school. All parents included in the study were, therefore, within a distance considered to be feasible for walking to school.
Then, kernel density was used to create a map for each safety factor data in the objective and perceptions datasets. Kernel density was selected to transform the sample of individual point (e.g. parent location) or line (e.g. speed of traffic along roadway) data into a continuous surface across the study area for each local SRTS program. Density techniques provide an advantage to visualizing the large datasets used in the study as a concentration of the observations over the included area.[171]
Table 10. Summary of GIS Measures and Safety Classification for Mapping Purposes
Safety factors GIS Measure (within study area) Unsafe (Barrier = 1) Distance Distance from home to school -- Speed of traffic Posted speed limit in miles per Average speed > 30 MPH hour (MPH)
Amount of traffic Average daily traffic volume AADT > 3000 vehicles per day (AADT)
Sidewalks or pathways Sidewalk continuity (total length Continuity < 80% of sidewalk / total length of street)
Safety of intersections and Number of traffic lanes Average > 2 traffic lanes crossings Violence or crime Number of registered sex Total number of offenders > 0 offenders
Spatial and Non-Spatial Analysis Attribute tables from datasets created in
ArcGIS during the process of mapping data were exported using the ‘Table to Excel’ command. These files contained the necessary spatial information (X and Y coordinates)
94 for the parent location and the objective safety data joined to the parent data. These datasets were used for the following analyses.
A join count statistic was calculated for all factors in both the objective and perception datasets to determine the extent of spatial dependence. Spatial analyses were conducted in R version 3.3.1 and Studio version 1.1.423 (https://www.R-project.org/) using the joincount.test command (spdep package) and checked against a join count permutation test (joincount.mc) using 100 random permutations. The join count statistic is intended for use with categorical variables and can show the amount of clustering and dispersion of binary data (safe/unsafe) by comparing the expected and actual number of same number (e.g. 0 or 1) joins in a dataset.[172] Evidence of non-random data is found when there are far more or fewer same number joins than expected.
Next, the amount of agreement between objective and perceived safety for each school and program was also calculated to explore how well the two datasets “matched”.
Agreement was summarized in four categories (agree safe, agree unsafe, perceived unsafe but objectively safe, and perceived safe but objectively unsafe). Following this, agreement between the objective and subjective datasets were tested for significance using chi-square analysis.
Results
A summary of the final sample mapped for each of the three local SRTS programs is shown in Table 11. Characteristics of each program sample are provided in Appendix
F-H.
95 Unmatched addresses that could not be rematched were excluded from program datasets used in analysis. The geocoding tool could not find matching addresses for 41 of the West Homestead Elementary School families, which led to the school being excluded from analysis. Parents that were rematched to an address outside the 1-mile study area for their school were also excluded. Descriptive statistics were calculated for the final dataset.
Table 11. Summary of Sample for Mapping
Program Schools Parents SFSRTS 30 4,291 WalkSafe 21 3,567 Columbus Safe Routes 31 2,925
Mapping Presence of Safety Barriers. A map for each of the objective and perceived safety barriers was created. The geographical unit of analysis, or study area, for the objective data was a 1-mile buffer around each of the school locations. Objective data mapped represent the ‘unsafe’ definitions previously described. Parental perceptions, too, represent only safety barriers. Distance has been firmly established as a significant barrier in the existing literature. Therefore, results for this safety barrier are not presented or discussed within the manuscript. Results for three factors (speed, intersections, and offenders) are presented. Data on these three factors were available for all three local
SRTS programs included in the study.
96 SFSRTS Objective Safety Barriers
Nearly all road segments in the SFSRTS study areas had a medium or high
density of unsafe speed ( >30 MPH). More distinct unsafe areas emerged for safety of
intersections and crime/violence. An area in the northeast of the city had a high density of
roadways with more than two lanes of traffic. A smaller area within the same location
had a high density of registered sex offenders.
Figure 8. SFSRTS Density of Objective Safety for Speed, Intersections and Crime
97 WalkSafe Objective Safety Barriers
Objective safety did not appear to be consistently unsafe for all study areas for the
WalkSafe program. Approximately three schools had a low density of unsafe speeds and a similar number, or more, had low density of unsafe intersections and low density of registered sex offenders.
Figure 9. WalkSafe Density of Objective Safety for Speed, Intersections and Crime
Columbus Objective Safety Barriers
The traffic safety factors, speed and intersections, showed distinct areas of the
Columbus study area with high density of unsafe areas for walking to school. For each of these factors, a pattern of less safe traffic safety is seen in three spots. Two in the
98 downtown area are nearly identical for both speed greater than 30 MPH and roads with more than 2 lanes of traffic. A third spot in the northern part of the city along the interstate had medium or high density of unsafe traffic factors. One spot in the downtown area with a medium density of sex offenders was visible from the density mapping.
Figure 10. CSRTS Density of Objective Safety for Speed, Intersections and Crime
A kernel density map for perceived safety barriers was created for each safety factors for which objective data were mapped (speed, intersections and offenders). The same geographical unit of analysis was used. Maps are presented in Figures 11-13.
Overall, a similar pattern of perceived lack of safety was found across all three programs.
99 SFSRTS Perceived Safety Barriers
SFSRTS maps show a similar pattern of perception for both traffic safety factors
(speed and intersections). Two schools on the west side of the city were surrounded by high density of perceived unsafe speed and intersections. Parents at these same two schools also perceive there to be unsafe levels of crime/violence. Approximately 10 schools had a low density of parents that perceived the area to be unsafe according to the three factors presented.
Figure 11. SFSRTS Density of Perceived Barriers Speed, Intersections and Crime
WalkSafe Perceived Safety Barriers
Data for the WalkSafe program appeared to show a low density of perceived barriers. However, dense parental perception of barriers was most distinct in two locations. One of these locations consistently had medium to high density of perceiving the factors as unsafe across all three safety factors. The second location, a school in the
100 southern part of Miami-Dade County, appeared to have fewer parental concerns about intersections or crossings.
Figure 12. WalkSafe Density of Perceived Barriers Speed, Intersections and Crime
Columbus Perceived Safety Barriers
Overall, maps of perception data for the CSRTS program showed that parents generally perceived multiple safety barriers in the area between home and school. There were several areas with medium or high density for each of the safety factors presented.
There were also approximately two or three schools where fewer parents perceived the speed, intersections and crime to be unsafe. These were locations on the east side of the city.
101
Figure 13. CSRTS Density of Perceived Barriers Speed, Intersections and Crime
Assessment of Spatial Dependence. Join count tests were used to evaluate dispersion among the datasets. The null hypothesis of the test is that data are spatially random. A summary of the significance of results for each safety category (safe/unsafe) for all factors in both the objective and perception datasets is provided in Table 12. There is evidence of spatial dependence among each local SRTS program. The SFSRTS program data had the least evidence of data being spatially non-random. There was strong evidence in the objective WalkSafe data for barriers being spatially non-random. The only objective WalkSafe data that did not have evidence of being spatially non-random were the unsafe crime data. Among CSRTS results, the category of ‘safe’ had a significant result for every safety factor, both objective and perceived data.
102 Table 12. Join Count Test Result p-values by Dataset and Program (α = 0.05)
Objective San Francisco WalkSafe Columbus Speed Safe 0.51 < 0.0001 0.00 Unsafe 0.58 < 0.0001 0.32 Intersections Safe 0.34 < 0.0001 0.00 Unsafe 0.70 < 0.0001 0.39 Crime Safe 0.02 < 0.0001 0.00 Unsafe 0.69 0.06173 0.39 Perceptions
Speed Safe 0.29 0.50 0.00 Unsafe 0.24 0.19 0.97 Intersections Safe 0.07 0.00 0.00 Unsafe 0.47 0.92 0.26 Crime Safe 0.59 0.07 0.00 Unsafe 0.40 0.40 0.71
Analysis to “Match” Perceptions and Objective Data. A summary of analysis to “match” parental perceptions of safety with the objective safety is provided in
Table 13. Despite using the “walk zone” as the study area boundary and for parental inclusion in the study, about one-third of parents living within 1-mile of their children’s schools perceive the distance to be unsafe. More than half of parents in all programs disagreed with the speed of traffic along the route to school being unsafe, perceiving it to be safe despite an average posted speed limit above 30 MPH. The objectively measured 103 lack of safety matched with approximately one-third of WalkSafe and CSRTS parents that perceived an unsafe amount of traffic along the route to school. The largest proportion of disagreement between parental perception of safety and objectively measured safety was found among SFSRTS parents for the factor of crime/violence.
More than two-thirds of parents (66.3%) perceived the unsafe environment to be safe.
104 Table 13. Percent Agreement Between Parental Perception and Objective Safety Datasets
Percent Agreement (n) Percent Disagreement (n)
Perceived as Perceived as unsafe, safe, objectively objectively Safe Unsafe safe unsafe Distance SanFrancisco 71.8 (3083) - 28.2 (1208) - WalkSafe 74.0 (2676) - 26.0 (940) - Columbus 62.7 (1632) - 37.3 (970) - Speed SanFrancisco 6.9 (297) 24.7 (1061) 4.2 (181) 64.1 (2752) WalkSafe - 39.2 (1419) - 60.8 (2197) Columbus 40.0 (1040) - 3.8 (98) 56.3 (1464) Traffic SanFrancisco - - - - WalkSafe - 38.2 (1382) - 61.8 (2234) Columbus - 35.8 (931) - 64.2 (1671) Sidewalks SanFrancisco - - - - WalkSafe 24.3 (877) 11.2 (405) 3.9 (140) 60.7 (2194) Columbus 38.6 (1004) 13.6 (353) 12.8 (333) 35.0 (912) Intersections SanFrancisco 19.6 (841) 27.7 (1187) 12.9 (552) 39.9 (1711) WalkSafe 18.6 (671) 26.6 (961) 8.9 (323) 45.9 (1661) Columbus 6.3 (164) 34.9 (908) 4.0 (104) 54.8 (1426) Crime SanFrancisco 7.3 (313) 21.9 (939) 4.5 (194) 66.3 (2845) WalkSafe 1.6 (57) 39.3 (1420) 1.1 (39) 58.1 (2100) Columbus - 39.4 (1026) - 60.6 (1576)
The agreement or “matching” of the perception and objective datasets was further explored using chi-squared analysis with the additional safety variables of traffic and sidewalks. Data was available on these factors for the WalkSafe and CSRTS programs. 105 Chi-square testing was used to identify any significant association between the two datasets (objective and perceived). As noted in Table 14, there were several instances where a small number of observations in one of the four categories precluded the selected analysis from being run on the data.
Results of the analysis for the SFSRTS program suggested that perceived speed and crime safety data are related to the objective measures (p-value < 0.001). There was evidence, too, that the two intersections datasets for the WalkSafe program are related (p- value = 0.02).
Table 14. Summary of Chi-Squared Analysis of Agreement Between Objective and Perceived Data at the Program Level
P-value Results from X2 Test (α = 0.05) Local SRTS Speed Traffic Inter- Side- Crime Program sections walks SFSRTS <0.001 -- 0.41 -- <0.001
WalkSafe -- -- 0.02 0.17 0.96
CSRTS -- -- 0.98 0.08 --
Discussion
Overall, presence and patterning of safety barriers was explored through a combination of mapping and analysis. This approach, using both objective and perceived datasets has improved upon designs used previously to better understand barriers to participation in walk to school behavior. Results have clearly demonstrated important 106 patterns across the study areas and disagreement between objective and perceived safety.
These results represent the main novel contribution of the study to promotion of walking to school. To the best of the investigator’s knowledge, there is currently no other study that has utilized SRTS Parent Survey data from multiple programs to study spatial relationships between traffic and neighborhood safety barriers. The study has shown specific factors (speeds over 30 MPH, roadways with more than two lanes and presence of registered sex offenders) differ within local program areas. The perception of those factors, too, varies. The results also show the complexity of understanding safety barriers and changing walk to school behavior. At the same location, certain factors may be objectively safe but perceived as unsafe.
Presence of objective and perceived safety barriers was investigated through density maps that revealed concentrations of barriers for each local SRTS program. Maps of data for the SFSRTS program showed speed to be a major barrier across most of the city. However, the presence of perceived barriers to safety were concentrated in areas of the city that appeared to be safe according to the objective data. Two areas of Miami-
Dade County participating in the WalkSafe program had high concentrations of perceived unsafe speed, intersection and crime conditions. These were distinct on the map. The perceptions, too, were concentrated in a suburban area with fewer nearby schools, compared to other parts of the county. The CSRTS program demonstrated three notable areas with a high concentration of speed and intersection barriers. These areas were similar on both the objective and perceived safety maps. Across all three programs, the
107 presence of objective traffic safety barriers was evident. There were, however, some differences in the presence and patterns of safety concerns across programs.
Patterning of the data within and across programs was assessed beyond initial visual inspection of the data using join count spatial analysis. There were some spatially non-random results for WalkSafe and CSRTS, indicating geographical variability of safety barriers. These results have highlighted the importance of continued research to carefully investigate the potential cause(s) of this variation. Non-spatial tabulation, too, revealed some surprising results in the disagreement between parental perceptions of safety and the objective measure of traffic and neighborhood safety. For example, there was 50% or greater disagreement on speed among all local SRTS programs studied.
Parents perceived the speed to be safe in locations that were objectively unsafe (speeds >
30 MPH).
Although the relationship between safety and walking behavior has been recognized, this study adds the integration of objective GIS data with data on parental perceptions. The study of each type of data, objective and subjective, independently can have utility for understanding the relationship to behavior. However, an integrated approach is necessary. Walk-to-school behavior is influenced by both objective and perceived measures, as demonstrated by existing evidence, and thus better understood in this complete context.[17,65,77,173] Based on present results, study conclusions based on both objective and perceived data on environmental safety factors are more credible than one or the other alone. This has already been demonstrated with other populations for similar health behaviors.[8,174,175] The integrated approach in the present study
108 allowed for a more complete analysis of safety and contributed to compelling evidence on salient safety factors for parents. The technique also offered the additional advantage of analysis on a large, multisite dataset.
The SRTS Parent Survey data, together with corresponding GIS data, allowed for the safety of walking to school to be explored within an appropriate context. The study used real life constraints to first conceptualize, then operationalize, analysis of safety in the space between home and school for elementary school children. The SRTS programs receive funding to be applied to the area within 2-miles of participating school sites. The national SRTS program and associated research has also judged 1-mile or less to be walking distance for children.[6,38,39] The geographic constraints translated readily to study area boundaries for the analysis. The Parent Survey form also provided an existing list of frequently cited safety barriers to include as factors in the analysis. These influences provided meaningful examination of the data. The availability of SRTS data allowed for a novel method of investigating safety at the fine, school-level scale. Many existing studies on safety use data aggregated to higher levels, such as zip codes or census tracts.
Existing theory and literature have also found that the specific domain of physical activity, active travel (walking), and specific context (families walking to school) influence study findings. The present study examined walking within these constraints to offer more precise guidance in addressing safety barriers that prevent walking to school.
A review of evidence on influences on walking documented the importance of separating
109 studies of walking to school from other destinations, such as parks, and from other physical activity behaviors.[28,176,177]
The evaluation of agreement, or “matching” of objective and perception data provides some guidance for program implementation and future research. Additional research that applies other safety data sets to further examine which factors have high levels of agreement could have utility for individual SRTS programs as well as the national program. Findings from the study suggest what needs to be enforced, on what to educate families, what to re-engineer to improve safety and how to encourage planners to address these perceptions in the design of the physical built environment.
The study was designed to sufficiently support both internal and external validity and ensure scientific rigor as well as practical application. Random or other biases present in the study are likely to be inconsequential to the reported results.
Methodological issues for the exploration of associations between the environment and travel decisions identified in previous studies were addressed, including (1) inaccurate geocoding of the school address, (2) choice of how to measure the environment, and (3) scale of data.
The use of data collected by various agencies in three different locations, encompassing three different geographic regions, led to some inconsistencies across datasets. Although, steps were taken in the designing of the analysis to reduce those inconsistencies, measurement of individual safety barriers differed slightly among the local SRTS programs included in the study. Initially, safety was operationalized using the literature from relevant disciplines and aligned with the data sets used for measurement
110 and analyses. Then, the researcher worked to obtain similarly collected data from the transportation agencies in each location. Analysis of data for each local SRTS program was conducted independently. Data that were missing for any single program did not influence analysis for either of the other local SRTS programs. Safety factors were considered static since secondary data were used. Secondary data were used to make a multi-site study feasible. Direct spatial data acquisition in three separate states and for multiple schools in each location would have been time consuming and expensive. The selected data sets leveraged existing data that had not been combined and examined in this way. Despite data being obtained from a variety of sources in multiple locations, standard data sets were included in the study. Purposeful selection of datasets helped to ensure the accuracy of data was similar across the three local SRTS programs. Analytic technique, such as descriptive statistics and tests for association, were applied to make influential differences in safety factor data transparent.
The selected factors do not include all possible environmental factors that influence safety and it is possible that other important factors were not included, although the selection was informed by published literature. The data are specific to the locations selected for inclusion in the present study and may therefore limit the generalizability of the findings to other settings. These data are not relevant to schools that are not currently participating in the SRTS program, to rural or suburban school districts, or to schools that serve grades 6 through 12. Analytic techniques in the study provide only an ecological, descriptive, and exploratory set of results. Further study will be needed to examine the causes of spatial dependence at the school and program levels.
111 The narrow definition of safety in the study minimized issues that have limited the efficient translation of research to practice for program planners and policy makers, such as the varied construction and measurement of environmental influences on walking. The framework and design of the study were intended to yield results that would provide recommendations for local and state agencies, as well as other SRTS partners, to be implemented within 6-months. Implementation of these recommendations with new insight on safety perceptions, will make useful changes to mitigate parental concerns and address physical barriers to walking to school. The evidence-informed recommendations will also promote targeted changes to address disparity and inequity in the prevalence of public health burdens related to child pedestrian safety.[14]
Although similarities were found among the most frequently perceived barriers, perceptions of safety for families living within 1-mile of their schools differed within and among study sites. The results can be used to understand the school and neighborhood- level patterns of barriers to safely walking to school. Synergy among public health, transportation and planning theories have been explored more recently as the connections between conditions of the environment and health behavior become clearer.[178,179]
Research in this area can benefit from the use of context, such as the SRTS program, to analyze these school and neighborhood patterns. Future research should consider partnering with local SRTS programs to explore existing data and consider qualitative data collection techniques that would allow parents to expand on their selection of each safety barrier. In addition, more research should incorporate parental perceptions of the
112 built environment and traffic danger with objective measures, such as those explored in the present study.
113 Chapter 5. Manuscript #2 Introduction
In 2015, the prevalence of overweight/obesity was estimated to be 13.9% among children ages 2 to 5 years and 18.4% among children ages 6 to 11 years by the Centers for Disease Control and Prevention. (https://www.cdc.gov/) Physical activity is a proven strategy to mitigate this problem. Lack of physical activity, however, is a major health problem among children and youth in the United States.[180–182] A significant decline in the proportion of children that walk to school is one suspected cause of physical inactivity among this age group.[2,39] Children that walk to school are more likely to obtain the recommended levels of moderate-to-vigorous physical activity.[181,183–186]
Increasing the number of walking trips to school was identified as a national health strategy to address lack of physical activity among children and reverse the potential for negative health impacts across their lifespan.[147]
The choice to allow children to walk to school is a complex decision for parents of elementary school children. Factors at multiple levels influence the feasibility, accessibility and safety of walking to school.[16,17,111] Safety, in particular, is a critical influence on parental decision-making in choosing whether or not to walk to school.[28,78,187] The relationship among parental perceptions of safety, objective safety of the environment and walking to school is not clearly understood. Identifying and better understanding the collection of social and physical barriers in the space between home and school can help inform programs and policies intended to increase the prevalence of walk-to-school behavior.
114 Research from the discipline of city/urban planning concerned with the design of urban environments and support for walking often emphasize features of the physical environment from the city or zip code level that can be objectively measured using GIS or other remote techniques. Features at this higher, macro-scale, such as number of intersections, are often the variables of interest.[151,188,189] As the approach to city and transportation planning continues to shift, recognizing the connections among place, transportation and health research has begun to emphasize features at the neighborhood level.[52,190] Exploration of these neighborhood level features has also included the subjective experience of the environment for people that are walking.[13,29,101,191]
Previous research has grouped variables to investigate how the built environment affects the decision to walk or not walk. This has been tested for both walking for recreation and walking for utility (transportation).[101,169] For both types of walking, results showed that safety of the environment was “ the most important built environment characteristic
(of those tested)”.[90]
Integrating data on the quality of the environment for walking, its objective and perceived safety, can address the gap in knowledge about relationships between objective and perceived safety while controlling for potential confounding factors. The purpose of the study was to identify family, school and environmental level factors that predict the outcome of walking to school among families participating in SRTS programming.
The study built predictive models of walking to school using data collected by the SRTS program together with objectively measured data on a list of safety factors--known to be important to parental decisions to allow their children to walk to school--to identify
115 significant factors. Results will support promotion of walking to school by programs like
SRTS and the healthful benefits for elementary school children and their families.
Methods
Study Design
The study was a cross-sectional, multilevel study using GIS data and data from families and schools participating in three local SRTS programs described previously.
Study Sample
The study analyzed data from the SRTS Parent Survey collected by a convenience sample of three local SRTS programs from three distinct regions of the United States.
Participating schools are listed in Appendix A. The programs had an overall average response rate to the survey of 24.7%, ranging from 18.9% to 32.3%. The sample included data corresponding to Parent Survey participants that provided information on their usual mode of travel to school. A total of 4,291 families attending 30 schools were included from the SFSRTS program; 3,739 families attending 22 schools were included from the
WalkSafe program; and 1,745 families attending 30 schools were included from the
Columbus Safe Routes program (Appendix G). There was a multilevel structure in the chosen sample with individuals/families (level 1) nested within schools (level 2). The individual outcome of interest was walking to school.
Data Collection and Measures
Walking to school. The outcome of interest in the study was children walking to school. The outcome has been measured at the family level using the parent-reported usual mode of travel to school. Data were collected through use of the SRTS Parent
116 Survey (Appendix C), which was distributed to families by participating local programs.
The survey was developed for use by SRTS programs nationally to capture data on parents’ knowledge, attitudes and beliefs about walking or biking to school.[99] Parents reported the usual mode of arrival and departure from the school by their child on the survey. Travel mode data from the survey has been validated.[134,135] Parent Survey data are stored online on the National Center for SRTS Data website
(www.saferoutesdata.org).
The outcome of walking to school was measured as parents and their child, or children, walking the entire journey from home to school. Walk-to-school behavior described in this study was not inclusive of other non-motorized forms of transportation, such as biking and skateboarding, nor is it inclusive of multi-modal commutes, such as walking to a transit stop to then take the bus for a portion of the journey. The selected outcome of walking to school excludes other forms of active transportation because of initial differences in the barriers to participation as well as differences in the enforcement.
Riding a bike to school, for example, requires a bicycle and a helmet and bicycles are considered vehicles, which are ridden in the street.
Parent level data. Participant addresses were approximated using parents’ response to the Parent Survey question asking for the names of the streets marking the intersection nearest to their home. Address data were used to determine distance from the school. Information about parents’ perceived safety barriers (distance, speed of traffic along route, amount of traffic along route, sidewalks, safety of intersections and
117 crossings, and violence or crime) were collected by the Parent Survey (described above).
These data, too, were accessed through the National Center for SRTS Data website.
School level data. Information about the school was obtained from publicly available websites for the school districts and the NCES. School level data include the characteristics of size (total enrollment), socioeconomic status (proportion of children that qualify for free-and-reduced-price meals), proportion of non-White enrollment, and estimated proportion of children that usually walk to the school. Data from the 2014-2015 school year on school characteristics were obtained from two online sources. Total number of students enrolled at the school (referred to as enrollment), proportion of student body who were eligible for free and reduced-price meal (FRPM), and non-white were obtained from the NCES (https://nces.ed.gov/ccd/schoolsearch/). These characteristics were included in the analyses in as school level covariates. The estimated proportion of walking trips to school was taken from the National Center for SRTS Data site (www.saferoutesdata.org). Enrollment reflects school size, which was considered when building predictive models on walk to school behavior. Although all schools are part of large, urban school districts, there may be significant differences in the size of schools among schools participating in individual SRTS programs. The proportion of students FRPM-eligible was used as a measure of socioeconomic status of families included in the study, which has a known relationship with walking. Higher income negatively impacts the likelihood of walking, and may also be related to vehicle ownership.[2] The proportion of non-white students was also included in the study as a
118 family level predictor of walking to school. There is evidence that rates of walking to school may differ among ethnic/racial groups [192]
Environmental level data. Factors included in the study were speed of traffic along the route, amount of traffic along the route, sidewalks or pathways, safety of intersections or crossings, and violence or crime. Objective data on these factors were available through datasets provided online by municipal and state agencies. Indirect audits were conducted using Google Maps to assess the validity of the data on objective safety factors. Due to resource limitations, only a sample of street segments for schools from the study sample were audited with this method. The audit was conducted independently by the researcher in October and November 2017. Urban form attributes, related to land use and proximity of amenities, are environmental factors known to influence walking. These environmental factors were measured using the WalkScore of each school’s zip code. WalkScore is a validated measure of neighborhood walkability, which assigns a score ranging from 0 to 100.[193,194] Scores were assigned using the same 1-mile boundary that was used by SRTS as the maximum limit for a walkable distance. Higher scores indicated greater walkability. Perceptions of safety were captured by the Parent Survey.
Data Analysis
The outcome of interest, walking to school was modeled with logistic regression.
Analyses were undertaken to build a parsimonious predictive model for the outcome of walking to school. Given the structure of the data, it was useful to employ a multilevel approach to analysis. A classic random effect was included to model unstructured
119 between-school variations. The dichotomous outcome variable facilitated the use of logistic regression; outcomes have been interpreted as logged odds then exponentiated and reported as an odds ratio (OR). Two versions of the outcome of walking to school were modeled, first walking was compared to all other modes (bicycling, carpool, school bus, public transit, family vehicle and other), then walking was compared to driving
(family vehicle) alone. Both two-level and three-level models were built for each of these model outcomes, which allowed for inferences within and among programs. Families were nested within schools and schools were nested within local SRTS programs. A summary of the levels included in the modeling is provided here to assist the reader in understanding the analytic approach.
• Family, Level-1, data, which includes the child-specific and family characteristics
from the Parent Survey
• School, Level-2, data, which includes the school specific characteristics from
NCES and objective factors aggregated to the 1-mile study area
• Program, Level-3, data, which was the highest-level grouping factor
An important consideration for the accuracy of estimates and their standard errors in the design of multilevel analysis is design effect. Design effect, according to Kish (1965),
“indicates how much the standard errors are underestimated in a complex sample” compared to a simple random sample.[195] Dependence among all observations is expressed as the intraclass correlation coefficient (ICC). In multilevel, or clustered, samples, design effect is approximately equal to 1 + (average cluster size -1) x ICC. In
120 the present study, the average cluster size was 27.3. Prior research on sufficient sample sizes for effective multilevel modelling described the value of 2 as a small design effect.
[196] This value was used in the present study to compare simulated and actual ICC and evaluate design effect. The largest possible sample size for the school level was used from the available SRTS program data, resulting in the inclusion of more than 1,500 observations at the lower (family) level. This added strength to the cross-sectional design and balanced at least one of the potential limitations from use of secondary data for analysis.
Prior to building the model, continuous variables were examined for linearity in the logit. Simple logistic regression analyses were run on individual covariates (independent) variables to test for significance. Variables with a p-value equal to or less than 0.20 were retained for subsequent analyses. A backward selection method was then used to construct the final models for each local SRTS program and the for three-level models comparing factors across programs. Results of the models estimated the “risk” of walking to school associated with each of the safety variables. The OR and associated 95% confidence intervals (CI) were calculated from the multilevel mixed effects logistic regression models using STATA version 15 statistical software (StataCorp LC, College
Station, TX).
Prior to analysis, some re-categorization of Parent Survey data was necessary. The number of children in grades K through 8 living in the household were categorized in two groups (one child and more than one child). Language of the survey was categorized into two groups (English or Non-English) due to small numbers of Spanish, Haitian-Creole
121 and Cantonese surveys. Grades levels (K through 5) were also collapsed into three categories (K-1, 2-3, and 4-5). Finally, parent education (Grades 1 through 8, Grades 9 through 11, Grade 12 or GED, College 1 to 3 years, College 4 or more years, prefer not to answer) was categorized into two groups (GED or less, and Some college or more). No response or selection of ‘prefer not to answer’ were coded as missing. In the three-level models, response categories on parental belief about their distance from school were collapsed into the categories of ‘1-mile or less’ and ‘greater than 1-mile’.
Results
Characteristics of the schools have been included in Appendix B. Descriptive statistics were calculated and aggregated to the local program level to provide a summative overview. Overall, the final sample of 9,055 participants provided data from three local SRTS programs and 80 schools. The socio-demographic characteristics of the programs are summarized in the table below.
Table 15. Summary of School Characteristics by Program (Averages)
School Characteristics by Program (%)
Number Estimated FRPM Enrolled Non-White Walk Trips Program Eligible (2014-2015) to School SFSRTS 433 57.8 82.5 28.0 WalkSafe 600 90.6 97.6 28.7 Columbus 412 86.8 61.2 16.0
122 Overall, the included schools had an average proportion of 80.4% non-white students. In this study, the proportion of low-resourced families was defined as the percentage of children eligible for free or reduced-price lunch. [https://nces.ed.gov/] The proportion of low-resourced families covered the entire range from zero to 100% across schools, with an average of 78.4% among all programs. [https://nces.ed.gov/] There was a mean number of 94 participants per school. Table 15 shows the characteristics of the participants by local SRTS program. Sample sizes for each of the local SRTS programs ranged from 1,593 (CSRTS) to 3,930 (SFSRTS). School level information on the sample is available in Appendix G.
There was a significantly larger proportion of children that walked to school in the SFSRTS program compared to each of the other local programs (X2[2] = 815.3, p <
0.0001). CSRTS also had a larger proportion of ‘Other’ modes (bike, school bus, public transit, carpool, other) than the other two local programs (X2[2] = 824.4, p < 0.0001). The gender and grade level of children included in the sample was relatively similar across all three programs. Approximately half of participants in all three programs had only one child in grades K through 8. However, CSRTS had a higher percentage of participants with more than one child in grades K through 8 (58.7%) compared to SFSRTS (47.6%) and WalkSafe (49.9%). CSRTS also had the highest proportion of participants that incorrectly estimated their distance to school as more than 1-mile (21.5%). Overall, an average of about 5% of participants did not know the estimated distance to their child’s school. Grade level distribution of the final sample is given in Appendix H.
123 First, stratified models, with the outcome of walk versus all other modes, was run.
Results of this model for each local SRTS program are shown in Tables 17 through 19 below. A total of seven variables were retained in the final model for each SFSRTS and
WalkSafe. The final model for CSRTS retained four variables. The perception of distance as a barrier to walking was retained in both the SFSRTS and Columbus Safe Routes models. The perception of crime as a barrier was retained in the WalkSafe and Columbus
Safe Routes models. The only level 2 variable retained by more than one program was the proportion of walkers at the school.
Next, stratified models with the outcome of walk versus family vehicle (excluding all other modes) was run. Overall, a higher number of variables were retained in models comparing walk with family vehicle than in models comparing to all other modes. A total of 13 variables were retained in the final Model for WalkSafe; the final model for
SFSRTS retained 10. The final model for the CSRTS program again retained the fewest variables (5). Three level 1 variables (parents’ estimated distance to school, highest level of completed education, and perception of sidewalks as a barrier) were retained in the final Model B for both SRTS and WalkSafe. Perception of crime as a barrier was retained by both WalkSafe and CSRTS. Two level 2 variables were retained in the final Model B across all three local SRTS programs (overall proportion of students that walk to school, average number of lanes to cross between home and school). WalkScore and AADT were significant in both the WalkSafe and CSRTS models. The proportion of students eligible for FRPM was significant in both the SFSRTS and WalkSafe final models.
Child’s grade level, parental perception of traffic as a barrier, and number of registered
124 sex offenders were retained only in the SFSRTS final model. Child’s gender, parental perception of speed as a barrier, school size (enrollment) and the proportion of non-white students were only retained in the WalkSafe model. Variables retained in the final
CSRTS model (parental perception of crime as a barrier, proportion of students that walk to school, proportion of students eligible for FRPM, AADT, and average number of lanes of traffic) were also retained in one or both of the other program models.
Among the SFSRTS program, the odds of walking to school were 30% lower than odds of using any other mode when parents perceived the amount of traffic along the route to be a barrier and 24% lower than odds of using family vehicle. Odds of walking were also lower when parents had less than college education compared to either all other modes (OR: 0.73, CI: [0.59-0.92]) or family vehicle alone (OR: 0.76, CI: [0.57-1.00]).
For every one percent increase in the proportion of students at the school that walk to school, odds of walking were 3% higher than odds of using any other mode. Odds were similar in the model comparing walking to use of family vehicle (OR: 1.04, CI: [1.02-
1.05]).
Among the WalkSafe program, the odds of families walking to school if their child was female were approximately 20% lower than odds of using any other mode (OR:
0.81, CI: [0.68-0.97]), or using family vehicle (OR: 0.79, CI: [0.65-0.96]). Perception of crime/violence as a barrier lowered the odds of walking to school compared to all other modes by 30% (OR: 0.66, CI: [0.54-0.80]). In the model comparing walking to family vehicle, parental perception of sidewalks or pathways changed the odds of walking to school by 80% (OR: 1.8, CI: [1.4-2.36]). Odds of walking to school were 1.63 times the
125 odds of using any other mode (CI: [1.16-2.29]), and the odds of using a family vehicle
(CI: [1.13-2.32]), for families that completed the survey in a language other than English.
The proportion of non-white students enrolled at schools was also influential for walking to school. Odds of walking versus using any other mode increased 20% for each increase in the percent of non-white students at a school (CI: [1.09-1.31]). When odds of walking were compared to odds of using family vehicle, the change was 14% (CI: [1.05-1.23]).
Every unit increase in the average speed of traffic (in MPH) along the route between home and school decreased the odds of walking to school by more than 60% (CI: [0.22-
0.69]) compared to using any other mode.
Among the CSRTS program, the change in odds of walking to school was at least
30% when parents perceived crime/violence as a barrier. Odds of walking, compared to all other modes, when crime was a perceived barrier were 0.63 (CI: [0.46-0.85]), and 0.51 compared to using family vehicle (CI: [0.37-0.71]). Every unit increase in the average speed of traffic (in MPH) along the route between home and school decreased the odds of walking to school by 76% compared to using all other modes (CI: [0.008-0.70]). An increase in average speed changed the odds of walking by 0.37 (CI: [0.14-0.96]) compared to using family vehicle.
126 Table 16. Participant Characteristics by SRTS Program
SFSRTS WalkSafe Columbus Safe Routes (3,928) (3,534) (1,593) Child gender N % N % N % Female 2,037 52.0 1,786 51.9 884 55.7 Child grade K-1 1,637 41.7 1,046 29.6 566 35.5 2nd - 3rd 1,332 33.9 1,184 33.5 602 37.8 4th - 5th 959 24.4 1,304 36.9 425 26.7 Arrival mode Walk 2,070 52.7 854 24.2 357 22.4 Family Vehicle 1,351 34.4 2,327 65.9 849 53.3 Other 509 13.0 353 10.0 387 24.3 Number of children (K-8) Only 1 1,994 52.4 1,634 50.1 637 41.3 More than 1 1,808 47.6 1,628 49.9 904 58.7 Estimated distance to school Less than ¼ mile 1,484 38.7 1,358 39.5 523 33.5 ¼ mile up to ½ mile 764 19.9 609 17.7 277 17.7 ½ mile up to 1 mile 967 25.2 770 22.4 337 21.6 More than 1 mile 433 11.3 528 15.3 336 21.5 Don’t know 185 4.80 177 5.10 90 5.80 Continued
127 Table 16. Continued
SFSRTS WalkSafe Columbus Safe Routes (3,928) (3,534) (1,593) Parent Education N % N % N % GED or less At least some college Survey Language English Non-English1 Parental Belief School Encourages Walking Encourages or strongly encourages Neither encourages or discourages Discourages or strongly discourages No Response Gender 15 0.40 90 2.50 0 0.00 Grade 2 0.10 0 0.00 0 0.00 Number of children 128 3.30 272 7.70 52 3.30 Estimated distance to school 97 2.50 92 2.60 30 1.90 Parent education Parental belief 1Spanish, Haitian-Creole, Cantonese
128 Table 17. SFSRTS Multilevel Logistic Regression Model Results
Walk versus All Other Modes Walk versus Family Vehicle (only) Univariate Associations Best Fit Univariate Associations Best Fit OR 95% CI OR 95% CI OR 95% CI OR 95% CI Level 1 variables Family socio-demographics Parent education 1 At least some college 0.76 0.65-0.90 0.76 0.60-0.96 0.70 0.58-0.84 0.70 0.53-0.92 Parental beliefs 2 Distance to school ¼-mile up to ½-mile 0.29 0.24-0.35 0.25 0.21-0.32 0.30 0.24-0.37 0.26 0.20-0.33 ½-mile up to 1-mile 0.10 0.08-0.12 0.09 0.07-0.11 0.10 0.08-0.12 0.08 0.06-0.10 More than 1-mile 0.03 0.02-0.04 0.03 0.02-0.04 0.03 0.02-0.04 0.03 0.02-0.04 Don’t know 0.17 0.12-0.23 0.09 0.06-0.14 0.26 0.18-0.38 0.14 0.08-0.22 3 Parental perceived barriers Amount of traffic along route 0.64 0.55-0.73 0.76 0.63-0.91 0.69 0.59-0.80 0.78 0.63-0.97 Sidewalks/pathways 0.22 0.01-0.43 1.53 1.14-2.07 Level 2 variables School data Students that walk to school (%) 1.03 1.03-1.04 1.03 1.01-1.05 1.04 1.03-1.05 1.03 1.01-1.06 School neighborhood data Lanes to cross along route (average) 1.31 1.07-1.56 3.42 1.40-8.38 1Referent group parent has education of GED or less 2Referent group parent estimates distance to school of less than ¼-mile 3Referent group parent does not perceive safety factor to be a barrier 129 Table 18. WalkSafe Multilevel Logistic Regression Model Results
Walk versus All Other Modes Walk versus Family Vehicle (only) Univariate Associations Best Fit Univariate Associations Best Fit OR 95% CI OR 95% CI OR 95% CI OR 95% CI Level 1 variables Family socio-demographics Survey language1 English 1.74 1.31-2.31 1.5 1.08-2.08 Child’s gender Female 0.82 0.70-0.96 0.79 0.66-0.95 0.81 0.69-0.95 0.78 0.63-0.94 Parental beliefs Distance to school More than ¼-mile2 0.21 0.18-0.25 0.22 0.19-0.27 0.22 0.18-0.26 0.23 0.19-0.28 Parental perceived barriers Speed of traffic along route 0.52 0.44-0.61 0.67 0.54-0.82 0.51 0.43-0.60 0.65 0.53-0.81 Sidewalks/pathways 1.17 0.9 1.62 1.26-2.07 1.24 1.00-1.53 1.76 1.36-2.28 Crime/violence 0.52 0.44-0.61 0.64 0.52-0.78 0.51 0.43-0.60 0.65 0.53-0.79 Level 2 variables School data Non-white students (%) 1.07 1.05-1.10 1.09 1.01-1.18 School neighborhood data WalkScore 1.01 1.00-1.01 1.02 1.00-1.03 1Referent group was Non-English (Spanish, Haitian-Creole, Cantonese) 2Referent group was parent-estimated distance to school of less than ¼-mile
130 Table 19. Columbus Safe Routes Multilevel Logistic Regression Model Results
Walk versus All Other Modes Walk versus Family Vehicle (only) Univariate Associations Best Fit Univariate Associations Best Fit OR 95% CI OR 95% CI OR 95% CI OR 95% CI Level 1 variables Parental perceived barriers Safety of intersections and crossings 0.55 0.42-0.71 0.65 0.48-0.88 Crime/violence 0.58 0.45-0.75 0.64 0.47-0.88 0.54 0.41-0.70 0.48 0.35-0.65 Level 2 variables School data Students that walk to school (%) 1.03 1.03-1.04 1.03 1.02-1.06 1.03 1.02-1.04 1.04 1.02-1.05 School neighborhood data Number of lanes (maximum) 1.10 1.00-1.19 1.26 1.04-1.51
131 Finally, three level models were run to compare programs. Two separate models were built using the outcomes of walk, first comparing with use of all other modes (e.g., bike, school bus, public transit, family vehicle, carpool, and other), then comparing with family vehicle only. An overview of the resulting models is given below in Tables 20 and
21 with referent groups noted below each table. Odds of families walking to school if they had more than one child in the home were 15% higher than odds of using any other mode (OR: 1.15, CI: [1.04-1.28]). Perceptions of speed along the route to school, amount of traffic along the route to school, safety of intersections or crossings, and crime or violence all lowered the odds of walking to school by an average of 18.3%.
132 Table 20. Summary of Three Level (Family, School and Program) Logistic Regression
Model Comparing Outcome of Walking to All Other Modes of Travel to School
Walk versus All Other Modes Univariate Associations Best Fit OR 95% CI OR 95% CI Level 1 variables Family socio-demographics 1 More than 1 child in the household 1.09 1.00-1.19 1.15 1.04-1.28 Parental beliefs 2 Distance to school is > 1-mile 0.20 0.17-0.23 0.19 0.16-0.22 School encourages walking to school3 0.34 0.31-37 0.55 0.49-0.62 4 Parental perceived barriers Amount of speed along route 0.57 0.52-0.63 0.84 0.72-0.97 Amount of traffic along route 0.53 0.48-0.58 0.78 0.67-0.91 Sidewalks/pathways 0.85 0.76-0.96 1.47 1.26-1.71 Safety of intersections and crossings 0.73 0.67-80 0.86 0.75-0.98 Crime/violence 0.55 0.50-0.61 0.80 0.71-0.91 Level 2 variables School environment 5 WalkScore 1.02 1.03-1.03 1.03 1.02-1.04 1Referent group only 1 child in the household 2Referent group distance to school is 1-mile or less 3Referent group school discourages, strongly discourages or neither encourages or discourages walking to school 4Referent group parent does not perceive safety factor to be a barrier 5WalkScore is a walkability score that categorizes the level of car dependence at zip code level from 0 (car dependent) to 100 (walker’s paradise)
Overall, level 1 variables appeared to have a greater impact on the odds of walking to school compared to driving than did level 2 variables. The odds of families walking to school if their child was female were approximately 0.89 times the odds of driving to school (CI: [0.80-0.99]). The odds of walking were 78% lower than odds of driving to school if the parent perceived the distance to school as more than 1-mile (CI:
[0.19-0.27]). When distance was a safety barrier, however, the odds of walking to school
133 were 1.20 times the odds of driving to school. Perceptions of the traffic safety barriers, speed and traffic along the route to school, and the neighborhood safety barrier of crime/violence, were all significant factors in the final model. The proportion of non- white students enrolled at schools, WalkScore of the school neighborhood, and number of registered sex offenders within 1-mile of the school location each changed the odds of walking to school by approximately 0.01.
134 Table 21. Summary of Three Level (Family, School and Program) Logistic Regression
Model Comparing Outcome of Walking to School with Driving a Family Vehicle
Walk versus Family Vehicle (only) Univariate Associations Best Fit OR 95% CI OR 95% CI Level 1 variables Family socio-demographics Child is female 0.90 0.82-0.99 0.89 0.80-0.99 Parental beliefs 1 Distance to school is > 1-mile 0.23 0.20-0.27 0.22 0.19-0.27 2 Parental perceived barriers Distance from home to school 0.92 0.83-1.02 1.20 1.06-1.37 Amount of speed along route 0.59 0.53-0.65 0.84 0.72-0.99 Amount of traffic along route 0.55 0.50-0.61 0.82 0.70-0.96 Crime/violence 0.56 0.50-0.62 0.71 0.62-0.80 Level 2 variables School data Non-white students (%) 1.00 1.00-1.00 1.01 1.00-1.01 School neighborhood data 3 WalkScore 1.03 1.03-1.03 1.02 1.01-1.03 Registered sex offenders within 1-mile4 1.01 1.01-1.02 1.01 1.01-1.02 1Referent group parental belief was distance to school is 1-mile or less 2Referent group parent does not perceive safety factor to be a barrier 3WalkScore is a walkability score that categorizes the level of car dependence at zip code level from 0 (car dependent) to 100 (walker’s paradise) 4Count of the number of registered sex offenders within 1-mile of the school location
Discussion
This study of safety barriers from multiple, geographically representative local
SRTS programs found that although similarities exist, the combination of barriers that prevent walking to school are not consistent across all SRTS programs. Results suggest safety factors that are most salient for parents in different programs and also provide a
135 useful advance in the scientific knowledge on families’ decision-making for the journey to school. These initial results are important to both public health and transportation professionals as they may suggest how to remove barriers that prevent families from experiencing the healthful benefits of walking to school. But, identification of safety barriers specific to each local SRTS programs is critical to increasing walk to school behavior among elementary school families.
Findings from the study agree with previous findings that parents tend to overestimate the distance between home and school and generally perceive even short distances of 1-mile or less to be “too far” to walk. The significant barriers found when comparing walking with all other modes, inclusively, did not differ greatly from the comparison of walking with driving. However, a smaller set of safety barriers were significant when comparing walking with driving, which may be more useful to local programs in comprehensively addressing safety with limited resources. Stratified analyses revealed that the number of traffic lanes is a meaningful safety barrier for all parents. Professionals involved in school siting and city planning should consider this perspective. Reducing the average number of lanes that a family would cross on the route to school can have a positive effect on walk-to-school behavior.
There are three limitations to the study that are important to point out. The safety factors included in the study do not include all possible factors. Influential factors may not have been included, although selection of factors used both the SRTS Parent Survey and published literature. The way that factors were operationalized in the study may also have influenced results of the study. Multiple attempts were made during data acquisition
136 and again in analysis to use the most appropriate objective measure for each of the perceived safety barriers. Data in the study were specific to the three local SRTS programs and their locations. This may therefore limit the generalizability of the findings to other settings or to schools not participating in SRTS programming. The small sample size of local SRTS programs included in the study impacted the ability to detect significant effects across programs. However, results do measure important personal, geographic and contextual factors that may influence walking to school within the context of the SRTS program. This study is the first to use these SRTS program data in this way and explore a method of developing an evidence-based approach to practical programmatic decision-making. Future research should consider further examination of these barriers using a large random sample of local SRTS programs.
There were some similarities in meaningful safety factors among the three local
SRTS programs when comparing the outcome of walking to school with all other modes.
Parents’ judgment of the distance between home and school, perceived safety of intersections and crossings, and the proportion of students that walk to school were present in at least two of the three final models comparing walking to school with all other modes. In the three-level model, parents’ judgement of the distance between home and school was again significant. Four of the perceived safety barriers (speed, traffic, intersections and crime) significantly reduced the odds of choosing to walk to school compared to using any other mode. The perception of sidewalks or pathways as a safety barrier appeared to show support for walking to school in all models. This is potentially a limitation of the wording of the Parent Survey from which the study data were obtained.
137 Parents’ selection of sidewalks/pathways on the survey could have indicated this factor to be a facilitator for walking rather than a barrier.
Three safety barriers in the SFSRTS model comparing walking to all other modes that appeared to be most critical: parent education, average number of lanes and sidewalks. This finding agrees with a similarly designed analysis using a large cohort of more than 4,000 subjects that tested univariate and two-level mixed regression models containing individual and school-level variables. The rate of walking was positively associated with proximity.[40] A study of neighborhoods in California, using survey data from parents of third, fourth and fifth grade parents also found walking was related to safety that adults felt within the neighborhood. This study defined neighborhood even more narrowly than the present study, limiting the area of interest to within ¼-mile of the school site. A similar environment variable included in the study was presence of sidewalks. However, parents did not report on incidental trips that were less than 10 minutes walking. [90]
The final model of the WalkSafe program data comparing walking to school with all other modes found family socio-demographic factors (language, child’s gender and parent-estimated distance to school) and parents’ perceived barriers (speed of traffic along route, sidewalks/pathways and crime/violence) were most influential. Family language other than English as its primary language had a positive association with the odds of walking to school. This finding aligns with prior research in the context of SRTS and active travel to school, which indicates a social influence that could be supported by the local SRTS program. However, the relationship between primary language and
138 walking may be biased since studies have found it difficult to measure it independent of related family and neighborhood characteristics.[16] Not surprisingly, the traffic safety barrier of speed was significant. Similar to the SFSRTS model, parental perception of sidewalks/pathways as a barrier to walking had an OR greater than one. This result is counterintuitive and could suggest a problem with the Parent Survey design or its interpretation. Although the study examined the effects of neighborhood environment at the school level, there were no school level variables in the final model. The lack of significant school-level factors may be related to one or more unmeasured factors, including vehicle ownership. Even with the use of objective measures for safety variables, heterogeneity of neighborhood environments across Miami-Dade County may also have influenced the results.
Among the Columbus dataset, perceived barriers (safety of intersections and crossings, and crime/violence) and overall proportion of students that walk to school were significant. The perceived barriers had an important influence on the odds of walking to school compared to use of any other mode. Odds of walking were reduced by more than 30% for each of these two barriers compared to other modes. The WHO has suggested ten major strategies for reducing the risk of road traffic crashes for children. At least two of these strategies include enhancements to road infrastructure, such as traffic controls at intersections, that address vulnerabilities of child pedestrians.[34] Significant barriers to walking are consistent with findings from a study of walkability and safety around elementary schools in Texas. Among the 73 public elementary schools studied, there were higher annual rates of motor-vehicle crashes and violent crime (Part-I crimes)
139 around those schools that better supported walkability (e.g., shorter distances to school and more sidewalks).[164]
Findings from the non-stratified models comparing the odds of walking to school to the odds of using a family vehicle confirmed pervious research. In the final model, parents living within 1-mile of school that perceived the distance to be greater than 1- mile were 78% less likely to walk or allow their children to walk than they were to drive.
The relationship between distance and walking to school is well-established in the literature. However, this finding is worth noting because it provides some additional insight to parental perceptions. The study included only families that live within 1-mile of school. The survey included answer choices for parents, including an answer choice of
“Don’t know”. Parents answered the question of distance from home to school as 1-mile up to 2 miles or greater than 2-miles from among the answer choices provided, which demonstrates the strength of these parental perceptions. Other individual or family-level variables, including the child being female, and the perceptions of speed, traffic volume and crime/violence as barriers were important in the final model. Interestingly, in the stratified models, gender and perception of speed were only significant among the
WalkSafe program.
The finding that the odds of walking to school versus being driven are different for male and female children is important. Parental perceptions that differentially impact children of elementary age likely contributes to health consequences. These consequences, experienced by females at higher rates than their male peers, may begin as early as adolescence and continue or worsen in adulthood. Previous research on walking
140 and biking to school among adolescents found an even more profound difference between the odds of walking for males compared to females.[197] Findings from these and other studies suggest that parental safety perceptions are discouraging female children from walking to school. This decreases the opportunity to obtain the same amount of physical activity as male peers and increases time spent sedentary (e.g., being driven to school).
This relationship requires further study but can be more immediately be addressed by
SRTS program implementation.
The examined safety barriers, speed of traffic along route, amount of traffic along route, and crime/violence were significant predictors of families’ decision to walk or not walk to school. This finding supports other work and indicates potential interventions to be prioritized by local SRTS programs, nationally.[34,44,151] The result agrees with research on traffic related injury for all road users. Speed has been identified as a critical factor in traffic-related collisions.[33,198] Enforcement of existing school speed zone limits or other speed limits within 1-mile of schools would contribute to a reduction in speed-related collisions and associated injuries or fatalities. An extensive literature review using the Active Living Research database found traffic volume to be consistently correlated with walking among children.[22] A large cohort study that utilized mixed regression models also found walking rates were higher in neighborhoods with lower traffic density.[40] Crime or violence, too, is consistently correlated with walking. The direction of the relationship, however, has been inconsistent.[151] Results differ between reported and objectively measured walking or physical activity.[22,77,151] The current study supports the importance of measuring safety factors individually, using both
141 objective and perception data, to determine patterns of association. High levels of safety concern among parents is a pattern across varied studies and has consistent and negative associations with walking.
Importantly, the analysis builds upon findings from previous research that has identified the locations of the most salient safety barriers among families living within 1- mile of the same schools studied here. Results from the present analysis provide knowledge of the combination of factors more likely preventing families from choosing to walk, which can then be examined together with information about the location of those factors. This contributes to a more comprehensive understanding of the influence of factors within the overall context of both the physical and social environments. There are three main strengths of the study: (1) use of standard, validated measurement of the dependent variable, walking to school; (2) use of a multilevel analysis that acknowledges the complexity of the decision-making process and the array of factors on differing levels that influence the choices available, and ultimately the travel decision; and (3) inclusion of both the parental-level perceptions of safety barriers and the environment-level measure of safety barriers.
Finally, the findings of this study are important to researchers advancing movements like Vision Zero and Complete Streets. This study has moved beyond the identification of associations between individual features and walking focused on a context that targeted a population especially sensitive to safety. Additionally, the study has examined the composite features of the environment between home and school
(traffic and neighborhood safety barriers) that have sufficient evidence in the existing
142 literature of a significant influence on the decision to walk, or not walk, to school. The study accounted for and built upon established knowledge on specific features associated with walking and expanded this knowledge to find impactful features in the environment that could be modified to improve safety for the vulnerable population of children walking to school.
143 Chapter 6. Manuscript #3
Introduction
The significant decline in the proportion of families that walk to school coupled with the increase in sedentary behavior has led to major public health impacts on children’s health.[2,155,199,200] In response, researchers began to explore the effects of population level changes to create supportive policies and environments for walking.
[101,201–203] Research on the utility of these changes has grown rapidly in the last decade and led to promotion of walking for physical activity.[204,205] Government and other agencies that seek to protect the wellbeing of children have increasingly focused on ways to facilitate physical activity before, during and after the school day. In 2015, the
Surgeon General’s “Step it up!” campaign was released. The campaign was a call to action to promote walking and walkable communities.[205] In 2011, Healthy People
2020 (healthypeople.gov) included specific objectives to increase the proportion of walking trips to school that were a distance of 1-mile or less.[206]
A review of evidence by the U.S. Task Force on Community Preventive Services found that traffic and neighborhood design policies can be effective in increasing walking, particularly in the areas around schools.[209] Policy strategies, then, are a useful strategy to achieve public health objectives outlined in Healthy People 2020 (Table 22).
Legislation at the federal level to fund non-infrastructure transportation alternatives programming has recognized this as a recommended approach to increasing physical activity and safety. Policies that address environmental design and create facilitative infrastructure for walking have the power to make impactful reductions in traffic and 144 neighborhood safety barriers and promote health. Additionally, pedestrian-friendly designs can address physical threats to safety of children walking to school. Policies at all levels could affect environment and behavior to increase the number of children that safely walk to school.
Table 22. Sample of Healthy People 2020 Topic Areas and Objectives [208]
Topic Area Objective
Injury and Reduce motor vehicle crash-related deaths (IVP-13) Violence Reduce nonfatal motor vehicle crash-related injuries (IVP-14) Prevention Reduce pedestrian deaths on public roads (IVP-18) Reduce nonfatal pedestrian injuries on public roads (IVP-19) Reduce children’s exposure to violence (IVP-42)
Physical Increase the proportion of trips made by walking (PA-13) Activity ● Increase the proportion of trips of 1 mile or less made to school by walking by children and adolescents aged 5 to 15 years (PA-13.2)
Social Neighborhood and Built Environment Determinants ● Reduce children’s exposure to violence (IVP-41) of Health
The design of policies to increase walking can be a useful tool in mitigating obstacles for walking trips to school. Transportation policies have historically been most heavily motivated by city planning that accommodates automobiles. As a result, the design of the environment has diminished the presence and safety of pedestrians.[17,144,178,179] Walking increases, however, when policies make the use of motorized travel less attractive. For example, policies that add traffic calming
145 infrastructure and enforce lower speed limits have successfully reduced the use of motorized modes of travel.[207] Reduced speed limits are beneficial for all road users, especially vulnerable populations such as school-aged children traveling from home-to- school.[208] Similar effects are seen when supportive policies for walking are implemented within the context of schools (e.g., at school, district or state levels).[75]
Consistency in policy support for walking at all levels is important, however, policies in place at individual levels (e.g., school or school district) have a stronger effect on behavior change than policies at more distant levels (e.g, state or regional).[210,211]
The inclusion of the transportation alternatives program Safe Routes to School
(SRTS) within school policies has been suggested by experts as one strategy to add permanence to the promotion of walking to/from school at the local level.[69] Design of supportive policy for SRTS has been outlined by the National Center for SRTS to include seven “P’s” (power, philosophy, policy, procedure, project, partnerships, promotion).[51]
Policies that support SRTS and its program goal have been implemented at the school, school district and state levels, nationally. SRTS aligns with existing school policy structures, such as wellness and transportation plans, which can help translate existing interest from participating program schools into commitment to the program’s mission.
Although studies have shown promising evidence for policies that support walking, it remains unclear the level of adoption for policies that increase opportunities for walk-to-school behavior. This study sought to identify and classify existing policies at the school, district, local, regional, state and federal levels that relate to, and potentially support, walking to school. This aim has not yet been addressed within the context of the
146 SRTS program with a comprehensive scope. The assignment of a score is one way to quantify and estimate the strength of identified policies to effectively support SRTS activities, which improve health and safety for children that can or do walk to school.
Research Methods
Study Design
A systematic review process was used to identify and examine SRTS-related policies at the school, district, regional, state and federal levels. The definition of policy for the purposes of the present research was conceptualized according to the definition provided by the National SRTS organization. Policy was defined as a “a high-level overall plan embracing the general goals and acceptable procedures especially of a governmental body” and limited to the areas of education and transportation, which most closely align with the study aim.[51] A broad, inclusive definition of policy was used to support collection of policies at multiple levels that may influence parental decisions about transportation to school. Published, publicly available legislative, regulatory or agency action were included. The policy levels and types, variables for analysis, and data collection procedures are summarized below.
The study’s conceptual model proposed a reciprocal relationship between policy and the environment as well as a relationship between policy and the outcome of walking to school. Policies can have an impact on the environment by establishing criteria for design that require supportive elements, which is part of the social ecological approach to behavior change.[210] The conceptual framework also applied the Hierarchy of Walking
Needs, which proposes that there are levels in a meaningful order required to promote
147 behavior change. Effective policy approaches that seek to change behavior must consider the organization of these needs and the personal attributes that influence them (e.g., demographic traits and the setting).
Study Sample
The sample of policies at all levels included in the study were based on an initial list of schools identified using the National Center for SRTS Data
(www.saferoutesdata.org). Schools from each of the three local SRTS programs
(SFSRTS, WalkSafe and CSRTS) with available Parent Survey data formed the initial list.
Data Source
Policies were identified using two main search strategies (1) manual search of relevant websites and (2) systematic search of legislative databases. The manual search involved an online search of school, district, city, regional, state, and federal websites to identify and gather all potentially relevant policies. The websites for all levels of the
Parent Teacher Association (PTA) were also searched. An example of the search process is summarized in Figure 9 below. The researcher manually reviewed all menu options of each website to inspect each webpage for policy or relevant links to policy. Once the site review was completed, an internal search was conducted using the search tool on the individual websites. The search terms “walk” and “safe routes” were used in separate searches on each site for all policy levels. The search terms and results from each of the internal site searches were recorded as the process moved forward to ensure continuity of
148 documentation between and across searches, and accuracy of data. A list of sites searched has been included as Appendix I.
Legislative databases, WestLaw and NexisLexis were reviewed as a secondary search strategy to complement the manual search for relevant policies. A systematic search was conducted with assistance from a subject librarian. However, no additional policies were identified for inclusion using this strategy. The use of these two strategies, in combination, helped to ensure identification of the greatest number of possibly relevant and available policies.
The criteria for inclusion were policies that related to any of the three overall
SRTS program aims (increase physical activity, improve environments for walking or biking, or decrease pedestrian injury). All identified policies were initially included for review.
Measures
Policies and associated data were organized and summarized by use of a policy scan tool (Figure 10). The tool was used to assess descriptive characteristics of the identified policies, including type of policy and vulnerable populations mentioned. The policy scan tool was created in Excel and functioned as both the inventory tool and a database of collected policies. Information on collected policies was entered directly into the tool, according to the tool’s headings. Policies were then evaluated using the scoring guide (Appendix J). The scoring guide was a comprehensive tool based on existing, relevant criteria for the study aims. The scoring included criteria developed by expert
149 agencies for the types of policy collected during the policy scan and that have been implemented by trained reviewers in similar contexts.[51,141,142,145]
Policy Scan Data Tool
A data tool was developed by the investigator during collection of the policies.
The tool was tested with a sample of policies by a second researcher and inter-rater reliability was assessed.
Figure 14. Policy Scan Data Tool
150 Policy Scoring Guide
A policy scoring guide was developed based on existing policy evaluation criteria
(Table 23). The major elements of the scoring guide were: Power, Philosophy, Policy,
Procedure, Project, Partnerships and Promotion, which have been outlined and defined by SRTS in the Local Policy Guide. These elements are known as “The Seven P’s of
Policy Change” and provide a framework for effective policy.[51]
Power refers to key stakeholders and champions within the decision-making body that can enact and enforce the policy. Philosophy refers to the values to be established by the policy, or a vision for enabling more children to walk to school. The values and vision differ at the various levels of policy or in different locations. For example, a state department of transportation may value decreased traffic vehicle-to-vehicle crashes while a local school district may value reduction in school bus transportation budget. Inclusion of the philosophy in the written policy is a way to “memorialize” the shared vision. Once the policy is enacted, this becomes a tool for problem-solving among decision-makers and outreach to stakeholders. The element of Policy is intended to establish accountability by documenting a responsible agency (agencies) and plan for enforcement within the language of the policy. A statement about how the policy will be regulated, or enforced, can strengthen the level of investment from agency staff or elected officials.
This element also provides clarity on an action plan for achieving the vision. Agency leaders and officials included in the policy become accountable to stakeholders.
Procedure, as described in the Local Policy Guide, relates to direction for the policy, such as timeline and scripting of the policy to preserve the vision from future changes in
151 priorities. In the scoring guide the strength of the policies’ procedural direction was measured whether model SRTS language was used. Model language for the program has been developed and implemented successfully to address the complexities of the policy change or adoption processes. Project refers to presence of specific actions (“projects”) planned to achieve the desired vision. For example, construction of 80 miles of multi-use trails that connect to on-street bike lanes in a certain jurisdiction or retiming of traffic signals to allow pedestrians additional time for crossing certain roadways. Statement of planned or successfully completed actions can provide a way measure progress toward achieving the vision. Partnerships identify the resources to work as a team to achieve the state policy vision and are recommended to include more than one agency. A city policy, therefore, should state at least one partnership that is not a department, division or section of the city government. The element of Promotion is focused on making the policy “real” and obtaining results. Statement of specific goals in the policy identifies benchmarks by which to measure results of the policy and continue incremental change overtime.
Individual scoring elements were pulled from the existing evaluation tools and categorized by the “P’s” of the policy guide. Some modifications were made to scoring prompts to (1) allow for binary response, and (2) use pedestrian-specific language. For example, “What actions have been implemented?” was changed to “Does the policy list actions (planned or implemented) to address pedestrian safety?” Each element was assigned a binary score (0 or 1). Presence of the element within the policy received a score of 1; absence of the element received a score of 0. The score provided a measure with which to compare individual policies during analysis and identify gaps in the
152 strength of support for SRTS in each policy. A total score was also used to evaluate polices. Policies were scored out of a possible total of 14 points.
153 Table 23. Policy Scoring Tool
Indicate the level at which the policy is implemented (Federal/State/Regional/Local/School District)
Power Does the policy reference the key power people (schools)? Philosophy Does the policy include a stated Vision? Policy Does the policy make any statement on enforcement or regulation? Does the policy indicate the responsible party for enforcement or regulation? Procedure Does the policy utilize model language supporting Safe Routes to School? Project Does the policy list actions (planned or implemented) to address pedestrian safety? Partnerships Does the policy make any statement on inter-agency collaboration? Does the policy indicate partnerships for implementation? Promotion Does the policy have stated goals for pedestrian safety? Does the policy have stated goals for child pedestrian safety?
Community advocacy level Does the policy mention community input during the development of the policy? Agency staff level Does the policy reference staff or agencies responsible for implementation? Does the policy reference staff an elected or governing body responsible for Elected body level implementation?
Health Impacts Does the policy mention expected measurable health impacts?
154 Data Analysis
All identified policies underwent a brief initial review for possible inclusion in the policy scan (n = 245). Policies were excluded after initial review based on title and summary information. After initial exclusions, a total of 109 polices from federal, state, regional, city and district levels, as well as PTA policies from both national and state levels, were retained for possible inclusion in the policy scan. Inclusion and exclusion criteria for policies in the scan were developed during the initial review process. Criteria were applied iteratively after an additional random subset of policies was reviewed by >1 researcher, and consensus was researched regarding the decision to exclude a policy.
Policies were excluded from the policy scan if (1) they were not relevant to SRTS program aims, (2) not considered policy according to the given definition, or (3) they were a component of or amendment to an already included policy.
Two qualitative methods were used in the analysis. First, inventory of the collected policies was guided by the policy scan data tool. The title, year enacted, type of policy, responsible agency, focus, vulnerable populations mentioned, and reference for each policy were included in the inventory using the data tool. A description of the tool has been provided above in Figure 10. If the year enacted was not available from the policy document, additional internet searching was used to find more information. The search process to determine the year the policy was enacted, including terms and results, were documented in a search flow worksheet. Policies in the scan were coded as one of three types: legislation, regulation, or agency action. ‘Vulnerable populations mentioned’ used binary coding (yes/no) to evaluate presence of specific reference to each of the
155 following vulnerable road user populations within the policy text: pedestrians, children or students, disabled, minority, and low income or disadvantaged populations. ‘Funding’ captured any mention of financial support for the policy’s implementation. This did not include reference to a need for or planned sources from which to secure funding.
‘Reference’ is a direct link to the online location of the identified policy.
Next, policies were scored using the Policy Scoring Guide, described above and available in Appendix S. The policy scoring guide was applied only to selected policies
(wellness, city master plan and complete streets) because the tool was adopted from existing criteria for these policies. The guide was also revised to account for the context, design and aims of the study. Policies could receive a maximum score of 14 points.
Scoring elements included seven attributes of policies, called the 7 P’s, defined by the
SRTS Local Policy Guide.[51] All elements in the guide were measured as binary
(present or absent). In the case of two similar policies at the same level being included in the policy scan (e.g., two regional transportation master plans for the same region), only the most recent plan was scored. The scoring was conducted by the investigator in July
2017. A second reader used the investigator’s protocol to independently score a randomly selected sample of policies in September and October 2017. Consensus meetings were held to discuss any discrepancies and revise the scoring guide protocol to incorporate revisions decided by the two researchers. The inter-rater reliability was tested by calculating percent agreement.
156 Inter-rater reliability, measured by percent agreement between scores, was assessed on a random sample of policies during initial review. Overall, there was 61% agreement between the scores of the two reviewers (KS, CT). A summary of agreement is given in
Table 24. After the initial independent scoring, consensus meetings were held, and final scoring was assigned by the two reviewers.
Table 24. Summary of Inter-rater Agreement for Sample Scoring of Policies
Level of policy No. of Policies % in Sample Agreement Federal 0 -- State 3 69 Regional 2 58 Local (city) 3 42 School District 3 72
Descriptive analysis of policies was facilitated by the policy scan data tool. The headers (type of policy and vulnerable populations mentioned) represent variables used in descriptive analysis. Similar descriptive analysis of policies was facilitated by the policy scoring guide, supplemented by subjective qualitative summary of inventory and scoring.
Results
Policy Inventory
Existing policies were identified and described to estimate the frequency of SRTS policy at all levels. A final sample of 86 policies were included in the policy scan. A summary of the policy scan results is presented in Table 25. A total of three states
(California, Florida and Ohio), three regions (San Francisco Bay Area, Miami-Dade
157 County, and Central Ohio), 14 cities (San Francisco, Coral Gables, Doral, Hialeah
Gardens, Homestead, Key Biscayne, Miami, Miami Beach, Miami Gardens, Miami
Shores, North Miami, Opa-Locka, South Miami, and Columbus), and three school districts (San Francisco Unified School District, Miami-Dade County Public Schools, and
Columbus City Schools) were included. School level policies were inventoried separately. Overall, most identified policies were classified as regulation (52.3%).
Excluding the federal level, policies were most prevalent at the state level with an approximate ratio of 8 policies per state. One-quarter of identified policies did not mention pedestrians but more than 60% included language about children or students
(Appendix P). Approximately 40% of policies explicitly mentioned the SRTS program and half mentioned walking to school.
158 Table 25. Summary of Policy Scan
Total number of policies included in scan* 86 Type n % Legislation (act, bill, policy) 30 34.9 Regulation (tax, standards, incentives/grants, guidelines, Master Plans) 45 52.3 Agency action (position statement) 11 12.8 Level Federal 13 15.1 State (3) 24 27.9 Regional (3) 11 12.8 Local/City (14) 29 33.7 School District (3) 3 3.5 PTA** 6 7.0 Populations mentioned Pedestrians 65 75.6 Children/students 54 62.8 Disabilities 33 38.4 Minority(ities) 15 17.4 Low income/disadvantaged 22 25.6 Explicitly mentioned Safe Routes to School 35 40.7 Walking to school 43 50.0 *Does not include school level policies **Includes policies from National PTA, California PTA, Florida PTA and Ohio PTA
Individual results of the inventory summary by level of policy are presented separately in the Appendix (J through O). Years when policies were enacted ranged from
1998 through 2017. Most policies identified a single agency or collection of agencies responsible for implementation. Most frequently, the state transportation agency was identified as the agency responsible for implementation and supplying the necessary funding. Among federal, state and regional levels, though, 16 (33.3%) policies did not mention funding. A sample of relevant language from individual policies at each level is 159 shown in Table 26 with full results for Federal, State, Regional and Local levels displayed in Appendix Q; PTA and School District results are presented separately in
Appendix R and S, respectively.
160 Table 26. Sample of Relevant Language from Policies
Policy Title Sample of relevant language in policy Federal The purposes of the program shall be (1) to enable and encourage children, including those with disabilities, to walk and bicycle to school; (2) to make bicycling and walking to school a safer and more appealing transportation alternative, thereby encouraging a healthy and active lifestyle from an Safe, Accountable, Flexible, early age; and (3) to facilitate the planning, development, Efficient Transportation and implementation of projects and activities that will Equity Act: A Legacy for improve safety and reduce traffic, fuel consumption, and air Users pollution in the vicinity of schools. State Caltrans develops integrated multimodal projects in balance with community goals, plans, and values. Addressing the safety and mobility needs of bicyclists, pedestrians, and transit users in all projects, regardless of funding, is implicit in these objectives. Bicycle, pedestrians, and transit travel is Complete Streets-Integrating facilitated by creating 'complete streets" beginning early in the Transportation System system planning and continuing through project delivery and (DD-64-R2) maintenance and operations. Regional Policy CHD-3B. Encourage walking and bicycle riding as a means of transportation to and from school, by implementing capital projects that support the development Safer People Safe Streets of safe routes to school. Local/City Objective 4.2. Target safety and walkability improvements near schools and areas with higher rates of senior pedestrian Pedestrian Strategy injuries. School District Columbus City Schools The District will promote physical activity opportunities Comprehensive Wellness through programs that support wellness and education Policy benefits of walking and bicycling to school. PTA Whereas, Parents city safety issues and traffic concerns as the number one reason for not allowing their children to walk or bike to school; this concern is substantiated by the fact that there is a high probability the result with be fatal when a pedestrian is involved in an accident...Resolved, That PTA and its constituent associations encourage and Resolution on Improved collaborate with school administrators and local officials to Infrastructure Around bring attention to unsafe walking and biking routes to Schools schools...
161 A total of 130 school websites were reviewed. There were no wellness or transportation policies at the school level that were created as separate and distinct from the district level policy. However, some schools did provide general guidance on arrival and dismissal procedures that included language relevant to SRTS or were found to be participating in SRTS-relevant transportation programs at the district level. These policies were used to demonstrate and summarize school level policies identified in the review (Table 27).
This inventory was an overview of available policies, intended to supply the reader with contextual connections necessary to understand how each level of policy may influence local implementation of SRTS. The scope of the inventory was defined specifically for this research and may have excluded policies relevant to similar but other interests. In addition, new policy documents have likely been published or existing policies updated since the writing of these results.
162 Table 27. Summary of School Level Policies
School Policy Title Sample of relevant language in policy San Francisco Safe Routes to School Grattan STOP, DROP & GO DO - Yield to pedestrians. Many of our Elementary families walk to school and the crosswalks School will be full at drop off time. WalkSafe Program Toussaint 2016-2017 Parent Students are to use the sidewalks, stay out of L'Ouverture Handbook the parking lot, cross at the crosswalks, and Elementary obey the crossing guard. The decision as to School whether a child should walk or bike to school is the parents’. If you believe your child is mature enough to do so, please review safety procedures with your child. All members of the Toussaint L’Ouverture Elementary family should follow these safety guidelines. Inconsiderate and unsafe practices constitute a severe threat to student safety.
Eugenia B. SchoolPool The FREE service offered to schools in Thomas K-8 Miami-Dade was designed to reduce traffic Center congestion, pedestrian hazards, parking demand, and environmental impacts around schools through the promotion of carpooling, bicycling, and walking.
Columbus Safe Routes Georgian Heights Georgian Heights 2. For arrival, have your child exit the car on Elementary Elementary School Car the sidewalk side of the car in next to the School Line FLAG POLE. Ohio Avenue Safe Routes to School SRTS encourages parents to walk or bicycle Elementary Information with students to and from school. This map School is a guide. Parents are responsible for choosing the most appropriate way to go based on their knowledge of conditions along the route, and the experience level of their child.
163 Policy Scoring
The level of support provided by existing policies for children that can or do walk to school was measured using the policy scoring process. The PTA and School level policies were not included in the scoring due to a lack of relevant policies. None of the policies that were scored addressed all of the policy change components recommended by the SRTS Local Policy Guide. Overall, federal policies achieved the highest average score while state level policies had the lowest average score. Policy scores ranged from a minimum of 4 to a maximum of 13. No policy achieved the total possible 14 points.
Policies most frequently scored 11 points. The San Francisco Complete Streets Law and
Columbus Pedestrian Thoroughfare Plan were the two lowest scoring policies, each earning four points.
A summary of policy scoring is presented below (Table 28). Scores for individual policies are presented by level of policy in Table 29. Full results of the policy scoring analysis are available in Appendix S.
Table 28. Summary of Policy Scoring Results
Level of policy No. of Policies Average Included Score* Federal 1 11.0 State 6 7.2 Regional 5 9.4 Local (city) 9 8.9 School District 3 9.0 *Policies were scored out of 14 points
164 By local SRTS program, WalkSafe (n=10) had the highest average policy score of 9.5 and most narrow range from 7 to 11. San Francisco Safe Routes to School had a total of six policies included with an overall average score of 9.3. Scores for the San
Francisco Safe Routes to School program ranged from 4 to 13 points. Columbus Safe
Routes had the lowest average score as a program (6.6). Scoring for the program included a sample of seven policies whose scores ranged from 4 to 10.
165 Table 29. Results of Policy Scoring by Level
Policy Title Score Federal Final Rule: Local School Wellness Policy Implementation Under 11 the Healthy Hunger-Free Kids Act of 2010 San Francisco Safe Routes to School State California Transportation Plan 2040 10 Complete Streets Law 4 Complete Streets-Integrating the Transportation System (DD-64- 5 R2) Regional Plan Bay Area 2040 11 Local (city) San Francisco Pedestrian Strategy 13 School District Wellness Policy 13
WalkSafe Program State Florida Pedestrian and Bicycle Strategic Safety Plan 11 Regional Miami-Dade County Complete Streets Resolution 7 Miami-Dade 2040 Bicycle/Pedestrian Plan 11 Local (city) Bicycle and Pedestrian Mobility Plan for the City of Miami 9 Gardens 11 Sustainable Opa-Locka 2030 Comprehensive Development 8 Master Plan 10 Village of Key Biscayne Master Plan 9 Homestead Transportation and Transit Master Plan 11 City of Doral 2010 Transportation Master Plan City of North Miami Transportation Master Plan School District Wellness Policy 8 Columbus Safe Routes State Access Ohio 2040 8 Ohio Department of Education 2016-2017 Wellness and Physical 5 Education Regional The 2016-2040 Columbus Metropolitan Transportation Plan 8 Mid-Ohio Regional Planning Commission Complete Streets 10 Policy Local (city) Columbus Complete Streets Resolution 5 Columbus Pedestrian Thoroughfare Plan 4 School District Comprehensive Wellness Policy 6
166 Discussion
Policies can help create neighborhood and physical environments that are safe from injury, reduce exposure to harm, and promote safely and easily walking to school.
The design of safe, supportive environments is critical to addressing the multiple Healthy
People 2020 objectives. However, the study has outlined a policy environment that appears to only moderately support walking to school and safety of those trips for children. At least one distinct SRTS-related policy was identified at every level in each of the study locations. None of those policies, though, contained all seven of the recommended components. State level policies are common but weak, primarily lacking explicit inclusive language to be effective. Although federal mandates have emphasized physical activity as a necessary element in school wellness policies, the inclusion of
SRTS in school policies was lower than expected. The prevalence of vehicle-centric transportation policies, too, emphasized a lack of equitable planning for all modes of transportation. Overall, policies across locations, categories and levels could be more effective in protecting vulnerable road users, such as children, and in promoting walk-to- school behavior.
While many policies, at various levels, were inclusive of pedestrians and walking, only half of all studied policies mentioned ‘walking to school’. At the federal level, there were four policies that did not mention SRTS or walking to school, but 11 of the 13 total policies mentioned children. There were 10 policies without mention of walking to school at the state level, three at the regional level and 15 at the city/local jurisdiction level. The most notable deficiencies of inclusive language were seen at the state and local
167 levels. State policies in Florida were most frequently lacking mention of vulnerable populations. The absence of language to target policies for vulnerable populations, such as children traveling to school, potentially indicates a lack of consideration for these populations in writing of the policy.
Results also demonstrate the range of SRTS-related policy adoption. The SRTS program was included in more than 40% of the policies in the scan and half explicitly mentioned walking to school, which demonstrates a level of success in promoting walk to school behavior and sustaining the program through policy. However, this also means half of policies have not yet contributed to the overall level of success. There was an absence of school level SRTS policies across all three of the included programs. At the school level, there were no distinct policies for active travel to school. Any written statement that mentioned walking at the school level simply restated the district level policy. School level policy has demonstrated useful impact on important subgroups of children whose participation in physical activity are known to decline as they age. Ward
(2015) found a positive association between school level policies and girls’ participation in physical activity as a group.[75] In this way, school level policies can influence both physical and social support for walking to school. District level policies can provide a useful standard from which to create a tailored school level policy. Then district and school policies, together, add clarity to and promotion of walking as a mode of school transportation. Presence of an arrival or dismissal procedure is one influential factor for participation in walk-to-school programming.[212] Schools could implement arrival/dismissal policies that use guidance from the district level policy to create
168 supportive environments for walking to school. Legislative policies at the school level are particularly important because of the proximity of their influence on children. Although the present study only reviewed school policies published online, a web-based process potentially simulates parents’ access to information on policy and procedure at the school level. Availability of a school level policy on the school website, especially as online parent portals and paper-free communication gain importance, is part of a comprehensive approach to activity promotion and injury prevention. The results of this study build upon existing work by the SRTS program that has highlighted anecdotal success of individual programs, primarily at the local program level, and program research demonstrating significant evidence of the program’s ability to increase the proportion of children that walk to school.
Policies, too, need to be written with “powerful language” to ensure a commitment of state, regional, city, district and school resources to “processes and procedures that will support safe and healthy communities.”[51] None of the policies identified in the scan included all seven of the policy change components recommended by the SRTS Local Policy Guide (power, philosophy, policy, procedure, project, partnerships, promotion). The average scores of the state, regional, local and district policies ranged from 5 to 6.5, out of total 14 possible points. Among these policies, points were frequently lost when scoring the elements of Partnership and Promotion. For example, California’s Complete Streets Law and Access Ohio 2040 both scored zero points due to absence of language within the policy on inter-agency collaboration or not having a statement of pedestrian safety goals. Child pedestrian safety goals were also
169 absent from Florida’s Bicycle and Pedestrian Safety Plan. Goals stated directly in the policy can be critical for other elements, such as enforcement and evaluation of the policy. Creation of strong school level policies and changes to the language of policies at all other levels may be necessary for SRTS programs to be effective and sustainable.
Inclusion of the term ‘pedestrian,’ and the explicit mention of schools as a destination, within the policy language concretely acknowledges people as road users and walking as an equitable form of transportation. The identified gaps in existing policy outline opportunities for policymakers and program leadership to improve support for the SRTS programs and their public health goals.
While simply having a policy related to SRTS can be viewed as an important demonstration of support for the program, weaknesses in these policies prevent them from achieving potential positive impacts on health. Systematic examination of policies at all levels and across diverse geography underscored a deficiency in support for SRTS at the state level. The sample of state level policies for California and Ohio each met half, or fewer, of the scoring criteria. State level policies that earned low scores were missing at least three recommended SRTS policy elements. The polices did not include goals for protection of pedestrian safety or goals for child pedestrian safety (Promotion) or inter- agency collaborations (Partnerships), as noted earlier. The SRTS framework functions as a list of agencies to collaborate in the writing, enforcement and promotion of policies.
Support for SRTS would improve simply by identifying an entity to be held accountable for enforcement of the policy from among the partners (Policy).
170 Finally, regulation was the most prevalent type of policy in the scan. Regulation can be beneficial in creating funding streams for infrastructure improvements that serve the needs of non-vehicular traffic and de-incentivizing travel by motor vehicle. However, legislative policies that more directly influence the behavior of walking to school are needed. Adoption of policies that increase/decrease opportunities for physical activity is one theory-based policy strategy to effectively change physical activity behavior, including walking to school. Results from a review by Dunton et al. (2010) suggested that this policy strategy, driven by variables and processes from social cognitive theory, can promote modifications to the environment that may influence perceived barriers.[117]
This strategy is also directly related to at least two areas defined in The Ottawa Charter for Health Promotion, (1) building healthy public policy and (2) creating supportive environments.[213] Walking to school, and the SRTS program, cut across multiple strategic areas identified by CDC (2009) for addressing poor health among children and youth. This includes encouraging physical activity or limiting sedentary activity, creating safe communities that support physical activity, and encouraging communities to organize for change.[214] Institutionalizing SRTS policy components at multiple levels would fill gaps in existing legislative support for child pedestrians. Presence of a policy at multiple levels would also add consistency to support across different environmental contexts and jurisdictions in the space between home and school.[151,210]
Empirical research on ecological approaches to increasing physical activity has highlighted the importance of policy strategies.[128,151,210] Policy interventions, part of an ecological model of health behavior, have particular use in the area of promoting
171 physical activity through walk-to-school behavior. Walking to school has a specific physical setting and has been shown by the existing evidence base to be associated with other physical activity behaviors among young people.[91] Studies of pediatric pedestrian injury, too, have concluded that behavioral interventions are not sufficient to prevent injury.[215] SRTS policies are a useful intervention because they seek to provide opportunities for walking to school or other physical activity, as well as improve safety.
Collectively, the policy review process (“scan”) and scoring have provided a step toward surveillance and evaluation of implemented policies. This policy review process
(“scan”) serves as an exploratory capacity-building tool for SRTS and has the potential to be utilized nationally by the SRTS program. Identifying and characterizing existing
SRTS-related policies, as done in the study, provided a brief assessment of the support for walking to school at each level. Scoring of policies further assessed the relative strength of individual policies to enable and promote safely walking to school. Results emphasize the need for policy revision to address identified gaps and create “strong” policies. A strong policy, in the present context, can be defined as policy that includes all elements known to effectively promote walking to school. The inventory used the existing seven “ P’s” framework published by the SRTS National Partnership and serves as a starting point for stakeholders to draft policy amendments. The framework was developed to assist in the creation of supportive environments for walking to school and the successful institutionalizing of SRTS through policy. Strong policies can mandate environmental designs that protect children from traffic-related injury on the walk to school and the promote walking as safe, accessible form of transportation.
172 Several limitations of the research should be noted. First, the review is limited to indirect methods of data generation. The methods did not include collection of any qualitative data directly related to the policies. No surveys, focus groups or interviews were conducted. However, the data generation method selected allowed for inclusion of six different levels of policy for each of three different local SRTS programs. Second, not all policies may be published online or publicly available due to resource limitations of the agency. Policies may be available that were not found by the investigator. Although, a combination of search strategies was used to ensure an exhaustive inventory. The published policies collected for review may be outdated, which potentially influenced the scoring process. Lastly, the local SRTS programs included in the overall study design served public schools in urban districts. This presents a limitation in the representativeness of the sample. The resulting policy inventory does not apply outside of the study context, for example, in rural settings where feasibility of walking to school is limited by distance and lack of access to public transit. The selected local programs already have SRTS programming implemented and may therefore be biased toward more support for walking.
Despite these limitations, the study has several strengths. First, the study included a large sample size of policies, including diverse SRTS programs. The programs, too, represented varied geographic locations, nationally. The diversity of included programs contributed to the identification of key similarities among policies and suggests meaningful findings. The policy scan process used in the present study has systematically reviewed the existence and completeness of policy at multiple levels for multiple
173 programs. Prior SRTS program evaluations, conducted at local, state and national scales, have not examined policies in this way. The findings have provided an overview of
SRTS-related policies that exist to enable and influence walking to school. The study has built awareness and understanding of the existing policies, and useful recommendations for revisions. Further research is needed to build on this review process by connecting policy presence and strength to relevant health outcomes. Individual policy elements, and similarities among the identified policies that scored well should be further explored to determine how they positively impact the SRTS program.
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202 Appendix A. Sample of Schools San Francisco Safe Routes to School Program (SFSRTS) Alamo Elementary School Alvarado Elementary School Argonne Elementary School Bessie Carmichael Elementary School Bryant Elementary School Buena Vista/Horace Mann K-8 Center Chinese Immersion School at De Avila Cleveland Elementary School Commodore Sloat Elementary School Dianne Feinstein Elementary School El Dorado Elementary School ER Taylor Elementary School Fairmount Elementary School George Peabody Elementary School George Washington Carver Elementary School Glen Park Elementary School Gordon J Lau Elementary School Grattan Elementary School Jean Parker Elementary School Lafayette Elementary School Leonard Flynn Elementary School Longfellow Elementary School Marshall Elementary School Monroe Elementary School Rosa Parks Elementary School Sherman Elementary School Spring Valley Elementary School Stevenson Elementary School Sunnyside Elementary School Sunset Elementary School
WalkSafe Program Arcola Lake Elementary School Charles R. Drew Elementary School Coral Terrace Elementary School Earlington Heights Elementary School Eugenia B. Thomas Elementary School Fulford Elementary School Gratigny Elementary School Henry M. Flagler Elementary School Jesse J. McCrary Elementary School
203 Kelsey Pharr Elementary School Liberty City Elementary School Lillie C. Evans Elementary School Miami Shores Elementary School North Miami Elementary School Olinda Elementary School Orchard Villa Elementary School Paul L. Dunbar Elementary School Southside Elementary School Toussaint L'Ouverture Elementary School W. J. Bryan Elementary School West Little River/ Dr. Henry Mack Elementary School
Columbus Safe Routes Program
Alpine Elementary School Avondale Elementary School Binns Elementary School Cedarwood Elementary School Clinton Elementary School Colerain Elementary School Como Elementary School Devonshire Elementary School Eakin Elementary School Easthaven Elementary School Gables Elementary School Georgian Heights Elementary School Huy Elementary School Indian Springs Elementary School Lincoln Park Elementary School Lindbergh Elementary School Maize Elementary School North Linden Elementary School Ohio Avenue Elementary School Parsons Elementary School Salem Elementary School Scottwood Elementary School Southwood Elementary School at Reeb Starling PreK-8 Center Valley Forge Elementary School Watkins Elementary School West Broad Elementary School
204 West Mound Elementary School Westgate Elementary School Windsor Elementary School Winterset Elementary School
205 Appendix B. Descriptive Characteristics of Included Schools
San Francisco Safe Routes to School Program
Estimated Enrollment FRPM Eligible Non-White School name Walk Trips to (2014-2015) (%) (%) School (%)
Alamo Elementary School 538 37.6 96.8 30.3 Alvarado Elementary School 528 36.8 63.2 15.0 Argonne Elementary School 447 39.1 67.8 30.0 Bessie Carmichael K-8 Center 636 84.8 95.2 35.3 Bryant Elementary School 239 89.5 96.7 53.0 Buena Vista Horace Mann K-8 Center 557 63.7 87.5 21.9 Chinese Immersion School at De Avila 397 19.4 83.9 6.0 Cleveland Elementary School 353 81.5 98.6 33.4 Commodore Sloat Elementary School 391 40.2 73.0 9.3 Dianne Feinstein Elementary School 507 29.0 71.6 10.2 El Dorado Elementary School 256 86.3 99.1 22.4 ER Taylor Elementary School 656 77.7 98.5 37.0 Fairmount Elementary School 392 43.0 88.8 16.0 George Peabody Elementary School 266 26.4 87.7 32.1 George Washington Carver Elementary School 239 90.4 99.0 29.5 Glen Park Elementary School 356 64.1 78.5 14.4 Gordon Lau Elementary School 648 73.8 98.8 37.4 Grattan Elementary School 394 14.6 45.0 26.9 Jean Parker Elementary School 278 92.8 98.7 57.0 206 Lafayette Elementary School 543 36.8 68.3 35.0 Leonard Flynn Elementary School 456 71.9 11.6 33.5 Longfellow Elementary School 588 81.3 99.3 38.4 Marshall Elementary School 263 75.3 94.6 49.8 Monroe Elementary School 511 70.7 95.9 35.4 Rosa Parks Elementary School 422 55.0 83.9 26.0 Sherman Elementary School 397 44.6 68.0 18.6 Spring Valley Elementary School 337 79.6 95.0 32.9 RL Stevenson Elementary School 465 57.6 96.8 17.0 Sunnyside Elementary School 385 40.8 58.2 12.3 Sunset Elementary School 402 29.2 74.0 25.2
207 WalkSafe Program
Estimated Enrollment FRPM Non-White School name Walk Trips to (2014-2015) Eligible (%) (%) School (%)
Arcola Lake Elementary School 506 96.8 98.2 43.0 Charles R. Drew K-8 Center 448 94.9 100.0 58.0 Coral Terrace Elementary School 463 94.2 98.3 -- Dr. Henry W. Mack/West Little River K-8 507 96.4 99.0 24.0 Earlington Heights Elementary School 458 98.9 100.0 45.0 Eugenia B. Thomas K-8 Center 1627 39.8 94.6 19.0 Fulford Elementary School 526 93.9 98.7 21.0 Gratigny Elementary School 683 92.1 98.0 19.0 Henry M. Flagler Elementary School 795 88.2 98.9 5.0 Jesse J. McCrary Elementary School 643 95.6 98.6 35.0 Kelsey Pharr Elementary School 295 96.9 97.6 14.0 Liberty City Elementary School 432 97.2 99.8 26.0 Lillie C. Evans K-8 Center 456 99.1 99.8 31.0 Miami Shores Elementary School 799 73.3 88.9 7.0 North Miami Elementary School 558 93.7 99.5 41.0 Olinda Elementary School 428 94.2 98.6 42.0 Orchard Villa Elementary School 418 97.6 99.5 40.0 Paul Laurence Dunbar K-8 Center 376 97.1 98.4 23.0 Southside Elementary School 841 64.0 88.6 16.0
208 Toussaint L' Ouverture Elementary School 434 94.0 98.6 40.0 W. J. Bryan Elementary School 730 96.0 96.6 25.0 West Homestead K-8 Center 778 99.1 97.4 29.0
209 Columbus Safe Routes Program Estimated Enrollment FRPM Eligible Non-White School name Walk Trips to (2014-2015) (%) (%) School (%) Alpine Elementary School 539 81.1 77.4 6.0 Avondale Elementary School 311 100.0 43.4 68.2 Binns Elementary School 330 95.5 38.5 6.0 Cedarwood Alternative Elementary School 406 98.5 51.0 11.0 Clinton Elementary School 430 23.5 17.4 14.0 Como Elementary School 342 100.0 56.4 13.0 Devonshire Alternative Elementary School 498 87.8 79.3 11.0 Eakin Elementary School 336 100.0 87.8 75.3 Easthaven Elementary School 440 100.0 97.3 12.0 Gables Elementary School 414 40.1 58.2 3.0 Georgian Heights Alternative Elementary School 530 73.6 42.5 7.0 Huy Elementary School 444 100.0 64.2 17.0 Indian Springs Elementary School 417 51.1 35.5 6.0 Lincoln Park Elementary School 377 96.8 55.4 -- Lindbergh Elementary School 235 100.0 31.5 12.0 Livingston Elementary School 472 98.3 93.2 9.9 Maize Elementary School 314 85.7 66.6 6.0 North Linden Elementary School 447 100.0 81.0 5.0 Ohio Avenue Elementary School 316 100.0 95.6 23.0 Parsons Elementary School 471 100.0 23.6 3.0 Salem Elementary School 370 100.0 80.0 5.0 Scottwood Elementary School 475 100.0 93.7 17.0
210 Southwood Elementary School 362 97.5 39.0 16.0 Starling PreK-8 Center 627 0.0 34.3 16.6 Valley Forge Elementary School 296 100.0 85.5 8.0 Watkins Elementary School 367 100.0 80.4 17.0 West Broad Elementary School 518 94.6 45.0 33.0 West Mound Elementary School 480 97.9 43.3 17.0 Westgate Alternative Elementary School 329 100.0 25.5 15.0 Windsor STEM Academy 503 100.0 96.0 15.7 Winterset Elementary School 299 56.2 44.5 9.0
211 Appendix C. Safe Routes to School Parent Survey
212
213 Appendix D. Geoprocessing Technique Flow Process
214
214 Appendix E. Summary of Descriptive Statistics of Variables for SFSRTS Parent Surveys (%)
Perceived Barriers to Walking to School School (surveys included) English Grades Gender Walk Distance Speed Volume Sidewalks Inter- Violence Language K-3 (female) to sections School Alamo Elementary School (484) 94.2 79.1 54.7 61.5 30.0 30.8 30.4 12.6 42.1 24.6 Alvarado Elementary School (213) 92.0 66.7 53.5 50.7 43.7 26.3 31.0 17.4 42.3 21.1 Argonne Elementary School (92) 96.7 89.1 51.1 54.1 25.0 29.3 22.8 6.5 40.2 20.7 Bessie Carmichael Elementary School (99) 96.0 78.8 50.5 70.8 28.3 33.3 32.3 19.2 44.4 41.4 Bryant Elementary School (45) 77.8 77.8 46.7 68.2 53.3 68.9 51.1 28.9 60.0 71.1 Buena Vista/Horace Mann K-8 Center (41) 56.1 82.9 58.5 50.0 36.6 36.6 41.5 34.1 43.9 39.0 Chinese Immersion School at De Avila (32) 100.0 50.0 59.4 25.0 31.3 40.6 53.1 21.9 53.1 25.0 Cleveland Elementary School (89) 43.8 91.0 55.7 56.8 15.7 14.6 14.6 7.9 37.1 30.3 Commodore Sloat Elementary School (73) 98.6 82.2 53.4 20.0 34.2 46.6 47.9 15.1 56.2 30.1 Dianne Feinstein Elementary School (124) 100.0 76.6 51.6 39.3 25.0 29.8 27.4 9.7 45.2 21.8 El Dorado Elementary School (42) 83.3 52.4 50.0 32.4 33.3 23.8 14.3 19.0 35.7 35.7 ER Taylor Elementary School (261) 37.2 74.3 50.0 55.6 28.4 20.7 18.8 11.5 34.5 29.9 Fairmount Elementary School (82) 98.8 64.6 47.6 45.9 23.2 35.4 37.8 13.4 47.6 22.0 George Peabody School (240) 98.8 70.8 45.6 47.0 21.7 23.8 22.5 9.6 32.5 10.4 G. W. Carver Elementary School (52) 100.0 80.8 44.2 48.9 17.3 38.5 11.5 3.8 28.8 42.3 Glen Park Elementary School (50) 88.0 86.0 62.0 51.2 36.0 20.0 30.0 16.0 46.0 16.0 Gordon J Lau Elementary School (60) 95.0 60.0 46.7 71.7 36.7 38.3 38.3 18.3 43.3 35.0 Grattan Elementary School (367) 100.0 78.2 53.1 67.1 26.2 23.2 25.9 13.4 34.9 15.5 Jean Parker Elementary School (63) 57.1 60.3 55.6 76.3 30.2 36.5 27.0 11.1 46.0 33.3 Lafayette Elementary School (113) 99.1 72.6 50.4 55.8 27.4 31.0 32.7 13.3 47.8 31.9 Leonard Flynn Elementary School (175) 65.1 78.9 50.9 58.6 23.4 27.4 26.3 12.0 30.3 21.7 Longfellow Elementary School (288) 64.9 76.0 51.7 60.5 27.1 30.9 26.4 14.6 42.7 31.6 Marshall Elementary School (63) 36.5 69.8 43.5 62.7 17.5 34.9 39.7 14.3 46.0 49.2 Monroe Elementary School (125) 44.8 76.8 56.5 56.8 20.0 29.6 27.2 12.0 50.4 29.6 Rosa Parks Elementary School (70) 97.1 77.1 48.5 63.1 35.7 22.9 25.7 20.0 48.6 41.4 Sherman Elementary School (112) 99.1 75.9 48.6 45.8 33.9 33.0 34.8 14.3 42.0 28.6 215 Spring Valley Elementary School (111) 52.3 81.1 54.1 47.5 29.7 36.0 29.7 13.5 35.1 31.5 Stevenson Elementary School (67) 85.1 80.6 49.3 33.3 29.9 35.8 32.8 10.4 58.2 35.8 Sunnyside Elementary School (152) 98.0 78.9 48.7 44.5 32.2 28.3 24.3 13.2 38.2 15.1 Sunset Elementary School (506) 100.0 74.7 53.3 36.1 24.9 26.1 24.5 9.9 37.5 26.9
216 Appendix F. Summary of Descriptive Statistics of Variables for WalkSafe Program Parent Surveys (%)
Perceived Barriers to Walking to School School (surveys included) English Grades Gender Walk Distance Speed Volume Sidewalks Inter- Violence Language K-3 (female) to sections School Arcola Lake Elementary School (41) 87.8 39.5 58.5 35.9 22.0 14.6 19.5 7.3 12.2 29.3 Charles R. Drew K-8 Center (33) 100 81.8 48.5 64.5 24.2 24.2 21.2 6.1 21.2 30.3 Coral Terrace Elementary School (96) 33.3 32.6 52.1 8.7 21.9 46.9 49.0 15.6 33.3 40.6 Earlington Heights Elementary School (123) 92.7 58.8 55.7 45.9 22.0 24.4 21.1 8.9 19.5 30.9 Eugenia B. Thomas Elementary School (1544) 89.7 56.4 49.1 24.3 29.4 37.2 38.3 17.9 36.9 32.6 Fulford Elementary School (47) 80.9 60.5 66.0 30.2 14.9 36.2 29.8 10.6 42.6 48.9 Gratigny Elementary School (134) 92.5 24.8 57.1 19.4 21.6 31.3 29.1 9.7 25.4 34.3 Henry M. Flagler Elementary School (556) 87.4 64.1 55.0 8.1 28.4 57.9 59.0 12.9 44.8 61.2 Jesse J. McCrary Elementary School (35) 91.4 51.4 37.1 23.3 17.1 20.0 22.9 5.7 31.4 28.6 Kelsey Pharr Elementary School (31) 74.2 70.4 61.3 33.3 35.5 35.5 25.8 19.4 32.3 41.9 Liberty City Elementary School (44) 97.7 73.7 45.5 43.2 27.3 20.5 20.5 25.0 18.2 34.1 Lillie C. Evans K-8 Center (71) 95.8 55.2 49.3 37.1 16.9 19.7 18.3 8.5 22.5 35.2 Miami Shores Elementary School (220) 97.7 44.6 56.1 5.6 28.2 46.8 45.0 16.8 44.5 53.6 North Miami Elementary School (67) 100 57.7 52.3 35.9 19.4 49.3 41.8 7.5 34.3 46.3 Olinda Elementary School (41) 100 54.3 48.8 36.1 17.1 7.3 12.2 7.3 9.8 34.1 Orchard Villa Elementary School (84) 100 70.8 54.8 51.9 15.5 14.3 9.5 8.3 15.5 29.8 Paul L. Dunbar Elementary School (49) 89.8 36.2 54.2 50.0 22.4 30.6 18.4 14.3 20.4 26.5 Southside Elementary School (190) 75.3 75.3 52.9 26.9 18.9 45.3 44.7 16.3 45.8 45.8 Toussaint L’Ouverture Elementary School (68) 100 60.0 64.8 53.8 30.9 39.7 26.5 13.2 32.4 36.8 West Homestead Elementary School (43) 90.7 81.0 41.9 40.0 34.9 25.6 25.6 23.3 34.9 37.2 Dr. Henry Mack/ 96.0 West Little River K-8 Center (124) 78.1 48.4 30.7 29.0 32.3 22.6 12.1 24.2 37.1 W. J. Bryan Elementary School (98) 98.0 63.8 48.9 20.4 29.6 51.0 41.8 20.4 42.9 52.0
217 Appendix G. Summary of Descriptive Statistics of Variables for Columbus SRTS Program Parent Surveys (%)
Perceived Barriers to Walking to School School (surveys included) Grades Gender Walk Distance Speed Volume Sidewalks Inter- Violence K-3 (female) sections Alpine Elementary School (121) 63.6 56.2 5.0 50.0 39.7 38.0 27.3 45.5 46.3 Avondale Elementary School (58) 72.4 50.0 46.6 37.0 24.1 22.4 19.0 32.8 41.4 Binns Elementary School (81) 76.5 51.9 8.6 44.4 42.0 44.4 43.2 42.0 45.7 Cedarwood Elementary School (84) 70.2 58.3 29.8 39.9 35.7 28.6 22.6 39.3 36.9 Clinton Elementary School (178) 82.6 49.4 32.6 36.2 37.6 39.9 25.3 43.3 16.9 Colerain Elementary School (58) 86.2 37.9 17.2 70.2 36.2 41.4 44.8 39.7 13.8 Como Elementary School (116) 66.4 56.9 10.3 56.1 36.2 44.8 34.5 37.1 39.7 Devonshire Alternative Elementary School (127) 74.0 55.1 16.5 17.8 40.9 34.6 18.9 37.8 32.3 Eakin Elementary School (101) 65.3 46.5 40.6 46.9 19.8 15.8 11.9 23.8 30.7 East Columbus Elementary School (32) 62.5 59.4 15.6 37.8 50.0 43.8 50.0 46.9 56.3 East Linden Elementary School (45) 51.1 55.6 20.0 42.9 35.6 33.3 28.9 37.8 42.2 Easthaven Elementary School (63) 54.0 55.6 12.7 75.4 33.3 30.2 15.9 28.6 42.9 Ecole Kenwood Alternative Elementary School (57) 75.4 61.4 1.8 43.8 57.9 59.6 45.6 54.4 36.8 Fairmoor Elementary School (64) 48.4 51.6 28.1 25.8 32.8 28.1 25.0 39.1 51.6 Fairwood Alternative Elementary School (31) 54.8 51.6 16.1 51.0 29.0 29.0 12.9 35.5 35.5 Forest Park Elementary School (51) 60.8 54.9 2.0 39.3 45.1 43.1 19.6 51.0 54.9 Gables Elementary School (84) 67.9 63.1 7.1 38.4 40.5 39.3 38.1 47.6 21.4 Georgian Heights Alternative Elementary School (73) 76.7 52.1 13.7 16.7 28.8 30.1 16.4 34.2 34.2 Hamilton STEM Academy (30) 46.7 63.3 43.3 33.3 36.7 33.3 13.3 26.7 36.7 Highland Elementary School (30) 70.0 60.0 33.3 32.7 46.7 30.0 33.3 46.7 46.7 Huy Elementary School (55) 70.9 58.2 20.0 51.2 27.3 29.1 25.5 38.2 45.5 Indian Springs Elementary School (86) 89.5 52.3 9.3 60.0 53.5 47.7 45.3 47.7 20.9 Indianola Informal Alternative School (115) 63.5 58.3 20.0 32.4 37.4 42.6 31.3 44.3 27.8 Innis Elementary School (37) 70.3 43.2 16.2 50.0 29.7 29.7 29.7 35.1 24.3 Leawood Elementary School (38) 65.8 63.2 34.2 45.5 26.3 28.9 13.2 34.2 39.5 Lincoln Park Elementary School (49) 54.5 54.5 0.0 36.7 72.7 81.8 45.5 72.7 63.6 218 Lindbergh Elementary School (54) 77.6 53.1 32.7 40.7 22.4 28.6 16.3 38.8 49.0 Linden Elementary School (36) 57.4 53.7 1.9 47.2 38.9 37.0 31.5 33.3 40.7 Livingston Elementary School (63) 66.7 50.0 13.9 49.2 52.8 47.2 38.9 58.3 72.2 Maize Elementary School (111) 77.8 58.7 22.2 49.5 30.2 30.2 15.9 28.6 38.1 North Linden Elementary School (57) 69.4 52.3 2.7 40.4 41.4 42.3 32.4 42.3 44.1 Oakland Park Elementary School (56) 75.4 54.4 0.0 51.8 22.8 26.3 28.1 29.8 43.9 Ohio Avenue Elementary School (68) 67.9 48.2 0.0 39.1 33.9 39.3 39.3 39.3 42.9 Parkmoor Elementary School (39) 82.6 34.8 4.3 25.0 34.8 39.1 30.4 34.8 34.8 Parsons Elementary School (159) 64.7 60.3 27.9 46.2 32.4 20.6 11.8 32.4 39.7 Salem Elementary School (166) 82.1 64.1 12.8 43.4 48.7 43.6 15.4 48.7 61.5 Scottwood Elementary School (97) 78.6 55.3 3.1 54.2 48.4 45.9 36.5 42.8 38.4 Shady Lane Elementary School (68) 71.1 62.7 6.0 39.2 41.0 32.5 25.3 45.8 49.4 Siebert Elementary School (80) 58.8 59.8 19.6 42.6 40.2 38.1 20.6 34.0 41.2 Southwood Elementary School At Reeb (106) 75.0 54.4 8.8 45.0 29.4 33.8 23.5 27.9 25.0 Starling PreK-8 Center (137) 68.8 61.3 10.0 43.4 38.8 38.8 18.8 40.0 36.3 Stewart Alternative Elementary School (51) 76.4 56.6 17.0 21.9 31.1 29.2 15.1 35.8 61.3 Trevitt Elementary School (32) 60.6 51.1 29.9 64.7 36.5 37.2 18.2 37.2 42.3 Valley Forge Elementary School (59) 64.7 54.9 0.0 15.6 35.3 37.3 23.5 39.2 49.0 Valleyview Elementary School (34) 62.5 46.9 43.8 45.8 25.0 12.5 15.6 25.0 37.5 Watkins Elementary School (120) 71.2 69.5 6.8 29.4 35.6 33.9 18.6 49.2 45.8 West Broad Elementary School (55) 70.6 58.8 14.7 38.3 32.4 44.1 47.1 58.8 35.3 West Mound Elementary School (104) 63.3 48.3 13.3 25.5 48.3 45.0 40.0 43.3 53.3 Westgate Elementary School (103) 69.1 50.9 20.0 31.7 32.7 38.2 9.1 32.7 50.9 Windsor STEM Academy (84) 77.9 55.8 20.2 35.0 46.2 46.2 27.9 38.5 51.0 Winterset Elementary School (106) 62.1 54.4 13.6 16.7 43.7 45.6 42.7 43.7 49.5 Woodcrest Elementary School (55) 69.0 54.8 19.0 50.0 19.0 21.4 11.9 16.7 31.0
219 Appendix H. Grade Level Distribution of SRTS Parent Survey Responses
25.0%
20.0%
15.0%
10.0%
5.0%
0.0% K 1st 2nd 3rd 4th 5th
SFSRTS WalkSafe CSRTS
Chart data n K 1st 2nd 3rd 4th 5th 1,008 759 741 743 558 479 SFSRTS 4,291 (23.5) (17.7) (17.3) (17.3) (13.0) (11.2) 486 560 584 600 723 562 WalkSafe 3,739 (13.8) (15.9) (16.6) (17.1) (20.6) (16.0) 325 290 353 296 236 162 CSRTS 1,745 (19.6) (17.4) (21.2) (17.8) (14.2) (9.7)
220 Appendix I. List of Websites Searched for Policy Scan Source Reference URL PTA National PTA http://www.pta.org/ State PTA California PTA http://capta.org/ Florida PTA https://floridapta.org/ Ohio PTA http://www.ohiopta.org/ Regional PTA San Francisco http://www.sfpta.org/ Miami-Dade County http://www.dccptaptsa.org/ District 10, Ohio No website for the district PTA Federal Government Department of Education https://www.ed.gov/ Department of Transportation www.transportation.gov National Highway Traffic Safety Administration https://www.nhtsa.gov/ Federal Highway Administration https://www.fhwa.dot.gov/ State Government Department of Education California http://www.cde.ca.gov/ Florida http://www.fldoe.org/ Ohio http://education.ohio.gov/ Department of Transportation California http://www.dot.ca.gov/ Florida http://www.fdot.gov/ Ohio http://www.dot.state.oh.us/pages/home.aspx Regional Government and Agencies San Francisco Bay Area, California Metropolitan Transportation Commission http://mtc.ca.gov/ Bay Area Transportation http://generalplan.sfplanning.org/ Miami-Dade County, Florida Miami-Dade County http://miamidade.gov/ Metropolitan Transportation Organization http://www.miamidadetpo.org/ Franklin County, Ohio Franklin County https://www.franklincountyohio.gov/ Mid-Ohio Regional Planning Council http://www.morpc.org/ City Government California San Francisco http://generalplan.sfplanning.org/ Florida Coral Gables http://www.coralgables.com/ Doral https://www.cityofdoral.com/ Florida City http://www.floridacityfl.us/ Hialeah http://www.hialeahfl.gov/index.php?lang=en Hialeah Gardens http://www.cityofhialeahgardens.com/cohg2/ Homestead http://ci.homestead.fl.us/ Key Biscayne http://keybiscayne.fl.gov/ Miami http://www.miamigov.com/planning/# Miami Beach http://www.miamibeachfl.gov/ Miami Gardens https://www.miamigardens-fl.gov/ Miami Shores http://www.miamishoresvillage.com/ North Miami http://www.northmiamifl.gov/ Opa-Locka http://www.opalockafl.gov/ 221 South Miami http://www.southmiamifl.gov/ Ohio Columbus https://www.columbus.gov/ School Districts San Francisco Unified School District http://sfusd.edu/ Miami-Dade County Public Schools http://www.dadeschools.net/ Columbus City Schools http://www.ccsoh.us/ Schools San Francisco Safe Routes to School Alamo Elementary School https://aes-sfusd-ca.schoolloop.com/ Alvarado Elementary School http://alvaradoschool.net/ Argonne Elementary School https://argonnesf.org/ Bessie Carmichael Elementary School https://fec-sfusd-ca.schoolloop.com/ Bret Harte Elementary School https://bhes-sfusd-ca.schoolloop.com/ Bryant Elementary School https://bryant-sfusd-ca.schoolloop.com/ Buena Vista/Horace Mann K-8 Center http://www.wearebvhm.com/ Cesar Chavez Elementary School https://cces-sfusd-ca.schoolloop.com/ Chinese Immersion School at De Avila https://wdaes-sfusd-ca.schoolloop.com/ Cleveland Elementary School https://cleveland-sfusd-ca.schoolloop.com/ Commodore Sloat Elementary School http://commodoresloat.com/ Dianne Feinstein Elementary School https://dfes-sfusd-ca.schoolloop.com/ El Dorado Elementary School https://edes-sfusd-ca.schoolloop.com/ ER Taylor Elementary School https://ertes-sfusd-ca.schoolloop.com/ Fairmount Elementary School http://www.wearefairmount.com/ Garfield Elementary School http://www.garfieldelementarysf.org/ George Peabody Elementary School http://peabodyschool.com/ George Washington Carver Elementary School https://carver-sfusd-ca.schoolloop.com/ Glen Park Elementary School https://gpes-sfusd-ca.schoolloop.com/ Gordon J Lau Elementary School https://gjles-sfusd-ca.schoolloop.com/ Grattan Elementary School http://www.grattanschool.org/ Jean Parker Elementary School https://jpes-sfusd-ca.schoolloop.com/ Jefferson Elementary School https://jefferson-sfusd-ca.schoolloop.com/ John Yehall Chin Elementary School https://chin-sfusd-ca.schoolloop.com/ Lafayette Elementary School http://lafayettedolphins.net/ Lawton Elementary School https://lawton-sfusd-ca.schoolloop.com/ Leonard Flynn Elementary School https://leonard-sfusd-ca.schoolloop.com/ Longfellow Elementary School https://longfellow-sfusd-ca.schoolloop.com/ Marshall Elementary School https://marshall-sfusd-ca.schoolloop.com/ Monroe Elementary School https://monroe-sfusd-ca.schoolloop.com/ Paul Revere Elementary School http://www.paulreveresf.org/ Rosa Parks Elementary School https://rosaparks-sfusd-ca.schoolloop.com/ Sherman Elementary School http://shermanschool.org/ Spring Valley Elementary School https://springvalley-sfusd-ca.schoolloop.com/ Stevenson Elementary School https://stevenson-sfusd-ca.schoolloop.com/ Sunnyside Elementary School http://www.sunnysidek5.org/ Sunset Elementary School https://sunset-sfusd-ca.schoolloop.com/ Ulloa Elementary School https://ulloa-sfusd-ca.schoolloop.com/ WalkSafe Program Amelia Earhart Elementary School http://aearhart.dadeschools.net/ Arcola Lake Elementary School http://arcolalake.dadeschools.net/ Auburndale Elementary School http://auburndale.dadeschools.net/ Avacado Elementary School http://avocado.dadeschools.net/ Barbara Hawkins Elementary School http://bjh.dadeschools.net/ 222 Benjamin Franklin K-8 Center http://benfranklink8.dadeschools.net/ Biscayne Gardens Elementary School http://bge.dadeschools.net/ Bob Graham Education Center (K-8) http://bgec.dadeschools.net/ Caribbean Elementary School http://caribbean.dadeschools.net/ Charles R. Drew Elementary School http://drew.dadeschools.net/ Charles R. Hadley Elementary School http://crhadley.dadeschools.net/ Citrus Grove Elementary School http://citrusgroveelementary.com/ Coral Terrace Elementary School http://cte.dadeschools.net/ Dante B. Fascell Elemetnary School http://dbfe.dadeschools.net/ Dr. Robert B. Ingram Elementary School http://drrbi.dadeschools.net/ Dr. William A. Chapman Elementary School http://www.drwachapman.org/ Earlington Heights Elementary School http://earlingtonheightselem.dadeschools.net/ Edison Park K-8 Center http://edisonpark.dadeschools.net/ Eneida M. Hartner Elementary School http://eneidamhartner.org/ Eugenia B. Thomas Elementary School http://ebt.dadeschools.net/ Flamingo Elementary School http://flamingo.dadeschools.net/ Frances S. Tucker Elementary School http://www.tuckereagles.org/ Fulford Elementary School http://fulford.dadeschools.net/ Golden Glades Elementary School http://goldenglades.wixsite.com/goldenglades Gratigny Elementary School http://gratignyelementary.net/ Gulfstream Elementary School* http://gulfstreamelm.dadeschools.net/ Henry E. S. Reeves Elementary School http://henryreeves.dadeschools.net/ Henry M. Flagler Elementary School http://hmf.dadeschools.net/ Holmes Elementary School http://www.holmeselementary.org/ Irving and Beatrice Peskoe K-8 Center http://peskoe.dadeschools.net/ Jesse J. McCrary Elementary School http://jmccrary.dadeschools.net/ Joella C. Good Elementary School http://www.joellacgood.org/ Kelsey Pharr Elementary School http://kelseypharr.dadeschools.net/ Kensington Park Elementary School http://kpe.dadeschools.net/ Lake Stevens Elementary School http://lstevens.dadeschools.net/ Laura C. Saunders Elementary School http://lcsaunders.dadeschools.net/ Leisure City K-8 Center http://lck8.org/ Lenora B. Smith Elementary School http://lbs.dadeschools.net/ Liberty City Elementary School http://libertycitye.dadeschools.net/ Lillie C. Evans Elementary School http://lcevans.dadeschools.net/ Linda Lentin K-8 Center http://llk-8.dadeschools.net/ Ludlam Elementary School http://ludlam.dadeschools.net/ Mae M. Walters Elementary School http://mwalters.dadeschools.net/ Melrose Elementary School http://melrose.dadeschools.net/ Miami Gardens Elementary School http://miamigardenselem.org/ Miami Lakes K-8 Center http://mles.dadeschools.net/ Miami Park Elementary School http://miamipark.dadeschools.net/ Miami Shores Elementary School http://www.miamishoreselementary.net/ Morningside Elementary School http://morningside.dadeschools.net/ Myrtle Grove K-8 Center http://mgrove.dadeschools.net/ Nathan B. Young Elementary School http://nbyoung.dadeschools.net/ Natural Bridge Elementary School http://nbe.dadeschools.net/ North Hialeah Elementary School http://nhes.dadeschools.net/ North Miami Elementary School http://nmiamielem.dadeschools.net/ Norwood Elementary School http://norwood.dadeschools.net/ Oak Grove Elementary School http://oakgrovelementary.dadeschools.net/ Olinda Elementary School http://olinda.dadeschools.net/ Orchard Villa Elementary School 223 Paul L. Dunbar Elementary School http://orchardvillaelementaryschool.dadeschools. Phillis Wheatley Elementary School net/ Phyllis Ruth Miller Elementary School http://dunbar.dadeschools.net/ Pine Villa Elementary School http://pwes.dadeschools.net/ Rainbow Park Elementary School http://phyllisruthmiller.weebly.com/ Riverside Elementary School http://pinevilla.dadeschools.net/ Santa Clara Elementary School http://rainbowpark.dadeschools.net/ Scott Lake Elementary School http://www.riversideelem.com/ South Miami Heights Elementary School http://www.santaclaraes.org/ South Pointe Elementary School http://scottlakevikings.org/ Southside Elementary School http://smhe.dadeschools.net/ Toussaint L'Ouverture Elementary School http://www.southpointedolphins.org/ Van E. Blanton Elementary School http://southside.dadeschools.net/ W. J. Bryan Elementary School http://toussaint.dadeschools.net/ West Homestead Elementary School http://vblanton.dadeschools.net/ West Little River/Dr. Henry Mack Elementary School http://wjbryan.dadeschools.net/ Columbus Safe Routes http://www.whk8dadeschools.net/ Africentric Early College Elementary School http://wlre.dadeschools.net/ Alpine Elementary School Avalon Elementary School Avondale Elementary School http://africentricearlycollege.ccsoh.us/ Beaty Park Elementary School http://alpinees.ccsoh.us/ Berwick Alternative Elementary School http://www.ccsoh.us/AvalonES Binns Elementary School http://www.ccsoh.us/AvondaleES Broadleigh Elementary School http://www.ccsoh.us/BeattyParkES Burroughs Elementary School http://www.ccsoh.us/BerwickES Cassady Elementary School http://www.ccsoh.us/BinnsES Cedarwood Elementary School http://www.ccsoh.us/BroadleighES Clinton Elementary School http://www.ccsoh.us/BurroughsES Colerain Elementary School http://www.ccsoh.us/CassadyAlternativeES Columbus Spanish Immersion Elementary School http://www.ccsoh.us/CedarwoodalternativeES Como Elementary School http://www.ccsoh.us/ClintonES Cranbrook Elementary School http://www.ccsoh.us/ColerainES Devonshire Elementary School http://www.ccsoh.us/ColumbusSpanishImmersion Duxberry Park Elementary http://www.ccsoh.us/ComoES Eakin Elementary School http://www.ccsoh.us/CranbrookES East Columbus Elementary School http://www.ccsoh.us/DevonshireAlternativeES East Linden Elementary School http://www.ccsoh.us/DuxberryParkAlternativeES Eastgate Elementary School http://www.ccsoh.us/EakinES Easthaven Elementary School http://www.ccsoh.us/EastColumbusES Ecole Kenwood Alternative Elementary School http://www.ccsoh.us/EastLindenES Fairmoor Elementary School http://www.ccsoh.us/EastgateES Fairwood Alternative Elementary School http://www.ccsoh.us/EasthavenES Forest Park Elementary School http://www.ccsoh.us/EcoleKenwoodES Gables Elementary School http://www.ccsoh.us/FairmoorES Georgian Heights Elementary School http://www.ccsoh.us/FairwoodAlternativeES Hamilton Elementary School http://www.ccsoh.us/ForestParkES Highland Elementary School http://www.ccsoh.us/GablesES Huy Elementary School http://www.ccsoh.us/GeorgianHeightsAlternative Indian Springs Elementary School ES Indianola Informal Alternative School (K-8) http://www.ccsoh.us/HamiltonSTEMAcademy Innis Elementary School http://www.ccsoh.us/HighlandES Leawood Elementary School http://www.ccsoh.us/HuyES 224 Liberty Elementary School http://www.ccsoh.us/IndianSpringsES Lincoln Park Elementary School http://www.ccsoh.us/IndianolaInformalES Lindbergh Elementary School http://www.ccsoh.us/InnisES Linden Elementary School http://www.ccsoh.us/LeawoodES Livingston Elementary School http://www.ccsoh.us/LibertyES Maize Elementary School http://www.ccsoh.us/LincolnParkES Moler Elementary School http://www.ccsoh.us/LindberghES North Linden Elementary School http://www.ccsoh.us/LindenSTEMAcademy Northtowne Elementary School http://www.ccsoh.us/LivingstonES Oakland Park Elementary School http://www.ccsoh.us/MaizeES Oakmont Elementary School http://www.ccsoh.us/MolerES Ohio Avenue Elementary School http://www.ccsoh.us/NorthLindenES Olde Orchard Alternative Elementary School http://www.ccsoh.us/NorthtowneES Parkmoor Elementary School http://www.ccsoh.us/OaklandParkAlternativeES Parsons Elementary School http://www.ccsoh.us/OakmontES Salem Elementary School http://www.ccsoh.us/OhioAvenueES Scottwood Elementary School http://www.ccsoh.us/OldeOrchardAlternativeES Shady Lane Elementary School http://www.ccsoh.us/ParkmoorES Siebert Elementary School http://www.ccsoh.us/ParsonsES South Mifflin Elementary School http://www.ccsoh.us/SalemES Southwood Elementary School at Reeb http://www.ccsoh.us/ScottwoodES Starling K-8 http://www.ccsoh.us/ShadyLaneES Stewart Alternative Elementary School http://www.ccsoh.us/SiebertES Sullivant Elementary School http://www.ccsoh.us/SouthMifflinSTEMAcadem Trevitt Elementary School y Valley Forge Elementary School http://www.ccsoh.us/SouthwoodES Valleyview Elementary School http://starlingms.ccsoh.us/Default.aspx Watkins Elementary School http://www.ccsoh.us/StewartAlternativeES Weinland Park Elementary School http://www.ccsoh.us/SullivantES West Broad Elementary School http://www.ccsoh.us/TrevittES West Mound Elementary School http://www.ccsoh.us/ValleyForgeES Westgate Elementary School http://www.ccsoh.us/ValleyviewES Windsor Elementary School http://www.ccsoh.us/WatkinsES Winterset Elementary School http://www.ccsoh.us/WeinlandParkES Woodcrest Elementary School http://www.ccsoh.us/WestBroadES http://www.ccsoh.us/WestMoundES http://www.ccsoh.us/WestgateAlternativeES http://www.ccsoh.us/WindsorSTEMAcademy http://www.ccsoh.us/WintersetES http://www.ccsoh.us/WoodcrestES Other sites National Association of State Boards of Education http://www.nasbe.org/healthy_schools/hs The Centers for Disease Control and Prevention https://www.cdc.gov/healthyschools/npao/strategi es.htm
225 Appendix J. Inventory of Federal Policies
Policy Title Year Type Reference
Intermodal Surface Transportation Efficiency Act 1991 Legislation https://www.fhwa.dot.gov/planning/public_invo
of 1991 lvement/archive/legislation/istea.cfm Flexibility in Highway Design 2001 Regulation https://www.fhwa.dot.gov/environment/publicat
ions/flexibility/flexibility.pdf Safe, Accountable, Flexible, Efficient 2005 Legislation https://www.fhwa.dot.gov/safetealu/ Transportation Equity Act: A Legacy for Users Highway Safety Program Guideline No. 14 2006 Regulation https://one.nhtsa.gov/nhtsa/whatsup/tea21/tea21
Pedestrian and Bicycle Safety programs/pages/PedBikeSafety.htm National School Transportation Specifications and 2010 Regulation http://www.nasdpts.org/ncstonline/Documents/
Procedures NST2010Pubwithlinks_000.pdf United States Department of Transportation Policy 2010 Agency action https://www.fhwa.dot.gov/environment/bicycle_
Statement on Bicycle and Pedestrian pedestrian/guidance/policy_accom.cfm Accommodation Regulations and Recommendations Moving Ahead for Progress in the 21st Century 2012 Legislation https://www.fhwa.dot.gov/map21/ Act Safer People, Safer Streets: Summary of US 2014 Agency Action https://www.transportation.gov/sites/dot.gov/file Department of Transportation Action Plan to s/docs/safer_people_safer_streets_summary_doc Increase Walking and Biking and Reduce _acc_v1-11-9.pdf Pedestrian and Bicyclist Fatalities
Flexibility in Highway Design 2015 Legislation https://www.fhwa.dot.gov/fastact/
226 Final Rule: Local School Wellness Policy 2016 Legislation https://www.gpo.gov/fdsys/pkg/FR-2016-07- Implementation Under the Healthy Hunger-Free 29/pdf/2016-17230.pdf Kids Act of 2010 Healthy Students, Promising Futures: State and 2016 Regulation https://www2.ed.gov/admins/lead/safety/healthy
Local Action Steps and Practices to Improve -students/toolkit.pdf School-Based Health Strategic Agenda for Pedestrian and Bicycle 2016 Agency Action https://www.fhwa.dot.gov/environment/bicycle_
Transportation pedestrian/publications/strategic_agenda/ Policy Statement to Support the Alignment of 2017 Agency action https://www2.ed.gov/about/inits/ed/earlylearnin
Health and Early Learning Systems g/files/health-early-learning-statement.pdf
227 Appendix K. Inventory of State Policies
California, San Francisco Safe Routes to School Program Policy Title Year Type Reference
California Transportation Plan 2040 2016 Regulation http://www.dot.ca.gov/hq/tpp/californiatrans
portationplan2040/
Complete Streets Implementation Action Plan 2.0 2014-2017 Agency Action http://www.dot.ca.gov/hq/tpp/offices/ocp/do
cs/CSIAP2_rpt.pdf
Senate Bill No 99; Chapter 359_Active Transportation 2013 Legislation http://www.catc.ca.gov/programs/ATP/SB_9 Program 9_2013.pdf
Complete Streets-Integrating the Transportation 2014 Legislation http://www.dot.ca.gov/hq/tpp/offices/ocp/do
System (DD-64-R2) cs/dd_64_r2.pdf
Complete Streets Law 2008 Legislation ftp://www.leginfo.ca.gov/pub/07- 08/bill/asm/ab_1351-
1400/ab_1358_bill_20080930_chaptered.pdf Senate Bill No. 391; Chapter 585; California 2009 Legislation http://leginfo.legislature.ca.gov/faces/billNav
Transportation Plan Client.xhtml?bill_id=200920100SB391
228 Senate Bill 168; SEC. 56 Section 2382 of the Streets 2017 Legislation https://leginfo.legislature.ca.gov/faces/billNa
and Highways Code vClient.xhtml?bill_id=201720180SB168
Florida, WalkSafe Program Policy Title Year Type Reference Gabby's Law for Student Safety 2015 Legislation http://www.fldoe.org/core/fileparse.php/7513
/urlt/41-2015.pdf
2017 Highway Safety Plan 2017 Regulation https://www.nhtsa.gov/sites/nhtsa.dot.gov/fil
es/documents/fl_fy17hsp_0.pdf
Best Practices for Pedestrian and Bicycle Safety 2015 Regulation http://www.alerttodayflorida.com/resources/ FBest%20Practices%20for%20Pedestrian%2 0and%20Bicycle%20Safety%20-
%20Website.pdf Florida Pedestrian and Bicycle Strategic Safety Plan 2013 Regulation http://www.fdot.gov/safety/6- Resources/FloridaPedestrianandBicycleStrat
egicSafetyPlan.pdf Ramon Turnquest School Crossing Guard Act 1992 Legislation http://www.leg.state.fl.us/Statutes/index.cfm ?App_mode=Display_Statute&Search_Strin g=&URL=0300-
0399/0316/Sections/0316.75.html
229 Florida School Crossing Guard Training Guidelines 2012 Regulation http://www.fdot.gov/safety/2A- Programs/Bike- Ped/FSCGTGuidelinesMarch2016.pdf 6A-3.0171 Responsibilities of School Districts for 2017 Legislation https://www.flrules.org/gateway/RuleNo.asp
Student Transportation ?ID=6A-3.0171
Required and optional elements of comprehensive 2017 Legislation http://www.leg.state.fl.us/Statutes/index.cfm plan; studies and surveys ?App_mode=Display_Statute&URL=0100-
0199/0163/Sections/0163.3177.html Safe Paths to Schools Program_Title XXVI; Chapter 2002 Legislation https://www.flsenate.gov/Laws/Statutes/2012
335; 335.066 /Chapter335/All
Conserve by Bicycle Program 2006 Legislation http://www.leg.state.fl.us/Statutes/index.cfm/ ch0849/index.cfm?App_mode=Display_Stat ute&Search_String=&URL=0300-
0399/0335/Sections/0335.067.html Ohio, Columbus Safe Routes Program Policy Title Year Type Reference Access Ohio 2040 2014 Regulation http://www.dot.state.oh.us/Divisions/Plannin g/SPR/StatewidePlanning/access.ohio/AO40 _library/ODOTAccessOhio2014.pdf
230 ODOT Active Transportation Guide: A Reference for 2014 Regulation https://www.dot.state.oh.us/Divisions/Planni Communities ng/SPR/bicycle/Documents/Final%20ODOT %20Active%20Transportation%20Plan%20
Guide%2011-24-14.pdf
Statewide Transportation Improvement Program 2017 Regulation https://www.dot.state.oh.us/Divisions/Planni
ng/STIP/Pages/default.aspx
2016-2017 Wellness and Physical Education 2017 Legislation https://education.ohio.gov/getattachment/Top ics/Data/Report-Card- Resources/Sections/District- Details/Technical-Documentation-Wellness-
and-Physical-Education-pdf.pdf.aspx
231 Appendix L. Inventory of Regional Policies
Bay Area, California, San Francisco Safe Routes to School Program Policy Title Year Type Reference
Plan Bay Area 2040 2017 Regulation http://2040.planbayarea.org/ Complete Streets Checklist Guidance 2016 Regulation http://mtc.ca.gov/sites/default/files/Routine
_Accommodation_guidance_FINAL.pdf Miami-Dade County, Florida, WalkSafe Program Policy Title Year Type Reference
Miami-Dade 2040 Bicycle/Pedestrian Plan: Miami-Dade 2014 Regulation http://miamidadetpo.org/library/plans/mia
MPO GPC V #7 mi-dade-2040-bicycle-pedestrian-plan.pdf Complete Streets Resolution 2016 Legislation http://www.miamidade.gov/neatstreets/libr
ary/complete-streets-resolution.pdf Resolution Endorsing the 20th Annual "Walk to School 2016 Legislation http://www.miamidadetpo.org/library/boar Day" Event ds/TPO-Governing-
Board/Resolutions/2016-51-mpo-board.pdf Safer People Safe Streets 2016 Agency Action http://www.miamidade.gov/neatstreets/libr ary/safer-people-safer-streets/local-action-
plan.pdf
232 Mid-Ohio, Ohio, Columbus Safe Routes Program Policy Title Year Type Reference
The 2016-2040 Metropolitan Transportation Plan 2016 Regulation http://www.morpc.org/Assets/MORPC/file s/060216FINAL%20MTP%20REPORT%
20merged.pdf Making Strides: Pedestrian Best Practices 2005 2005 Regulation http://www.morpc.org/trans/PedBestPracti
ces05.pdf 2012-2035 Metropolitan Transportation Plan 2012 Regulation http://www.morpc.org/Assets/MORPC/file s/2012MTP_HighResVersion_Sept2014.pd f 2006 Regional Bicycle Transportation Facilities Plan 2007 Regulation http://www.morpc.org/trans/BikePedRegio
nalBicycleTransportationFacilitiesPlan.pdf MORPC Complete Streets Policy 2010 Legislation http://www.morpc.org/trans/CompleteStree ts_MORPC_CS_PolicyFINAL2010-03-
31.pdf
233 Appendix M. Inventory of Local Policies
City and County of San Francisco, San Francisco Safe Routes to School Program Policy Title Year Policy Type Reference Transportation Element Regulation http://generalplan.sfplanning.org/I4_Trans portation.htm Pedestrian Strategy 2013 Regulation http://archives.sfmta.com/cms/rpedmast/d ocuments/1-29-13PedestrianStrategy.pdf Various Local Municipalities, WalkSafe Program
Policy Title Year Policy Type Reference
2025 Comprehensive Plan: Goals, Objectives, Policies (Village 2013 Regulation http://www.miamishoresvillage.com/villa of Miami Shores) ge-department/planning-and- zoning?sid=59:Comprehensive-Plan-
Documents Miami Bicycle Master Plan 2009 Regulation http://miamigov.com/bicycleInitiatives/do
cs/Final_MBMP.pdf Bicycle/Pedestrian Mobility Plan for the Miami Downtown 2010 Regulation http://www.miamigov.com/bicycleinitiati Development Authority Area ves/docs/bicycle-pedestrian-mobility- plan-for-miami-downtown-2011-03.pdf North Miami Florida EAR-Based Comprehensive Plan 2016 Regulation http://www.northmiamifl.gov/docs/2015_ Amendments EAR- Based_Comprehensive_Plan_Amendment
s.pdf City of North Miami Transportation Master Plan 2005 Regulation http://www.northmiamifl.gov/departments /cpd/files/NMTMPFinal.pdf
234 Sustainable Opa-Locka 2030 Comprehensive Development 2015 Regulation http://www.opalockafl.gov/index.aspx?NI Master Plan D=285 City of South Miami Community Redevelopment Area Plan 1998 Regulation http://www.southmiamifl.gov/DocumentC
enter/View/562%20 (Appendix A) City of South Miami Community Redevelopment Area Phase II 2005 Regulation http://www.southmiamifl.gov/DocumentC
Plan Supplement enter/View/562 City of South Miami Comprehensive Plan 2011 Regulation http://www.southmiamifl.gov/index.aspx? NID=179 Homestead Comprehensive Plan: Goals, Objectives & Policies 2011 Regulation http://local.cityofhomestead.com/media/p
df/comp-plan.pdf Village of Key Biscayne Master Plan 2008 Regulation http://keybiscayne.fl.gov/clientuploads/Bu ilding,%20Zoning%20Planning%20&%2 0Public%20Works/Planning%20Division/ Comprehensive%20Master%20Plan%20- %20EAR/VKB_MasterPlan_1995_Amen ded12-9-08_Corr9-2-10.pdf City of Coral Gables Comprehensive Plan 2010 Regulation http://coralgables.com/modules/showdocu ment.aspx?documentid=11063 City of Doral 2010 Transportation Master Plan 2010 Regulation https://www.cityofdoral.com/all- departments/public-works/master-plan/ City of Hialeah Gardens, Florida 2025 Comprehensive Plan 2007 Regulation http://www.cityofhialeahgardens.com/coh g2/images/stories/file/comprehensive%20
plan%202025.pdf City of Hialeah Gardens 2025 Comprehensive Plan 2011 Regulation http://miamibeachfl.gov/WorkArea/linkit. aspx?LinkIdentifier=id&ItemID=65891&l
ibID=68869 Miami Comprehensive Neighborhood Plan: Goals, Objectives, 2015 Regulation http://www.miamigov.com/planning/com
Policies prehensiveplan.html
235 Overtown-Wynwood Bicycle Pedestrian Mobility Plan 2014 Regulation http://miamidadetpo.org/library/studies/ov ertown-wynwood-bikeped-mobility-plan-
2014-09.pdf South Miami Intermodal Transportation Plan 2015 Regulation http://miamidadetpo.org/library/studies/so uth-miami-intermodal-transportation-
plan-final-report-2015-01.pdf Bicycle and Pedestrian Mobility Plan for the City of Miami 2013 Regulation http://miamidadetpo.org/library/studies/m Gardens iami-gardens-bicycle-and-pedestrian-
mobility-plan-final-2013-04.pdf
City of Miami Gardens Recreational Trails Master Plan 2006 Regulation https://www.miamigardens-
fl.gov/documentcenter/view/165 City of Columbus, Columbus Safe Routes Program Policy Title Year Policy Type Reference Sidewalk and Bikeway Facility Requirements Rules and 2012 Regulation https://www.columbus.gov/uploadedFiles/ Regulations Public_Service/Transportation/Mobility/S idewalk%20and%20Bikeway%20Require ments%20Rules%20and%20Regulations
%20-EFF%2001012012.pdf Columbus Bicentennial Bikeways Plan 2008 Regulation https://www.columbus.gov/publicservice/
bicycle-program/Columbus-Bike-Plan/ Columbus Pedestrian Thoroughfare Plan 2007 Regulation http://www.morpc.org/pdf/CPTP%20Vol
%202%20Report%20Analysis.pdf Connect Columbus Factbook 2016 Agency https://www.columbus.gov/uploadedFiles/ Action Columbus/Departments/Public_Service/T raffic_Management/Multimodal_Thoroug hfare_Plan/Connect%20Columbus%20Fa ct%20Book%20-%20Final%202016-12-
01.pdf 236 Complete Streets Resolution 2008 Legislation http://www.morpc.org/trans/Cbus_comple
te_streets_resolution.pdf The Columbus Green Community Plan: Green Memo III 2015 Agency https://www.columbus.gov/WorkArea/Do
Action wnloadAsset.aspx?id=2147486721
237 Appendix N. Inventory of District Policies
District Policy Title Year Type Reference http://www.sfusd.edu/en/nutrition-school- meals/policies-and-standards/official- San Francisco Unified Wellness Policy 2015 Legislation wellness-policy.html http://nutrition.dadeschools.net/Wellness/We
Miami-Dade County Wellness Policy 2006 Legislation llness_Policy.pdf
Columbus City Schools Comprehensive Wellness Policy 2015 Legislation http://www.neola.com/columbuscity-oh/
238 Appendix O. Inventory of Parent Teacher Association (PTA) Policies
Policy Title Year Type Reference National PTA http://www.pta.org/advocacy/content.cfm?I
Resolution on School Health Councils 2006 Legislation temNumber=1394&navItemNumber=4615 http://www.pta.org/advocacy/content.cfm?I
Resolution on Improved Infrastructure Around Schools 2012 Legislation temNumber=3949&navItemNumber=4615 National PTA Position Statement -- Child Safety and Agency https://www.pta.org/about/content.cfm?Ite
Protection 1998 Action mNumber=986 California PTA http://downloads.capta.org/res/SafeRoutes
Safe Routes to School for All Children 2008 Legislation ToSchoolForAllChildren.pdf Florida PTA https://floridapta.org/wp- Agency content/uploads/2017/01/2016_LEGISLAT
2015/2016 Legislative Priorities 2015 Action IVE_PRIORITIES_1.pdf Ohio PTA http://www.ohiopta.org/Portals/0/Advocac y%20Updates/Ohio%20PTA%202016%20 Agency Legislative%20Priorities%20Pamphlet-
2016 Ohio PTA Legislative Priorities & Position Statements 2016 Action smh.pdf
239 Appendix P. Inventory of Vulnerable Populations Mentioned in Policies
Federal
Safe Routes Vulnerable Populations Mentioned
Children/ Low income/ Pedestrians students Disabilities Minority Disadvantaged Flexibility in Highway Design 1 1 1 1 1
Moving Ahead for Progress in the 21st Century Act 1 1 1 1 1 Safe, Accountable, Flexible, Efficient Transportation Equity Act: A 1 1 1 1 1 Legacy for Users Strategic Agenda for Pedestrian and Bicycle Transportation 1 1 1 1 1 Safer People, Safer Streets: Summary of US Department of Transportation Action Plan to Increase Walking and Biking and Reduce 1 1 0 1 1 Pedestrian and Bicyclist Fatalities Flexibility in Highway Design 1 1 1 0 0 Highway Safety Program Guideline No. 14 Pedestrian and Bicycle 1 1 0 0 1 Safety United States Department of Transportation Policy Statement on Bicycle and Pedestrian Accommodation Regulations and 1 1 1 0 0 Recommendations Healthy Students, Promising Futures: State and Local Action Steps and 0 1 0 0 1 Practices to Improve School-Based Health
Intermodal Surface Transportation Efficiency Act of 1991 1 0 1 0 0 240 Policy Statement to Support the Alignment of Health and Early 0 1 1 0 0 Learning Systems
Final Rule: Local School Wellness Policy Implementation Under the 0 1 0 0 0 Healthy Hunger-Free Kids Act of 2010 National School Transportation Specifications and Procedures 0 0 1 0 0
241 State California, San Francisco Safe Routes to School Program Safe Routes Vulnerable Populations Mentioned Children/ Low income/ Pedestrians students Disabilities Minority Disadvantaged California Transportation Plan 2040 1 1 1 1 1
Complete Streets Implementation Action Plan 2.0 1 1 1 0 1
Complete Streets Law 1 1 1 0 0
Complete Streets-Integrating the Transportation System (DD-64-R2) 1 1 1 0 0
Pedestrian Accessibility Guidelines for Highway Projects 1 1 1 0 0 Senate Bill 168; SEC. 56 Section 2382 of the Streets and Highways 1 1 0 0 1 Code Senate Bill 375; Chapter 728_Transportation planning; travel demand 1 0 1 0 1 models; sustainable communities strategy; environmental review Senate Bill 99; Chapter 359_Active Transportation Program 1 1 0 0 1
Senate Bill No 99; Chapter 359_Active Transportation Program 0 1 1 0 1
Toward an Active California: State Bicycle + Pedestrian Plan 1 1 1 0 0
California Assembly Bill No. 115; Chapter 20 1 1 0 0 0
Senate Bill No. 760 1 0 0 0 1
242 Sustainable Communities and School Planning 0 1 0 0 0
Senate Bill No. 391; Chapter 585; California Transportation Plan 0 0 0 0 0
243 State
Florida, WalkSafe Program Safe Routes Vulnerable Populations Mentioned Children/ Low income/ Pedestrians students Disabilities Minority Disadvantaged 2017 Highway Safety Plan 1 1 0 1 0
Florida Pedestrian and Bicycle Strategic Safety Plan 1 1 0 1 0
Conserve by Bicycle Program 1 1 0 0 0
Florida School Crossing Guard Training Guidelines 1 1 0 0 0
Required and optional elements of comprehensive plan; studies and 1 0 0 0 1 surveys Safe Paths to Schools Program_Title XXVI; Chapter 335; 335.066 1 1 0 0 0 6A-3.0171 Responsibilities of School Districts for Student 0 1 0 0 0 Transportation Best Practices for Pedestrian and Bicycle Safety 1 0 0 0 0
Gabby's Law for Student Safety 0 1 0 0 0
Ramon Turnquest School Crossing Guard Act 0 1 0 0 0
244 State Ohio, Columbus Safe Routes Program Safe Routes Vulnerable Populations Mentioned Children/ Low income/ Pedestrians students Disabilities Minority Disadvantaged
ODOT Active Transportation Guide: A Reference for Communities 1 1 1 1 0
Statewide Transportation Improvement Program 1 0 1 1 1
Access Ohio 2040 1 0 1 0 1
2016-2017 Wellness and Physical Education 0 1 0 0 0
245 Regional Safe Routes Vulnerable Populations Mentioned Children/ Low income/ Pedestrians students Disabilities Minority Disadvantaged Bay Area, San Francisco Safe Routes to School Program Plan Bay Area 2040 1 1 1 0 1 Complete Streets Checklist Guidance 1 1 1 0 0 Miami-Dade County, WalkSafe Program Complete Streets Resolution 1 1 1 0 0 Safer People Safe Streets 1 1 1 0 0 Resolution Endorsing the 20th Annual "Walk to School Day" 1 1 0 0 0 Event Miami-Dade 2040 Bicycle/Pedestrian Plan: Miami-Dade MPO 1 1 0 0 0 GPC V #7 Mid-Ohio, Columbus Safe Routes Program Making Strides: Pedestrian Best Practices 2005 1 1 1 1 1
The 2016-2040 Metropolitan Transportation Plan 1 1 1 1 0
2012-2035 Metropolitan Transportation Plan 1 0 0 1 1
2006 Regional Bicycle Transportation Facilities Plan 1 1 1 0 0
MORPC Complete Streets Policy 1 0 0 0 0
246 Local City and County of San Francisco, San Francisco Safe Routes to School Program Safe Routes Vulnerable Populations Mentioned Children/ Low income/ Pedestrians students Disabilities Minority Disadvantaged
Pedestrian Strategy 1 1 1 0 0
Transportation Element 1 1 0 0 1
247 Local Various Municipalities, WalkSafe Program
Safe Routes Vulnerable Populations Mentioned
Children/ Low income/ Pedestrians students Disabilities Minority Disadvantaged Miami Comprehensive Neighborhood Plan: Goals, Objectives, 1 1 1 1 1 Policies
2025 Comprehensive Plan 1 1 1 0 0
Overtown-Wynwood Bicycle Pedestrian Mobility Plan 1 1 1 0 0
South Miami Intermodal Transportation Plan 1 1 1 0 0
Bicycle and Pedestrian Mobility Plan for the City of Miami 1 1 0 0 0 Gardens
City of Coral Gables Comprehensive Plan 0 1 1 0 0
City of Doral 2010 Transportation Master Plan 1 1 0 0 0
City of Miami Gardens Recreational Trails Master Plan 1 1 0 0 0
City of North Miami Transportation Master Plan 1 1 0 0 0
248 Master Plan 1 1 0 0 0
Miami Bicycle Master Plan 1 1 0 0 0
2025 Comprehensive Plan: Goals, Objectives, Policies 1 0 0 0 0
Bicycle/Pedestrian Mobility Plan for the Miami Downtown 1 0 0 0 0 Development Authority Area
City of Hialeah Gardens, Florida 2025 Comprehensive Plan 1 0 0 0 0
City of South Miami Community Redevelopment Area Phase II 1 0 0 0 0 Plan Supplement
City of South Miami Community Redevelopment Area Plan 1 0 0 0 0
City of South Miami Comprehensive Plan 1 0 0 0 0
Homestead Comprehensive Plan: Goals, Objectives & Policies 1 0 0 0 0
North Miami Florida EAR-Based Comprehensive Plan 1 0 0 0 0 Amendments
Sustainable Opa-Locka 2030 Comprehensive Development 1 0 0 0 0 Master Plan
Local City of Columbus, Columbus Safe Routes Program 249 Safe Routes Vulnerable Populations Mentioned
Policy Title Children/ Low income/ Pedestrians students Disabilities Minority Disadvantaged
Connect Columbus Factbook 1 1 0 1 1
Columbus Bicentennial Bikeways Plan 1 1 1 0 0
The Columbus Green Community Plan: Green Memo III 1 1 0 0 0
Columbus Pedestrian Thoroughfare Plan 1 0 0 0 0
Complete Streets Resolution 1 0 0 0 0
Sidewalk and Bikeway Facility Requirements Rules and Regulations 1 0 0 0 0
250 Appendix Q. Inventory of Relevant Language from Policies
Federal Explicit Mention Sample of Relevant Language in Policy Safe Routes Walking to School to School Safe, Accountable, Flexible, Efficient Transportation Equity Act: A Legacy for Users The purposes of the program shall be (1) to enable and encourage children, including those with disabilities, to walk and bicycle to school; (2) to make bicycling and walking to school a safer and more appealing transportation alternative, thereby encouraging a healthy and active lifestyle from an early age; and (3) to facilitate the planning, development, and implementation of projects and activities that will improve safety and reduce traffic, fuel consumption, and air pollution in the vicinity of schools. 1 0 Moving Ahead for Progress in the 21st Century Act The term 'transportation alternatives' means any of the following activities when carried out as part of any program or project authorized or funded under this title, or as an independent program or project related to surface transportation: (B) Construction, planning, and design of infrastructure-related projects and systems that will provide safe routes for non-drivers, including children, older adults, and individuals with disabilities to access daily needs. 1 0 Flexibility in Highway Design Funds apportioned to a State under section 104(b)(2) for the surface transportation block grant program may be obligated for the following: (6) Recreational trails projects eligible for funding under section 206, pedestrian and bicycle projects in accordance with section 217 (including modifications to comply with accessibility requirements under the Americans with Disabilities Act of 1990 (42 U.S.C. 12101 et seq.)), and the safe routes to school program under section 1404 of SAFETEA-LU U.S.C. 402 note). 1 0
251 Final Rule: Local School Wellness Policy Implementation Under the Healthy Hunger-Free Kids Act of 2010 The rule proposed specific content for the local school wellness policies. At a minimum, policies were required to include: specific goals for nutrition promotion and education, physical activity, and other school-based activities that promote student wellness and rely on evidence-based strategies. 0 0 National School Transportation Specifications and Procedures The sole criterion used to establish transportation eligibility should not only be the distance between a student's home address and the student's school of attendance; rather, travel to and from school must take into account various critieria. Safety must be the primary concern, and critieria should take into account the ages of students and potentially hazardous situations, such as roadway and walk pathway conditions, speed limits, railroad crossings, lighting conditions, etc. 0 0 Highway Safety Program Guideline No. 14 Pedestrian and Bicycle Safety Each State should have centralized program planning, implementation, and coordination to promote pedestrian and bicycle safety program issues as part of a comprehensive highway safety program. Evaluation should be used to revise existing programs, develop new programs, and determine progress and success of pedestrian and bicycle safety programs. The State Highway Safety office should: Develop safety initiatives to reduce fatalities and injuries among high-risk groups as indicated by crash and injury data trends, including children, older adults, and alcohol-impaired pedestrians and bicyclists. 1 0 United States Department of Transportation Policy Statement on Bicycle and Pedestrian Accommodation Regulations and Recommendations In support of this commitment, transportation agencies and local communities should go beyond minimum design standards and requirements to create safe, attractive, sustainable, accessible, and convenient bicycling and walking networks. Such actions should include: Ensuring that there are transportation choices for people of all ages and abilities, especially children: Pedestrian and bicycle facilities should meet accessibility requirements and provide safe, convenient, and interconnected transportation networks. For example, children should have safe and convenient options for walking and bicycling to school and parks. People who cannot or prefer not to drive should have safe and efficient transportation choices. 0 0
252 Policy Statement to Support the Alignment of Health and Early Learning Systems The U.S. Department of Health and Human Services and the U.S. Department of Education envision a national where all children enter school healthy and ready to learn. We aspire to achieve the following: All children and their families live in healthy and supportive communities with: Safe paces for play and active living to promote physical activity. 0 0 Healthy Students, Promising Futures: State and Local Action Steps and Practices to Improve School-Based Health School learning environments should be designed to promote and reinforce health and well-being, including opportunities for, and access to, daily physical activity, high-quality, nutritious school food, and rigorous and effective nutrition and health education. 0 0 Strategic Agenda for Pedestrian and Bicycle Transportation In order to meet its ambitious safety goals, FHWA will work closely with partner agencies to discern root causes and effective countermeasures that address a wide variety of factors…Other factors that influence safety include infrastructure conditions, traveler behavior, traffic characteristics, and urban design elements. In addition considerations must be given to the different types and levels of treatments appropriate for children and older adults, people with disabilities, and other travelers with unique needs or characteristics. 1 0 Intermodal Surface Transportation Efficiency Act of 1991 Pedestrian walkways and bicycle transportation facilities to be constructed under this section shall be located and designed pursuant to an overall plan to be developed by each metropolitan planning organization and State and incorporated into their comprehensive annual long-range plans in accordance with sections 134 and 135 of this title, respectively. such plans shall provide due consideration for safety and contiguous routes. 0 0
253 Flexibility in Highway Design In order for a designed to be sensitive to the project's surrounding environment, he or she must consider its context and physical location carefully during this stage of project planning…A benefit of the designer gathering information about the physical character of the area and the values of the community is that the information will help the designer shape how the project will look and identify any physical constraints or opportunities early in the process. Some questions to ask at this stage include: Are there concentrations of children, the elderly, or disabled individuals with special design and access needs (e.g., pedestrian crosswalks, curb cuts, audible traffic signals, median refuge areas)? 0 0 Safer People, Safer Streets: Summary of US Department of Transportation Action Plan to Increase Walking and Biking and Reduce Pedestrian and Bicyclist Fatalities FHWA supports the National Center for Safe Routes to School, which assists States and communities in enabling and encouraging children to safely walk and bicycle to school. The National Center serves as the information clearinghouse for the Federal Safe Routes to School program. The organization provides technical support and resources and coordinates online registration efforts for U.S. Walk to School Day and facilitates worldwide promotion and participation. 1 1
254 State
Explicit Mention Safe Routes Walking Sample of relevant language in policy to School to school California, San Francisco Safe Routes to School Program Sustainable Communities and School Planning The location, accessibility, quality, maintenance, safety, and use of a school can have a significant impact on the health and well-being of a community. A school district can help advance its community's sustainability goals by including: Promoting Active Transportation. Safe routes to school promote active forms of transportation (e.g., walking and biking) with associated health benefits and reduced pollution and traffic near schools. Creating safe routes to by removing existing barriers or mitigating safety issues is much more difficult and expensive to accomplish after construction than if the school is originally sited and designed correctly. 0 0 California Assembly Bill No. 115; Chapter 20 In developing the guidelines with regard to project eligibility, the commission shall include, but need not be limited to, the following project types: ...(8) Safe Routes to School projects that improve the safety of children walking and bicycling to school, in accordance with Section 1404 of Public Law 109-59. (9) Safe routes to transit projects, which will encourage transit by improving biking and walking routes to mass transportation facilities and school bus stops. 0 0 Toward an Active California: State Bicycle + Pedestrian Plan E1.2 Provide active transportation technical assistance as part of existing Caltrans technical assistance programs. Expand the offerings of the Active Transportation Resource Center to provide resources, webinars, and tools beyond Safe Routes to School to include all users and destinations. 0 0
255 Senate Bill No. 760 Existing law establishes the Active Transportation Program in the Department of Transportation for the purpose of encouraging increased use of active modes of transportation, such as biking and walking, and declares the intent of the Legislature that the program achieve specific goals, including, among other things, increasing the proportion of trips accomplished by biking and walking and the safety and mobility for nonmotorized users. This bill would establish a Division of Active Transportation within the department and require that an undersecretary of the Transportation Agency be assigned to give attention to active transportation program matters to guide progress toward meeting the department's active transportation program goals and objectives. 0 0 California Transportation Plan 2040 Several statewide initiatives are underway to identify strategies for expanding active transportation opportunities. The multi-agency collaborative, Health in All Policies Task Force (HIAP), aims to make bicycling and walking a more attractive and safer transportation option for shorter trips particularly on highways and local roads. In addition, Safe Routes to School (SRTS) aims to increase the number of children who walk or bicycle to school. 1 1 Complete Streets Implementation Action Plan 2.0 It is the intent of the Legislature to require in the development of the circulation element of a local government's general plan that the circulation of users of streets, roads, and highways be accommodated in a manner suitable for the respective setting in rural, suburban, and urban contexts, and that users of streets, roads, and highways include bicyclists, children, persons with disabilities, motorists, movers of commercial goods, pedestrians, public transportation, and seniors. 1 0 Senate Bill No 99; Chapter 359_Active Transportation Program In developing guidelines with regard to project eligibility, the commission shall include, but need not 1 1 be limited to, the following project types: Safe Routes to School projects that improve the safety of children walking and bicycling to school, in accordance with Section 1404 of Public Law 109-59.
256 Complete Streets-Integrating the Transportation System (DD-64-R2) Caltrans develops integrated multimodal projects in balance with community goals, plans, and values. Addressing the safety and mobility needs of bicyclists, pedestrians, and transit users in all projects, 0 0 regardless of funding, is implicit in these objectives. Bicycle, pedestrians, and transit travel is facilitated by creating 'complete streets" beginning early in system planning and continuing through project delivery and maintenance and operations. Complete Streets Law This bill would require, commencing January 1, 2011, that the legislative body of a city or county, upon any substantive revision of the circulation element of the general plan, modify the circulation to plan for a balanced, multimodal transportation network that meets the needs of all users of streets, 0 0 roads, highways, defined to include motorists, pedestrians, bicyclists, children, persons with disabilities, seniors, movers of commercial goods, and users of public transportation, in a manner that is suitable to the rural, suburban, or urban context of the general plan. Senate Bill No. 391; Chapter 585; California Transportation Plan In developing the California Transportation Plan pursuant to Sections 65072 and 65072.1, the department shall address how the state will achieve maximum feasible emissions reductions in order to attain a statewide reduction of greenhouse gas emissions to 1990 levels by 2020 as required by the 0 0 California Global Warming Solutions Act of 2006, and 80 percent below 1990 levels by 2050, taking into consideration the use of alternative fuels, new vehicle technology, tailpipe emissions reductions, and expansion of public transit, commuter rail, intercity rail, bicycling, and walking. Senate Bill 375; Chapter 728_Transportation planning; travel demand models; sustainable communities strategy; environmental review Each transportation planning agency designated under Section 29532 or 29532.1 shall prepare and adopt a regional transportation plan directed at achieving a coordinated and balanced regional transportation system, including, but not limited to, mass transportation, highway, railroad, maritime, bicycle, pedestrian, goods movement, and aviation facilities and services. This plan shall be action- oriented and pragmatic, considering both the short-term and long-term future, and shall present clear, concise policy guidance to local and state officials.
257 Senate Bill 99; Chapter 359_Active Transportation Program In developing the guidelines with regard to project eligibility, the commission shall include, but need not be limited to, the following project types: ...(8) Safe Routes to School projects that improve the 0 0 safety of children walking and bicycling to school, in accordance with Section 1404 of Public Law 109-59. (9) Safe routes to transit projects, which will encourage transit by improving biking and walking routes to mass transportation facilities and school bus stops. Pedestrian Accessibility Guidelines for Highway Projects All pedestrian facilities on all projects are to be accessible in accordance with State and Federal laws. The following guidance and best practices capture the lessons learned through the years since the 0 0 passage of the ADA and to document the Federal and State regulatory standards that apply. Early consultation with the Design Coordinator is recommended to discuss pedestrian accessibility issues and their resolution. Senate Bill 168; SEC. 56 Section 2382 of the Streets and Highways Code The California Transportation Commission shall develop guidelines and project selection criteria for the Active Transportation Program in consultation with the Active Transportation Program Workgroup, which shall be formed for purposes of providing guidance on matters including, but not limited to, development of subsequent revisions to program guidelines, schedules and procedures, project 1 1 selection criteria, performance measures, and program evaluation. The workgroup shall include, but not be limited to, representatives of government agencies and active transportation stakeholder organizations with expertise in pedestrian and bicycle issues, including Safe Routes to School programs. Florida, WalkSafe Program Gabby's Law for Student Safety The bill allows a district school board and other governmental entities to enter into an interlocal agreement for the identification and correction of hazardous walking conditions as long as the 1 1 agreement: Implements the Safe Paths to School Program; or Establishes standards for student safety and identifies and corrects hazardous walking conditions that meet or exceed the standards established in this bill.
258 2017 Highway Safety Plan The University of Miami School of Medicine will address pedestrian injury and fatalities among children ages 5-14 through continued implementation of the WalkSafe evidence-based education 1 0 curriculum for elementary and middle schools. The program utilizes the National Safe Routes to School model that includes education, engineering, evaluation, enforcement, and encouragement. Best Practices for Pedestrian and Bicycle Safety Florida Pedestrian and Bicycle Policy and Guidance Initiatives establish, clarify, and update the Florida Department of Transportation (FDOT) standards, manuals, and other guidance materials to incorporate pedestrian and bicycle safety on Florida roadways...The updated and revised guidance provides a 0 1 framework for consistent implementation of improved facilities for bicyclists and pedestrians on Florida roadways. The focus on bicyclist and pedestrian safety is incorporated in all phases of a project, from planning to construction.
Florida Pedestrian and Bicycle Strategic Safety Plan 1 0 Objective 3.10.9. Partner with school-based education programs to promote pedestrian and bicycle safety. Promote the Safe Routes to School program through our partnership. Ramon Turnquest School Crossing Guard Act The Department of Transportation shall adopt uniform guidelines for the training of school crossing 0 0 guards. Each local governmental entity administering a school crossing guard program shall provide a training program for school crossing guards according to the uniform guidelines.
Florida School Crossing Guard Training Guidelines 0 1 Adult school crossing guards play an important role in helping children cross streets safely at key locations on their ways to school.
6A-3.0171 Responsibilities of School Districts for Student Transportation 0 1 To assure that county and city officials are advised of hazards on bus routes and hazards involving students walking to and from school.
259 Required and optional elements of comprehensive plan; studies and surveys Each local government's transportation element shall address traffic circulation, including the types, 0 0 locations, and extent of existing and proposed major thoroughfares and transportation routes, including bicycle and pedestrian ways. Safe Paths to Schools Program_Title XXVI; Chapter 335; 335.066 There is established in the Department of Transportation the Safe Paths to Schools Program to consider 1 1 the planning and construction of bicycle and pedestrians ways to provide safe transportation for children from neighborhoods to schools, parks, and the state's greenways and trails systems.
Conserve by Bicycle Program 1 1 The purpose of the Conserve by Bicycle Program are to: (f) Provide safe ways for children to travel from their homes to their schools by supporting the Safe Paths to Schools Program. Ohio, Columbus Safe Routes Program Access Ohio 2040 Next steps: Create Bicycle/Pedestrian Coordinator roles in each of ODOT's 12 District offices to work with ODOT's Statewide Bicycle/Pedestrian Coordinator; ODOT's Bicycle/Pedestrian Coordinators, 0 0 along with statewide planning staff, will coordinate with local jurisdictions to field verify the proposed routing for U.S. and SBRs. ODOT Active Transportation Guide: A Reference for Communities Safety for all users must be a top priority. Special attention must be paid to vulnerable street users, including children, the elderly and persons with disabilities….Safety is often a pronounced concern at 1 1 intersections, where crossings and conflicts (both among and between vehicles, pedestrians and bicyclists) are more concentrated. Statewide Transportation Improvement Program The Transportation Alternatives Program (TAP) provides funding for projects that support transportation by improving non-motorized transportation facilities, historic preservation, scenic and 0 0 environmental aspects. ODOT allocates transportation alternatives funds to the MPOs and keeps the remainder for a statewide projects selection process.
260 2016-2017 Wellness and Physical Education The physical education and wellness measures are required per state law…The legislature enacted this law because wellness and physical education are important components of a student's academic 0 0 success. The accompany this law, the legislature also adopted ORC Section 3302.032 (A) and 3302.032 (B) to create wellness and physical education measures on the building and district report cards.
261
Regional Explicit Mention
Safe Routes Walking Sample of relevant language in policy to School to school Bay Area, San Francisco Safe Routes to School Program Plan Bay Area 2040 The One BayArea Grant (OBAG) program allows flexibility to invest in a community's transportation infrastructure by providing funding for Transportation for Livable Communities, bicycle and pedestrian improvements, local streets and roads preservation, and planning activities, while also providing specific funding opportunities for Safe Routes to Schools projects and Priority Conversation Areas. 1 0 Complete Streets Checklist Guidance Please indicate needed pedestrian, bicycle, or transit improvements in the project area that staff or the public have identified. Examples include: accommodations for the elderly or disabled or school age children. 0 0 Miami-Dade County, WalkSafe Program
Miami-Dade 2040 Bicycle/Pedestrian Plan: Miami-Dade MPO GPC V #7 Objective 1.5: Ensure that the network is convenient and adequate by utilizing universal pedestrian bicycle facilities that provide access and mobility for all users of the community including children, adults, the elderly and disabled. 1 1 Complete Streets Resolution Whereas, a "Complete Streets" Program could among other things: contribute to the development of a connected and complete transportation network that will reduce hazards and improve safety for pedestrians and cyclists, especially vulnerable elements of the population, who may be unable to operate a motor vehicle, such as young children, the elderly, and the physically disabled. 0 1
262 Resolution Endorsing the 20th Annual "Walk to School Day" Event Now, therefore, be it resolved by the governing board of the Metropolitan Planning Organization for the Miami Urbanized Area, that this Governing Board endorses the 20th Annual International "Walk to School Day" scheduled for October 5, 2016. 0 1
Safer People Safe Streets Policy CHD-3B. Encourage walking and bicycle riding as a means of transportation to and from school, by implementing capital projects that support the development of safe routes to school. 1 1 Mid-Ohio, Columbus Safe Routes Program The 2016-2040 Metropolitan Transportation Plan MORPC encourages and supports efforts to increase walking and bicycling to school among students in grades K-8. 1 1 Making Strides: Pedestrian Best Practices 2005 Another significant movement is the Safe Routes to School initiative…the focus of the program is to encourage children to walk and bike to school and to target improvement to increase the safety of the routes. 1 1 2012-2035 Metropolitan Transportation Plan SAFETEA-LU established the Safe Routes to School (SRTS) program to improve the ability of primary and middle school students to walk and bicycle to school safely. ODOT administers the program in Ohio. The program provides federal transportation funds for right-of-way and construction phases of infrastructure projects, among other eligible activities. 1 1 2006 Regional Bicycle Transportation Facilities Plan Goal II: Provide an accessible transportation system with a range of choice. Provide facilities for desired levels of pedestrian, bicycle and transit travel. 0 0
263 MORPC Complete Streets Policy The Complete Streets policy builds upon these efforts and promotes a multimodal transportation system that is integrated with sustainable land use developments. Its main objective is to design and build roads that safely and comfortably accommodate all users of roadways, including motorists, cyclists, pedestrians, transit and school bus riders, delivery and service personnel, freight haulers, and emergency responders. It includes people of all ages and abilities. 0 1
264 Local Explicit Mention Safe Routes to Walking to Sample of relevant language in policy School school City and County of San Francisco, San Francisco Safe Routes to School Program Transportation Element Safety is a concern in the development and accommodation of any part of the transportation system, but safety for pedestrians (which includes disabled persons in wheelchairs and other ambulatory devices) should be given priority where conflicts exist with other modes of transportation. (Policy 1.2) 0 0 Pedestrian Strategy Objective 4.2. Target safety and walkability improvements near schools and areas with higher rates of senior pedestrian injuries. 0 1 Various Municipalities, WalkSafe Program 2025 Comprehensive Plan: Goals, Objectives, Policies Objective 5: Miami-Dade County Public Schools, in conjunction with the Village and other appropriate agencies, will strive to improve security and safety for students and staff. Policy 5.4: Coordinate with Miami-Dade County Public Schools and other appropriate agencies to provide for pedestrian and traffic safety in the area of schools, and signalization for educational facilities. 0 0 Miami Bicycle Master Plan Action 3: Expand Safe Routes to School Partnerships. Collaborate with Miami-Dade County Public Schools, public health organizations, parent-teacher associations, the FDOT, and local advocacy groups to expand the Safe Routes to School program, whereby students are further encouraged to bicycle and walk to school through innovations such as Freiker (Frequent Bike) and the University of Miami's successful WalkSafe and BikeSafe program. 1 0
265 Bicycle/Pedestrian Mobility Plan for the Miami Downtown Development Authority Area The primary goal established by the Committee is to promote a green urban environment where pedestrian and bicycle mobility are the transportation priorities. 0 0 North Miami Florida EAR-Based Comprehensive Plan Amendments Policy 1.14.2. As provided for in the Interlocal Agreement between North Miami and the Miami-Dade County School Board, the City will continue to work with the School Board to plan future public school sites in the City and ensure adequate lands are available; ensure safe routes to school are incorporated; proximate to neighborhoods with sufficient access, safety and security; and to, to accommodate the present and future student population of the City. 0 0 City of North Miami Transportation Master Plan Neighborhood traffic management strategies are important components of enhancing the quality of life for residents of North Miami. The following are the recommended neighborhood traffic management strategies: Safe Routes to School. In addition to teaching children and adults to behave safely in traffic, there is a new program evolving to ensure that schools are accessible by children who walk or bicycle. 1 0 Sustainable Opa-Locka 2030 Comprehensive Development Master Plan Policy T-1.3: Pedestrian Level of Service Standards. The City shall seek to maintain a pedestrian Level of Service Standard of B or better on all roadways with designated pedestrian facilities in accordance with the flowing definitions: LOS A - Highly pedestrian oriented and attractive for pedestrian trips, with sidewalks, pedestrian friendly intersection design, low vehicular traffic volume, and ample pedestrian amenities; LOS B- Similar to A, but with fewer amenities and low to moderate level of interaction with motor vehicles. 0 0 City of South Miami Community Redevelopment Area Plan 11. "Friendly" Green Streets" Bikeway and Pedestrian Plan: If not addressed in the forthcoming Evaluation and Appraisal Report (E.A.R.), develop a CRA-wide Friendly Green Streets Plan which interconnects with areas outside the CRA and fills in the gaps in the bikeway and sidewalk system within the CRA. 0 0
266 City of South Miami Community Redevelopment Area Phase II Plan Supplement In addition, a deficient sidewalk and bikeway system (including the station area), congested roadways and restrictive rights-of-ways point to the need for a comprehensive study of intermodal relationships including a detailed bikeways and sidewalk plan. 0 0 City of South Miami Comprehensive Plan FLU Policy 1.3.2. The City shall seek to ensure bicycle and pedestrian connectivity in all areas within its boundaries, in accordance with neighborhood plans and the Comprehensive Long Range Transportation Study. 0 0
Homestead Comprehensive Plan: Goals, Objectives & Policies Policy 4.3: Provide a pedestrian network for all major destinations within the City including schools, public institutions, the Downtown District and areas containing or generating pedestrian traffic. 0 1 Village of Key Biscayne Master Plan Most residents - especially children- will choose to ride their bicycles throughout the Village streets. To maintain the safety of these bicyclists, local streets such as those which are direct routes to school should be given priority for speed control, thus providing a safer bicycling environment. However, constructing bicycle and pedestrian facilities on local streets should be avoided wherever possible, since the commingling of these various modes of transportation serves to create a safe environment for all than if the modes were segregated. 0 0 City of Coral Gables Comprehensive Plan Policy EDU-1.5.4. Coordinate with Miami-Dade County Public Schools and other appropriate agencies to provide for pedestrian and traffic safety in the area of schools, and signalization for educational facilities. 0 0 City of Doral 2010 Transportation Master Plan 2.2.17. The City shall manage growth through the maintenance of multimodal mobility across the City, encourage integrated, safe pedestrian and bicycle system which reduce reliance on motorized vehicles, and provides convenient access to schools, activity centers, transit stops, parks and other recreation areas throughout the City. 0 1
267 City of Hialeah Gardens, Florida 2025 Comprehensive Plan Policy 1.3.6. The City shall continue to seek opportunities to provide pedestrian and bicycle paths in all districts. The City shall seek to provide connectivity between park sites via bicycle and pedestrian paths by 2015. 0 0 2025 Comprehensive Plan Policy 7.8: Safe Roadway Designs. The City shall eliminate or minimize roadway designs which lead to hazardous conditions by… 4. requiring the elimination or the minimization of conflicts between roadway, bicycle and pedestrian 0 traffic by reasonable separation of vehicles, bicycles and pedestrians, particularly near schools, parks and other areas where children are concentrated. 0
Miami Comprehensive Neighborhood Plan: Goals, Objectives, Policies Policy EDU-1.4.4: Coordinate with the Miami-Dade County Public Schools and municipalities to provide pedestrian and traffic safety in the area of schools, and signalization for educational facilities. 0 0 Overtown-Wynwood Bicycle Pedestrian Mobility Plan Active transportation, such as bicycling, walking, or accessing public transportation, has the potential to serve a greater market share of trips than it currently does. Facilities such as wide sidewalks, pedestrian crossing features at key intersections, bicycle parking areas, and interconnected bike lanes are important for attracting a greater modal share for alternative travel modes. Focusing planning efforts on alternative transportation modes is vital. 0 0 South Miami Intermodal Transportation Plan In addition, areas close to parks, schools, and similar pedestrian destinations require special pedestrian consideration. Pedestrian-oriented designs should also aim to minimize conflicts with other modes and exposure to motor vehicle traffic. Intersections must be designed for pedestrians of all ages and abilities. 0 0
Bicycle and Pedestrian Mobility Plan for the City of Miami Gardens Project 14: School-Related Improvements. Prioritize bicycle and pedestrian facility improvements near schools to improve safety for children walking and biking to and from school. 0 1 268 City of Miami Gardens Recreational Trails Master Plan Objective A3: Provide safe routes to schools. 1 0 City of Columbus, Columbus Safe Routes Program Sidewalk and Bikeway Facility Requirements Rules and Regulations The following sidewalks and bikeway facilities requirements and standards are hereby imposed for purposes of increasing safety, facilitating general accessibility, providing links in an overall system of sidewalks and bikeways, supporting the use of mass transit, encouraging a balanced and complete transportation system, improving access to employment locations, providing access to recreation areas, facilitating accessibility for disabled persons, and otherwise promoting the general health, safety and welfare of the public. 0 0
Columbus Bicentennial Bikeways Plan Objective: Involve all of the City's schools in Safe Routes to Schools Programs. The growing national Safe Routes to Schools provides multiple benefits for healthy, safety, mobility and the environment. 1 1 Columbus Pedestrian Thoroughfare Plan Capital improvement plans, area plans, bikeway and (street) thoroughfare plans should all incorporate the results of this Plan as they are being created and updated. The resulting city process should be a seamless approach to developing the public right of way such that pedestrians are treated as important roadway users and their needs are considered from the outset of any roadway design effort. 0 1 Connect Columbus Factbook The visions and goals from each of the planning documents reviewed influenced the goals that were created for Connect Columbus. After receiving public input, the following goals were established: Health + Safety. Balanced access for walking, biking, and active transportation that promotes health, well-being, and safety citywide, while protecting needs of our most vulnerable populations. 1 1
269 Complete Streets Resolution Whereas, pedestrians, bicyclists, motorists and transit riders of all ages and abilities are able to safely move along and across a Complete Street; and Whereas, Columbus traffic engineers and transportation division officials are currently studying Complete Streets principles to ensure that whenever possible, the entire right of way of every Columbus roadway is designed and operated to enable safe access for all users;...Be it resolved by the Council of the City of Columbus: That this Council supports the implementation of Complete Streets policies in Columbus, and urges the Public Service Department and the Transportation Division to include these policies in all street construction, reconstruction and repair projects. 0 0 The Columbus Green Community Plan: Green Memo III Objective 4: Reduce vehicle-pedestrian crashes by 25% over the next five years. 1 0
270 Appendix R. Inventory of Relevant Language from Parent Teacher Association Policies
Policy Title Sample of relevant language in policy
National PTA Resolution on School Health Whereas, School health councils address and coordinate the activities of a coordinated school Councils health program (CSHP), which consists of the following eight components: school environment, comprehensive school health education, health services, school meals and nutrition, physical education, counseling and psychological and mental health services, staff health promotion, and family and community involvement in schools...Resolved, The National PTA and its constituent organizations encourage schools to develop school health councils in order to foster the connection between good health and learning... Resolution on Improved Whereas, Parents city safety issues and traffic concerns as the number one reason for not allowing Infrastructure Around Schools their children to walk or bike to school; this concern is substantiated by the fact that there is a high probability the result with be fatal when a pedestrian is involved in an accident...Resolved, That PTA and its constituent associations encourage and collaborate with school administrators and local officials to bring attention to unsafe walking and biking routes to schools... National PTA Position Statement -- A founding purpose of National PTA is to promote safety for children and youth. National PTA Child Safety and Protection urges its members at all levels to monitor, support, and advocate for laws and programs in the following areas: Safety. Include safety education in school curriculum and community programs.
California PTA
271 Safe Routes to School for All Resolved, That the California State PTA and its units, councils and districts urge legislators and Children local government agencies to allocate funding for more adult crossing guards and the implementation of engineering improvements around schools, such as traffic calming measures, improved street crossings, sidewalks, bike lanes and walkways to create safer routes to school.
Florida PTA 2015/2016 Legislative Priorities Florida PTA urges the Legislature to support daily physical education programs taught by certified Physical Education teachers as an integral part of every child's education and to support efforts to improve the nutritional value of foods and beverages served and sold in schools throughout the state. Ohio PTA 2016 Ohio PTA Legislative Legislative Focus Areas: Support increased physical activities during the school day for K-12 Priorities & Position Statements students.
272 Appendix S. Inventory of Relevant Language from School District Wellness Policies
District Sample of Relevant Language in Wellness Policy
Columbus City Schools The District will promote physical activity opportunities through programs that support wellness and education benefits of walking and bicycling to school.
Miami-Dade County School District District Policy: All students and staff will be encouraged to participate in the nationally recommended levels of a minimum of sixty (60) minutes or more per day of physical activity.
San Francisco Unified School District District staff shall work with relevant City departments and local agencies (e.g., the San Francisco Safe Routes to School Partnership) to assess walking and biking conditions at each school and leverage opportunities to make it easier for students to walk or bike to school.
273 Appendix T. Results of Policy Scoring
Healthy Hunger-Free Kids Act of 2010 (Final Rule: Local Policy Scoring Tool School Wellness Policy Implementation Under the HHFKA)
Indicate the level at which the policy is implemented Federal
Does the policy… Power Reference the key power people (schools)? 1 Philosophy Include a stated Vision? 0 Policy Make any statement on enforcement or regulation? 1 Indicate the responsible party for enforcement or 1 regulation? Procedure Utilize model language supporting Safe Routes to 1 School? Project List actions (planned or implemented) to address 1 pedestrian safety? Partnerships Make any statement on inter-agency collaboration? 1 Indicate partnerships for implementation? 1 Promotion Have stated goals for pedestrian safety? 0 Have stated goals for child pedestrian safety? 0 Community advocacy Mention community input during the development 1 level of the policy? Agency staff level Reference staff or agencies responsible for 1 implementation? Elected body level Reference staff an elected or governing body 1 responsible for implementation? 1 Health Impacts Mention expected measurable health impacts?
Total score 11
274
Policy Scoring Tool California Transportation Plan 2040
Indicate the level at which the policy is implemented State
Does the policy… Power Reference the key power people (schools)? 1 Philosophy Include a stated Vision? 1 Policy Make any statement on enforcement or 0 regulation? Indicate the responsible party for enforcement 0 or regulation? Procedure Utilize model language supporting Safe Routes 1 to School? Project List actions (planned or implemented) to 1 address pedestrian safety? Partnerships Make any statement on inter-agency 1 collaboration? Indicate partnerships for implementation? 1 Promotion Have stated goals for pedestrian safety? 1 Have stated goals for child pedestrian safety? 0 Community advocacy level Mention community input during the 1 development of the policy? Agency staff level Reference staff or agencies responsible for 1 implementation? Elected body level Reference staff an elected or governing body 1 responsible for implementation? 0 Health Impacts Mention expected measurable health impacts?
Total score 10
275 Complete Streets-Integrating the Transportation System Policy Scoring Tool (DD-64-R2)
State Indicate the level at which the policy is implemented Does the policy… Power Reference the key power people (schools)? 0 Philosophy Include a stated Vision? 1 Policy Make any statement on enforcement or 0 regulation? Indicate the responsible party for enforcement 0 or regulation? Procedure Utilize model language supporting Safe Routes 1 to School? Project List actions (planned or implemented) to 1 address pedestrian safety? Partnerships Make any statement on inter-agency 0 collaboration? Indicate partnerships for implementation? 0 Promotion Have stated goals for pedestrian safety? 0 Have stated goals for child pedestrian safety? 0 Community advocacy level Mention community input during the 0 development of the policy? Agency staff level Reference staff or agencies responsible for 1 implementation? Elected body level Reference staff an elected or governing body 1 responsible for implementation? 0 Health Impacts Mention expected measurable health impacts?
Total score 5
276
Policy Scoring Tool California Complete Streets Law
State Indicate the level at which the policy is implemented Does the policy… Power Reference the key power people (schools)? 0 Philosophy Include a stated Vision? 0 Policy Make any statement on enforcement or 1 regulation? Indicate the responsible party for enforcement 1 or regulation? Procedure Utilize model language supporting Safe Routes 1 to School? Project List actions (planned or implemented) to 0 address pedestrian safety? Partnerships Make any statement on inter-agency 0 collaboration? Indicate partnerships for implementation? 0 Promotion Have stated goals for pedestrian safety? 0 Have stated goals for child pedestrian safety? 0 Community advocacy level Mention community input during the 0 development of the policy? Agency staff level Reference staff or agencies responsible for 1 implementation? Elected body level Reference staff an elected or governing body 0 responsible for implementation? 0 Health Impacts Mention expected measurable health impacts?
Total score 4
277
Policy Scoring Tool Florida Pedestrian and Bicycle Strategic Safety Plan
State Indicate the level at which the policy is implemented Does the policy… Power Reference the key power people (schools)? 1 Philosophy Include a stated Vision? 1 Policy Make any statement on enforcement or 1 regulation? Indicate the responsible party for enforcement 1 or regulation? Procedure Utilize model language supporting Safe Routes 1 to School? Project List actions (planned or implemented) to 1 address pedestrian safety? Partnerships Make any statement on inter-agency 0 collaboration? Indicate partnerships for implementation? 1 Promotion Have stated goals for pedestrian safety? 1 Have stated goals for child pedestrian safety? 0 Community advocacy level Mention community input during the 0 development of the policy? Agency staff level Reference staff or agencies responsible for 1 implementation? Elected body level Reference staff an elected or governing body 1 responsible for implementation? 1 Health Impacts Mention expected measurable health impacts?
Total score 11
278
Policy Scoring Tool Access Ohio 2040
State Indicate the level at which the policy is implemented Does the policy… Power Reference the key power people (schools)? 1 Philosophy Include a stated Vision? 1 Policy Make any statement on enforcement or 0 regulation? Indicate the responsible party for enforcement 0 or regulation? Procedure Utilize model language supporting Safe Routes 1 to School? Project List actions (planned or implemented) to 0 address pedestrian safety? Partnerships Make any statement on inter-agency 1 collaboration? Indicate partnerships for implementation? 1 Promotion Have stated goals for pedestrian safety? 0 Have stated goals for child pedestrian safety? 0 Community advocacy level Mention community input during the 1 development of the policy? Agency staff level Reference staff or agencies responsible for 1 implementation? Elected body level Reference staff an elected or governing body 1 responsible for implementation? 0 Health Impacts Mention expected measurable health impacts?
Total score 8
279
Policy Scoring Tool Ohio Department of Education 2016-2017 Wellness and Physical Education
State Indicate the level at which the policy is implemented Does the policy… Power Reference the key power people (schools)? 1 Philosophy Include a stated Vision? 0 Policy Make any statement on enforcement or 1 regulation? Indicate the responsible party for enforcement 1 or regulation? Procedure Utilize model language supporting Safe Routes 0 to School? Project List actions (planned or implemented) to 0 address pedestrian safety? Partnerships Make any statement on inter-agency 0 collaboration? Indicate partnerships for implementation? 0 Promotion Have stated goals for pedestrian safety? 0 Have stated goals for child pedestrian safety? 0 Community advocacy level Mention community input during the 0 development of the policy? Agency staff level Reference staff or agencies responsible for 1 implementation? Elected body level Reference staff an elected or governing body 1 responsible for implementation? 0 Health Impacts Mention expected measurable health impacts?
Total score 5
280
Policy Scoring Tool Plan Bay Area 2040
Regional Indicate the level at which the policy is implemented Does the policy… Power Reference the key power people (schools)? 1 Philosophy Include a stated Vision? 1 Policy Make any statement on enforcement or 1 regulation? Indicate the responsible party for enforcement 0 or regulation? Procedure Utilize model language supporting Safe Routes 1 to School? Project List actions (planned or implemented) to 1 address pedestrian safety? Partnerships Make any statement on inter-agency 1 collaboration? Indicate partnerships for implementation? 1 Promotion Have stated goals for pedestrian safety? 0 Have stated goals for child pedestrian safety? 0 Community advocacy level Mention community input during the 1 development of the policy? Agency staff level Reference staff or agencies responsible for 1 implementation? Elected body level Reference staff an elected or governing body 1 responsible for implementation? 1 Health Impacts Mention expected measurable health impacts?
Total score 11
281
Policy Scoring Tool Miami-Dade County Compete Streets Resolution
Regional Indicate the level at which the policy is implemented Does the policy… Power Reference the key power people (schools)? 0 Philosophy Include a stated Vision? 0 Policy Make any statement on enforcement or 0 regulation? Indicate the responsible party for enforcement 0 or regulation? Procedure Utilize model language supporting Safe Routes 1 to School? Project List actions (planned or implemented) to 1 address pedestrian safety? Partnerships Make any statement on inter-agency 1 collaboration? Indicate partnerships for implementation? 1 Promotion Have stated goals for pedestrian safety? 0 Have stated goals for child pedestrian safety? 0 Community advocacy level Mention community input during the 1 development of the policy? Agency staff level Reference staff or agencies responsible for 1 implementation? Elected body level Reference staff an elected or governing body 1 responsible for implementation? 0 Health Impacts Mention expected measurable health impacts?
Total score 7
282 Miami-Dade 2040 Bicycle/Pedestrian Plan Policy Scoring Tool
Regional Indicate the level at which the policy is implemented Does the policy… Power Reference the key power people (schools)? 1 Philosophy Include a stated Vision? 1 Policy Make any statement on enforcement or 1 regulation? Indicate the responsible party for enforcement 0 or regulation? Procedure Utilize model language supporting Safe Routes 1 to School? Project List actions (planned or implemented) to 1 address pedestrian safety? Partnerships Make any statement on inter-agency 1 collaboration? Indicate partnerships for implementation? 1 Promotion Have stated goals for pedestrian safety? 1 Have stated goals for child pedestrian safety? 1 Community advocacy level Mention community input during the 1 development of the policy? Agency staff level Reference staff or agencies responsible for 0 implementation? Elected body level Reference staff an elected or governing body 0 responsible for implementation? 1 Health Impacts Mention expected measurable health impacts?
Total score 11
283 The 2016-2040 Columbus Metropolitan Transportation Policy Scoring Tool Plan
Regional Indicate the level at which the policy is implemented Does the policy… Power Reference the key power people (schools)? 1 Philosophy Include a stated Vision? 0 Policy Make any statement on enforcement or 0 regulation? Indicate the responsible party for enforcement 0 or regulation? Procedure Utilize model language supporting Safe Routes 1 to School? Project List actions (planned or implemented) to 1 address pedestrian safety? Partnerships Make any statement on inter-agency 1 collaboration? Indicate partnerships for implementation? 1 Promotion Have stated goals for pedestrian safety? 0 Have stated goals for child pedestrian safety? 0 Community advocacy level Mention community input during the 1 development of the policy? Agency staff level Reference staff or agencies responsible for 0 implementation? Elected body level Reference staff an elected or governing body 1 responsible for implementation? 1 Health Impacts Mention expected measurable health impacts?
Total score 8
284 Mid-Ohio Regional Planning Commission Complete Policy Scoring Tool Streets Policy
Regional Indicate the level at which the policy is implemented Does the policy… Power Reference the key power people (schools)? 1 Philosophy Include a stated Vision? 1 Policy Make any statement on enforcement or 1 regulation? Indicate the responsible party for enforcement 1 or regulation? Procedure Utilize model language supporting Safe Routes 1 to School? Project List actions (planned or implemented) to 1 address pedestrian safety? Partnerships Make any statement on inter-agency 1 collaboration? Indicate partnerships for implementation? 0 Promotion Have stated goals for pedestrian safety? 1 Have stated goals for child pedestrian safety? 0 Community advocacy level Mention community input during the 0 development of the policy? Agency staff level Reference staff or agencies responsible for 1 implementation? Elected body level Reference staff an elected or governing body 1 responsible for implementation? 0 Health Impacts Mention expected measurable health impacts?
Total score 10
285
Policy Scoring Tool San Francisco Pedestrian Safety Strategy
Local Indicate the level at which the policy is implemented Does the policy… Power Reference the key power people (schools)? 1 Philosophy Include a stated Vision? 1 Policy Make any statement on enforcement or 1 regulation? Indicate the responsible party for enforcement 1 or regulation? Procedure Utilize model language supporting Safe Routes 1 to School? Project List actions (planned or implemented) to 1 address pedestrian safety? Partnerships Make any statement on inter-agency 1 collaboration? Indicate partnerships for implementation? 1 Promotion Have stated goals for pedestrian safety? 0 Have stated goals for child pedestrian safety? 1 Community advocacy level Mention community input during the 1 development of the policy? Agency staff level Reference staff or agencies responsible for 1 implementation? Elected body level Reference staff an elected or governing body 1 responsible for implementation? 1 Health Impacts Mention expected measurable health impacts?
Total score 13
286 Bicycle and Pedestrian Mobility Plan for the City of Policy Scoring Tool Miami Gardens
Local Indicate the level at which the policy is implemented Does the policy… Power Reference the key power people (schools)? 1 Philosophy Include a stated Vision? 1 Policy Make any statement on enforcement or 0 regulation? Indicate the responsible party for enforcement 0 or regulation? Procedure Utilize model language supporting Safe Routes 1 to School? Project List actions (planned or implemented) to 1 address pedestrian safety? Partnerships Make any statement on inter-agency 1 collaboration? Indicate partnerships for implementation? 1 Promotion Have stated goals for pedestrian safety? 1 Have stated goals for child pedestrian safety? 0 Community advocacy level Mention community input during the 1 development of the policy? Agency staff level Reference staff or agencies responsible for 1 implementation? Elected body level Reference staff an elected or governing body 0 responsible for implementation? 0 Health Impacts Mention expected measurable health impacts?
Total score 9
287 Sustainable Opa-Locka 2030 Comprehensive Policy Scoring Tool Development Master Plan
Local Indicate the level at which the policy is implemented Does the policy… Power Reference the key power people (schools)? 1 Philosophy Include a stated Vision? 1 Policy Make any statement on enforcement or 0 regulation? Indicate the responsible party for enforcement 1 or regulation? Procedure Utilize model language supporting Safe Routes 1 to School? Project List actions (planned or implemented) to 1 address pedestrian safety? Partnerships Make any statement on inter-agency 1 collaboration? Indicate partnerships for implementation? 0 Promotion Have stated goals for pedestrian safety? 1 Have stated goals for child pedestrian safety? 1 Community advocacy level Mention community input during the 1 development of the policy? Agency staff level Reference staff or agencies responsible for 1 implementation? Elected body level Reference staff an elected or governing body 1 responsible for implementation? 0 Health Impacts Mention expected measurable health impacts?
Total score 11
288
Policy Scoring Tool Village of Key Biscayne Master Plan
Local Indicate the level at which the policy is implemented Does the policy… Power Reference the key power people (schools)? 1 Philosophy Include a stated Vision? 0 Policy Make any statement on enforcement or 0 regulation? Indicate the responsible party for enforcement 0 or regulation? Procedure Utilize model language supporting Safe Routes 1 to School? Project List actions (planned or implemented) to 1 address pedestrian safety? Partnerships Make any statement on inter-agency 1 collaboration? Indicate partnerships for implementation? 1 Promotion Have stated goals for pedestrian safety? 1 Have stated goals for child pedestrian safety? 1 Community advocacy level Mention community input during the 0 development of the policy? Agency staff level Reference staff or agencies responsible for 0 implementation? Elected body level Reference staff an elected or governing body 1 responsible for implementation? 0 Health Impacts Mention expected measurable health impacts?
Total score 8
289
Policy Scoring Tool Homestead Transportation and Transit Master Plan
Local Indicate the level at which the policy is implemented Does the policy… Power Reference the key power people (schools)? 1 Philosophy Include a stated Vision? 1 Policy Make any statement on enforcement or 0 regulation? Indicate the responsible party for enforcement 0 or regulation? Procedure Utilize model language supporting Safe Routes 1 to School? Project List actions (planned or implemented) to 1 address pedestrian safety? Partnerships Make any statement on inter-agency 1 collaboration? Indicate partnerships for implementation? 1 Promotion Have stated goals for pedestrian safety? 1 Have stated goals for child pedestrian safety? 0 Community advocacy level Mention community input during the 1 development of the policy? Agency staff level Reference staff or agencies responsible for 1 implementation? Elected body level Reference staff an elected or governing body 1 responsible for implementation? 0 Health Impacts Mention expected measurable health impacts?
Total score 10
290
Policy Scoring Tool City of Doral 2010 Transportation Master Plan
Local Indicate the level at which the policy is implemented Does the policy… Power Reference the key power people (schools)? 1 Philosophy Include a stated Vision? 0 Policy Make any statement on enforcement or 0 regulation? Indicate the responsible party for enforcement 1 or regulation? Procedure Utilize model language supporting Safe Routes 1 to School? Project List actions (planned or implemented) to 1 address pedestrian safety? Partnerships Make any statement on inter-agency 1 collaboration? Indicate partnerships for implementation? 0 Promotion Have stated goals for pedestrian safety? 1 Have stated goals for child pedestrian safety? 0 Community advocacy level Mention community input during the 1 development of the policy? Agency staff level Reference staff or agencies responsible for 1 implementation? Elected body level Reference staff an elected or governing body 1 responsible for implementation? 0 Health Impacts Mention expected measurable health impacts?
Total score 9
291
Policy Scoring Tool City of North Miami Transportation Master Plan
Local Indicate the level at which the policy is implemented Does the policy… Power Reference the key power people (schools)? 1 Philosophy Include a stated Vision? 1 Policy Make any statement on enforcement or 0 regulation? Indicate the responsible party for enforcement 1 or regulation? Procedure Utilize model language supporting Safe Routes 1 to School? Project List actions (planned or implemented) to 1 address pedestrian safety? Partnerships Make any statement on inter-agency 1 collaboration? Indicate partnerships for implementation? 1 Promotion Have stated goals for pedestrian safety? 1 Have stated goals for child pedestrian safety? 1 Community advocacy level Mention community input during the 1 development of the policy? Agency staff level Reference staff or agencies responsible for 0 implementation? Elected body level Reference staff an elected or governing body 1 responsible for implementation? 0 Health Impacts Mention expected measurable health impacts?
Total score 11
292
Policy Scoring Tool Columbus Complete Streets Resolution
Local Indicate the level at which the policy is implemented Does the policy… Power Reference the key power people (schools)? 0 Philosophy Include a stated Vision? 0 Policy Make any statement on enforcement or 0 regulation? Indicate the responsible party for enforcement 0 or regulation? Procedure Utilize model language supporting Safe Routes 1 to School? Project List actions (planned or implemented) to 1 address pedestrian safety? Partnerships Make any statement on inter-agency 0 collaboration? Indicate partnerships for implementation? 0 Promotion Have stated goals for pedestrian safety? 1 Have stated goals for child pedestrian safety? 1 Community advocacy level Mention community input during the 0 development of the policy? Agency staff level Reference staff or agencies responsible for 1 implementation? Elected body level Reference staff an elected or governing body 0 responsible for implementation? 0 Health Impacts Mention expected measurable health impacts?
Total score 5
293
Policy Scoring Tool Columbus Pedestrian Thoroughfare Plan
Local Indicate the level at which the policy is implemented Does the policy… Power Reference the key power people (schools)? 1 Philosophy Include a stated Vision? 0 Policy Make any statement on enforcement or 0 regulation? Indicate the responsible party for enforcement 0 or regulation? Procedure Utilize model language supporting Safe Routes 1 to School? Project List actions (planned or implemented) to 1 address pedestrian safety? Partnerships Make any statement on inter-agency 0 collaboration? Indicate partnerships for implementation? 0 Promotion Have stated goals for pedestrian safety? 1 Have stated goals for child pedestrian safety? 0 Community advocacy level Mention community input during the 0 development of the policy? Agency staff level Reference staff or agencies responsible for 0 implementation? Elected body level Reference staff an elected or governing body 0 responsible for implementation? 0 Health Impacts Mention expected measurable health impacts?
Total score 4
294
Policy Scoring Tool MDCPS Wellness Policy
District Indicate the level at which the policy is implemented Does the policy… Power Reference the key power people (schools)? 1 Philosophy Include a stated Vision? 0 Policy Make any statement on enforcement or 1 regulation? Indicate the responsible party for enforcement 1 or regulation? Procedure Utilize model language supporting Safe Routes 0 to School? Project List actions (planned or implemented) to 0 address pedestrian safety? Partnerships Make any statement on inter-agency 1 collaboration? Indicate partnerships for implementation? 1 Promotion Have stated goals for pedestrian safety? 0 Have stated goals for child pedestrian safety? 0 Community advocacy level Mention community input during the 1 development of the policy? Agency staff level Reference staff or agencies responsible for 1 implementation? Elected body level Reference staff an elected or governing body 1 responsible for implementation? 0 Health Impacts Mention expected measurable health impacts?
Total score 8
295
Policy Scoring Tool SFUSD Wellness Policy
District Indicate the level at which the policy is implemented Does the policy… Power Reference the key power people (schools)? 1 Philosophy Include a stated Vision? 0 Policy Make any statement on enforcement or 1 regulation? Indicate the responsible party for enforcement 1 or regulation? Procedure Utilize model language supporting Safe Routes 1 to School? Project List actions (planned or implemented) to 1 address pedestrian safety? Partnerships Make any statement on inter-agency 1 collaboration? Indicate partnerships for implementation? 1 Promotion Have stated goals for pedestrian safety? 1 Have stated goals for child pedestrian safety? 1 Community advocacy level Mention community input during the 1 development of the policy? Agency staff level Reference staff or agencies responsible for 1 implementation? Elected body level Reference staff an elected or governing body 1 responsible for implementation? 1 Health Impacts Mention expected measurable health impacts?
Total score 13
296
Policy Scoring Tool CCS Comprehensive Wellness Policy
District Indicate the level at which the policy is implemented Does the policy… Power Reference the key power people (schools)? 1 Philosophy Include a stated Vision? 0 Policy Make any statement on enforcement or 0 regulation? Indicate the responsible party for enforcement 0 or regulation? Procedure Utilize model language supporting Safe Routes 0 to School? Project List actions (planned or implemented) to 0 address pedestrian safety? Partnerships Make any statement on inter-agency 1 collaboration? Indicate partnerships for implementation? 1 Promotion Have stated goals for pedestrian safety? 0 Have stated goals for child pedestrian safety? 0 Community advocacy level Mention community input during the 1 development of the policy? Agency staff level Reference staff or agencies responsible for 1 implementation? Elected body level Reference staff an elected or governing body 1 responsible for implementation? 0 Health Impacts Mention expected measurable health impacts?
Total score 6
297