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. Author manuscript; available in PMC: 2013 Jan 1.
Published in final edited form as: Health Place. 2012 Jan;18(1):24–30. doi: 10.1016/j.healthplace.2011.07.004

Impact of a Pilot Walking School Bus Intervention on Children’s Pedestrian Safety Behaviors: A Pilot Study

Jason A Mendoza a,b,c,*, Kathy Watson a,1, Tzu-An Chen a, Tom Baranowski a,c, Theresa A Nicklas a,c, Doris K Uscanga a, Marcus J Hanfling b,d
PMCID: PMC3259456  NIHMSID: NIHMS328090  PMID: 22243904

Abstract

Walking school buses (WSB) increased children’s physical activity, but impact on pedestrian safety behaviors (PSB) is unknown. We tested the feasibility of a protocol evaluating changes to PSB during a WSB program. Outcomes were school-level street crossing PSB prior to (Time 1) and during weeks 4-5 (Time 2) of the WSB. The protocol collected 1252 observations at Time 1 and 2548 at Time 2. Mixed model analyses yielded: intervention schoolchildren had 5-fold higher odds (p<0.01) of crossing at the corner/crosswalk but 5-fold lower odds (p<0.01) of stopping at the curb. The protocol appears feasible for documenting changes to school-level PSB.

Keywords: Walking School Bus, Safe Routes to School, Injury Prevention, Active Commuting to School, Pedestrian Safety, Neighborhood Safety

Introduction

Encouraging physical activity among youth is important for addressing the rising rates of childhood obesity worldwide (Wang and Lobstein, 2006; World Health Organization, 2010). Reports on children’s active commuting to school (walking or cycling to school, henceforth termed active commuting) to improve children’s physical activity appear promising. Epidemiological studies from multiple countries have reported positive associations between children’s active commuting and total daily physical activity including from England (Cooper et al., 2003), Scotland (Alexander et al., 2005), Australia (Spinks et al., 2006), Germany (Landsberg et al., 2007), Canada (Loucaides et al., 2007), and the United States (Mendoza et al., 2011; Saksvig et al., 2007; Sirard et al., 2005). Active commuting is the main behavior of interest for the Safe Routes to School (SRTS) Program, which originated in Denmark (Brown et al., 2007), and in the US promotes walking and bicycling to school safely by primary and middle school students through improvements to schools’ walking environments and promotional activities (Brown et al., 2007).

The “walking school bus” (WSB) program is an integral part of SRTS programs (National Center for Safe Routes to School, 2006). A WSB is a group of children that walks to and from school with parents or other adults, in which the children are picked up throughout the neighborhood. WSB programs have the potential to improve children’s pedestrian safety behaviors through two main mechanisms: (1) walking with an adult decreases children’s pedestrian risk by almost 70% (Roberts, 1995) and (2) adult leaders can teach and model safe street crossing behaviors on the way to and from school. Children’s pedestrian safety is important to promoting active commuting, since it influences parents’ decisions on their children’s active commuting (Dellinger and Staunton, 2002; Martin and Carlson, 2005). Moreover, pedestrian injuries are an important contributor of pediatric unintentional injuries, which are the leading cause of mortality among children aged 1-19 years (National Center for Injury Prevention and Control, 2010). Improving children’s pedestrian safety behaviors could be an additional important benefit of WSBs, besides increasing children’s active commuting and physical activity. A previous systematic review of randomized controlled trials (RCTs) on pedestrian safety programs concluded that these education programs, some that directly targeted children and others that targeted parents, have shown promise for increasing knowledge and pedestrian behaviors (Duperrex et al., 2009). While preliminary evaluations of WSB and similar walk to school programs in Scotland (McKee et al., 2007) and the US (Heelan et al., 2009; Mendoza et al., 2009; Sirard et al., 2008; Staunton et al., 2003) have reported improving rates of children’s active commuting, WSB studies evaluating pedestrian safety behaviors are lacking. As recommended for pilot studies, in which the main goal is to test feasibility of a research protocol (Arain et al., 2010; Kraemer et al., 2006; Leon et al., 2011), the goal of this pilot study was to evaluate the feasibility of a protocol to measure changes to children’s pedestrian safety behaviors at the school-level associated with a WSB program. A secondary goal was to evaluate the potential influence of the WSB program, neighborhood safety, and intersection characteristics on children’s pedestrian safety behaviors at the school-level.

Methods

Design

This pilot study on children’s pedestrian safety behaviors was conducted as part of a cluster RCT of a WSB program among low-income 4th grade elementary schoolchildren, in which significant increases in children’s active commuting and moderate-to-vigorous physical activity were reported elsewhere (Mendoza et al., 2011). A full description of methods for that study including the related CONSORT flow diagram have been reported in detail (Mendoza et al., 2011; Mendoza et al., 2010b). Briefly, 4th grade children were enrolled (26.1% of all 4th graders) and baseline outcomes were assessed prior to random assignment of schools to a study condition. All enrolled 4th grade children agreed to participate in the WSB program if their school was randomly assigned to the intervention condition. During the 4-5 week intervention period, the intervention children made 20.9 +/− 13.4 trips by active commuting (Mendoza et al., 2011). For the present study, children’s pedestrian safety behaviors assessed at major school intersections were the primary outcome of interest and anonymously measured among all child pedestrians (regardless of grade-level) approaching study schools as described below. Schools were matched by race/ethnicity and socioeconomic status (percent of children who qualified for the US federal free/reduced price lunch program) and then randomly assigned within school pairs to intervention (n=4) or control (n=4) conditions. Time 1 measurements occurred prior to both random assignment and implementation of the intervention in March 2009. Time 2 measurements occurred during weeks 4-5 of the intervention. Participants and research staff at Time 2 were not blinded to the assignment of schools to the intervention, since it was a behavioral program. This study received approval through the Institutional Review Board of Baylor College of Medicine and the Department of Research and Accountability of the Houston Independent School District. This study was registered on clinicaltrials.gov and the identifier number is NCT00758615.

Setting

The setting was elementary schools from the Houston Independent School District (HISD) located in Houston, TX, which is the 4th largest city in the US (Planning and Development Department). Schools were recruited from HISD based on having >75% of children qualified for the free/reduced lunch program (a proxy for school socioeconomic status), responding to a district-wide letter describing the study, and informal observations on the schools’ walking environments, i.e. street connectivity, road traffic/presence of arterial roads, and sidewalk conditions.

Intervention

The walking school bus program at each intervention school was based on publicly available guidelines issued by the US National Center for Safe Routes to School (National Center for Safe Routes to School, 2006). Intervention schools had one to three WSB routes organized around children’s home residences. Study staff walked the 4th grade participants to and from school up to five days per week, although the children and parents decided when the children participated. Study staff underwent a 4-hour classroom and field-based training on the WSB and pedestrian safety led by the study investigators. Staff members were expected to model, teach, and be evaluated on teaching the following pedestrian safety behaviors during the walk to and from school: 1) crossed at a corner or crosswalk, 2) crossed with an adult or safety patrol, 3) stopped at the curb, 4) looked left-right-left, and 5) walked and did not run across the street. These behaviors were selected from previous child pedestrian injury prevention studies (Rivara et al., 1991; Rosenbloom et al., 2008; Zeedyk and Kelly, 2003; Zeedyk et al., 2002) and were theorized to be related to pedestrian injuries, although direct links have not been established. Children were postulated to learn the pedestrian safety behaviors through observational learning (Bandura, 1976), i.e. by observing staff members properly crossing a street, and by direct teaching and reinforcement of those behaviors by the staff to the children. Direct teaching and reinforcement occurred by having the children take turns co-leading the walking groups and helping the adult staff to decide when to cross the street safely. Siblings who attended the same school as the 4th grade WSB participants were allowed to walk with the WSBs as a practical measure. Parents were encouraged but not required to walk with the WSBs. Study staff and WSB children wore bright fluorescent safety vests during the intervention period. WSB routes had approximately 8-12 children for every two staff members and averaged 0.8 miles in total length. No intervention was conducted at the control schools, which only received the usual information provided by HISD on school transportation options. The intervention and control conditions were launched simultaneously in March 2009, after Time 1 assessments, and continued for five weeks.

Outcome variables

Crossing a street is one of the most vulnerable acts for child pedestrians (Hotz et al., 2009), and children’s pedestrian safety behaviors related to crossing a street were measured by trained research assistants using a previously validated observational instrument (Mendoza et al., 2010a). Children of all grade levels were unobtrusively observed at major intersections at each school for completion (yes/no) of five street crossing behaviors listed in the Intervention subsection above. Each of the five street crossing behaviors (yes=1; no=0) and a composite score (the sum from 0-5 of the five behaviors) were determined for each school. Among low-income elementary schoolchildren in HISD, this instrument had acceptable sensitivity (85%), specificity (83%), high percent agreement (91%), and moderate reliability (for the composite score, r=0.55, p<0.01) comparing trained research assistants with an expert observer (Mendoza et al., 2010a). The pedestrian safety behaviors were observed during Time 1 (before the intervention) and Time 2 (during weeks 4 and 5 of the intervention) before the start of the school day. Research assistants were instructed not to interact with the child pedestrians, which precluded the collection of individual-level sociodemographic data including names. Therefore the pedestrian safety data reflect child pedestrians of any grade level (kindergarten – 5th grade) approaching the study schools; i.e. these were school-level, cross-sectional observations, and were not limited to 4th grade children enrolled in the WSB study.

Covariates

At each of the major intersections where research assistants scored the child pedestrians’ street crossing behaviors, research assistants also noted the number of lanes of traffic, defined as lanes that pedestrians may cross and where motor vehicles either continue through the intersection or turn left or right. A weighted average of the number of lanes of traffic for each school was used in analyses, based on the numbers of children observed at that intersection. As an exploratory hypothesis, we believed that traffic lanes would be inversely associated with pedestrian safety behaviors. We based this hypothesis on the postulation that with greater traffic lanes, the complexity of crossing the street would increase and thereby result in greater opportunities for error.

Parents of the 4th grade children enrolled in the WSB study at the intervention and control schools completed questions on their perceptions of neighborhood safety using the Disorder subscale of the Neighborhood Environment for Children Rating Scales at Time 1. This subscale was composed of items on which parents rated the family’s neighborhood for safety, violence, drug traffic, and child victimization (Coulton et al., 1996). Among previous urban samples, the subscale had acceptable internal consistency (Cronbach’s alpha = 0.95), reliability (generalizability coefficient = 0.84), and discriminated between high and low risk neighborhoods (p<0.01) with regard to child maltreatment rates (Coulton et al., 1996). The subscale was reported to be inversely related to children’s television viewing in a large national US study (Burdette and Whitaker, 2005). The parents’ scores for this subscale were combined and averaged for each school to produce a school-level rating. As an exploratory hypothesis, we believed that neighborhood disorder would be inversely associated with pedestrian safety behaviors.

Statistical Analysis

Frequencies and percentages were used to describe school characteristics and the prevalence of the pedestrian safety behaviors. To assess the feasibility of the protocol for measuring changes to children’s pedestrian safety associated with the WSB program, we expected to conduct pedestrian safety observations on at least ½ of all active commuters at the study schools, i.e. 17% of weekly trips (Mendoza et al., 2011). Therefore, the protocol was considered feasible if we collected observational data on at least 798 children/week crossing a major school intersection each at Time 1 and Time 2. For the unadjusted bivariate analyses between children’s pedestrian safety behaviors and the average number of traffic lanes for the intersections or parents’ perceptions of neighborhood safety, we used: 1) the point-biserial correlation for the relationship between binary (the individual item scores for the pedestrian safety behaviors) and interval variables (traffic lanes or neighborhood safety) and 2) the Pearson correlation to determine the relationship between interval variables (the composite pedestrian safety behaviors score, traffic lanes, and neighborhood safety). To compare intervention versus control schools for each of the children’s pedestrian safety behaviors and the composite pedestrian safety scores, we used generalized mixed model analyses and mixed model analyses, respectively. Because children in the same school shared similar characteristics, the outcomes of interest could be influenced by the schools themselves. Therefore, children (level one) were considered nested within schools (level two). In addition, since the data was collected on different groups of children at each assessment point, we cannot match Time 1 and Time 2 data at the child-level. Hence, time was treated as a between groups factor. For these models, school was a random and time was a fixed effect. The average number of traffic lanes for the intersections observed and parents’ perception of neighborhood safety were school-level covariates.

Results

The eight study schools were selected from a total of 15 HISD elementary schools that expressed initial interest in the study after a district-wide solicitation announcement. Schools were excluded based on the following criteria: inability to accommodate the study and measurements (n=3) or poor walking environments, e.g. no sidewalks, low street connectivity, and major arterial roads/highways adjacent to the school (n=4). All eight schools completed the study. School-level characteristics provided by the district are reported in Table 1 (Information Services, 2009).

Table 1.

School demographics by intervention and control conditions.1

Enrollment Hispanic (%) African-
American (%)		 Free/Reduced
Price Lunch (%)		 Academic Rating
Intervention
Schools
A 701 78 13 84 Exemplary
B 935 94 4 95 Recognized
C 471 8 92 94 Recognized
D 580 43 50 84 Exemplary
Control Schools
A 490 92 8 93 Exemplary
B 506 93 5 97 Exemplary
C 492 7 92 95 Recognized
D 521 59 41 98 Exemplary
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1

Provided by the Houston Independent School District (HISD) for the 2008-2009 school year. Academic ratings were based on the Texas Education Agency Accountability System, which rated schools according to four categories (Exemplary, Recognized, Acceptable, and Unacceptable) based on school-wide performance on standardized test scores, rates of completing grades, and dropouts. Paired schools share the same letter in lieu of their actual names, as requested by HISD.

As the main indication of the feasibility of the protocol to collect data on children’s pedestrian safety behaviors, we successfully recorded 1252 observations at Time 1 and 2548 observations at Time 2. Both were well above the threshold of 798 observations that was based on observing at least ½ of all child pedestrians’ weekly trips at Time 1.

In unadjusted analyses at Time 1, there were no differences in the prevalence of the pedestrian safety behaviors at the intervention compared to the control schools (all p > 0.05). Also at Time 1, the number of traffic lanes at each intersection was negatively associated with the composite score of children’s pedestrian safety behaviors (r = −0.14, p < 0.01, Table 2). Examining the behaviors individually, with increasing traffic lanes, fewer children stopped at the curb (r = −0.26, p < 0.01). The number of traffic lanes was not significantly associated with any of the other pedestrian safety behaviors (all p > 0.05).

Table 2.

Prevalence (95% confidence intervals) of children’s pedestrian safety behaviors, and the unadjusted correlations between neighborhood safety or traffic lanes and the behaviors.1,2,3

Prevalence (%)

at Time 1
(n=1252)		 Correlation to Traffic
Lanes
at Time 1
(n=1252)		 Correlation to
Neighborhood Safety
at Time 1
(n=1252)
Composite Score, mean (s.d.) or
correlations		 2.8 (0.9) −0.14**(−0.19,−0.09) −0.01 (−0.06, 0.05)
Crossed at a corner/crosswalk 77.2 (74.8, 79.4) 0.004 (−0.05, 0.06) 0.08**(0.02, 0.13)
Crossed with an adult or safety patrol 91.6(90.1,93.2) 0.001 (−0.05, 0.06) 0.08**(0.02, 0.13)
Stopped at the curb 37.0 (34.3, 39.7) −0.26 **(−0.31,−0.20) −0.09**(−0.15, −0.04)
Looked left-right-left 2.6(1.7,3.4) 0.01(−0.05, 0.07) −0.04(−0.09, 0.02)
Walked (did not run) across the street 75.8 (73.4, 78.2) −0.01 (−0.07, 0.04) −0.03 (−0.08, 0.03)
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1

Significant correlation to Traffic Lanes or Neighborhood Safety at Time 1 effects at p < 0.05 (*) and p < 0.01 (**). Point-biserial correlation and Pearson correlation were used for individual street crossing behaviors and the composite score, respectively.

In unadjusted analyses at Time 1, parents’ perceptions of neighborhood safety, measured by the Disorder subscale, was not related to the composite score of children’s pedestrian safety behaviors (Table 2, p > 0.05). Examining the pedestrian safety behaviors individually, with greater neighborhood disorder, more children crossed at a corner or crosswalk (r=0.08, p < 0.01), more crossed with an adult or safety patrol (r = 0.08. p < 0.01), and fewer children stopped at the curb (r = −0.09, p < 0.01).

The intracluster correlation coefficients for the pedestrian safety behaviors ranged from 0.02 to 0.53 (Table 3), which reflects wide variability in the clustering of the behaviors within schools. The generalized mixed model analyses yielded significant group by time effects for the WSB on some pedestrian safety behaviors (Table 3). Compared to child pedestrians observed at the control schools, child pedestrians at the intervention schools had a five-fold higher odds of crossing at the corner or crosswalk (OR = 5.01, 95% CI [2.79, 8.99], p < 0.01) and five-fold lower odds of stopping at the curb versus controls (OR = 0.21, 95% CI [0.15, 0.31], p < 0.01). There were no significant relationships with the composite score or any of the other pedestrian safety behaviors (all p > 0.05). Both neighborhood disorder and number of traffic lanes were not significantly associated with the pedestrian safety outcomes (all p > 0.05) in the mixed models.

Table 3.

Odds ratios (95% confidence intervals) for the school-level child pedestrian safety behaviors (n=2548 observations).1

Intraclu
ster
Correla
tion		 Model
Fit		 Group Time Group*Tim
e		 School-level
Neighborhood Safety		 School
Intersec
tion
Traffic
Lanes
Composite Score b** 0.16 0.31 (−0.34,
0.95)		 0.30 (0.18,
0.41)		 −0.05 (−0.20,
0.10)		 0.03 (−0.10, 0.15) −0.09 (−
0.35,
0.18)
Crossed at a
corner/crosswalkb**, c**		 0.18 1.01 2.45 (0.61,
9.85)		 1.55 (1.15,
2.09)		 5.01 (2.79,
8.99)		 1.10 (0.85, 1.43) 0.97
(0.54,
1.74)
Crossed with an adult or
safety patrolb**		 0.53 1.15 1.30 (0.06,
27.90)		 0.32 (0.21,
0.49)		 1.77 (0.99,
3.18)		 1.19 (0.67, 2.12) 0.83
(0.23,
2.94)
Stopped at the curbb**, c** 0.25 0.99 4.06 (0.76,
21.81)		 3.21 (2.41,
4.28)		 0.21 (0.15,
0.31)		 1.06 (0.77, 1.45) (0.33,
1.35)
Looked left-right-leftb** 0.24 0.99 1.86 (0.32,
10.97)		 5.15 (2.75,
9.67)		 1.21 (0.54,
2.74)		 1.00 (0.74, 1.39) 0.69
(0.35,
1.38)
Walked (did not run)
across the street		 0.02 1.00 0.67 (0.41,
1.10)		 1.22 (0.89,
1.65)		 1.47 (0.98,
2.20)		 0.96 (0.89, 1.05) 0.91
(1.34,
1.10)
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1

Odds ratios for Group (a), Time (b), and Group by Time (c) effects at p < 0.05(*) and p < 0.01(**). The reference group is comprised of the control schools.

Discussion

To complement the growing literature on the contribution of WSB programs to children’s active commuting to school, we report the feasibility of a protocol to collect school-level pedestrian safety observations during a pilot WSB RCT. Although the protocol was determined to be feasible at collecting fairly comprehensive school-level data, the cross-sectional design did not allow for the longitudinal tracking of individual-level pedestrian safety behaviors. Individual-level data, albeit more logistically complex to collect, would be more useful to demonstrate longitudinal changes to pedestrian safety behaviors, especially since the intervention was solely targeted at 4th grade students and not the entire school populations. However, these school-level observations resulted in the collection of “real world” observations on children’s street crossing behaviors, which may differ from artificial or investigator-manipulated street crossing scenarios. Future studies should consider strategies for unobtrusively identifying study participants as they commute to school, e.g. requiring enrolled participants (both intervention and control) to wear bright vests, each with a highly visible unique ID number, during the assessment periods so that longitudinal individual-level measurements can be collected.

In exploratory analyses, the mixed model showed no effect on the composite score for the pedestrian safety behaviors; however, there were associations with some individual item scores. The intervention schools had a five-fold improvement in child pedestrians crossing at the corner or crosswalk, i.e. at intersections where they can generally be seen by traffic versus non-intersection/mid-block locations. Since the majority (74-82%) of US child pedestrian fatalities from 2001-2009 occurred at non-intersection locations (National Center for Statistics and Analysis, 2011), decreasing non-intersection crossings may help address this important source of childhood mortality. In contrast, the intervention schools had an unexpected decrease in child pedestrians stopping at the curb. For this behavior, only children who fully stopped at the curb prior to entering the street were scored as completing the behavior; children who slowed down but did not fully stop were scored as not completing the behavior. We speculate that for some children, it may be impractical to fully stop at the curb when there is limited time to cross the street, as is the case for children walking in a group such as with the WSB. The overall prevalence of children crossing with an adult or safety patrol was high (>87% at Time 1 and 2), which may also make it impractical for the children to fully stop at the curb if they were being directed to cross the street by an adult or safety patrol. Taken together, these conditions may result in fewer children stopping completely at the curb. Thus, the general recommendation or criterion for all child pedestrians to fully stop at the curb may not be applicable to children who cross the street and are being directed to cross by an adult or safety patrol as in a WSB. Additionally, most children regardless of study condition (>75% at Time 1 and 2) walked and did not run across the street. Walking across the street likely reduced their risk of injury resulting from “darting out” or running into the roadway, a behavior related to 12% of US pedestrian deaths from 1997-2005 (Chang, 2008). Further study is necessary to confirm these findings and examine them in the context of traffic conditions and other pedestrian safety behaviors.

These exploratory short-term results are consistent with several previous randomized controlled trials of child pedestrian safety programs that reported modest or mixed results from a systematic review updated in 2009 (Duperrex et al., 2009). Present results also build upon other child pedestrian safety studies, many of which had larger effects, but were not randomized controlled trials (Barton et al., 2007; Demetre and Lee, 1992; Glang et al., 2005; Gresham et al., 2001; Hotz et al., 2004; Preusser and Lund, 1988; Rivara et al., 1991; Rothengatter, 1984; Young and Lee, 1987) or relied on children’s self-reports of their pedestrian safety rather than on observations of the behaviors (Berry and Romo, 2006; Gresham et al., 2001; Morrongiello and Kiriakou, 2006).

While most parents agree that children should be taught pedestrian safety skills, few parents actually teach those skills to their children while crossing the street (Morrongiello and Barton, 2009; Zeedyk and Kelly, 2003). The WSB provides an opportunity for parents and other adults to repeatedly teach and model pedestrian safety to children on the walk to and from school. There are several safety-related advantages to the WSB program in addition to promoting active commuting to school: (1) pedestrian safety education occurs during the children’s commute to school, which provides for practical, frequent, real world lessons; (2) the intervention specifically targets children who walk to and from school and who are thereby at risk for pedestrian injuries, and (3) the intervention takes place before and after school and does not interfere with classroom time. The main disadvantages are related to (1) program implementation, which can be logistically difficult among low-income families or low-resource schools; (2) program availability, which can be limited since only a proportion of children regularly participated in WSB programs (Mendoza et al., 2009); however, the WSB program could be used with other promising pedestrian safety programs to improve child pedestrian safety, such as computer-based or virtual reality programs that potentially have wide reach (McComas et al., 2002; Schwebel and McClure, 2010; Thomson et al., 2005; Tolmie et al., 2005); and (3) the potential for children to become reliant on adults to safely cross the street. This reliance on adults may be mitigated by allowing children to co-lead the walking groups and encouraging older children to independently walk to school when developmentally appropriate, i.e. older children “graduate” from the WSB program.

In unadjusted analyses, the number of traffic lanes at school intersections was negatively associated with the composite score of children’s pedestrian safety behaviors. This relationship was entirely driven by the negative association between traffic lanes and children stopping at the curb: with more traffic lanes, fewer children fully stopped at the curb before crossing the street, perhaps due to the greater distance involved in crossing the street, greater traffic volume associated with larger streets, and the constraint of crossing a larger distance during a time-limited opportunity. Similarly, in unadjusted analyses, parents’ perceptions of neighborhood safety were significantly but weakly correlated with children’s pedestrian safety behaviors: with greater neighborhood disorder, children were slightly more likely to cross at a corner or crosswalk and cross with an adult or safety patrol, but slightly less likely to stop at the curb. Given the very small associations, these findings are likely not clinically significant. To our knowledge, this is the first study to examine the relationship between parents’ perception of neighborhood safety and children’s pedestrian safety behaviors. These preliminary bivariate results are informed by parallel studies conducted in Australia and the US examining neighborhood built environment or safety and childhood obesity or physical activity outcomes (Carver et al., 2010; Grow et al., 2008; Lumeng et al., 2006; Molnar et al., 2004; Timperio et al., 2005), and suggest the need for further study with additional environmental variables and adequately powered samples. Neither traffic lanes nor neighborhood safety were significantly associated with child pedestrian safety outcomes in the generalized mixed model from the present study. These null findings suggest that environmental influences on children’s pedestrian safety behaviors may be less important than the influence of other pedestrians, whether peers or adults, or the safety patrol.

Like most pilot studies, this study has limitations. First, we used cross-sectional school-level data on child pedestrians of any grade level and not longitudinal data on the 4th grade WSB study participants due to logistic complexity. This design likely diluted the impact of the intervention since many of the child pedestrians observed at intervention schools were not directly involved in the WSB program. However, this school-wide assessment approach has been used previously to examine pedestrian behaviors in the “real world” (Hotz et al., 2004). Second, generalizability may be limited since all schools were low-income, composed primarily of ethnic minority children, and located in urban settings in Houston. Third, although establishing changes to pedestrian safety behaviors during the intervention was an important first step, we do not know if the changes are generalizable outside of the walking school bus intervention. Future studies should measure pedestrian safety behaviors post-intervention, to determine sustainability of the potential behavior change. Finally, although we included data on the number of traffic lanes at each intersection and parents’ perception of neighborhood safety, we had only limited data on the neighborhood built environment, which has been associated with pedestrian injuries (LaScala et al., 2004; Newbury et al., 2008; Schuurman et al., 2009). Despite these limitations, this pilot study has a number of strengths: 1) the design was a randomized controlled trial, 2) it is among the first WSB studies to examine children’s pedestrian safety, 3) it used validated measures of pedestrian safety (Mendoza et al., 2010a) to assess children’s pedestrian safety behaviors in the field rather than relying on children’s self-reported behaviors or their safety knowledge, and 4) we conducted the study among underrepresented ethnic minority schoolchildren who have a disproportionate risk for unintentional injuries in the US (Pressley et al., 2007).

Conclusion

This pilot study demonstrated the feasibility of collecting school-level pedestrian safety behavior outcomes and changes to those outcomes during a WSB program study. In exploratory analyses, the WSB was associated with more children crossing at an intersection, but fewer children fully stopping at the curb. These mixed results suggest modification to the WSB program may be necessary in order to improve children’s pedestrian safety behaviors on the walk to and from school. Further WSB studies, preferably fully powered experimental trials that longitudinally follow participants’ pedestrian safety behaviors in the long term, should be conducted in a variety of settings among diverse populations to formally evaluate pedestrian safety and physical activity outcomes. Moreover, studies that examine the influence of the built environment, use objective measures of neighborhood safety, and consider vehicular traffic are also necessary to evaluate their influences on the WSB and children’s pedestrian safety.

Acknowledgements

We are grateful to the children and parents who participated in this study and the reviewers who provided many helpful comments to improve this work. We thank the teachers, principals, administrators, and staff of HISD, for their support and partnership in this study. This work was supported, in part, by Active Living Research of the Robert Wood Johnson Foundation (63773), the National Cancer Institute (1R21CA133418), and the Harris County Hospital District Foundation. The first author was supported, in part, by a career development award from the National Cancer Institute (1K07CA131178). This work was also supported by and is a publication of the US Department of Agriculture / Agricultural Research Service (USDA/ARS) Children’s Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, Texas, and was funded with federal funds from the USDA/ARS under Cooperative Agreement No. 58-6250-6001. The funders had no role in the study design; in the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the paper for publication. The contents of this publication do not necessarily reflect the views or policies of the funders or Baylor College of Medicine, nor does mention of trade names, commercial products, or organizations imply endorsement from the funders or Baylor College of Medicine.

Footnotes

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