Are child pedestrians at increased risk of injury on one-way compared to two-way streets?

Effectiveness of road safety interventions: An evidence and gap map

Background

Road Traffic injuries (RTI) are among the top ten leading causes of death in the world resulting in 1.35 million deaths every year, about 93% of which occur in low- and middle-income countries (LMICs). Despite several global resolutions to reduce traffic injuries, they have continued to grow in many countries. Many high-income countries have successfully reduced RTI by using a public health approach and implementing evidence-based interventions. As many LMICs develop their highway infrastructure, adopting a similar scientific approach towards road safety is crucial. The evidence also needs to be evaluated to assess external validity because measures that have worked in high-income countries may not translate equally well to other contexts. An evidence gap map for RTI is the first step towards understanding what evidence is available, from where, and the key gaps in knowledge.

Objectives

The objective of this evidence gap map (EGM) is to identify existing evidence from all effectiveness studies and systematic reviews related to road safety interventions. In addition, the EGM identifies gaps in evidence where new primary studies and systematic reviews could add value. This will help direct future research and discussions based on systematic evidence towards the approaches and interventions which are most effective in the road safety sector. This could enable the generation of evidence for informing policy at global, regional or national levels.

Search Methods

The EGM includes systematic reviews and impact evaluations assessing the effect of interventions for RTI reported in academic databases, organization websites, and grey literature sources. The studies were searched up to December 2019.

Selection Criteria

The interventions were divided into five broad categories: (a) human factors (e.g., enforcement or road user education), (b) road design, infrastructure and traffic control, (c) legal and institutional framework, (d) post-crash pre-hospital care, and (e) vehicle factors (except car design for occupant protection) and protective devices. Included studies reported two primary outcomes: fatal crashes and non-fatal injury crashes; and four intermediate outcomes: change in use of seat belts, change in use of helmets, change in speed, and change in alcohol/drug use. Studies were excluded if they did not report injury or fatality as one of the outcomes.

Data Collection and Analysis

The EGM is presented in the form of a matrix with two primary dimensions: interventions (rows) and outcomes (columns). Additional dimensions are country income groups, region, quality level for systematic reviews, type of study design used (e.g., case-control), type of road user studied (e.g., pedestrian, cyclists), age groups, and road type. The EGM is available online where the matrix of interventions and outcomes can be filtered by one or more dimensions. The webpage includes a bibliography of the selected studies and titles and abstracts available for preview. Quality appraisal for systematic reviews was conducted using a critical appraisal tool for systematic reviews, AMSTAR 2.

Main Results

The EGM identified 1859 studies of which 322 were systematic reviews, 7 were protocol studies and 1530 were impact evaluations. Some studies included more than one intervention, outcome, study method, or study region. The studies were distributed among intervention categories as: human factors (n = 771), road design, infrastructure and traffic control (n = 661), legal and institutional framework (n = 424), post-crash pre-hospital care (n = 118) and vehicle factors and protective devices (n = 111). Fatal crashes as outcomes were reported in 1414 records and non-fatal injury crashes in 1252 records. Among the four intermediate outcomes, speed was most commonly reported (n = 298) followed by alcohol (n = 206), use of seatbelts (n = 167), and use of helmets (n = 66). Ninety-six percent of the studies were reported from high-income countries (HIC), 4.5% from upper-middle-income countries, and only 1.4% from lower-middle and low-income countries. There were 25 systematic reviews of high quality, 4 of moderate quality, and 293 of low quality.

Authors' Conclusions

The EGM shows that the distribution of available road safety evidence is skewed across the world. A vast majority of the literature is from HICs. In contrast, only a small fraction of the literature reports on the many LMICs that are fast expanding their road infrastructure, experiencing rapid changes in traffic patterns, and witnessing growth in road injuries. This bias in literature explains why many interventions that are of high importance in the context of LMICs remain poorly studied. Besides, many interventions that have been tested only in HICs may not work equally effectively in LMICs. Another important finding was that a large majority of systematic reviews are of low quality. The scarcity of evidence on many important interventions and lack of good quality evidence-synthesis have significant implications for future road safety research and practice in LMICs. The EGM presented here will help identify priority areas for researchers, while directing practitioners and policy makers towards proven interventions.

Developing machine-learning-based models to diminish the severity of injuries sustained by pedestrians in road traffic incidents

An essential step in devising measures to improve road safety is road accident prediction. In particular, it is important to identify the risk factors that increase the likelihood of severe injuries in the event of an accident. There are two distinct ways of analyzing data in order to produce predictions: machine learning and statistical methods. This study explores the severity of road traffic injuries sustained by pedestrians through the use of machine-learning methodology. In general, the goal of the statistician is to model and understand the connections between variables, whereas machine learning focuses on more intricate and expansive datasets, with the aim of creating algorithms that can recognize patterns and make predictions without being explicitly programmed. The ability to handle very large datasets constitutes a distinct advantage of machine learning over statistical techniques. In addition, machine-learning models can be adapted to a wide range of data sources and problem domains, and can be utilized for numerous tasks, from image identification to natural language processing. Machine-learning models may be taught to recognize patterns and make predictions automatically, minimizing the need for manual involvement and enabling rapid data processing of enormous quantities of data. The use of new data to retrain or fine-tune a machine-learning model allows the model to adapt to changing conditions and enhances its accuracy over time. Finally, while non-linear interactions between variables can be difficult to predict using conventional statistical techniques, they can be recognized by machine-learning models. The study begins by compiling an inventory of features linked to both the accident and the environment, focusing on those that exert the greatest influence on the severity of pedestrian injuries. The "optimal" algorithm is then chosen based on its superior levels of accuracy, precision, recall, and F1 score. The developed model should not be regarded as fixed; it should be updated and retrained on a regular basis using new traffic accident data that mirror the evolving interplay between the road environment, driver characteristics, and pedestrian conduct. Having been constructed using Israeli data, the current model is predictive of injury outcomes within Israel. For broader applicability, the model should undergo retraining and reassessment using traffic accident data from the pertinent country or region.

Using ordered and unordered logistic regressions to investigate risk factors associated with pedestrian crash injury severity in Victoria, Australia

INTRODUCTION

The safety of pedestrians is a major concern in Victoria, Australia. Despite the considerable number of pedestrian fatalities and injuries in traffic crashes, a limited number of studies focused on pedestrian crash severity in Victoria.

METHODS

This study investigates and identifies the influential factors determining the severity of pedestrian injuries in traffic crashes in Victoria by using crash data from 2010 to 2019. An unordered multinomial logit model and an ordered logit model are developed for this purpose.

RESULTS

The results indicate that pedestrian crashes on weekends, in the period of 10 a.m. to 10 p.m., on dark streets, at intersections, in areas with a speed limit above 50 km/h, and on medians or footpaths are associated with a higher probability of severe and fatal injuries. Male pedestrians, children, and older adults (>59) were more likely to sustain a higher level of injury in crashes. Concerning the driver characteristics, no significant relationship was found between pedestrian injury severity and driver gender and license status, but older drivers were more likely to cause severe and fatal injuries. Pedestrian collisions with motorcycles, heavy vehicles, light commercial vehicles, bus/minibus/coach, and trams increase the probability of more severe injuries compared to cars. Moreover, older vehicles are associated with a higher probability of severe pedestrian injuries. Comparison of the model results illustrated that the MNL model was slightly better fitted on the data than the ordered logit model, but the conclusions inferred from these two models were generally similar.

PRACTICAL APPLICATION

To reduce the injuries of pedestrian crashes, we recommend improving lighting conditions and sidewalk design, implementing speed reduction strategies at high pedestrian activity areas, introducing more pedestrian crossings at midblock, installing warning signs to drivers, and discouraging the use of vehicles that are more than 20 years old.

Objective and Perceived Traffic Safety for Children: A Systematic Literature Review of Traffic and Built Environment Characteristics Related to Safe Travel

The literature on children’s active transportation has shown the influence of the built environment characteristics on walking and crashes. Various reviews have examined those two questions. One influence on walking is the perception of traffic safety. However, it is not clear how, or even if, the built environment affects such perceptions. This research aims to understand which traffic and built environment characteristics influence objective and subjective/perceived traffic safety for children based on the analysis of previous studies in the field. Two types of research were used: the first examines the association between traffic and built environment characteristics and child pedestrian and/or cyclist collisions/injuries; the second relates to the perception of safety by parents and children for active transportation and, where studied, its relationship with built environment characteristics. A systematic review was conducted using five electronic databases. The total number of articles retrieved was reduced to 38 following the eligibility criteria and quality assessment, where 25 articles relate to injuries among children and 13 articles pertain to perception of safety. The results showed that high traffic volume and high vehicle speed are the main reasons children and parents feel unsafe when children use active travel, which matches the main findings on objective safety. Few articles on perception of safety related to the objective built environment were found. However, consistent findings exist. The presence of sidewalk was related to the safety of children. The presence of a crossing guard was positively related to perceived safety but was associated with higher rates of injuries among children. Intersection density was related to unsafe perceptions but was not statistically associated with objective traffic safety. Additionally, population density was found to be positively related to injuries among children, but not to perception of safety. The results help policy strategy to enhance the safety of children when using active transport modes.

Child Pedestrian Safety: Study of Street-Crossing Behaviour of Primary School Children with Adult Supervision

Road traffic accidents are the primary cause of injuries and fatalities among children. The current study focuses on children’s (un)safe crossing behaviour in a real traffic situation accompanied by an adult at a crosswalk in front of their school. The study aims to investigate if there are differences in crossing behaviour related to road infrastructure (i.e., one-way and two-way street, elevated and non-elevated street crossing), the gender of the child, and the effect of the accompanying adult’s behaviour on the child’s crossing behaviour. Primary school children from two urban schools in Flanders (Belgium) were observed for three days while crossing the street in front of their school in the morning and afternoon. A total of 241 child–adult pairs were observed. Descriptive analysis, Pearson chi-square tests, and binary logistic regression models were used to find differences between groups. More than half of the crossings exhibited two or more unsafe behaviours. Not stopping at the curb before crossing was the most unsafe behaviour, exhibited by 47.7% of children; not looking for oncoming traffic before and during the crossing was the second most unsafe behaviour, exhibited by 39.4% of the children. The only difference between boys’ and girls’ crossing behaviour was in stopping at the curb with girls 1.901 times more likely to stop before crossing as compared to boys. Adults holding hands of the child resulted in safer behaviours by children. The children not holding hands displayed significantly riskier behaviour in running or hopping while crossing the street and being distracted. The study reinforces the need to improve the transportation system through infrastructural interventions (elevated crosswalks), as well as educating and training children and the parents on safe crossing behaviour in traffic.

The Relationship of Urban Form on Children and Adolescent Health Outcomes: A Scoping Review of Canadian Evidence

Urban form can have an impact on health outcomes in children, and the synthesis of findings can identify gaps in the literature and regional reviews may help guide policymakers. This study aims to complete a scoping review of the research relating urban form to health outcomes in children and adolescents from urban Canadian settings. Thirteen online databases were searched to identify studies that had objective measures of urban form and health outcomes. Two research assistants independently reviewed 27,444 titles and abstracts, and 176 full-text articles, returning 32 unique studies with youth-specific data. The majority of the included studies were cross-sectional or ecological (n = 26). Six studies used Canada-wide data and the rest were from Ontario (n = 11), Alberta (n = 6), and Quebec (n = 6). Urban form characteristics included neighbourhood food environment (n = 11), parks/natural space/greenness (n = 10), road or intersection characteristics (n = 7), and aggregated urban form measures (n = 7). Studies examined a variety of health outcomes: the majority considered weight status (n = 16) and injury (n = 10). Although there is over-reliance on mainly cross-sectional study designs, there is evidence suggesting that urban form is associated with health outcomes in Canadian youth, with parks/greenspace, road connectivity, and road characteristics most consistently associated with health outcomes in youth.

State-of-the-art review: preventing child and youth pedestrian motor vehicle collisions: critical issues and future directions

Aim

To undertake a comprehensive review of the best available evidence related to risk factors for child pedestrian motor vehicle collision (PMVC), as well as identification of established and emerging prevention strategies.

Methods

Articles on risk factors were identified through a search of English language publications listed in Medline, Embase, Transport, SafetyLit, Web of Science, CINHAL, Scopus and PsycINFO within the last 30 years (~1989 onwards).

Results

This state-of-the-art review uses the road safety Safe System approach as a new lens to examine three risk factor domains affecting child pedestrian safety (built environment, drivers and vehicles) and four cross-cutting critical issues (reliable collision and exposure data, evaluation of interventions, evidence-based policy and intersectoral collaboration).

Conclusions

Research conducted over the past 30 years has reported extensively on child PMVC risk factors. The challenge facing us now is how to move these findings into action and intervene to reduce the child PMVC injury and fatality rates worldwide.

"Outta my way!" Individual and environmental correlates of interactions between pedestrians and vehicles during street crossings

Because pedestrian crash rates remain lower than other collision types, surrogate measures such as traffic interactions are now used in road safety research to complement crash history. Using naturalistic data collection, we sought to assess 1) the likelihood of occurrence of interactions between pedestrians and vehicles based on individual and crossing characteristics; and 2) differences in interaction characteristics between children, adult and senior pedestrians. Observations of pedestrian crossing behaviours (n=4687) were recorded at 278 crossings. For recorded interactions (n=843), information was collected to characterize the behaviours of involved parties. A mixed-effect logit regression model was performed to assess the factors associated with interactions. Chi-square tests evaluated differences between age groups and characteristics of observed interactions. Older adults were those more likely to be involved in an interaction event. Bicycle paths, different crossing surface material and one-way streets were significantly associated with fewer interactions with vehicles, while parked vehicles nearby and crossings on arterial roads were significantly associated with more interactions. Children and the elderly (80 years of age or more) did have distinct patterns of interaction, with more careful drivers/cyclists behaviours being observed towards children and lesser regulation compliance towards the elderly. Given the growing emphasis and adoption of active transportation in many cities, the number of interactions between pedestrians and vehicles during street crossings is likely to increase. Educating drivers and pedestrians to respect each other's space requires an understanding of where, between whom, and under what circumstances interactions occur. Such an approach can also help identify which engineering and enforcement programs are needed to ensure safe pedestrian crossings since interactions can be good markers of uncomfortable crossing situations that may deter walking and lead to more collisions.

Child pedestrian safety knowledge, behaviour and road injury in Cape Town, South Africa

Pedestrian injuries are a leading cause of death among South African children, and young children residing in low-income communities are more at risk, due to various factors such as inadequate road infrastructure, exposure to traffic due to reliance on walking as a means of transport, and lack of supervision. This study used a cross-sectional, non-randomized self-report survey to assess pedestrian safety knowledge, road-crossing behaviour and pedestrian injuries of primary school children in selected low-income settings in Cape Town. The survey focused on three primary schools that had joined the Safe Kids Worldwide Model School Zone Project and was administered to 536 children aged 6-15 years, in their home language of isiXhosa. Descriptive and bivariate analyses as well as multivariate regression analyses were conducted to investigate potential predictor variables for pedestrian collision severity and unsafe road-crossing behaviour. Walking was the sole form of travel for 81% of the children, with a large proportion regularly walking unsupervised. Children who walk to or from school alone were younger and reported riskier road-crossing behaviour, although children who walk accompanied tended to have higher pedestrian collision severity. "Negligent Behaviour" related to road-crossing was significantly associated with higher pedestrian collision severity, with predictors of "Negligent Behaviour" including the lack of pedestrian safety knowledge and greater exposure to traffic in terms of time spent walking. More than half of the reported pedestrian collisions involved a bicycle, and older boys (10-15 years) were most at risk of experiencing a severe pedestrian injury. The findings substantiate emerging evidence that children in low-income settings are at greater risk for child pedestrian injury, and emphasise the need for evidence-based safety promotion and injury prevention interventions in these settings.

School environments and social risk factors for child pedestrian-motor vehicle collisions: A case-control study

BACKGROUND

Child pedestrian-motor vehicle collisions (PMVCs) have decreased in Canada in the past 20 years. Many believe this trend is explained by the rise in automobile use for all travel. Initiatives to increase walking to school need to consider PMVC risk. Potential risk factors related to walking to school, the built environment and social factors were examined for schools with historically high child PMVC rates.

METHODS

Child PMVCs (age 4-12 years) from 2000 to 2013 and built environment features were mapped within school attendance boundaries in the City of Toronto, Canada. Case and control schools were in the highest and lowest PMVC quartiles respectively. Observational counts of travel mode to school were conducted. Logistic regression evaluated walking to school, built environment and social risk factors for higher PMVC rates, stratified by geographic location (downtown vs. inner suburbs).

RESULTS

The mean PMVC rates were 18.8/10,000/year (cases) and 2.5/10,000/year (controls). One-way street density (OR=4.00), school crossing guard presence (OR=3.65) and higher social disadvantage (OR=1.37) were associated with higher PMVCs. Higher residential land use density had a protective effect (OR=0.56). More walking was not a risk factor. While several built environment risk factors were identified for the inner suburbs; only social disadvantage was a risk factor within older urban neighbourhoods.

CONCLUSIONS

Several modifiable environmental risk factors were identified for child PMVCs. More walking to school was not associated with increased PMVCs after controlling for the environment. School social disadvantage was associated with higher PMVCs with differences by geographic location. These results have important implications for the design of roadways around schools.

Multilevel models for evaluating the risk of pedestrian-motor vehicle collisions at intersections and mid-blocks

Walking is a popular form of physical activity associated with clear health benefits. Promoting safe walking for pedestrians requires evaluating the risk of pedestrian-motor vehicle collisions at specific roadway locations in order to identify where road improvements and other interventions may be needed. The objective of this analysis was to estimate the risk of pedestrian collisions at intersections and mid-blocks in Seattle, WA. The study used 2007-2013 pedestrian-motor vehicle collision data from police reports and detailed characteristics of the microenvironment and macroenvironment at intersection and mid-block locations. The primary outcome was the number of pedestrian-motor vehicle collisions over time at each location (incident rate ratio [IRR] and 95% confidence interval [95% CI]). Multilevel mixed effects Poisson models accounted for correlation within and between locations and census blocks over time. Analysis accounted for pedestrian and vehicle activity (e.g., residential density and road classification). In the final multivariable model, intersections with 4 segments or 5 or more segments had higher pedestrian collision rates compared to mid-blocks. Non-residential roads had significantly higher rates than residential roads, with principal arterials having the highest collision rate. The pedestrian collision rate was higher by 9% per 10 feet of street width. Locations with traffic signals had twice the collision rate of locations without a signal and those with marked crosswalks also had a higher rate. Locations with a marked crosswalk also had higher risk of collision. Locations with a one-way road or those with signs encouraging motorists to cede the right-of-way to pedestrians had fewer pedestrian collisions. Collision rates were higher in locations that encourage greater pedestrian activity (more bus use, more fast food restaurants, higher employment, residential, and population densities). Locations with higher intersection density had a lower rate of collisions as did those in areas with higher residential property values. The novel spatiotemporal approach used that integrates road/crossing characteristics with surrounding neighborhood characteristics should help city agencies better identify high-risk locations for further study and analysis. Improving roads and making them safer for pedestrians achieves the public health goals of reducing pedestrian collisions and promoting physical activity.

Motor vehicle-pedestrian collisions and walking to school: the role of the built environment

OBJECTIVES

Initiatives to increase active school transportation are popular. However, increased walking to school could increase collision risk. The built environment is related to both pedestrian collision risk and walking to school. We examined the influence of the built environment on walking to school and child pedestrian collisions in Toronto, Canada.

METHODS

Police-reported pedestrian collision data from 2002 to 2011 for children ages 4 to 12, proportion of children walking to school, and built environment data were mapped onto school attendance boundaries. Collision rates were calculated by using 2006 census populations and modeled by using negative binomial regression.

RESULTS

There were 481 collisions with a mean collision rate of 7.4/10 000 children per year. The relationship between walking proportion and collision rate was not statistically significant after adjusting for population density and roadway design variables including multifamily dwelling density, traffic light, traffic calming and 1-way street density, school crossing guard presence, and school socioeconomic status.

CONCLUSIONS

Pedestrian collisions are more strongly associated with built environment features than with proportions walking. Road design features were related to higher collision rates and warrant further examination for their safety effects for children. Future policy designed to increase children's active transportation should be developed from evidence that more clearly addresses child pedestrian safety.

Roadway characteristics and pediatric pedestrian injury

Changing the built environment is a sound, but often underutilized approach to injury control. The authors reviewed the literature and conducted a meta-analysis to synthesize the evidence on the association of roadway characteristics with risk of pediatric pedestrian injury. To synthesize the data, they converted results to odds ratios based on direct results or abstracted outcomes and used Bayesian meta-analytic approaches by modeling outcomes as the logit of a normally distributed set of outcomes with vague prior distributions for the central measure of effect and its variance. On the basis of 10 studies of roadway features restricted exclusively to pediatric populations, the synthesized effect estimate for the association of roadway characteristics with pedestrian injury risk was 2.5 (95% credible interval: 1.8, 3.2). The probability of a new study showing an association between the built roadway and pediatric pedestrian injury was nearly 100%. The authors concluded that the built environment is directly related to the risk of pedestrian injury. This review and meta-analysis suggests that even modest interventions to the built roadway environment may result in meaningful reductions in the risk of pediatric pedestrian injury.

The risk of pedestrian injury and fatality in collisions with motor vehicles, a social ecological study of state routes and city streets in King County, Washington

This study examined the correlates of injury severity using police records of pedestrian-motor-vehicle collisions on state routes and city streets in King County, Washington. Levels of influence on collision outcome considered (1) the characteristics of individual pedestrians and drivers and their actions; (2) the road environment; and (3) the neighborhood environment. Binary logistic regressions served to estimate the risk of a pedestrian being severely injured or dying versus suffering minor or no injury. Significant individual-level influences on injury severity were confirmed for both types of roads: pedestrians being older or younger; the vehicle moving straight on the roadway. New variables associated with increased risk of severe injury or death included: having more than two pedestrians involved in a collision; and on city streets, the driver being inebriated. Road intersection design was significant only in the state route models, with pedestrians crossing at intersections without signals increasing the risk of being injured or dying. Adjusting for pedestrians' and drivers' characteristics and actions, neighborhood medium home values and higher residential densities increased the risk of injury or death. No other road or neighborhood environment variable remained significant, suggesting that pedestrians were not safer in areas with high pedestrian activity.

Diagnostic analysis of the logistic model for pedestrian injury severity in traffic crashes

This study attempts to evaluate the injury risk of pedestrian casualties in traffic crashes and to explore the factors that contribute to mortality and severe injury, using the comprehensive historical crash record that is maintained by the Hong Kong Transport Department. The injury, demographic, crash, environmental, geometric, and traffic characteristics of 73,746 pedestrian casualties that were involved in traffic crashes from 1991 to 2004 are considered. Binary logistic regression is used to determine the associations between the probability of fatality and severe injury and all contributory factors. A consideration of the influence of implicit attributes on the trend of pedestrian injury risk, temporal confounding, and interaction effects is progressively incorporated into the predictive model. To verify the goodness-of-fit of the proposed model, the Hosmer-Lemeshow test and logistic regression diagnostics are conducted. It is revealed that there is a decreasing trend in pedestrian injury risk, controlling for the influences of demographic, road environment, and other risk factors. In addition, the influences of pedestrian behavior, traffic congestion, and junction type on pedestrian injury risk are subject to temporal variation.