MétaCan
Menu
Back to cohort
Record W2152877906 · doi:10.1542/peds.2014-0600

There and Back Again: Safety and Health on the Journey to School

2014· letter· en· W2152877906 on OpenAlexaboutno aff
Gilbert C. Liu, Jason A. Mendoza

Bibliographic record

VenuePEDIATRICS · 2014
Typeletter
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsnot available
Fundersnot available
KeywordsRecreationTRIPS architectureMedicinePedestrianInjury preventionOccupational safety and healthPoison controlSuicide preventionHuman factors and ergonomicsEnvironmental healthGerontologyTransport engineeringEngineering

Abstract

fetched live from OpenAlex

Active school transportation (AST) has been associated with children attaining more moderate-to-vigorous physical activity and a healthier BMI.1–3 Similar to Canadian children, US rates of AST declined from 48% in 1969 to 13% in 2009.4 There are many reasons for this decline, but parents report distance (62% of respondents), traffic-related injury (30%), and weather (19%) as the top 3 barriers.5There are many benefits to AST. Children in developed countries are not sufficiently active and obesity remains a global threat.6 Families driving students to school represent 10% to 14% of US traffic during the morning commute,4 and often such trips are less than a half mile. Communities that have invested in infrastructure to promote walking or biking have shown increased property values, improved air quality, reduced urban heat injury, and greater social cohesion.7–9In 2005, the US Congress established a Safe Routes to School (SRTS) program to improve safety on walking and bicycling routes to elementary and middle schools and to encourage travel between home and school using these modes.10 SRTS was apportioned $612 million benefiting 15 000 schools.11 In 2012, Congress discontinued protected SRTS funding. SRTS initiatives must now compete with other requests such as the Transportation Enhancements and Recreational Trails programs, and show evidence of both increased active transportation and reduced collisions.12 Although pedestrian injury is a major consideration for AST, few studies have examined this rare outcome. In this issue, Rothman et al13 examine AST, the built environment, and associations with pedestrian collisions in Toronto.This Canadian study is among the first to reveal that a higher rate of children walking or biking to school has no significant association with traffic-related injury. This is welcome and important evidence for policy makers who have invested in AST and for activists who pursue more widespread AST. Whether this research will convince parents to forego driving their children to school remains to be seen, but these findings should encourage the growing numbers of Canadian families whose children are walking or biking to school. US readers should be especially inspired by AST occurring during Canadian winters!The authors identify opportunities to expand on their research. Foremost is the limitation posed by the cross-sectional design of their study. The authors report 2 nonintuitive findings: both traffic crossing guards and traffic calming were associated with more pedestrian collisions. These findings are not surprising, given the ecological nature of the study. Streets with more pedestrian collisions are prime targets for interventions to calm traffic or for placing public safety personnel such as crossing guards. Interpreting the results of Rothman et al, it is reasonable to conclude that traffic safety improvements and crossing guards were thus appropriately allocated. This example underscores the need to better define causal relationships. You do not want to get rid of fire trucks just because they are more numerous with more severe fires. Similarly, we caution against extrapolating Rothman et al’s findings to give crossing guards and traffic-calming features the budgetary ax. Although rigorous experimental designs proving the effectiveness of AST are difficult and expensive, built-environment interventions have been successfully evaluated by using longitudinal or quasi-experimental designs; furthermore, a solid body of evidence is available to guide strategies to promote walking or biking in adult commuting.A US-based study in New York City with a before and after design informs the directionality of built-environment interventions and school-aged pedestrian collisions. Investigators reported a reduction in pedestrian injury rates during school-travel hours from 8.8 per 10 000 population per year (preintervention) to 4.4 per 10 000 population per year (postintervention) in census tracts that had SRTS interventions.14 School-aged pedestrian injury rates in census tracts without SRTS interventions showed no change.14 This study should provide policy makers with reassurance that SRTS programs likely reduce the risk of child pedestrian collisions.Investigators should aim to obtain finer-level representation of environmental factors, ie, match the built environment to the actual collision location rather than a broad surrounding area. Also, future work needs to incorporate more accurate information on the speed of vehicular traffic and longer and more frequent time periods for assessing rates of AST (>1 day in different seasons), and applying spatial analyses or other analytic models that can address nonindependence of observations arising from phenomena such as subjects grouping by neighborhood.We recognize the many societal changes that have led to more students being driven to school. As parents, we empathize with families who worry about dangerous streets, distracted drivers, and challenging weather conditions that give pause to even letter carriers. When viewed through the lens of child health, AST is an “old school” form of physical activity that more children should adopt to make the daily trek to and from school. Programs to increase AST, such as SRTS, deserve well-designed evaluations that clearly document their contributions to child well-being and safety.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.047
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0030.004
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0300.003

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.060
GPT teacher head0.320
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2014
Admission routes1
Has abstractyes

Explore more

Same venuePEDIATRICSSame topicUrban Transport and AccessibilityFrench-language works237,207