Route-Based Analysis to Capture the Environmental Influences on a Child's Mode of Travel between Home and School
Bibliographic record
Abstract
Abstract This study examined environmental influences on a child's mode of travel between home and school. Grade 7 and 8 students (n = 614) from twenty-one schools throughout London, Ontario, participated in a school-based travel mode survey. Geographic information systems (GIS) were employed to examine environmental characteristics of the child's mode of travel between home and school measured at the scale of the likely travel route. Logistic regression was used to assess what factors influence both the to- and from-school trip. Over 62 percent of students living within 1.6 kilometers (1 mile) of school walked or biked to school and 72 percent walked or biked home from school. Actively commuting to school was positively associated with shorter trips, with distance being the most important correlate. Boys were significantly more likely to use active travel modes than girls. Higher traffic volume along the route was negatively related to rates of active travel and children from higher income neighborhoods were less likely to actively travel than children from lower income neighborhoods. In terms of environmental characteristics, the presence of street trees was positively associated and higher residential densities and mixed land uses were negatively associated with active travel to school. For the journey home, crossing major streets and increased intersection density were negatively associated with active travel. The findings of this research give evidence that active travel is associated with the environmental characteristics of walking routes. This information should be considered for urban planning and school planning purposes to improve children's walking environments. En este estudio se examinan las influencias ambientales sobre el modo de desplazarse de un niño de la casa a la escuela. Los estudiantes de los niveles 7 y 8 (n=614) de veintiuna escuelas dispersas a través de London, Ontario, participaron en un reconocimiento sobre el modo de viaje a partir de la escuela. Se emplearon sistemas de información geográfica (SIG) para examinar las características ambientales del modo de viajar del niño entre la casa y la escuela, medidas a la escala de la ruta probable de viaje. Se utilizó la regresión logística para evaluar qué factores influyen el viaje hacia y desde la escuela. Más del 62 por ciento de los estudiantes que viven hasta 1.6 kilómetros (1 milla) de la escuela caminaban o se desplazaban en bicicleta a la escuela, y el 72 por ciento caminaban o iban en cicla a la casa desde la escuela. El conmutar activamente a la escuela estaba positivamente asociado con viajes más cortos, siendo en este caso la distancia el factor de correlación más importante. Los niños eran significativamente más propensos a usar modos activos de viaje que las niñas. El alto volumen de tráfico a lo largo de la ruta está negativamente asociado con las tasas de viaje activo y los niños de vecindarios de mayores ingresos son menos propensos al viaje activo que aquellos de vecindarios de ingresos más bajos. En cuanto a características ambientales se refiere, la existencia de árboles en la calle está positivamente asociada en tanto que una mayor densidad residencial y usos del suelo mixtos se asocian negativamente con el viaje activo hacia la escuela. En cuanto al desplazamiento hacia la casa, el cruzar calles mayores lo mismo que una mayor densidad de intersecciones resultaron asociadas negativamente con el viaje activo. Los hallazgos de esta investigación proveen evidencia de que el viaje activo está asociado con las características ambientales de las rutas peatonales. Esta información debe tenerse en cuenta para los propósitos de planificación urbana y escolar para mejorar los entornos peatonales de los niños. Key Words: active travelbuilt environmentchildren's healthGISwalkability关键词: 主动出行建筑环境孩子的健康地理信息系统可行走性Palabras clave: viaje activomedio ambiente construidosalud infantilSIGtransitabilidad peatonal Acknowledgments This research was funded by the Canadian Institutes of Health Research (Principal Investigator Jason Gilliland) and the Social Science and Humanities Research Council of Canada (CGS-Masters Scholarship to Kristian Larsen). We also wish to thank our collaborators: Patricia Tucker for supervising the school survey team and data entry; Janet Loebach for assisting with the survey and data entry; Patricia, Janet, Jennifer Irwin, and Meizi He for their advice and continued efforts on the larger project; and Kevin VanLierop and Martin Healy for GIS assistance. We especially thank the students, parents, teachers, principals, and research boards of the Thames Valley District School Board and the London District Catholic School Board, without whom this research would not have been possible. Notes aShortest path from home postal code to school. bRoad segment with highest traffic volume in buffer. cFemale as referent. dPercentage of land use in buffer dedicated to single detached homes. eNumber of street trees within 5 m of road edge in groups of 10 per square km. fIn $1,000s. gNumber of major streets crossed on route to school. hNumber of intersections in buffer per square km. 1. Students living within 1.6 kilometers of the school can obtain bus privileges if they have to overcome a hazard (such as crossing a major highway). A total of 3.8 percent of all students attending the twenty-one sampled schools were eligible to take the school bus due to a hazard. Children living in a dual-custody relationship might also have two addresses, although only one postal code was given; they might be entitled to take the bus from the other address. Some measurement errors could be due to our use of home postal codes to calculate travel distance to school, rather than precise home addresses; however, the median distance between every residential address in the city and its related postal code is only 80 meters, so this unlikely the cause of many discrepancies. Finally, errors related to the postal code given or mode of travel might explain a few cases as to why children claim to be taking the school bus when living less than 1.6 kilometers from school.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".