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The “Path” Not Taken: Exploring Structural Differences in Mapped- Versus Shortest-Network-Path School Travel Routes

机译:未走“路径”:探索映射的与最短网络路径的学校出行路线的结构差异

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Objectives. School route measurement often involves estimating the shortest network path. We challenged the relatively uncritical adoption of this method in school travel research and tested the route discordance hypothesis that several types of difference exist between shortest network paths and reported school routes. Methods. We constructed the mapped and shortest path through network routes for a sample of 759 children aged 9 to 13 years in grades 5 and 6 (boys?=?45%, girls?=?54%, unreported gender?=?1%), in Toronto, Ontario, Canada. We used Wilcoxon signed-rank tests to compare reported with shortest-path route measures including distance, route directness, intersection crossings, and route overlap. Measurement difference was explored by mode and location. Results. We found statistical evidence of route discordance for walkers and children who were driven and detected it more often for inner suburban cases. Evidence of route discordance varied by mode and school location. Conclusions. We found statistically significant differences for route structure and built environment variables measured along reported and geographic information systems–based shortest-path school routes. Uncertainty produced by the shortest-path approach challenges its conceptual and empirical validity in school travel research. Recent policy and research on children’s school travel has responded to reports of decadal declines in active school travel (AST)—that is, traveling to or from school under one’s own power, typically on foot or using a bicycle—in many Western nations. 1–6 Evidence of a similar trend is also beginning to emerge in some cities in the global south. 7 AST decline has been matched by increased prevalence of overweight and obesity in children and youths. 8–10 Children driven to and from school and other activities miss transport-centered opportunities for physical activity and health benefits 11–13 that, when combined with physical activity from other sources, could produce an active healthy lifestyle that may be sustained into adulthood. 14–19 Understanding how to encourage AST could progress through development of valid evidence about the relationship between school travel route characteristics and travel mode choice. School travel research has often examined the relationship between travel mode choice and home, school, and route environments. 20 Underpinning this work is the hypothesis that built environment (BE) features may enable or restrict household transport choices. A mix of BE effects, with some indication of difference by age, time of day, location (e.g., home, route, or school), and measurement approach (e.g., objective or subjective assessment), have been found. 21–23 Studies of home, school, and travel mode without route information have suggested that both objective measures and perceptions of BE features and their use (i.e., traffic on busy roads) predict AST. 21,23–25 Reported effects are not always in the same direction across studies. The odds of walking have been shown to increase with residential density in some studies but not in others. 21,23,24 Marked differences in BE effects have also been reported when separate models are estimated for the morning and afternoon school travel periods. 21 For example, and unique to their school-to-home model, Larsen et al. 21 found that the effect of mixed land use (AST is more likely with mixed land use) intensified for the trip home; residential density became significant, along with income (i.e., AST is more likely in lower income neighborhoods); and a street tree effect (i.e., trees provide shade and are a direct and indirect measure of neighborhood aesthetics), significant in the morning model, was not reproduced. Route-based studies extend the home, school, and travel mode work by including BE features that children might experience along their route that could influence a household’s school travel decisions. For example, a child’s possible interaction with busy roads while walking to or from school could underlie a parent’s decision to drive. Route-based studies have typically involved measuring BE characteristics along and around assumed routes modeled using a geographic information systems (GIS)–based shortest-network-path algorithm. 26–32 Although several diverse route effects have been reported, all studies have reproduced the finding that children are less likely to walk as route distance increases. 26–32 Here again, different effects are reported for to- and from-school trips. 26,27 For example, Larsen et al. 26 reported significant effects for the presence of street trees, detached housing, and land use mix, that did not materialize in their school-to-home model. Findings regarding route directness, typically measured as the deviation of an assumed GIS-estimated route from the straight-line distance between home and school, have also been inconsistent. For adults, route directness is often associated with the use of active modes. In the sch
机译:目标。学校路由测量通常涉及估计最短的网络路径。我们在学校旅行研究中对这种方法相对不严格的采用提出了挑战,并测试了路线不一致假设,即最短网络路径和报告的学校路线之间存在几种类型的差异。方法。我们为759名9至13岁的5和6年级的儿童(男孩为45%,女孩为54%,未报告性别为= 1%),通过网络路线构建了映射的最短路径,在加拿大安大略省多伦多市。我们使用Wilcoxon符号秩检验来比较报告的最短路径度量,包括距离,路径直接性,交叉路口和路径重叠。通过模式和位置​​探索了测量差异。结果。我们发现了被驾驶的学步车和儿童的路线不一致的统计证据,并且在郊区郊区的情况下更经常发现它。路线不一致的证据因模式和学校位置而异。结论。我们发现,沿报告的和基于地理信息系统的最短学校路线计算出的路线结构和构建的环境变量在统计上存在显着差异。最短路径方法产生的不确定性挑战了其在学校旅行研究中的概念和经验有效性。关于儿童学校旅行的最新政策和研究已经回应了许多西方国家关于主动学校旅行(AST)的十年下降的报告,即在自己的力量下(通常是步行或骑自行车)去学校旅行。 1-6在全球南部的一些城市也开始出现类似趋势的证据。 7 AST下降与儿童和青少年超重和肥胖的患病率增加相吻合。 8–10被驱赶往返学校和其他活动的儿童错过了以交通为中心的体育活动和健康福利机会11–13,如果与其他来源的体育活动相结合,可能会产生积极健康的生活方式,并可能持续到成年。 14–19通过开发有关学校出行路线特征与出行方式选择之间关系的有效证据,可以了解如何鼓励AST。学校出行研究经常检查出行方式选择与家庭,学校和路线环境之间的关系。 20假说的基础是建筑环境(BE)功能可能启用或限制家庭运输选择的假设。已经发现BE效果的混合,并在一定程度上表明了年龄,一天中的时间,位置(例如,家庭,路线或学校)和测量方法(例如,客观或主观评估)之间的差异。 21–23对没有路线信息的家庭,学校和出行方式的研究表明,BE的特征及其用途(即繁忙道路上的交通)的客观测量和感知都可以预测AST。 21,23–25在研究中,报告的效果并不总是朝着相同的方向发展。在某些研究中,步行的几率随居住密度的增加而增加,而在另一些研究中,则没有。 21,23,24当估计上午和下午学校旅行期间的单独模型时,也报告了BE影响的显着差异。 21例如,对于他们的学校到家庭模式而言,Larsen等人是独一无二的。 21发现,混合土地使用的影响(AST与混合土地使用的可能性更大)对旅行产生了影响;居民密度和收入都变得很重要(即,在低收入社区中AST的可能性更大);并没有重现出在早间模型中很明显的街头树效应(即树木提供阴影,是邻里美学的直接和间接度量)。基于路线的研究通过包含儿童可能沿途经历的BE功能,扩展了家庭,学校和出行方式的工作,这可能会影响家庭的学校出行决定。例如,孩子走路或上学时可能与繁忙的道路互动,这可能是父母决定开车的基础。基于路线的研究通常涉及沿假设路线及其周围使用基于地理信息系统(GIS)的最短网络路径算法建模的BE特性的测量。 26–32尽管已经报道了几种不同的路径影响,但所有研究都重现了发现,随着路径距离的增加,儿童走路的可能性降低。 26–32在这里,再次报道了往返学校的旅行的影响。 26,27例如,Larsen等。 26个报告了路边树木,独立式住房和土地使用混合的重大影响,但在他们的学校到家庭模型中却没有实现。关于路线直接性的发现也不一致,通常以假定的GIS估计路线与家庭和学校之间的直线距离的偏差来衡量。对于成年人来说,路线直接性通常与使用主动模式有关。在sch

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