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  • 标题:An Applied Ecological Framework for Evaluating Infrastructure to Promote Walking and Cycling: The iConnect Study
  • 本地全文:下载
  • 作者:David Ogilvie ; Fiona Bull ; Jane Powell
  • 期刊名称:American journal of public health
  • 印刷版ISSN:0090-0036
  • 出版年度:2011
  • 卷号:101
  • 期号:3
  • 页码:473-481
  • DOI:10.2105/AJPH.2010.198002
  • 语种:English
  • 出版社:American Public Health Association
  • 摘要:Improving infrastructure for walking and cycling is increasingly recommended as a means to promote physical activity, prevent obesity, and reduce traffic congestion and carbon emissions. However, limited evidence from intervention studies exists to support this approach. Drawing on classic epidemiological methods, psychological and ecological models of behavior change, and the principles of realistic evaluation, we have developed an applied ecological framework by which current theories about the behavioral effects of environmental change may be tested in heterogeneous and complex intervention settings. Our framework guides study design and analysis by specifying the most important data to be collected and relations to be tested to confirm or refute specific hypotheses and thereby refine the underlying theories. Interest in the relation between transportation and public health traditionally has focused on adverse local effects of motor traffic such as noise, air pollution, and injuries 1 but now also recognizes the potential health benefits of promoting walking and cycling and the wider adverse effects of dependence on motor vehicles. 2 Walking and cycling offer an ideal opportunity for people to incorporate physical activity into their daily lives, reducing their risk of chronic diseases such as diabetes and coronary heart disease. 3 , 4 A population shift toward more “active travel” also could help reduce traffic congestion and carbon emissions, to which the use of motor vehicles makes a large and inequitably distributed contribution. 5 – 9 Improving the infrastructure for walking and cycling recently has been identified as one of the most important policy recommendations for tackling obesity in both the United States and the United Kingdom. 9 , 10 Such recommendations are largely based on evidence from cross-sectional studies showing that certain characteristics of the physical environment—such as the design of residential neighborhoods and the availability of routes for walking and cycling—may be associated with patterns of physical activity in general and walking and cycling in particular. 11 , 12 However, evidence is limited from studies of actual interventions to show that altering transportation infrastructure or other aspects of the built environment has led to an increase in walking or cycling or a modal shift away from car use, let alone changes in overall physical activity or carbon emissions. 13 – 15 This lack of evidence reflects several unresolved challenges in this area of research, including problems of measurement and evaluation. The difficulty of measuring changes in walking, cycling, and physical activity in general is recognized in both the transportation and the physical activity fields 16 – 19 and is compounded by the difficulty of applying robust study designs to the evaluation of complex infrastructural interventions. 20 Existing research in this field has an evaluative bias in favor of interventions targeted at individuals, which may be easier to evaluate, 13 , 14 and is often characterized by methodological limitations such as the lack of representative population samples, prospectively collected data, control groups or areas, or sufficient duration of follow-up. 15 Meanwhile, only limited inferences about the population effects of new infrastructure can be drawn from routinely collected user monitoring data. 21 As a result, we lack the means to assess the potential travel, physical activity, and carbon emission effects of different approaches to promoting walking and cycling, to set appropriate targets, or to allocate resources for new capital projects efficiently. The Connect2 initiative (available at: http://www.sustransconnect2.org.uk ) offers an important opportunity to address both methodological and substantive applied research problems in this multidisciplinary field. Connect2 consists of a program of projects to build or improve local walking and cycling routes at 79 sites around the United Kingdom ( Figure 1 ) led by Sustrans, a charity that promotes sustainable transportation in various ways, including building infrastructure such as the National Cycle Network. Each Connect2 project involves a core landmark engineering project such as a bridge or crossing over a busy road, railway line, or river, which—together with the development or improvement of feeder routes—is intended to make it easier for pedestrians and cyclists to reach destinations in the local area. The iConnect (Impact of COnstructing Non-motorised Networks and Evaluating Changes in Travel) consortium (available at: http://www.iconnect.ac.uk ) is an independent multidisciplinary academic collaboration involving 7 United Kingdom universities and the Medical Research Council. The consortium is funded by the Engineering and Physical Sciences Research Council to conduct a 5-year research program to measure and evaluate the effects of Connect2. This collaboration will enable the collection of consistent longitudinal data at multiple sites with which to assess, for the first time, the effects of an infrastructural intervention on outcomes of interest across the 3 domains of travel, physical activity, and carbon emissions. Open in a separate window FIGURE 1 Map of Connect2 intervention sites: the iConnect study, United Kingdom 2008–2013. Source . Reproduced with permission of Sustrans (Bristol, UK). This first article from the iConnect consortium addresses the challenge of establishing an evaluative framework within which the effects of a complex program of infrastructural investment such as Connect2 can be studied. Subsequent articles will address more specific issues of sampling and measurement and the development of a complementary economic evaluation framework.
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