Cradock Angie L, Barrett Jessica L, Chriqui Jamie F, Evenson Kelly R, Goins Karin Valentine, Gustat Jeanette, Heinrich Katie M, Perry Cynthia K, Scanze Michele, Schmid Thomas L, Tabak Rachel G, Umstattd Meyer M Renee, Valko Cheryl
1 Department of Social and Behavioral Sciences, Harvard T. H. Chan School of Public Health, Boston, MA, USA.
2 Division of Health Policy and Administration, School of Public Health and the Institute for Health Research & Policy, University of Illinois at Chicago, Chicago, IL, USA.
Am J Health Promot. 2018 Mar;32(3):657-666. doi: 10.1177/0890117117738758. Epub 2017 Nov 6.
To assess predictors of stated support for policies promoting physically active transportation.
Cross-sectional.
US counties selected on county-level physical activity and obesity health status.
Participants completing random-digit dialed telephone survey (n = 906).
Survey measures assessed stated support for 5 policies to promote physically active transportation, access to active transportation facilities, and time spent in a car. County-level estimates included household car dependence and funding for bicycle-pedestrian projects.
Multivariable generalized linear mixed models using binary distribution and logit link, accounting for clustering within county.
Respondents supported policies for accommodating bicyclists and pedestrians through street improvements (89%), school active transportation programs (75%), employer-funded active commuting incentives (67%), and allocation of public funding (68%) and tax support (56%) for building and maintaining public transit. Residents spending >2 h/d (vs <0.7 hours) in cars were more likely to support street (odds ratio [OR]: 1.87; confidence interval [CI]: 1.09-3.22) and public transit (OR: 1.85; CI: 1.24-2.77) improvements. Residents in counties investing >$1.6 million in bicycle and pedestrian improvements expressed greater support for funding (OR: 1.71; CI: 1.04-2.83) and tax increases (OR: 1.73; CI: 1.08-2.75) for transit improvements compared to those with lower prior investments (<$276 100).
Support for policies to enable active transportation is higher where relevant investments in active transportation infrastructure are large (>$1.6 M), public transit is nearby, and respondents drive >2 h/d.
评估对促进积极出行政策的明确支持的预测因素。
横断面研究。
根据县级身体活动和肥胖健康状况选择的美国各县。
完成随机数字拨号电话调查的参与者（n = 906）。
调查测量评估了对5项促进积极出行政策、使用积极出行设施的情况以及在汽车中花费的时间的明确支持。县级估计包括家庭对汽车的依赖程度以及自行车和行人项目的资金。
使用二元分布和对数链接的多变量广义线性混合模型，考虑县内的聚类情况。
受访者支持通过街道改善来容纳骑自行车者和行人的政策（89%）、学校积极出行计划（75%）、雇主资助的积极通勤激励措施（67%）以及为建设和维护公共交通分配公共资金（68%）和税收支持（56%）。每天在汽车中花费超过2小时（与少于0.7小时相比）的居民更有可能支持街道（优势比[OR]：1.87；置信区间[CI]：1.09 - 3.22）和公共交通（OR：1.85；CI：1.24 - 2.77）改善。与先前投资较低（<276,100美元）的县相比，在自行车和行人改善方面投资超过160万美元的县的居民对交通改善的资金（OR：1.71；CI：1.04 - 2.83）和增税（OR：1.73；CI：1.08 - 2.75）表示出更大的支持。
在积极交通基础设施相关投资较大（>160万美元）、附近有公共交通且受访者每天开车超过2小时的地方，对促进积极出行政策的支持更高。
