Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill , Chapel Hill, NC , USA.
Front Public Health. 2016 May 2;4:63. doi: 10.3389/fpubh.2016.00063. eCollection 2016.
Health impact assessment (HIA) has been promoted as a means to encourage transportation and city planners to incorporate health considerations into their decision-making. Ideally, HIAs would include quantitative estimates of the population health effects of alternative planning scenarios, such as scenarios with and without infrastructure to support walking and cycling. However, the lack of baseline estimates of time spent walking or biking for transportation (together known as "active transportation"), which are critically related to health, often prevents planners from developing such quantitative estimates. To address this gap, we use data from the 2009 US National Household Travel Survey to develop a statistical model that estimates baseline time spent walking and biking as a function of the type of transportation used to commute to work along with demographic and built environment variables. We validate the model using survey data from the Raleigh-Durham-Chapel Hill, NC, USA, metropolitan area. We illustrate how the validated model could be used to support transportation-related HIAs by estimating the potential health benefits of built environment modifications that support walking and cycling. Our statistical model estimates that on average, individuals who commute on foot spend an additional 19.8 (95% CI 16.9-23.2) minutes per day walking compared to automobile commuters. Public transit riders walk an additional 5.0 (95% CI 3.5-6.4) minutes per day compared to automobile commuters. Bicycle commuters cycle for an additional 28.0 (95% CI 17.5-38.1) minutes per day compared to automobile commuters. The statistical model was able to predict observed transportation physical activity in the Raleigh-Durham-Chapel Hill region to within 0.5 MET-hours per day (equivalent to about 9 min of daily walking time) for 83% of observations. Across the Raleigh-Durham-Chapel Hill region, an estimated 38 (95% CI 15-59) premature deaths potentially could be avoided if the entire population walked 37.4 min per week for transportation (the amount of transportation walking observed in previous US studies of walkable neighborhoods). The approach developed here is useful both for estimating baseline behaviors in transportation HIAs and for comparing the magnitude of risks associated with physical inactivity to other competing health risks in urban areas.
健康影响评估（HIA）已被推广为一种手段，旨在鼓励交通和城市规划者将健康因素纳入其决策过程中。理想情况下，HIA 将包括对替代规划方案（例如有无支持步行和骑行基础设施的方案）的人口健康影响的定量估计。然而，由于缺乏与健康密切相关的交通方式下的步行或骑行的基准时间（统称为“主动交通”）估计，规划者通常无法进行此类定量估计。为了解决这一差距，我们使用 2009 年美国国家家庭出行调查的数据开发了一个统计模型，该模型根据用于通勤的交通方式以及人口统计学和建成环境变量来估计步行和骑行的基准时间。我们使用来自美国北卡罗来纳州罗利-达勒姆-教堂山都会区的调查数据验证了该模型。我们说明了经过验证的模型如何用于支持与交通相关的 HIA，通过估计支持步行和骑行的建成环境改造的潜在健康益处。我们的统计模型估计，平均而言，步行通勤者每天额外步行 19.8 分钟（95%CI 16.9-23.2），而驾车通勤者则每天额外步行 5.0 分钟（95%CI 3.5-6.4）。与驾车通勤者相比，乘坐公共交通工具的乘客每天额外步行 5.0 分钟（95%CI 3.5-6.4）。与驾车通勤者相比，骑自行车通勤者每天额外骑行 28.0 分钟（95%CI 17.5-38.1）。该统计模型能够将罗利-达勒姆-教堂山地区的观察到的交通身体活动预测到每天 0.5 个 MET 小时（相当于每天步行 9 分钟左右）以内，准确率为 83%。在罗利-达勒姆-教堂山地区，如果整个人群每周用于交通的步行时间增加 37.4 分钟（相当于以前在美国对适合步行的社区的研究中观察到的交通步行量），则估计可以避免 38 例（95%CI 15-59）过早死亡。在这里开发的方法对于估计交通 HIA 中的基准行为以及比较与身体活动不足相关的风险与城市地区其他竞争健康风险的大小都非常有用。
