Brondeel Ruben, Kestens Yan, Chaix Basile
Inserm, UMR-S 1136, Pierre Louis Institute of Epidemiology and Public Health, Nemesis team, Médecine Saint-Antoine, 27 rue Chaligny, UMR-S 1136, 75012, Paris, France.
Sorbonne Universités, UPMC Univ Paris 06, UMR-S 1136, Pierre Louis Institute of Epidemiology and Public Health, Nemesis team, Paris, France.
Int J Behav Nutr Phys Act. 2017 Oct 23;14(1):143. doi: 10.1186/s12966-017-0600-1.
Physical inactivity is widely recognized as one of the leading causes of mortality, and transport accounts for a large part of people's daily physical activity. This study develops a simulation approach to evaluate the impact of the Ile-de-France Urban Mobility Plan (2010-2020) on physical activity, under the hypothesis that the intended transport mode shifts are realized.
Based on the Global Transport Survey (2010, n = 21,332) and on the RECORD GPS Study (2012-2013, n = 229) from the French capital region of Paris (Ile-de-France), a simulation method was designed and tested. The simulation method used accelerometer data and random forest models to predict the impact of the transport mode shifts anticipated in the Mobility Plan on transport-related moderate-to-vigorous physical activity (T-MVPA). The transport mode shifts include less private motorized trips in favor of more public transport, walking, and biking trips.
The simulation model indicated a mean predicted increase of 2 min per day of T-MVPA, in case the intended transport mode shifts in the Ile-de-France Urban Mobility Plan were realized. The positive effect of the transport mode shifts on T-MVPA would, however, be larger for people with a higher level of education. This heterogeneity in the positive effect would further increase the existing inequality in transport-related physical activity by educational level.
The method presented in this paper showed a significant increase in transport-related physical activity in case the intended mode shifts in the Ile-de-France Urban Mobility Plan were realized. This simulation method could be applied on other important health outcomes, such as exposure to noise or air pollution, making it a useful tool to anticipate the health impact of transport interventions or policies.
身体活动不足被广泛认为是主要死因之一,而交通出行占人们日常身体活动的很大一部分。本研究开发了一种模拟方法,在假设法兰西岛城市交通出行规划(2010 - 2020年)预期的交通方式转变得以实现的情况下,评估其对身体活动的影响。
基于来自法国首都地区巴黎(法兰西岛)的全球交通调查(2010年,n = 21332)和记录GPS研究(2012 - 2013年,n = 229),设计并测试了一种模拟方法。该模拟方法使用加速度计数据和随机森林模型来预测交通出行规划中预期的交通方式转变对与交通相关的中度至剧烈身体活动(T - MVPA)的影响。交通方式转变包括减少私人机动出行,转而增加公共交通、步行和骑行出行。
模拟模型表明,如果法兰西岛城市交通出行规划中预期的交通方式转变得以实现,则预计与交通相关的中度至剧烈身体活动每天平均增加2分钟。然而,如果实现了交通方式转变,那么对于受教育程度较高的人群而言,其对与交通相关中度至剧烈身体活动的积极影响会更大。这种积极影响的异质性将进一步加剧现有在与交通相关身体活动方面按教育程度划分的不平等。
本文所提出的方法表明,如果法兰西岛城市交通出行规划中预期的交通方式转变得以实现,那么与交通相关的身体活动将显著增加。这种模拟方法可应用于其他重要的健康结果,如接触噪音或空气污染,使其成为预测交通干预措施或政策对健康影响的有用工具。