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基于结构方程模型的南京市就业者通勤行为特征对健康的影响研究
引用本文:曹晨,甄峰,汪侠,姜玉培.基于结构方程模型的南京市就业者通勤行为特征对健康的影响研究[J].地理科学进展,2020,39(12):2043-2053.
作者姓名:曹晨  甄峰  汪侠  姜玉培
作者单位:1.南京大学地理与海洋科学学院,南京 210023
2.江苏省智慧城市设计仿真与可视化工程实验室,南京 210093
3.南京大学建筑与城市规划学院,南京 210093
基金项目:国家自然科学基金项目(41571146);国家自然科学基金项目(41871134)
摘    要:通勤是城市就业者日常工作所必须面对的问题,长距离、长时间通勤以及机动化通勤方式带来的健康问题引起了国内外学者们的广泛关注。论文基于南京市居民身体活动及健康状况问卷调查数据,构建结构方程模型分析就业者通勤距离、通勤时间及通勤模式三者的关系及其对心理健康、身体健康以及健康行为的影响。研究发现:① 通勤距离对机动车通勤模式与通勤时间存在显著的正向直接效应,同时通勤距离对通勤时间存在显著的正向间接效应。② 在心理健康影响方面,通勤距离、通勤时间及机动车通勤模式对邻里关系有显著的负向直接效应,同时通勤距离与通勤模式对邻里关系还存在显著的负向间接效应;在身体健康影响方面,通勤距离降低了就业者超重或肥胖的发生概率,但增加了就业者选择机动车通勤模式的可能性,从而间接增加了就业者患慢性疾病的风险;在健康行为影响方面,通勤距离、通勤时间与睡眠时间显著负相关,机动车通勤模式对睡眠时间产生负向间接影响,与是否做家务显著负相关,与是否散步呈现显著的正相关。③ 通勤行为特征对健康的影响因就业者社会经济属性不同而存在差异,女性、年龄较大以及收入较低的就业者通勤行为特征对健康的影响更为显著。基于研究结果,提出优化城市职住空间、减少通勤时耗,降低小汽车依赖、促进积极通勤来提高就业者身体活动量,并为特殊群体的通勤创造更加有利的条件,进而提升其健康水平。

关 键 词:健康  通勤行为特征  城市就业者  结构方程模型  南京市  
收稿时间:2019-12-31
修稿时间:2020-05-29

Study on the influence of commuting behavior characteristics of urban residents on health in Nanjing City based on structural equation model
CAO Chen,ZHEN Feng,WANG Xia,JIANG Yupei.Study on the influence of commuting behavior characteristics of urban residents on health in Nanjing City based on structural equation model[J].Progress in Geography,2020,39(12):2043-2053.
Authors:CAO Chen  ZHEN Feng  WANG Xia  JIANG Yupei
Institution:1. School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210023, China
2. Provincial Engineering Laboratory of Smart City Design Simulation & Visualization, Jiangsu, Nanjing 210093, China
3. School of Architecture and Urban Planning, Nanjing University, Nanjing 210093, China
Abstract:Commuting is an issue that urban residents must face in their day-to-day work. The health problems caused by long-distance, long-time, and motorized commuting have aroused widespread concern of scholars in China and internationally. Based on the survey data of physical activity and health status of residents in eight typical communities in Nanjing City from 2017 to 2018, a structural equation model was constructed to analyze the relationship between commuting distance, commuting time, and commuting mode and their impacts on mental health, physical health, and health behavior. The research findings show that: 1) Commuting distance has a significantly positive direct effect on commuting mode and commuting time, while commuting distance has a significantly positive indirect effect on commuting time. 2) In terms of the impact on mental health, commuting distance, commuting time, and commuting mode have a significantly negative direct effect on the neighborhood relationship. At the same time, there is also a significantly negative indirect effect of commuting distance and commuting mode on the neighborhood relationship. In terms of the impact on physical health, commuting distance reduces the probability of overweight or obesity among urban residents, but increases the probability of workers choosing a motorized commuting mode, which indirectly increases the risk of chronic diseases for the commuters. In terms of the impact on health behavior, commuting distance and commuting time are significantly negative correlated with sleeping time. Commuting mode has a negative indirect impact on sleeping time. Motor vehicle commuting mode is also significantly negative correlated with housework and significantly positive correlated with walking behavior. 3) The impacts of commuting behavior characteristics on health vary depending on the socioeconomic attributes of the commuters. The commuting behavior characteristics of female, older, and lower-income workers have a more significant impact on health. Based on the results of this study, we recommend to optimize the working and living space in the city, reduce commuting time, reduce car dependence, promote active commuting to increase the physical activity of commuters, and create more favorable conditions for the commuting of special groups, thereby improve their health.
Keywords:health  commuting behavior characteristics  urban residents  structural equation model (SEM)  Nanjing City  
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