主办单位:成都体育学院
ISSN 1001-9154 CN 51-1097/G8

成都体育学院学报 ›› 2019, Vol. 45 ›› Issue (4): 113-120.doi: 10.15942/j.jcsu.2019.04.018

• 运动人体科学 • 上一篇    下一篇

城市老年人户外体力活动、久坐时间与客观建成环境因素关系研究

宋彦李青,王竹影   

  1. 南京师范大学体育科学学院,江苏 南京 210023
  • 出版日期:2019-07-15 发布日期:2019-08-06
  • 通讯作者: 王竹影,博士,教授,博士生导师,研究方向:体育人文社会学,E-mail:11961460541@qq.com。
  • 作者简介:宋彦李青,南京师范大学博士研究生,老年人休闲性体力活动与城市建成环境,E-mail:sylq113@163.com。
  • 基金资助:
    国家体育总局科教司重点项目:基于GIS、GPS和加速度计的老年人健身活动规律与社区健身设施优化布局研究(2017B007);国家社会科学基金项目:基于GIS的城市建成环境与老年人休闲性体力活动时空特征研究(2015BTY023)

Study on the Relationship of Built-in Environmental factors to Outdoor Physical Activity and Sedentary Time of The Elderly in Urban Areas

SONG Yanliqing,WANG Zhuying   

  1. College of Sports Science,Nanjing Normal University,Nanjing Jiangsu 210023
  • Online:2019-07-15 Published:2019-08-06

摘要: 目的: 研究城市老年人户外体力活动、久坐时间与客观建成环境因素的关系。方法: 选取研究区域内60岁以上老年人586人(男性258名、女性328名)佩戴ActiGraph加速度计4天测量其户外中高强度体力活动和久坐时间,依据有效样本人群的家庭住址,利用Gis技术分析缓冲区1 km以内人口密度、建筑密度、街道连通性、人均道路总长度、土地混合利用、交通站点数目、到达交通站点距离、到达健身休闲场所距离、到达商业场所距离等9个建成环境指标。之后依据33和66两个百分位数点对变量划分为三个等级赋值1、2和3,将人口学变量作为控制变量纳入logistic模型中。结果: 随着土地混合利用度每降低一个等级,户外体力活动的等级变化预估系数β分别为1.122,P=0.016和0.762,P=0.036,交通站点数目第1等级和等3等级之间变化的预估系数为0.720,P=0.029。到达交通站点距离第2等级和等3等级之间变化的预估系数为0.769,P=0.049。其他客观建成环境因素与老年人户外体力活动不存在相关性。随着人口密度每降低一个等级,久坐时间的等级变化预估系数β分别为0.745,P=0.004和0.751,P=0.014,人均道路总长度第2等级和等3等级之间变化的预估系数为0.926,P=0.029。其他客观建成环境因素与老年人久坐时间不存在相关性。 结论: 影响老年人每日户外体力活动客观建成环境因素有:土地混合利用、到达健身场所距离、交通站点数目以及到达交通站点距离。影响老年人每日久坐时间的客观建成环境因素有:人口密度、人均道路总长度。因此,规划部门再制定规划政策时,可通过改善上述建成环境因素,促进老年人每日体力活动,改变久坐生活方式,提高其健康水平,以应对我国人口老龄化所带来的健康危机和隐患。

关键词: 体力活动, 建成环境, 老年人, 久坐, 加速度计, GIS

Abstract: Objective: Study on the relationship of built-in environmental factors to outdoor physical activity and sedentary time in urban elderly. Methods: 586 urban elderly of over 60 years old (male 258, female 328) wore Actigraph accelerometer for 4 days and their high intensity outdoor physical activity and sedentary time were measured by the GIS technology on 9 built-in environmental indexes including population density, building density, street connectivity, total road length per capita, mixed utilization of land, number of traffic stations, distance to traffic station, distance to fitness and leisure place, distance to business place within 1 km buffer zone to the family address of effective sample population. The variables were then divided into the three levels of 1, 2 and 3 according to the two percentiles of 33 and 66, and the demographic variables were integrated into the logistic model as control variables. Results: As the mixed utilization of land decreases from one level to the next, the estimated coefficient β of the change in outdoor physical activity level is 1.122,P=0.016 and 0.762,P=0.036 respectively, and the estimated coefficient of change in the number of traffic stations from level 1 to level 3 is 0.720,P=0.029. The estimated coefficient of change in distance to traffic station from level 2 to level 3 is 0.769, P=0.049. There is no correlation between other built-in environmental factors and the outdoor physical activity of the elderly. As the population density decreases by one level, the estimated coefficient β of the sedentary time is 0.745, P=0.004 and 0.751, P=0.014 respectively, and the estimated coefficient of change in the total road length per capita from level 2 to level 3 is 0.926 and P=0.029. There is no correlation between other built-in environmental factors and the sedentary time of the elderly. Conclusion: The built-in environmental factors affecting the daily physical activity of the elderly are: mixed utility of land, distance to the fitness place, number of traffic stations, and distance to the traffic station. The built-in environmental factors that affect the elderly's daily sedentary time are: population density and total road length per capita. Therefore, when the planning departments redesign the planning policy, they can improve the daily physical activity of the elderly, change the sedentary lifestyle and improve their health level in the coming aging society of China by coping with the above-mentioned built-in environmental factors.

Key words: physical activity, built-in environment, elderly, sedentary, accelerometer, GIS

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