Suppr超能文献

社区街道网络与步行、骑行和慢跑的纵向关联:CARDIA 研究。

Longitudinal associations between neighborhood-level street network with walking, bicycling, and jogging: the CARDIA study.

机构信息

Department of Health Studies, University of Chicago, Chicago, IL 60637, USA.

出版信息

Health Place. 2010 Nov;16(6):1206-15. doi: 10.1016/j.healthplace.2010.08.005. Epub 2010 Aug 10.

Abstract

OBJECTIVE

To investigate the differential association between neighborhood-level street network with walking, bicycling, and jogging by urbanicity and gender.

METHODS

We used prospective data from 4 repeated exams on 5115 young adults recruited in 1985-1986, followed through 2000-2001, with self-reported walking, bicycling, and jogging. Using a Geographic Information System, we spatially and temporally linked time-varying residential locations to street network data within a 1 km Euclidean buffer. Two-part marginal effect modeling assessed longitudinal associations between neighborhood-level street network with walking, bicycling, and jogging, by urbanicity and gender, controlling for time-varying individual- and census-level covariates.

RESULTS

Neighborhood street density was positively associated with walking, bicycling, and jogging in low urbanicity areas, but in middle and high urbanicity areas, these associations became null (men) or inverse (women).

CONCLUSION

Characteristics of neighborhood streets may influence adult residents' walking, bicycling, and jogging, particularly in less urban areas. This research may inform policy efforts to encourage physical activity.

摘要

目的

探讨不同城市环境和性别的人群与街道网络在步行、骑自行车和慢跑方面的关联差异。

方法

我们使用前瞻性数据,对 1985-1986 年间招募的 5115 名年轻成年人进行了 4 次重复检查,随访至 2000-2001 年,记录了他们的步行、骑自行车和慢跑情况。我们使用地理信息系统,将时间变化的居住地点与 1 公里欧几里得缓冲区中的街道网络数据进行空间和时间关联。使用两部分边缘效应模型,控制个体和人口普查水平的时变协变量,评估了不同城市环境和性别的人群与街道网络在步行、骑自行车和慢跑方面的纵向关联。

结果

在低城市环境地区,街道密度与步行、骑自行车和慢跑呈正相关,但在中高城市环境地区,这些关联变得无效(男性)或相反(女性)。

结论

街道网络的特点可能会影响成年居民的步行、骑自行车和慢跑,特别是在城市环境较低的地区。这项研究可以为鼓励体育活动的政策提供信息。

相似文献

引用本文的文献

本文引用的文献

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验