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识别用于儿童肥胖和身体活动研究的对比性和可比性学校社区。

Identification of contrastive and comparable school neighborhoods for childhood obesity and physical activity research.

作者信息

Zhang Xingyou, Christoffel Katherine Kaufer, Mason Maryann, Liu Lin

机构信息

The Robert Graham Centre for Policy Studies in Family Medicine and Primary Care, American Academy of Physicians, 1350 Conneticut Avenue, NW, Suite 201, Washington, DC 20036, USA.

出版信息

Int J Health Geogr. 2006 Mar 30;5:14. doi: 10.1186/1476-072X-5-14.

Abstract

UNLABELLED

The neighborhood social and physical environments are considered significant factors contributing to children's inactive lifestyles, poor eating habits, and high levels of childhood obesity. Understanding of neighborhood environmental profiles is needed to facilitate community-based research and the development and implementation of community prevention and intervention programs. We sought to identify contrastive and comparable districts for childhood obesity and physical activity research studies. We have applied GIS technology to manipulate multiple data sources to generate objective and quantitative measures of school neighborhood-level characteristics for school-based studies. GIS technology integrated data from multiple sources (land use, traffic, crime, and census tract) and available social and built environment indicators theorized to be associated with childhood obesity and physical activity. We used network analysis and geoprocessing tools within a GIS environment to integrate these data and to generate objective social and physical environment measures for school districts. We applied hierarchical cluster analysis to categorize school district groups according to their neighborhood characteristics. We tested the utility of the area characterizations by using them to select comparable and contrastive schools for two specific studies.

RESULTS

We generated school neighborhood-level social and built environment indicators for all 412 Chicago public elementary school districts. The combination of GIS and cluster analysis allowed us to identify eight school neighborhoods that were contrastive and comparable on parameters of interest (land use and safety) for a childhood obesity and physical activity study.

CONCLUSION

The combination of GIS and cluster analysis makes it possible to objectively characterize urban neighborhoods and to select comparable and/or contrasting neighborhoods for community-based health studies.

摘要

未标注

社区的社会和自然环境被认为是导致儿童缺乏运动的生活方式、不良饮食习惯以及儿童肥胖率高的重要因素。需要了解社区环境概况,以促进基于社区的研究以及社区预防和干预计划的制定与实施。我们试图为儿童肥胖和身体活动研究确定对比性和可比性区域。我们应用地理信息系统(GIS)技术来处理多个数据源,以生成基于学校的研究中学校社区层面特征的客观定量指标。GIS技术整合了来自多个来源的数据(土地利用、交通、犯罪和普查区)以及理论上与儿童肥胖和身体活动相关的现有社会和建筑环境指标。我们在GIS环境中使用网络分析和地理处理工具来整合这些数据,并为学区生成客观的社会和自然环境指标。我们应用层次聚类分析,根据社区特征对学区组进行分类。我们通过使用这些区域特征为两项具体研究选择可比和对比学校,来测试其效用。

结果

我们为芝加哥所有412个公立小学学区生成了学校社区层面的社会和建筑环境指标。GIS和聚类分析的结合使我们能够识别出八个在儿童肥胖和身体活动研究的相关参数(土地利用和安全)上具有对比性和可比性的学校社区。

结论

GIS和聚类分析的结合使得客观描述城市社区特征以及为基于社区的健康研究选择可比和/或对比社区成为可能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e49a/1526711/2a2b3e9d31b6/1476-072X-5-14-1.jpg

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