Improving built environment measurement in physical activity research with omnidi

利用omnidi改善体育活动研究中的建筑环境测量

• 批准号: 8249806
• 负责人: Cheryl Kelly
• 金额: $ 16.05万
• 依托单位: UNIVERSITY OF COLORADO
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-04-01 至 2013-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8249806
• 关键词: Address; Adolescent; Adult; Agreement; Behavior; Categories; Characteristics; Child; Colon Carcinoma; Data; Destinations; Development; Diabetes Mellitus; Disadvantaged; Emerging Technologies; Environment; Goals; Health; Healthy People 2010; Hypertension; Image; Imagery; Income; Individual; Lead; Link; Longitudinal Studies; Malignant Neoplasms; Measurement; Measures; Methods; Modeling; Neighborhoods; Obesity; Outcome; Patient Self-Report; Persons; Physical activity; Population; Race; Reporting; Research; Research Personnel; Resolution; Social Desirability; Surveys; Techniques; Technology; Testing; Validation; Walking; base; behavior observation; cohort; density; heart disease risk; improved; innovation; interest; land use; meetings; physical conditioning; public health relevance; response; statistics; tool; validation studies; virtual

DESCRIPTION (provided by applicant): The goal of this project is to develop an alternative method to conducting field-based audits of the built environment and conduct preliminary validation of the approach's ability to predict physical activity behavior. The mounting number of field audit tools developed in recent years reflects increasing interest in built environment characteristics as determinants of physical activity and related health outcomes. High-resolution omnidirectional imagery (an emerging technology exemplified by Google Street View) provides a potential alternative to field-based approaches for detailed assessment of the built environment. This type of imagery is becoming more widely available and provides the ability to view the built environment from a virtual walk- through or drive-through perspective. Therefore, this study will examine the agreement between omnidirectional imagery and field-based audits. All audits will use the Active Neighborhood Checklist that measures 71 detailed built environment characteristics. The specific aims are: 1. examine the agreement between detailed measures of the built environment derived from publicly accessible imagery and in-person field audits; and 2. examine the relationship between detailed measures of the built environment derived from publicly available imagery and in-person field audits with physical activity behavior. To measure the agreement between results of field-based audits and those obtained through interpretation of the imagery, we will use observed agreement and Cohen's kappa statistic (K) to compare each checklist item across. Kappa will be used to compare dichotomous items (i.e. yes/no response choice), while the 1-way model intraclass correlation coefficient (ICC) will be used for multiple-choice questions. Because kappa yields higher agreement measures when auditors disagree on the distribution of categories in the data and lower measures when they agree, we also will use Krippendorffer's 1 which does not suffer from this disadvantage. We will use Pearson Product Correlation and T-tests to assess the ability of this approach to predict physical activity behavior. Imagery methods may enhance more comprehensive research on built environment determinants of physical activity and related health outcomes by improving the feasibility of conducting longitudinal studies of changes in the built environment for larger and more geographically dispersed cohorts. PUBLIC HEALTH RELEVANCE: Previous research suggests characteristics of the built environment influence physical activity and related health outcome. The goal of this study is to develop a new method of assessing the built environment that uses innovative image-based technology (e.g. Google Street View). If effective, this new method could advance the field by allowing for multi-regional and/or longitudinal studies of the built environment on physical activity and related health outcomes.

描述（由申请人提供）：本项目的目标是开发一种替代方法来进行基于现场的建筑环境审计，并对该方法预测身体活动行为的能力进行初步验证。近年来开发的实地审计工具越来越多，反映出人们越来越关注建筑环境特征作为身体活动和相关健康结果的决定因素。高分辨率全方位图像（以谷歌街景为例的一种新兴技术）为详细评估建筑环境提供了一种替代实地方法的潜在方法。这种类型的图像变得越来越广泛，并且提供了从虚拟步行或驾车通过视角查看建筑环境的能力。因此，本研究将探讨全方位图像和实地审计之间的协议。所有审计将使用活动邻里检查表，衡量71个详细的建筑环境特征。具体目标是：1.检查从公开获取的图像和现场审计中得出的建筑环境详细措施之间的一致性;以及2.研究建筑环境的详细措施之间的关系，从公开的图像和现场审计与身体活动行为。为了衡量基于现场的审计结果与通过图像解释获得的结果之间的一致性，我们将使用观察到的一致性和科恩的kappa统计量（K）来比较每个检查表项目。Kappa将用于比较二分项目（即是/否回答选择），而单因素模型组内相关系数（ICC）将用于多项选择题。因为当审计员对数据中类别的分布不同意时，kappa产生较高的一致性度量，而当他们同意时，kappa产生较低的度量，所以我们也将使用Krippendorffer 1，它不会受到这种缺点的影响。我们将使用皮尔逊产品相关性和T检验来评估这种方法预测体力活动行为的能力。成像方法可以通过提高对更大和地理上更分散的人群的建筑环境变化进行纵向研究的可行性，加强对体育活动和相关健康结果的建筑环境决定因素的更全面的研究。 公共卫生相关性：先前的研究表明，建筑环境的特征会影响身体活动和相关的健康结果。本研究的目标是开发一种新的方法来评估建筑环境，使用创新的基于图像的技术（例如谷歌街景）。如果有效，这种新方法可以通过允许对建筑环境对身体活动和相关健康结果的多区域和/或纵向研究来推进该领域。